Implementing precision medicine in a regionally organized healthcare system in Sweden

Qualitative exploration of 3D printing in Swedish healthcare: perceived effects and barriers

BACKGROUND

Three-dimensional (3D) printing produces objects by adding layers of material rather than mechanically reducing material. This production technology has several advantages and has been used in various medical fields to, for instance, improve the planning of complicated operations, customize medical devices, and enhance medical education. However, few existing studies focus on the adoption and the aspects that could influence or hinder the adoption of 3D printing.

OBJECTIVE

To describe the state of 3D printing in Sweden, explore the perceived effects of using 3D printing, and identify barriers to its adoption.

METHODS

A qualitative study with respondents from seven life science regions (i.e., healthcare regions with university hospitals) in Sweden. Semi-structured interviews were employed, involving 19 interviews, including one group interview. The respondents were key informants in terms of 3D printing adoption. Data collection occurred between April and May 2022 and then between February and May 2023. Thematic analysis was applied to identify patterns and themes.

RESULTS

All seven regions in Sweden used 3D printing, but none had an official adoption strategy. The most common applications were surgical planning and guides in clinical areas such as dentistry, orthopedics, and oral and maxillofacial surgery. Perceived effects of 3D printing included improved surgery, innovation, resource efficiency, and educational benefits. Barriers to adoption were categorized into organization, environment, and technology. Organizational barriers, such as high costs and lack of central decisions, were most prominent. Environmental barriers included a complex regulatory framework, uncertainty, and difficulty in interpreting regulations. Technological barriers were less frequent.

CONCLUSIONS

The study highlights the widespread use of 3D printing in Swedish healthcare, primarily in surgical planning. Perceived benefits included improved surgical precision, innovation, resource efficiency, and educational enhancements. Barriers, especially organizational and regulatory challenges, play a significant role in hindering widespread adoption. Policymakers need comprehensive guidance on 3D printing adoption, considering the expensive nature of technology investments. Future studies could explore adoption in specific clinical fields and investigate adoption in non-life science regions within and outside Sweden.

A national long-read sequencing study on chromosomal rearrangements uncovers hidden complexities

Clinical genetic laboratories often require a comprehensive analysis of chromosomal rearrangements/structural variants (SVs), from large events like translocations and inversions to supernumerary ring/marker chromosomes and small deletions or duplications. Understanding the complexity of these events and their clinical consequences requires pinpointing breakpoint junctions and resolving the derivative chromosome structure. This task often surpasses the capabilities of short-read sequencing technologies. In contrast, long-read sequencing techniques present a compelling alternative for clinical diagnostics. Here, Genomic Medicine Sweden-Rare Diseases has explored the utility of HiFi Revio long-read genome sequencing (lrGS) for digital karyotyping of SVs nationwide. The 16 samples from 13 families were collected from all Swedish healthcare regions. Prior investigations had identified 16 SVs, ranging from simple to complex rearrangements, including inversions, translocations, and copy number variants. We have established a national pipeline and a shared variant database for variant calling and filtering. Using lrGS, 14 of the 16 known SVs are detected. Of these, 13 are mapped at nucleotide resolution, and one complex rearrangement is only visible by read depth. Two Chromosome 21 rearrangements, one mosaic, remain undetected. Average read lengths are 8.3-18.8 kb with coverage exceeding 20× for all samples. De novo assembly results in a limited number of phased contigs per individual (N50 6-86 Mb), enabling direct characterization of the chromosomal rearrangements. In a national pilot study, we demonstrate the utility of HiFi Revio lrGS for analyzing chromosomal rearrangements. Based on our results, we propose a 5-year plan to expand lrGS use for rare disease diagnostics in Sweden.

Precision Diagnostics in Myeloid Malignancies: Development and Validation of a National Capture-Based Gene Panel

Gene panel sequencing has become a common diagnostic tool for detecting somatically acquired mutations in myeloid neoplasms. However, many panels have restricted content, provide insufficient sensitivity levels, or lack clinically validated workflows. We here describe the development and validation of the Genomic Medicine Sweden myeloid gene panel (GMS-MGP), a capture-based 191 gene panel including mandatory genes in contemporary guidelines as well as emerging candidates. The GMS-MGP displayed uniform coverage across all targets, including recognized difficult GC-rich areas. The validation of 117 previously described somatic variants showed a 100% concordance with a limit-of-detection of a 0.5% variant allele frequency (VAF), achieved by utilizing error correction and filtering against a panel-of-normals. A national interlaboratory comparison investigating 56 somatic variants demonstrated highly concordant results in both detection rate and reported VAFs. In addition, prospective analysis of 323 patients analyzed with the GMS-MGP as part of standard-of-care identified clinically significant genes as well as recurrent mutations in less well-studied genes. In conclusion, the GMS-MGP workflow supports sensitive detection of all clinically relevant genes, facilitates novel findings, and is, based on the capture-based design, easy to update once new guidelines become available. The GMS-MGP provides an important step toward nationally harmonized precision diagnostics of myeloid malignancies.

The expanding diagnostic toolbox for rare genetic diseases

Genomic technologies, such as targeted, exome and short-read genome sequencing approaches, have revolutionized the care of patients with rare genetic diseases. However, more than half of patients remain without a diagnosis. Emerging approaches from research-based settings such as long-read genome sequencing and optical genome mapping hold promise for improving the identification of disease-causal genetic variants. In addition, new omic technologies that measure the transcriptome, epigenome, proteome or metabolome are showing great potential for variant interpretation. As genetic testing options rapidly expand, the clinical community needs to be mindful of their individual strengths and limitations, as well as remaining challenges, to select the appropriate diagnostic test, correctly interpret results and drive innovation to address insufficiencies. If used effectively - through truly integrative multi-omics approaches and data sharing - the resulting large quantities of data from these established and emerging technologies will greatly improve the interpretative power of genetic and genomic diagnostics for rare diseases.

Bridging the Divide: A Review on the Implementation of Personalized Cancer Medicine

The shift towards personalized cancer medicine (PCM) represents a significant transformation in cancer care, emphasizing tailored treatments based on the genetic understanding of cancer at the cellular level. This review draws on recent literature to explore key factors influencing PCM implementation, highlighting the role of innovative leadership, interdisciplinary collaboration, and coordinated funding and regulatory strategies. Success in PCM relies on overcoming challenges such as integrating diverse medical disciplines, securing sustainable investment for shared infrastructures, and navigating complex regulatory landscapes. Effective leadership is crucial for fostering a culture of innovation and teamwork, essential for translating complex biological insights into personalized treatment strategies. The transition to PCM necessitates not only organizational adaptation but also the development of new professional roles and training programs, underscoring the need for a multidisciplinary approach and the importance of team science in overcoming the limitations of traditional medical paradigms. The conclusion underscores that PCM's success hinges on creating collaborative environments that support innovation, adaptability, and shared vision among all stakeholders involved in cancer care.

Trivial State Fuzzy Processing for Error Reduction in Healthcare Big Data Analysis towards Precision Diagnosis

There is a significant public health concern regarding medical diagnosis errors, which are a major cause of mortality. Identifying the root cause of these errors is challenging, and even if one is identified, implementing an effective treatment to prevent their recurrence is difficult. Optimization-based analysis in healthcare data management is a reliable method for improving diagnostic precision. Analyzing healthcare data requires pre-classification and the identification of precise information for precision-oriented outcomes. This article introduces a Cooperative-Trivial State Fuzzy Processing method for significant data analysis with possible derivatives. Trivial State Fuzzy Processing operates on the principle of fuzzy logic-based processing applied to structured healthcare data, focusing on mitigating errors and uncertainties inherent in the data. The derivatives are aided by identifying and grouping diagnosis-related and irrelevant data. The proposed method mitigates invertible derivative analysis issues in similar data grouping and irrelevance estimation. In the grouping and detection process, recent knowledge of the diagnosis progression is exploited to identify the functional data for analysis. Such analysis improves the impact of trivial diagnosis data compared to a voluminous diagnosis history. The cooperative derivative states under different data irrelevance factors reduce trivial state errors in healthcare big data analysis.

Diagnostic yield and clinical impact of germline sequencing in children with CNS and extracranial solid tumors-a nationwide, prospective Swedish study

Background

Childhood cancer predisposition (ChiCaP) syndromes are increasingly recognized as contributing factors to childhood cancer development. Yet, due to variable availability of germline testing, many children with ChiCaP might go undetected today. We report results from the nationwide and prospective ChiCaP study that investigated diagnostic yield and clinical impact of integrating germline whole-genome sequencing (gWGS) with tumor sequencing and systematic phenotyping in children with solid tumors.

Methods

gWGS was performed in 309 children at diagnosis of CNS (n = 123, 40%) or extracranial (n = 186, 60%) solid tumors and analyzed for disease-causing variants in 189 known cancer predisposing genes. Tumor sequencing data were available for 74% (227/309) of patients. In addition, a standardized clinical assessment for underlying predisposition was performed in 95% (293/309) of patients.

Findings

The prevalence of ChiCaP diagnoses was 11% (35/309), of which 69% (24/35) were unknown at inclusion (diagnostic yield 8%, 24/298). A second-hit and/or relevant mutational signature was observed in 19/21 (90%) tumors with informative data. ChiCaP diagnoses were more prevalent among patients with retinoblastomas (50%, 6/12) and high-grade astrocytomas (37%, 6/16), and in those with non-cancer related features (23%, 20/88), and ≥2 positive ChiCaP criteria (28%, 22/79). ChiCaP diagnoses were autosomal dominant in 80% (28/35) of patients, yet confirmed de novo in 64% (18/28). The 35 ChiCaP findings resulted in tailored surveillance (86%, 30/35) and treatment recommendations (31%, 11/35).

Interpretation

Overall, our results demonstrate that systematic phenotyping, combined with genomics-based diagnostics of ChiCaP in children with solid tumors is feasible in large-scale clinical practice and critically guides personalized care in a sizable proportion of patients.

Funding

The study was supported by the Swedish Childhood Cancer Fund and the Ministry of Health and Social Affairs.

Current and emerging sequencing-based tools for precision cancer medicine

Current precision cancer medicine is dependent on the analyses of a plethora of clinically relevant genomic aberrations. During the last decade, next-generation sequencing (NGS) has gradually replaced most other methods for precision cancer diagnostics, spanning from targeted tumor-informed assays and gene panel sequencing to global whole-genome and whole-transcriptome sequencing analyses. The shift has been impelled by a clinical need to assess an increasing number of genomic alterations with diagnostic, prognostic and predictive impact, including more complex biomarkers (e.g. microsatellite instability, MSI, and homologous recombination deficiency, HRD), driven by the parallel development of novel targeted therapies and enabled by the rapid reduction in sequencing costs. This review focuses on these sequencing-based methods, puts their emergence in a historic perspective, highlights their clinical utility in diagnostics and decision-making in pediatric and adult cancer, as well as raises challenges for their clinical implementation. Finally, the importance of applying sensitive tools for longitudinal monitoring of treatment response and detection of measurable residual disease, as well as future avenues in the rapidly evolving field of sequencing-based methods are discussed.

Micro-costing of genetic diagnostics in acute leukemia in Sweden: from standard-of-care to whole-genome sequencing

AIMS AND BACKGROUND

Whole-genome sequencing (WGS) is increasingly applied in clinical practice and expected to replace standard-of-care (SoC) genetic diagnostics in hematological malignancies. This study aims to assess and compare the fully burdened cost ('micro-costing') per patient for Swedish laboratories using WGS and SoC, respectively, in pediatric and adult patients with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML).

METHODS

The resource use and cost details associated with SoC, e.g. chromosome banding analysis, fluorescent in situ hybridization, and targeted sequencing analysis, were collected via activity-based costing methods from four diagnostic laboratories. For WGS, corresponding data was collected from two of the centers. A simulation-based scenario model was developed for analyzing the WGS cost based on different annual sample throughput to evaluate economy of scale.

RESULTS

The average SoC total cost per patient was €2,465 for pediatric AML and €2,201 for pediatric ALL, while in adults, the corresponding cost was €2,458 for AML and €1,207 for ALL. The average WGS cost (90x tumor/30x normal; sequenced on the Illumina NovaSeq 6000 platform) was estimated to €3,472 based on an annual throughput of 2,500 analyses, however, with an annual volume of 7,500 analyses the average cost would decrease by 23% to €2,671.

CONCLUSION

In summary, WGS is currently more costly than SoC, however the cost can be reduced by utilizing laboratories with higher throughput and by the expected decline in cost of reagents. Our data provides guidance to decision-makers for the resource allocation needed when implementing WGS in diagnostics of hematological malignancies.

Precision medicine in complex diseases-Molecular subgrouping for improved prediction and treatment stratification

Complex diseases are caused by a combination of genetic, lifestyle, and environmental factors and comprise common noncommunicable diseases, including allergies, cardiovascular disease, and psychiatric and metabolic disorders. More than 25% of Europeans suffer from a complex disease, and together these diseases account for 70% of all deaths. The use of genomic, molecular, or imaging data to develop accurate diagnostic tools for treatment recommendations and preventive strategies, and for disease prognosis and prediction, is an important step toward precision medicine. However, for complex diseases, precision medicine is associated with several challenges. There is a significant heterogeneity between patients of a specific disease-both with regards to symptoms and underlying causal mechanisms-and the number of underlying genetic and nongenetic risk factors is often high. Here, we summarize precision medicine approaches for complex diseases and highlight the current breakthroughs as well as the challenges. We conclude that genomic-based precision medicine has been used mainly for patients with highly penetrant monogenic disease forms, such as cardiomyopathies. However, for most complex diseases-including psychiatric disorders and allergies-available polygenic risk scores are more probabilistic than deterministic and have not yet been validated for clinical utility. However, subclassifying patients of a specific disease into discrete homogenous subtypes based on molecular or phenotypic data is a promising strategy for improving diagnosis, prediction, treatment, prevention, and prognosis. The availability of high-throughput molecular technologies, together with large collections of health data and novel data-driven approaches, offers promise toward improved individual health through precision medicine.

Precision medicine in rare diseases: What is next?

Molecular diagnostics is a cornerstone of modern precision medicine, broadly understood as tailoring an individual's treatment, follow-up, and care based on molecular data. In rare diseases (RDs), molecular diagnoses reveal valuable information about the cause of symptoms, disease progression, familial risk, and in certain cases, unlock access to targeted therapies. Due to decreasing DNA sequencing costs, genome sequencing (GS) is emerging as the primary method for precision diagnostics in RDs. Several ongoing European initiatives for precision medicine have chosen GS as their method of choice. Recent research supports the role for GS as first-line genetic investigation in individuals with suspected RD, due to its improved diagnostic yield compared to other methods. Moreover, GS can detect a broad range of genetic aberrations including those in noncoding regions, producing comprehensive data that can be periodically reanalyzed for years to come when further evidence emerges. Indeed, targeted drug development and repurposing of medicines can be accelerated as more individuals with RDs receive a molecular diagnosis. Multidisciplinary teams in which clinical specialists collaborate with geneticists, genomics education of professionals and the public, and dialogue with patient advocacy groups are essential elements for the integration of precision medicine into clinical practice worldwide. It is also paramount that large research projects share genetic data and leverage novel technologies to fully diagnose individuals with RDs. In conclusion, GS increases diagnostic yields and is a crucial step toward precision medicine for RDs. Its clinical implementation will enable better patient management, unlock targeted therapies, and guide the development of innovative treatments.

Implementation of precision medicine in healthcare-A European perspective

The technical development of high-throughput sequencing technologies and the parallel development of targeted therapies in the last decade have enabled a transition from traditional medicine to personalized treatment and care. In this way, by using comprehensive genomic testing, more effective treatments with fewer side effects are provided to each patient-that is, precision or personalized medicine (PM). In several European countries-such as in England, France, Denmark, and Spain-the governments have adopted national strategies and taken "top-down" decisions to invest in national infrastructure for PM. In other countries-such as Sweden, Germany, and Italy with regionally organized healthcare systems-the profession has instead taken "bottom-up" initiatives to build competence networks and infrastructure to enable equal access to PM. In this review, we summarize key learnings at the European level on the implementation process to establish sustainable governance and organization for PM at the regional, national, and EU/international levels. We also discuss critical ethical and legal aspects of implementing PM, and the importance of access to real-world data and performing clinical trials for evidence generation, as well as the need for improved reimbursement models, increased cross-disciplinary education and patient involvement. In summary, PM represents a paradigm shift, and modernization of healthcare and all relevant stakeholders-that is, healthcare, academia, policymakers, industry, and patients-must be involved in this system transformation to create a sustainable, non-siloed ecosystem for precision healthcare that benefits our patients and society at large.

Increased MYB alternative promoter usage is associated with relapse in acute lymphoblastic leukemia

Therapy-resistant disease is a major cause of death in patients with acute lymphoblastic leukemia (ALL). Activation of the MYB oncogene is associated with ALL and leads to uncontrolled neoplastic cell proliferation and blocked differentiation. Here, we used RNA-seq to study the clinical significance of MYB expression and MYB alternative promoter (TSS2) usage in 133 pediatric ALLs. RNA-seq revealed that all cases analyzed overexpressed MYB and demonstrated MYB TSS2 activity. qPCR analyses confirmed the expression of the alternative MYB promoter also in seven ALL cell lines. Notably, high MYB TSS2 activity was significantly associated with relapse (p = 0.007). Moreover, cases with high MYB TSS2 usage showed evidence of therapy-resistant disease with increased expression of ABC multidrug resistance transporter genes (e.g., ABCA2, ABCB5, and ABCC10) and enzymes catalyzing drug degradation (e.g., CYP1A2, CYP2C9, and CYP3A5). Elevated MYB TSS2 activity was further associated with augmented KRAS signaling (p < 0.05) and decreased methylation of the conventional MYB promoter (p < 0.01). Taken together, our results suggest that MYB alternative promoter usage is a novel potential prognostic biomarker for relapse and therapy resistance in pediatric ALL.

Diagnostic Yield From a Nationwide Implementation of Precision Medicine for all Children With Cancer

PURPOSE

Several studies have indicated that broad genomic characterization of childhood cancer provides diagnostically and/or therapeutically relevant information in selected high-risk cases. However, the extent to which such characterization offers clinically actionable data in a prospective broadly inclusive setting remains largely unexplored.

METHODS

We implemented prospective whole-genome sequencing (WGS) of tumor and germline, complemented by whole-transcriptome sequencing (RNA-Seq) for all children diagnosed with a primary or relapsed solid malignancy in Sweden. Multidisciplinary molecular tumor boards were set up to integrate genomic data in the clinical decision process along with a medicolegal framework enabling secondary use of sequencing data for research purposes.

RESULTS

During the study's first 14 months, 118 solid tumors from 117 patients were subjected to WGS, with complementary RNA-Seq for fusion gene detection in 52 tumors. There was no significant geographic bias in patient enrollment, and the included tumor types reflected the annual national incidence of pediatric solid tumor types. Of the 112 tumors with somatic mutations, 106 (95%) exhibited alterations with a clear clinical correlation. In 46 of 118 tumors (39%), sequencing only corroborated histopathological diagnoses, while in 59 cases (50%), it contributed to additional subclassification or detection of prognostic markers. Potential treatment targets were found in 31 patients (26%), most commonly ALK mutations/fusions (n = 4), RAS/RAF/MEK/ERK pathway mutations (n = 14), FGFR1 mutations/fusions (n = 5), IDH1 mutations (n = 2), and NTRK2 gene fusions (n = 2). In one patient, the tumor diagnosis was revised based on sequencing. Clinically relevant germline variants were detected in 8 of 94 patients (8.5%).

CONCLUSION

Up-front, large-scale genomic characterization of pediatric solid malignancies provides diagnostically valuable data in the majority of patients also in a largely unselected cohort.

Challenging gold standard hematology diagnostics through the introduction of whole genome sequencing and artificial intelligence

The diagnosis of hematological malignancies is rather complex and requires the application of a plethora of different assays, techniques and methodologies. Some of the methods, like cytomorphology, have been in use for decades, while other methods, such as next-generation sequencing or even whole genome sequencing (WGS), are relatively new. The application of the methods and the evaluation of the results require distinct skills and knowledge and place different demands on the practitioner. However, even with experienced hematologists, diagnostic ambiguity remains a regular occurrence and the comprehensive analysis of high-dimensional WGS data soon exceeds any human's capacity. Hence, in order to reduce inter-observer variability and to improve the timeliness and accuracy of diagnoses, machine learning based approaches have been developed to assist in the decision making process. Moreover, to achieve the goal of precision oncology, comprehensive genomic profiling is increasingly being incorporated into routine standard of care.

Simultaneous Ultra-Sensitive Detection of Structural and Single Nucleotide Variants Using Multiplex Droplet Digital PCR in Liquid Biopsies from Children with Medulloblastoma

Medulloblastoma is a malignant embryonal tumor of the central nervous system (CNS) that mainly affects infants and children. Prognosis is highly variable, and molecular biomarkers for measurable residual disease (MRD) detection are lacking. Analysis of cell-free DNA (cfDNA) in cerebrospinal fluid (CSF) using broad genomic approaches, such as low-coverage whole-genome sequencing, has shown promising prognostic value. However, more sensitive methods are needed for MRD analysis. Here, we show the technical feasibility of capturing medulloblastoma-associated structural variants and point mutations simultaneously in cfDNA using multiplexed droplet digital PCR (ddPCR). Assay sensitivity was assessed with a dilution series of tumor in normal genomic DNA, and the limit of detection was below 100 pg of input DNA for all assays. False positive rates were zero for structural variant assays. Liquid biopsies (CSF and plasma, n = 47) were analyzed from 12 children with medulloblastoma, all with negative CSF cytology. MRD was detected in 75% (9/12) of patients overall. In CSF samples taken before or within 21 days of surgery, MRD was detected in 88% (7/8) of patients with localized disease and in one patient with the metastasized disease. Our results suggest that this approach could expand the utility of ddPCR and complement broader analyses of cfDNA for MRD detection.

Building a precision medicine infrastructure at a national level: The Swedish experience

Precision medicine has the potential to transform healthcare by moving from one-size-fits-all to personalised treatment and care. This transition has been greatly facilitated through new high-throughput sequencing technologies that can provide the unique molecular profile of each individual patient, along with the rapid development of targeted therapies directed to the Achilles heels of each disease. To implement precision medicine approaches in healthcare, many countries have adopted national strategies and initiated genomic/precision medicine initiatives to provide equal access to all citizens. In other countries, such as Sweden, this has proven more difficult due to regionally organised healthcare. Using a bottom-up approach, key stakeholders from academia, healthcare, industry and patient organisations joined forces and formed Genomic Medicine Sweden (GMS), a national infrastructure for the implementation of precision medicine across the country. To achieve this, Genomic Medicine Centres have been established to provide regionally distributed genomic services, and a national informatics infrastructure has been built to allow secure data handling and sharing. GMS has a broad scope focusing on rare diseases, cancer, pharmacogenomics, infectious diseases and complex diseases, while also providing expertise in informatics, ethical and legal issues, health economy, industry collaboration and education. In this review, we summarise our experience in building a national infrastructure for precision medicine. We also provide key examples how precision medicine already has been successfully implemented within our focus areas. Finally, we bring up challenges and opportunities associated with precision medicine implementation, the importance of international collaboration, as well as the future perspective in the field of precision medicine.