Sphingolipid biosynthesis is essential for metabolic rewiring during TH17 cell differentiation.

T helper 17 (TH17) cells are implicated in autoimmune diseases, and several metabolic processes are shown to be important for their development and function. In this study, we report an essential role for sphingolipids synthesized through the de novo pathway in TH17 cell development. Deficiency of SPTLC1, a major subunit of serine palmitoyl transferase enzyme complex that catalyzes the first and rate-limiting step of de novo sphingolipid synthesis, impaired glycolysis in differentiating TH17 cells by increasing intracellular reactive oxygen species (ROS) through enhancement of nicotinamide adenine dinucleotide phosphate oxidase 2 activity. Increased ROS leads to impaired activation of mammalian target of rapamycin C1 and reduced expression of hypoxia-inducible factor 1-alpha and c-Myc-induced glycolytic genes. SPTLCI deficiency protected mice from developing experimental autoimmune encephalomyelitis and experimental T cell transfer colitis. Our results thus show a critical role for de novo sphingolipid biosynthetic pathway in shaping adaptive immune responses with implications in autoimmune diseases.

Detailed DNA methylation characterisation of phyllodes tumours identifies a signature of malignancy and distinguishes phyllodes from metaplastic breast carcinoma.

Phyllodes tumours (PTs) are rare fibroepithelial lesions of the breast that are classified as benign, borderline, or malignant. As little is known about the molecular underpinnings of PTs, current diagnosis relies on histological examination. However, accurate classification is often difficult, particularly for distinguishing borderline from malignant PTs. Furthermore, PTs can be misdiagnosed as other tumour types with shared histological features, such as fibroadenoma and metaplastic breast cancers. As DNA methylation is a recognised hallmark of many cancers, we hypothesised that DNA methylation could provide novel biomarkers for diagnosis and tumour stratification in PTs, whilst also allowing insight into the molecular aetiology of this otherwise understudied tumour. We generated whole-genome methylation data using the Illumina EPIC microarray in a novel PT cohort (n = 33) and curated methylation microarray data from published datasets including PTs and other potentially histopathologically similar tumours (total n = 817 samples). Analyses revealed that PTs have a unique methylome compared to normal breast tissue and to potentially histopathologically similar tumours (metaplastic breast cancer, fibroadenoma and sarcomas), with PT-specific methylation changes enriched in gene sets involved in KRAS signalling and epithelial-mesenchymal transition. Next, we identified 53 differentially methylated regions (DMRs) (false discovery rate < 0.05) that specifically delineated malignant from non-malignant PTs. The top DMR in both discovery and validation cohorts was hypermethylation at the HSD17B8 CpG island promoter. Matched PT single-cell expression data showed that HSD17B8 had minimal expression in fibroblast (putative tumour) cells. Finally, we created a methylation classifier to distinguish PTs from metaplastic breast cancer samples, where we revealed a likely misdiagnosis for two TCGA metaplastic breast cancer samples. In conclusion, DNA methylation alterations are associated with PT histopathology and hold the potential to improve our understanding of PT molecular aetiology, diagnostics, and risk stratification. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Clinical Impact of Comprehensive Molecular Profiling in Adolescents and Young Adults with Sarcoma.

Sarcomas are a heterogenous group of tumours that commonly carry poor prognosis with limited therapeutic options. Adolescents and young adults (AYAs) with sarcoma are a unique and understudied patient population that have only achieved modest survival gains compared to other groups. We present our institutional experience of AYAs with sarcoma who underwent comprehensive molecular profiling (CMP) via either large-panel targeted DNA sequencing or whole genome and transcriptome sequencing and evaluated the feasibility and clinical impact of this approach. Genomic variants detected were determined to be clinically relevant and actionable following evaluation by the Molecular Tumour Board. Clinicians provided feedback regarding the utility of testing three months after reporting. Twenty-five patients who were recruited for CMP are included in this analysis. The median time from consent to final molecular report was 45 days (interquartile range: 37-57). Potentially actionable variants were detected for 14 patients (56%), and new treatment recommendations were identified for 12 patients (48%). Pathogenic germline variants were identified in three patients (12%), and one patient had a change in diagnosis. The implementation of CMP for AYAs with sarcoma is clinically valuable, feasible, and should be increasingly integrated into routine clinical practice as technologies and turnaround times continue to improve.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Spatial transcriptomics and the anatomical pathologist: Molecular meets morphology.

In recent years anatomical pathology has been revolutionised by the incorporation of molecular findings into routine diagnostic practice, and in some diseases the presence of specific molecular alterations are now essential for diagnosis. Spatial transcriptomics describes a group of technologies that provide up to transcriptome-wide expression profiling while preserving the spatial origin of the data, with many of these technologies able to provide these data using a single tissue section. Spatial transcriptomics allows expression profiling of highly specific areas within a tissue section potentially to subcellular resolution, and allows correlation of expression data with morphology, tissue type and location relative to other structures. While largely still research laboratory-based, several spatial transcriptomics methods have now achieved compatibility with formalin-fixed paraffin-embedded tissue (FFPE), allowing their use in diagnostic tissue samples, and with further development potentially leading to their incorporation in routine anatomical pathology practice. This mini review provides an overview of spatial transcriptomics methods, with an emphasis on platforms compatible with FFPE tissue, approaches to assess the data and potential applications in anatomical pathology practice.

Bio-Inspired Intelligent Systems: Negotiations between Minimum Manifest Task Entropy and Maximum Latent System Entropy in Changing Environments.

In theoretical physics and theoretical neuroscience, increased intelligence is associated with increased entropy, which entails potential access to an increased number of states that could facilitate adaptive behavior. Potential to access a larger number of states is a latent entropy as it refers to the number of states that could possibly be accessed, and it is also recognized that functioning needs to be efficient through minimization of manifest entropy. For example, in theoretical physics, the importance of efficiency is recognized through the observation that nature is thrifty in all its actions and through the principle of least action. In this paper, system intelligence is explained as capability to maintain internal stability while adapting to changing environments by minimizing manifest task entropy while maximizing latent system entropy. In addition, it is explained how automated negotiation relates to balancing adaptability and stability; and a mathematical negotiation model is presented that enables balancing of latent system entropy and manifest task entropy in intelligent systems. Furthermore, this first principles analysis of system intelligence is related to everyday challenges in production systems through multiple simulations of the negotiation model. The results indicate that manifest task entropy is minimized when maximization of latent system entropy is used as the criterion for task allocation in the simulated production scenarios.

Real-world prevalence of PD-L1 expression in non-small cell lung cancer: an Australia-wide multi-centre retrospective observational study.

An investigator-initiated, Australia-wide multi-centre retrospective observational study was undertaken to investigate the real-world prevalence of programmed death ligand-1 (PD-L1) expression in non-small cell lung carcinoma (NSCLC). Multiple centres around Australia performing PD-L1 immunohistochemistry (IHC) were invited to participate. Histologically confirmed NSCLC of any stage with a PD-L1 IHC test performed for persons aged ≥18 years between 1 January 2018 and 1 January 2020, and eligible for review, were identified at each centre, followed by data extraction and de-identification, after which data were submitted to a central site for collation and analysis. In total data from 6690 eligible PD-L1 IHC tests from histologically (75%) or cytologically (24%) confirmed NSCLC of any stage were reviewed from persons with a median age of 70 years, 43% of which were female. The majority (81%) of tests were performed using the PD-L1 IHC SP263 antibody with the Ventana BenchMark Ultra platform and 19% were performed using Dako PD-L1 IHC 22C3 pharmDx assay. Reported PD-L1 tumour proportion score (TPS) was ≥50% for 30% of all tests, with 62% and 38% scoring PD-L1 ≥1% and <1%, respectively. Relative prevalence of clinicopathological features with PD-L1 scores dichotomised to <50% and ≥50%, or to <1% and ≥1%, were examined. Females scored ≥1% slightly more often than males (64% vs 61%, respectively, p=0.013). However, there was no difference between sexes or age groups (<70 or ≥70 years) where PD-L1 scored ≥50%. Specimens from patients with higher stage (III/IV) scored ≥1% or ≥50% marginally more often compared to specimens from patients with lower stage (I/II) (p≤0.002). Proportions of primary and metastatic specimens did not differ where PD-L1 TPS was ≥1%, however more metastatic samples scored TPS ≥50% than primary samples (metastatic vs primary; 34% vs 27%, p<0.001). Cytology and biopsy specimens were equally reported, at 63% of specimens, to score TPS ≥1%, whereas cytology samples scored TPS ≥50% slightly more often than biopsy samples (34% vs 30%, respectively, p=0.004). Resection specimens (16% of samples tested) were reported to score TPS ≥50% or ≥1% less often than either biopsy or cytology samples (p<0.001). There was no difference in the proportion of tests with TPS ≥1% between PD-L1 IHC assays used, however the proportion of tests scored at TPS ≥50% was marginally higher for 22C3 compared to SP263 (34% vs 29%, respectively, p<0.001). These real-world Australian data are comparable to some previously published global real-world data, with some differences noted.

Predicting breast cancer-specific survival in metaplastic breast cancer patients using machine learning algorithms.

Metaplastic breast cancer (MpBC) is a rare and aggressive subtype of breast cancer, with data emerging on prognostic factors and survival prediction. This study aimed to develop machine learning models to predict breast cancer-specific survival (BCSS) in MpBC patients, utilizing a dataset of 160 patients with clinical, pathological, and biological variables. An in-depth variable selection process was carried out using gain ratio and correlation-based methods, resulting in 10 variables for model estimation. Five models (decision tree with bagging; logistic regression; multilayer perceptron; naïve Bayes; and, random forest algorithms) were evaluated using 10-fold cross-validation. Despite the constraints posed by the absence of therapeutic information, the random forest model exhibited the highest performance in predicting BCSS, with an ROC area of 0.808. This study emphasizes the potential of machine learning algorithms in predicting prognosis for complex and heterogeneous cancer subtypes using clinical datasets, and their potential to contribute to patient management. Further research that incorporates additional variables, such as treatment response, and more advanced machine learning techniques will likely enhance the predictive power of MpBC prognostic models.

A Matched Molecular and Clinical Analysis of the Epithelioid Haemangioendothelioma Cohort in the Stafford Fox Rare Cancer Program and Contextual Literature Review.

BACKGROUND: Epithelioid haemangioendothelioma (EHE) is an ultra-rare malignant vascular tumour with a prevalence of 1 per 1,000,000. It is typically molecularly characterised by a WWTR1::CAMTA1 gene fusion in approximately 90% of cases, or a YAP1::TFE3 gene fusion in approximately 10% of cases. EHE cases are typically refractory to therapies, and no anticancer agents are reimbursed for EHE in Australia. METHODS: We report a cohort of nine EHE cases with comprehensive histologic and molecular profiling from the Walter and Eliza Hall Institute of Medical Research Stafford Fox Rare Cancer Program (WEHI-SFRCP) collated via nation-wide referral to the Australian Rare Cancer (ARC) Portal. The diagnoses of EHE were confirmed by histopathological and immunohistochemical (IHC) examination. Molecular profiling was performed using the TruSight Oncology 500 assay, the TruSight RNA fusion panel, whole genome sequencing (WGS), or whole exome sequencing (WES). RESULTS: Molecular analysis of RNA, DNA or both was possible in seven of nine cases. The WWTR1::CAMTA1 fusion was identified in five cases. The YAP1::TFE3 fusion was identified in one case, demonstrating unique morphology compared to cases with the more common WWTR1::CAMTA1 fusion. All tumours expressed typical endothelial markers CD31, ERG, and CD34 and were negative for pan-cytokeratin. Cases with a WWTR1::CAMTA1 fusion displayed high expression of CAMTA1 and the single case with a YAP1::TFE3 fusion displayed high expression of TFE3. Survival was highly variable and unrelated to molecular profile. CONCLUSIONS: This cohort of EHE cases provides molecular and histopathological characterisation and matching clinical information that emphasises the molecular patterns and variable clinical outcomes and adds to our knowledge of this ultra-rare cancer. Such information from multiple studies will advance our understanding, potentially improving treatment options.

Amniotic fluid rubidium concentration association with newborn birthweight: a maternal-neonatal pilot study.

BACKGROUND: Although most biological systems, including human tissues, contain rubidium, its biogeochemical functions and possible role in neonatal birthweight are largely unknown. An animal study indicated a correlation between rubidium deficiency in the maternal diet and lower newborn birthweight. OBJECTIVE: This pilot study measured rubidium concentrations in amniotic fluid during the second trimester of (low-risk) pregnancy and investigated potential correlations between rubidium levels and third-trimester newborn birthweight-small for gestational age, appropriate for gestational age, and large for gestational age-and between preterm birth and term birth in uncomplicated pregnancies. STUDY DESIGN: This prospective, single-center study investigated a possible relationship between rubidium concentration in second-trimester amniotic fluid and third-trimester birthweight percentile. Amniotic fluid (at a median gestational age of 19 weeks) was sampled to determine rubidium concentration. Maternal and newborn characteristics were obtained from participant and delivery records. RESULTS: After screening 173 pregnant women, 99 amniotic fluid samples were evaluated. Midpregnancy median rubidium concentrations were significantly lower among newborns that were classified as small for gestational age than among newborns that were classified as appropriate for gestational age (106 vs 136 µg/L; P<.01). Based on a logistic regression random forest model, amniotic fluid rubidium was identified as a significant contributing factor to appropriate-for-gestational-age birthweight with 54% of the total contribution. CONCLUSION: Amniotic fluid rubidium concentration seems to be a strong predictor of appropriate-for-gestational-age birthweight and a potential marker for newborn birthweight classifications. In particular, low rubidium concentrations in amniotic fluid during midpregnancy are linked to third-trimester lower birthweight percentile. These findings could potentially serve as a valuable tool for early identification of pregnancy outcomes. Further investigation is necessary to fully explore the effect of rubidium on fetal development.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Specific inhibition of an anticancer target, polo-like kinase 1, by allosterically dismantling its mechanism of substrate recognition.

Polo-like kinase 1 (Plk1) is considered an attractive target for anticancer therapy. Over the years, studies on the noncatalytic polo-box domain (PBD) of Plk1 have raised the expectation of generating highly specific protein-protein interaction inhibitors. However, the molecular nature of the canonical PBD-dependent interaction, which requires extensive water network-mediated interactions with its phospholigands, has hampered efforts to identify small molecules suitable for Plk1 PBD drug discovery. Here, we report the identification of the first allosteric inhibitor of Plk1 PBD, called Allopole, a prodrug that can disrupt intracellular interactions between PBD and its cognate phospholigands, delocalize Plk1 from centrosomes and kinetochores, and induce mitotic block and cancer cell killing. At the structural level, its unmasked active form, Allopole-A, bound to a deep Trp-Phe-lined pocket occluded by a latch-like loop, whose adjoining region was required for securely retaining a ligand anchored to the phospho-binding cleft. Allopole-A binding completely dislodged the L2 loop, an event that appeared sufficient to trigger the dissociation of a phospholigand and inhibit PBD-dependent Plk1 function during mitosis. Given Allopole's high specificity and antiproliferative potency, this study is expected to open an unexplored avenue for developing Plk1 PBD-specific anticancer therapeutic agents.

Targeting homologous recombination deficiency in uterine leiomyosarcoma.

BACKGROUND: Uterine leiomyosarcoma (uLMS) is a rare and aggressive gynaecological malignancy, with individuals with advanced uLMS having a five-year survival of < 10%. Mutations in the homologous recombination (HR) DNA repair pathway have been observed in ~ 10% of uLMS cases, with reports of some individuals benefiting from poly (ADP-ribose) polymerase (PARP) inhibitor (PARPi) therapy, which targets this DNA repair defect. In this report, we screened individuals with uLMS, accrued nationally, for mutations in the HR repair pathway and explored new approaches to therapeutic targeting. METHODS: A cohort of 58 individuals with uLMS were screened for HR Deficiency (HRD) using whole genome sequencing (WGS), whole exome sequencing (WES) or NGS panel testing. Individuals identified to have HRD uLMS were offered PARPi therapy and clinical outcome details collected. Patient-derived xenografts (PDX) were generated for therapeutic targeting. RESULTS: All 13 uLMS samples analysed by WGS had a dominant COSMIC mutational signature 3; 11 of these had high genome-wide loss of heterozygosity (LOH) (> 0.2) but only two samples had a CHORD score > 50%, one of which had a homozygous pathogenic alteration in an HR gene (deletion in BRCA2). A further three samples harboured homozygous HRD alterations (all deletions in BRCA2), detected by WES or panel sequencing, with 5/58 (9%) individuals having HRD uLMS. All five individuals gained access to PARPi therapy. Two of three individuals with mature clinical follow up achieved a complete response or durable partial response (PR) with the subsequent addition of platinum to PARPi upon minor progression during initial PR on PARPi. Corresponding PDX responses were most rapid, complete and sustained with the PARP1-specific PARPi, AZD5305, compared with either olaparib alone or olaparib plus cisplatin, even in a paired sample of a BRCA2-deleted PDX, derived following PARPi therapy in the patient, which had developed PARPi-resistance mutations in PRKDC, encoding DNA-PKcs. CONCLUSIONS: Our work demonstrates the value of identifying HRD for therapeutic targeting by PARPi and platinum in individuals with the aggressive rare malignancy, uLMS and suggests that individuals with HRD uLMS should be included in trials of PARP1-specific PARPi.

Six-year experience of Australia's first dedicated cancer of unknown primary clinic.

BACKGROUND: Diagnosis and management of cancers of unknown primary (CUP) remain challenging. This study examines the referral patterns, management and outcomes of patients referred to Australia's first dedicated CUP clinic. METHODS: Retrospective medical record review was conducted for patients seen at the Peter MacCallum Cancer Centre CUP clinic between July 2014 and August 2020. Overall survival (OS) was analysed for patients with a CUP diagnosis where treatment information was available. RESULTS: Of 361 patients referred, fewer than half had completed diagnostic work-up at the time of referral. A diagnosis of CUP was established in 137 (38%), malignancy other than CUP in 177 (49%) and benign pathology in 36 (10%) patients. Genomic testing was successfully completed in 62% of patients with initial provisional CUP and impacted management in 32% by identifying a tissue of origin or actionable genomic alteration. The use of site-specific, targeted therapy or immunotherapy was independently associated with longer OS compared to empirical chemotherapy. CONCLUSION: Our specialised CUP clinic facilitated diagnostic work-up among patients with suspected malignancy and provided access to genomic testing and clinical trials for patients with a CUP diagnosis, all of which are important to improve outcomes in this patient population.

Estrogen receptor beta expression in triple negative breast cancers is not associated with recurrence or survival.

BACKGROUND: Triple negative BCa (TNBC) is defined by a lack of expression of estrogen (ERα), progesterone (PgR) receptors and human epidermal growth factor receptor 2 (HER2) as assessed by protein expression and/or gene amplification. It makes up ~ 15% of all BCa and often has a poor prognosis. TNBC is not treated with endocrine therapies as ERα and PR negative tumors in general do not show benefit. However, a small fraction of the true TNBC tumors do show tamoxifen sensitivity, with those expressing the most common isoform of ERß1 having the most benefit. Recently, the antibodies commonly used to assess ERß1 in TNBC have been found to lack specificity, which calls into question available data regarding the proportion of TNBC that express ERß1 and any relationship to clinical outcome. METHODS: To confirm the true frequency of ERß1 in TNBC we performed robust ERß1 immunohistochemistry using the specific antibody CWK-F12 ERß1 on 156 primary TNBC cancers from patients with a median of 78 months (range 0.2-155 months) follow up. RESULTS: We found that high expression of ERß1 was not associated with increased recurrence or survival when assessed as percentage of ERß1 positive tumor cells or as Allred > 5. In contrast, the non-specific PPG5-10 antibody did show an association with recurrence and survival. CONCLUSIONS: Our data indicate that ERß1 expression in TNBC tumours does not associate with prognosis.

Identification errors in medical research: Privacy at all costs?

In laboratory medicine, a misidentified patient sample can lead to an incorrect tissue diagnosis, a potentially fatal blood transfusion error or other serious adverse events. Although well characterised in routine patient care, the overall impacts of misidentification errors in the clinical research setting are less conspicuous but potentially greater, with downstream effects that may extend beyond care at an individual level. When data discrepancies or queries arise in clinical trial data then a data clarification form (DCF) is issued to the researcher by the overseeing trial coordinator or sponsor. Higher rates of DCF's are sometimes used as a crude surrogate marker of poorer trial quality. However, data is scarce on misidentification rates in clinical trials. In five clinical trials involving 822 histology or blood specimens analysed by our pathology department, DCF's were issued for 21% (174) of specimens. Amongst these 67% (117 / 174) were related to sample identification. Although these errors were recognised before data was compromised or an adverse event occurred, they highlight an alarming lack of stringency of use of patient identifiers in the research setting. We therefore propose the use of an appropriate number of de-identified data points and a formalised specimen accession process as employed in routine care to mitigate misidentification errors and their impact in clinical research. Increased recognition in the research community of the likely effect of truncating or reducing the number of patient identifiers is needed to minimise misidentification errors in the research setting.

Australian Genomics: Outcomes of a 5-year national program to accelerate the integration of genomics in healthcare.

Australian Genomics is a national collaborative partnership of more than 100 organizations piloting a whole-of-system approach to integrating genomics into healthcare, based on federation principles. In the first five years of operation, Australian Genomics has evaluated the outcomes of genomic testing in more than 5,200 individuals across 19 rare disease and cancer flagship studies. Comprehensive analyses of the health economic, policy, ethical, legal, implementation and workforce implications of incorporating genomics in the Australian context have informed evidence-based change in policy and practice, resulting in national government funding and equity of access for a range of genomic tests. Simultaneously, Australian Genomics has built national skills, infrastructure, policy, and data resources to enable effective data sharing to drive discovery research and support improvements in clinical genomic delivery.