Many forms of cancer have multiple subtypes with different causes and clinical outcomes. Somatic tumor genome sequences provide a rich new source of data for uncovering these subtypes but have proven ...difficult to compare, as two tumors rarely share the same mutations. Here we introduce network-based stratification (NBS), a method to integrate somatic tumor genomes with gene networks. This approach allows for stratification of cancer into informative subtypes by clustering together patients with mutations in similar network regions. We demonstrate NBS in ovarian, uterine and lung cancer cohorts from The Cancer Genome Atlas. For each tissue, NBS identifies subtypes that are predictive of clinical outcomes such as patient survival, response to therapy or tumor histology. We identify network regions characteristic of each subtype and show how mutation-derived subtypes can be used to train an mRNA expression signature, which provides similar information in the absence of DNA sequence.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The anti-cancer immune response against mutated peptides of potential immunological relevance (neoantigens) is primarily attributed to MHC-I-restricted cytotoxic CD8+ T cell responses. ...MHC-II-restricted CD4+ T cells also drive anti-tumor responses, but their relation to neoantigen selection and tumor evolution has not been systematically studied. Modeling the potential of an individual’s MHC-II genotype to present 1,018 driver mutations in 5,942 tumors, we demonstrate that the MHC-II genotype constrains the mutational landscape during tumorigenesis in a manner complementary to MHC-I. Mutations poorly bound to MHC-II are positively selected during tumorigenesis, even more than mutations poorly bound to MHC-I. This emphasizes the importance of CD4+ T cells in anti-tumor immunity. In addition, we observed less inter-patient variation in mutation presentation for MHC-II than for MHC-I. These differences were reflected by age at diagnosis, which was correlated with presentation by MHC-I only. Collectively, our results emphasize the central role of MHC-II presentation in tumor evolution.
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•Patient- and residue-specific PHBR-II score estimates mutation presentation by MHC-II•Tumors are less likely to harbor driver mutations that bind well to MHC-II•Frequent driver mutations are universally poorly presented by MHC-II•MHC-II shows less inter-patient variability but stronger selective effects than MHC-I
Inter-individual variation in MHC-II genotype influences the evolution of patient-specific tumor mutational spectra, emphasizing the key role of CD4+ T cells in anti-tumor immunity.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
To estimate the productivity costs of premature mortality due to cancer in Australia, in aggregate and for the 26 most prevalent cancer sites.
A human capital approach was adopted to estimate the ...long term impacts of Australian cancer deaths in 2003. Using population mortality data, the labour force participation and the present value of lifetime income (PVLI) forgone due to premature mortality was estimated based on individual characteristics at the time of death including age, sex and socioeconomic status. Outcomes were modelled to the year 2030 using economic data from a national microsimulation model. A discount rate of 3% was applied and costs were reported in 2016 Australian dollars.
Premature deaths from cancer in 2003 resulted in 88,000 working years lost and a cost of $4.2 billion in the PVLI forgone. Costs were close to three times higher in males than females due to the higher number of premature deaths in men, combined with higher levels of workforce participation and income. Lung, colorectal and brain cancers accounted for the highest proportion of costs, while testicular cancer was the most costly cancer site per death.
The productivity costs of premature mortality due to cancer are significant. These results provide an economic measure of the cancer burden which may assist decision makers in allocating scare resources amongst competing priorities.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
MHC-I molecules expose the intracellular protein content on the cell surface, allowing T cells to detect foreign or mutated peptides. The combination of six MHC-I alleles each individual carries ...defines the sub-peptidome that can be effectively presented. We applied this concept to human cancer, hypothesizing that oncogenic mutations could arise in gaps in personal MHC-I presentation. To validate this hypothesis, we developed and applied a residue-centric patient presentation score to 9,176 cancer patients across 1,018 recurrent oncogenic mutations. We found that patient MHC-I genotype-based scores could predict which mutations were more likely to emerge in their tumor. Accordingly, poor presentation of a mutation across patients was correlated with higher frequency among tumors. These results support that MHC-I genotype-restricted immunoediting during tumor formation shapes the landscape of oncogenic mutations observed in clinically diagnosed tumors and paves the way for predicting personal cancer susceptibilities from knowledge of MHC-I genotype.
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•Development of a residue-centric patient MHC-I presentation score validated by MS•MHC-I genotype is associated with the appearance of specific oncogenic mutations•Oncogenic mutation frequency negatively correlates with population MHC-I presentation•Recurrent oncogenic mutations are biased toward peptides that are poorly presented
HLA genotype-restricted immunoediting during tumor formation shapes the landscape of oncogenic mutations observed in clinically diagnosed tumors.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
G protein-coupled receptors (GPCRs) are the most widely targeted gene family for Food and Drug Administration (FDA)-approved drugs. To assess possible roles for GPCRs in cancer, we analyzed The ...Cancer Genome Atlas (TCGA) data for mRNA expression, mutations, and copy number variation (CNV) in 20 categories and 45 subtypes of solid tumors and quantified differential expression (DE) of GPCRs by comparing tumors against normal tissue from the Gene Tissue Expression Project (GTEx) database. GPCRs are overrepresented among coding genes with elevated expression in solid tumors. This analysis reveals that most tumor types differentially express >50 GPCRs, including many targets for approved drugs, hitherto largely unrecognized as targets of interest in cancer. GPCR mRNA signatures characterize specific tumor types and correlate with expression of cancer-related pathways. Tumor GPCR mRNA signatures have prognostic relevance for survival and correlate with expression of numerous cancer-related genes and pathways. GPCR expression in tumors is largely independent of staging, grading, metastasis, and/or driver mutations. GPCRs expressed in cancer cell lines largely parallel GPCR expression in tumors. Certain GPCRs are frequently mutated and appear to be hotspots, serving as bellwethers of accumulated genomic damage. CNV of GPCRs is common but does not generally correlate with mRNA expression. Our results suggest a previously underappreciated role for GPCRs in cancer, perhaps as functional oncogenes, biomarkers, surface antigens, and pharmacological targets.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Precision cancer medicine promises to tailor clinical decisions to patients using genomic information. Indeed, successes of drugs targeting genetic alterations in tumors, such as imatinib that ...targets BCR–ABL in chronic myelogenous leukemia, have demonstrated the power of this approach. However, biological systems are complex, and patients may differ not only by the specific genetic alterations in their tumor, but also by more subtle interactions among such alterations. Systems biology and more specifically, network analysis, provides a framework for advancing precision medicine beyond clinical actionability of individual mutations. Here we discuss applications of network analysis to study tumor biology, early methods for N-of-1 tumor genome analysis, and the path for such tools to the clinic.
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•Networks provide a platform for inference from 'omic data.•Many network-based methods have been developed around cancer 'omic data analysis.•Most tumor network analyses rely on cohorts, but some N-of-1 methods exist.•Many challenges remain for applying network-based analysis in clinical settings.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Focal oncogene amplification and rearrangements drive tumor growth and evolution in multiple cancer types. We present AmpliconArchitect (AA), a tool to reconstruct the fine structure of focally ...amplified regions using whole genome sequencing (WGS) and validate it extensively on multiple simulated and real datasets, across a wide range of coverage and copy numbers. Analysis of AA-reconstructed amplicons in a pan-cancer dataset reveals many novel properties of copy number amplifications in cancer. These findings support a model in which focal amplifications arise due to the formation and replication of extrachromosomal DNA. Applying AA to 68 viral-mediated cancer samples, we identify a large fraction of amplicons with specific structural signatures suggestive of hybrid, human-viral extrachromosomal DNA. AA reconstruction, integrated with metaphase fluorescence in situ hybridization (FISH) and PacBio sequencing on the cell-line UPCI:SCC090 confirm the extrachromosomal origin and fine structure of a Forkhead box E1 (FOXE1)-containing hybrid amplicon.
To estimate the productivity impacts of a policy intervention on the prevention of premature mortality due to obesity.
A simulation model of the Australian population over the period from 2003 to ...2030 was developed to estimate productivity gains associated with premature deaths averted due to an obesity prevention intervention that applied a 10% tax on unhealthy foods. Outcome measures were the total working years gained, and the present value of lifetime income (PVLI) gained. Impacts were modelled over the period from 2003 to 2030. Costs are reported in 2018 Australian dollars and a 3% discount rate was applied to all future benefits.
Premature deaths averted due to a junk food tax accounted for over 8,000 additional working years and a $307 million increase in PVLI. Deaths averted in men between the ages of 40 to 59, and deaths averted from ischaemic heart disease, were responsible for the largest gains.
The productivity gains associated with a junk food tax are substantial, accounting for almost twice the value of the estimated savings to the health care system. The results we have presented provide evidence that the adoption of a societal perspective, when compared to a health sector perspective, provides a more comprehensive estimate of the cost-effectiveness of a junk food tax.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Understanding what matters most to patients and their caregivers is fundamental to delivering high-quality care. This systematic review aimed to characterize and appraise the evidence from discrete ...choice experiments eliciting preferences for palliative care.
A systematic literature search was undertaken for publications up until August 2022. Data were synthesized narratively. Thematic analysis was applied to categorize attributes into groups. Attribute development, frequency, and relative importance were analyzed. Subgroup analyses were conducted to compare outcomes between patient and proxy respondents.
Seventeen studies spanning 11 countries were included; 59% of studies solely considered preferences for patients with cancer. A range of respondent groups were represented including patients (76%) and proxies (caregivers 35%, health providers 12%, and the public 18%). A total of 117 individual attributes were extracted and thematically grouped into 8 broad categories and 21 subcategories. Clinical outcomes including quality of life, length of life, and pain control were the most frequently reported attributes, whereas attributes relating to psychosocial components were largely absent. Both patients and proxy respondents prioritized pain control over additional survival time. Nevertheless, there were differences between respondent cohorts in the emphasis on other attributes such as access to care, timely information, and low risk of adverse effects (prioritized by patients), as opposed to cost, quality, and delivery of care (prioritized by proxies).
Our review underscores the vital role of pain control in palliative care; in addition, it shed light on the complexity and relative strength of preferences for various aspects of care from multiple perspectives, which is useful in developing personalized, patient-centered models of care for individuals nearing the end of life.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Global but predictable changes impact the DNA methylome as we age, acting as a type of molecular clock. This clock can be hastened by conditions that decrease lifespan, raising the question of ...whether it can also be slowed, for example, by conditions that increase lifespan. Mice are particularly appealing organisms for studies of mammalian aging; however, epigenetic clocks have thus far been formulated only in humans.
We first examined whether mice and humans experience similar patterns of change in the methylome with age. We found moderate conservation of CpG sites for which methylation is altered with age, with both species showing an increase in methylome disorder during aging. Based on this analysis, we formulated an epigenetic-aging model in mice using the liver methylomes of 107 mice from 0.2 to 26.0 months old. To examine whether epigenetic aging signatures are slowed by longevity-promoting interventions, we analyzed 28 additional methylomes from mice subjected to lifespan-extending conditions, including Prop1
dwarfism, calorie restriction or dietary rapamycin. We found that mice treated with these lifespan-extending interventions were significantly younger in epigenetic age than their untreated, wild-type age-matched controls.
This study shows that lifespan-extending conditions can slow molecular changes associated with an epigenetic clock in mice livers.
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