Whole genome sequencing refines stratification and therapy of patients with clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing for a detailed description of the somatic mutational landscape of ccRCC. We identify candidate driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for therapeutic interventions. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The observations that higher T-cell infiltration is associated with better overall survival and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.

Analysis of 10,478 cancer genomes identifies candidate driver genes and opportunities for precision oncology.

Tumor genomic profiling is increasingly seen as a prerequisite to guide the treatment of patients with cancer. To explore the value of whole-genome sequencing (WGS) in broadening the scope of cancers potentially amenable to a precision therapy, we analysed whole-genome sequencing data on 10,478 patients spanning 35 cancer types recruited to the UK 100,000 Genomes Project. We identified 330 candidate driver genes, including 74 that are new to any cancer. We estimate that approximately 55% of patients studied harbor at least one clinically relevant mutation, predicting either sensitivity or resistance to certain treatments or clinical trial eligibility. By performing computational chemogenomic analysis of cancer mutations we identify additional targets for compounds that represent attractive candidates for future clinical trials. This study represents one of the most comprehensive efforts thus far to identify cancer driver genes in the real world setting and assess their impact on informing precision oncology.

Genetic landscape of interval and screen detected breast cancer.

Interval breast cancers (IBCs) are cancers diagnosed between screening episodes. Understanding the biological differences between IBCs and screen-detected breast-cancers (SDBCs) has the potential to improve mammographic screening and patient management. We analysed and compared the genomic landscape of 288 IBCs and 473 SDBCs by whole genome sequencing of paired tumour-normal patient samples collected as part of the UK 100,000 Genomes Project. Compared to SDBCs, IBCs were more likely to be lobular, higher grade, and triple negative. A more aggressive clinical phenotype was reflected in IBCs displaying features of genomic instability including a higher mutation rate and number of chromosomal structural abnormalities, defective homologous recombination and TP53 mutations. We did not however, find evidence to indicate that IBCs are associated with a significantly different immune response. While IBCs do not represent a unique molecular class of invasive breast cancer they exhibit a more aggressive phenotype, which is likely to be a consequence of the timing of tumour initiation. This information is relevant both with respect to treatment as well as informing the screening interval for mammography.

Phenome-wide Mendelian randomisation analysis of 378,142 cases reveals risk factors for eight common cancers.

For many cancers there are only a few well-established risk factors. Here, we use summary data from genome-wide association studies (GWAS) in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to identify potentially causal relationships for over 3,000 traits. Our outcome datasets comprise 378,142 cases across breast, prostate, colorectal, lung, endometrial, oesophageal, renal, and ovarian cancers, as well as 485,715 controls. We complement this analysis by systematically mining the literature space for supporting evidence. In addition to providing supporting evidence for well-established risk factors (smoking, alcohol, obesity, lack of physical activity), we also find sex steroid hormones, plasma lipids, and telomere length as determinants of cancer risk. A number of the molecular factors we identify may prove to be potential biomarkers. Our analysis, which highlights aetiological similarities and differences in common cancers, should aid public health prevention strategies to reduce cancer burden. We provide a R/Shiny app to visualise findings.

The molecular map of CLL and Richter's syndrome.

Clonal expansion of B-cells, from the early stages of monoclonal B-cell lymphocytosis through to chronic lymphocytic leukemia (CLL), and then in some cases to Richter's syndrome (RS) provides a comprehensive model of cancer evolution, notable for the marked morphological transformation and distinct clinical phenotypes. High-throughput sequencing of large cohorts of patients and single-cell studies have generated a molecular map of CLL and more recently, of RS, yielding fundamental insights into these diseases and of clonal evolution. A selection of CLL driver genes have been functionally interrogated to yield novel insights into the biology of CLL. Such findings have the potential to impact patient care through risk stratification, treatment selection and drug discovery. However, this molecular map remains incomplete, with extant questions concerning the origin of the B-cell clone, the role of the TME, inter- and intra-compartmental heterogeneity and of therapeutic resistance mechanisms. Through the application of multi-modal single-cell technologies across tissues, disease states and clinical contexts, these questions can now be addressed with the answers holding great promise of generating translatable knowledge to improve patient care.

Whole genome sequencing refines stratification and therapy of patients with clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing the most detailed somatic mutational landscape to date. We identify new driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for drug repurposing. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The twin observations that higher T-cell infiltration is associated with better outcome and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.

The impact of risk stratification by polygenic risk and age on breast cancer screening in women aged 40-49 years: a modelling study.

BACKGROUND: Polygenic Risk Scores (PRSs) have been proposed as a mechanism for risk-stratification of screening, increasing efficiency and enabling extension of existing programmes to improve survival in our aging population. We sought to model the impact of three hypothetical programmes of annual breast cancer screening in women aged 40-49 years: screening the PRS-defined high-risk quintile, screening the oldest quintile, and screening the full population. METHODS: In this UK-based modelling study, we used the published estimate of the area under the curve (AUC) of a currently available breast cancer PRS (0·64) to calculate the proportion of cancers captured by the PRS-defined high-risk quintile. We used population size estimates from the Office for National Statistics alongside age-stratified incidence rates of breast cancer, and age or stage-specific survival data from the National Cancer Registry, to build our model. We used stage-specific route-to-diagnosis data to reassign stage-specific survival for screen-detected cancers. Ethics approval was not required. FINDINGS: The PRS-defined high-risk quintile, oldest quintile, and full population capture 37% (n=2811), 29% (n=2198), and 100% (n=7533) of breast cancers occurring in women aged 40-49 each year. Annual screening of each group using digital mammography (sensitivity 70%, specificity 92%) would identify 1968, 1538, and 5273 breast cancers per year, respectively. This corresponds to an improvement in survival of 1·4% (102 deaths averted), 1·1% (80 deaths averted) and 3·6% (274 deaths averted) compared with baseline (no screening). Full population screening would require 4 369 703 mammograms and 354 246 confirmatory tests (breast biopsies) every year, while screening the oldest quintile would require 937 850 mammograms and 76 390 biopsies. Screening the PRS-defined high-risk quintile would require 873 941 mammograms and 71 658 biopsies, in addition to a PRS for all women in the age group (4 369 703). INTERPRETATION: Under favourable assumptions, stratifying screening by PRS rather than age results in modest gains in survival but increases overdiagnoses, logistical complexity, and economic costs. Our study is limited by our modelling parameters (anticipated to maximise survival estimates), including complete uptake of PRS profiling and cancer screening, no interval cancers, and application of screening tools superior to those currently available in the UK. Only with randomised controlled trials, can the uptake, clinical impact, costs, and harms of PRS-stratified screening be definitively assessed. FUNDING: The Wellcome Trust.

Utility of polygenic risk scores in UK cancer screening: a modelling analysis.

BACKGROUND: It is proposed that, through restriction to individuals delineated as high risk, polygenic risk scores (PRSs) might enable more efficient targeting of existing cancer screening programmes and enable extension into new age ranges and disease types. To address this proposition, we present an overview of the performance of PRS tools (ie, models and sets of single nucleotide polymorphisms) alongside harms and benefits of PRS-stratified cancer screening for eight example cancers (breast, prostate, colorectal, pancreas, ovary, kidney, lung, and testicular cancer). METHODS: For this modelling analysis, we used age-stratified cancer incidences for the UK population from the National Cancer Registration Dataset (2016-18) and published estimates of the area under the receiver operating characteristic curve for current, future, and optimised PRS for each of the eight cancer types. For each of five PRS-defined high-risk quantiles (ie, the top 50%, 20%, 10%, 5%, and 1%) and according to each of the three PRS tools (ie, current, future, and optimised) for the eight cancers, we calculated the relative proportion of cancers arising, the odds ratios of a cancer arising compared with the UK population average, and the lifetime cancer risk. We examined maximal attainable rates of cancer detection by age stratum from combining PRS-based stratification with cancer screening tools and modelled the maximal impact on cancer-specific survival of hypothetical new UK programmes of PRS-stratified screening. FINDINGS: The PRS-defined high-risk quintile (20%) of the population was estimated to capture 37% of breast cancer cases, 46% of prostate cancer cases, 34% of colorectal cancer cases, 29% of pancreatic cancer cases, 26% of ovarian cancer cases, 22% of renal cancer cases, 26% of lung cancer cases, and 47% of testicular cancer cases. Extending UK screening programmes to a PRS-defined high-risk quintile including people aged 40-49 years for breast cancer, 50-59 years for colorectal cancer, and 60-69 years for prostate cancer has the potential to avert, respectively, a maximum of 102, 188, and 158 deaths annually. Unstratified screening of the full population aged 48-49 years for breast cancer, 58-59 years for colorectal cancer, and 68-69 years for prostate cancer would use equivalent resources and avert, respectively, an estimated maximum of 80, 155, and 95 deaths annually. These maximal modelled numbers will be substantially attenuated by incomplete population uptake of PRS profiling and cancer screening, interval cancers, non-European ancestry, and other factors. INTERPRETATION: Under favourable assumptions, our modelling suggests modest potential efficiency gain in cancer case detection and deaths averted for hypothetical new PRS-stratified screening programmes for breast, prostate, and colorectal cancer. Restriction of screening to high-risk quantiles means many or most incident cancers will arise in those assigned as being low-risk. To quantify real-world clinical impact, costs, and harms, UK-specific cluster-randomised trials are required. FUNDING: The Wellcome Trust.

Risk factors for eight common cancers revealed from a phenome-wide Mendelian randomisation analysis of 378,142 cases and 485,715 controls.

For many cancers there are few well-established risk factors. Summary data from genome-wide association studies (GWAS) can be used in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to identify causal relationships. We performed a MR-PheWAS of breast, prostate, colorectal, lung, endometrial, oesophageal, renal, and ovarian cancers, comprising 378,142 cases and 485,715 controls. To derive a more comprehensive insight into disease aetiology we systematically mined the literature space for supporting evidence. We evaluated causal relationships for over 3,000 potential risk factors. In addition to identifying well-established risk factors (smoking, alcohol, obesity, lack of physical activity), we provide evidence for specific factors, including dietary intake, sex steroid hormones, plasma lipids and telomere length as determinants of cancer risk. We also implicate molecular factors including plasma levels of IL-18, LAG-3, IGF-1, CT-1, and PRDX1 as risk factors. Our analyses highlight the importance of risk factors that are common to many cancer types but also reveal aetiological differences. A number of the molecular factors we identify have the potential to be biomarkers. Our findings should aid public health prevention strategies to reduce cancer burden. We provide a R/Shiny app (https://mrcancer.shinyapps.io/mrcan/) to visualise findings.

Risk factors for eight common cancers revealed from a phenome-wide Mendelian randomisation analysis of 378,142 cases and 485,715 controls.

For many cancers there are few well-established risk factors. Summary data from genome-wide association studies (GWAS) can be used in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to identify causal relationships. We performed a MR-PheWAS of breast, prostate, colorectal, lung, endometrial, oesophageal, renal, and ovarian cancers, comprising 378,142 cases and 485,715 controls. To derive a more comprehensive insight into disease aetiology we systematically mined the literature space for supporting evidence. We evaluated causal relationships for over 3,000 potential risk factors. In addition to identifying well-established risk factors (smoking, alcohol, obesity, lack of physical activity), we provide evidence for specific factors, including dietary intake, sex steroid hormones, plasma lipids and telomere length as determinants of cancer risk. We also implicate molecular factors including plasma levels of IL-18, LAG-3, IGF-1, CT-1, and PRDX1 as risk factors. Our analyses highlight the importance of risk factors that are common to many cancer types but also reveal aetiological differences. A number of the molecular factors we identify have the potential to be biomarkers. Our findings should aid public health prevention strategies to reduce cancer burden. We provide a R/Shiny app (https://mrcancer.shinyapps.io/mrcan/) to visualise findings.

Survival in hematological malignancies in the Nordic countries through a half century with correlation to treatment.

Studies of survival in hematological malignancies (HMs) have generally shown an improvement over time, although most of these studies are limited by a short follow-up period. Using the NORDCAN database with data from Denmark, Finland, Norway and Sweden, we follow periodic increases in relative survival in seven HMs through half a century up to 2015-2019. Five-year survival improved in all seven HMs, reaching 90% for Hodgkin lymphoma (HL), myeloproliferative neoplasias and chronic lymphocytic leukemia (CLL), 60% for multiple myeloma (MM) and chronic myeloid leukemias (CMLs), 50% for the myelodysplastic syndromes and 30% for acute myeloid leukemia (AML). Improvements in survival over 50 years ranged from 20% to more than 50% units across the different HMs. The likely reasons for such progress include earlier diagnoses, improved risk stratification and advances in treatment. We observed differing temporal trends in improvements in survival. The gradual increases observed in HL, CLL and AML highlight the impact of optimization of existing therapies and improvements in diagnostics and risk stratification, whereas the rapid increases observed in the CMLs and MM highlight the impact of novel therapies. Recent therapeutic advances may further improve survival in HMs where survival remains low such as in AML.

Polygenic risk scores to stratify cancer screening should predict mortality not incidence.

Population-based cancer screening programs such as mammography or colonscopy generally directed at all healthy individuals in a given age stratum. It has recently been proposed that cancer screening could be restricted to a high-risk subgroup based on polygenic risk scores (PRSs) using panels of single-nucleotide polymorphisms (SNPs). These PRSs were, however, generated to predict cancer incidence rather than cancer mortality and will not necessarily address overdiagnosis, a major problem associated with cancer screening programs. We develop a simple net-benefit framework for evaluating screening approaches that incorporates overdiagnosis. We use this methodology to demonstrate that if a PRS does not differentially discriminate between incident and lethal cancer, restricting screening to a subgroup with high scores will only improve screening outcomes in a small number of scenarios. In contrast, restricting screening to a subgroup defined as high-risk based on a marker that is more strongly predictive of mortality than incidence will often afford greater net benefit than screening all eligible individuals. If PRS-based cancer screening is to be effective, research needs to focus on identifying PRSs associated with cancer mortality, an unchartered and clinically-relevant area of research, with a much higher potential to improve screening outcomes.

Epidemiology, genetics and treatment of multiple myeloma and precursor diseases.

Multiple myeloma (MM) is a hematological malignancy caused by the clonal expansion of plasma cells. The incidence of MM worldwide is increasing with greater than 140 000 people being diagnosed with MM per year. Whereas 5-year survival after a diagnosis of MM has improved from 28% in 1975 to 56% in 2012, the disease remains essentially incurable. In this review, we summarize our current understanding of MM including its epidemiology, genetics and biology. We will also provide an overview of MM management that has led to improvements in survival, including recent changes to diagnosis and therapies. Areas of unmet need include the management of patients with high-risk MM, those with reduced performance status and those refractory to standard therapies. Ongoing research into the biology and early detection of MM as well as the development of novel therapies, such as immunotherapies, has the potential to influence MM practice in the future.