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.

Prioritisation by FIT to mitigate the impact of delays in the 2-week wait colorectal cancer referral pathway during the COVID-19 pandemic: a UK modelling study.

OBJECTIVE: To evaluate the impact of faecal immunochemical testing (FIT) prioritisation to mitigate the impact of delays in the colorectal cancer (CRC) urgent diagnostic (2-week-wait (2WW)) pathway consequent from the COVID-19 pandemic. DESIGN: We modelled the reduction in CRC survival and life years lost resultant from per-patient delays of 2-6 months in the 2WW pathway. We stratified by age group, individual-level benefit in CRC survival versus age-specific nosocomial COVID-19-related fatality per referred patient undergoing colonoscopy. We modelled mitigation strategies using thresholds of FIT triage of 2, 10 and 150 µg Hb/g to prioritise 2WW referrals for colonoscopy. To construct the underlying models, we employed 10-year net CRC survival for England 2008-2017, 2WW pathway CRC case and referral volumes and per-day-delay HRs generated from observational studies of diagnosis-to-treatment interval. RESULTS: Delay of 2/4/6 months across all 11 266 patients with CRC diagnosed per typical year via the 2WW pathway were estimated to result in 653/1419/2250 attributable deaths and loss of 9214/20 315/32 799 life years. Risk-benefit from urgent investigatory referral is particularly sensitive to nosocomial COVID-19 rates for patients aged >60. Prioritisation out of delay for the 18% of symptomatic referrals with FIT >10 µg Hb/g would avoid 89% of these deaths attributable to presentational/diagnostic delay while reducing immediate requirement for colonoscopy by >80%. CONCLUSIONS: Delays in the pathway to CRC diagnosis and treatment have potential to cause significant mortality and loss of life years. FIT triage of symptomatic patients in primary care could streamline access to colonoscopy, reduce delays for true-positive CRC cases and reduce nosocomial COVID-19 mortality in older true-negative 2WW referrals. However, this strategy offers benefit only in short-term rationalisation of limited endoscopy services: the appreciable false-negative rate of FIT in symptomatic patients means most colonoscopies will still be required.

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.

Analysis of 153 115 patients with hematological malignancies refines the spectrum of familial risk.

Estimating familial cancer risks is clinically important in being able to discriminate between individuals in the population at differing risk for malignancy. To gain insight into the familial risk for the different hematological malignancies and their possible inter-relationship, we analyzed data on more than 16 million individuals from the Swedish Family-Cancer Database. After identifying 153 115 patients diagnosed with a primary hematological malignancy, we quantified familial relative risks (FRRs) by calculating standardized incident ratios (SIRs) in 391 131 of their first-degree relatives. The majority of hematological malignancies showed increased FRRs for the same tumor type, with the highest FRRs being observed for mixed cellularity Hodgkin lymphoma (SIR, 16.7), lymphoplasmacytic lymphoma (SIR, 15.8), and mantle cell lymphoma (SIR, 13.3). There was evidence for pleiotropic relationships; notably, chronic lymphocytic leukemia was associated with an elevated familial risk for other B-cell tumors and myeloproliferative neoplasms. Collectively, these data provide evidence for shared etiological factors for many hematological malignancies and provide information for identifying individuals at increased risk, as well as informing future gene discovery initiatives.

Effect of delays in the 2-week-wait cancer referral pathway during the COVID-19 pandemic on cancer survival in the UK: a modelling study.

BACKGROUND: During the COVID-19 lockdown, referrals via the 2-week-wait urgent pathway for suspected cancer in England, UK, are reported to have decreased by up to 84%. We aimed to examine the impact of different scenarios of lockdown-accumulated backlog in cancer referrals on cancer survival, and the impact on survival per referred patient due to delayed referral versus risk of death from nosocomial infection with severe acute respiratory syndrome coronavirus 2. METHODS: In this modelling study, we used age-stratified and stage-stratified 10-year cancer survival estimates for patients in England, UK, for 20 common tumour types diagnosed in 2008-17 at age 30 years and older from Public Health England. We also used data for cancer diagnoses made via the 2-week-wait referral pathway in 2013-16 from the Cancer Waiting Times system from NHS Digital. We applied per-day hazard ratios (HRs) for cancer progression that we generated from observational studies of delay to treatment. We quantified the annual numbers of cancers at stage I-III diagnosed via the 2-week-wait pathway using 2-week-wait age-specific and stage-specific breakdowns. From these numbers, we estimated the aggregate number of lives and life-years lost in England for per-patient delays of 1-6 months in presentation, diagnosis, or cancer treatment, or a combination of these. We assessed three scenarios of a 3-month period of lockdown during which 25%, 50%, and 75% of the normal monthly volumes of symptomatic patients delayed their presentation until after lockdown. Using referral-to-diagnosis conversion rates and COVID-19 case-fatality rates, we also estimated the survival increment per patient referred. FINDINGS: Across England in 2013-16, an average of 6281 patients with stage I-III cancer were diagnosed via the 2-week-wait pathway per month, of whom 1691 (27%) would be predicted to die within 10 years from their disease. Delays in presentation via the 2-week-wait pathway over a 3-month lockdown period (with an average presentational delay of 2 months per patient) would result in 181 additional lives and 3316 life-years lost as a result of a backlog of referrals of 25%, 361 additional lives and 6632 life-years lost for a 50% backlog of referrals, and 542 additional lives and 9948 life-years lost for a 75% backlog in referrals. Compared with all diagnostics for the backlog being done in month 1 after lockdown, additional capacity across months 1-3 would result in 90 additional lives and 1662 live-years lost due to diagnostic delays for the 25% backlog scenario, 183 additional lives and 3362 life-years lost under the 50% backlog scenario, and 276 additional lives and 5075 life-years lost under the 75% backlog scenario. However, a delay in additional diagnostic capacity with provision spread across months 3-8 after lockdown would result in 401 additional lives and 7332 life-years lost due to diagnostic delays under the 25% backlog scenario, 811 additional lives and 14 873 life-years lost under the 50% backlog scenario, and 1231 additional lives and 22 635 life-years lost under the 75% backlog scenario. A 2-month delay in 2-week-wait investigatory referrals results in an estimated loss of between 0·0 and 0·7 life-years per referred patient, depending on age and tumour type. INTERPRETATION: Prompt provision of additional capacity to address the backlog of diagnostics will minimise deaths as a result of diagnostic delays that could add to those predicted due to expected presentational delays. Prioritisation of patient groups for whom delay would result in most life-years lost warrants consideration as an option for mitigating the aggregate burden of mortality in patients with cancer. FUNDING: None.

Second primary cancers in non-Hodgkin lymphoma: Family history and survival.

Second primary cancers (SPCs) account for an increasing proportion of all cancer diagnoses and family history of cancer may be a risk factor for SPCs. Using the Swedish Family-Cancer Database on non-Hodgkin lymphoma (NHL), we assessed the influence of family history on risk of SPCs and of SPCs on survival. NHL patients were identified from the years 1958 to 2015 and generalized Poisson models were used to calculate relative risks (RRs) for SPCs and familial SPCs. Among 14,393 NHL patients, a total of 1,866 (13.0%) were diagnosed with SPC. Familial risk of nine particular cancers was associated with risks of these cancers as SPCs, with twofold to fivefold increase in RRs. At the end of a 25-year follow-up period, the survival probability for persons with SPC was only 20% of that for patients without SPC; the hazard ratio for SPC was 1.59 (95% CI: 1.46-1.72). Survival could be predicted by the prognostic groups based on first cancers and HRs increase systematically with worse prognosis yielding a trend of p = 4.6 × 10-5 . SPCs had deleterious consequences for survival in NHL patients. Family history was associated with increasing numbers of SPCs. Prevention of SPCs and their early detection is an important target in the overall strategy to improve survival in NHL patients. Counseling for avoidance of risk factors and targeted screening based on family history are feasible steps in risk reduction.

Genome-wide association study implicates immune dysfunction in the development of Hodgkin lymphoma.

To further our understanding of inherited susceptibility to Hodgkin lymphoma (HL), we performed a meta-analysis of 7 genome-wide association studies totaling 5325 HL cases and 22 423 control patients. We identify 5 new HL risk loci at 6p21.31 (rs649775; P = 2.11 × 10-10), 6q23.3 (rs1002658; P = 2.97 × 10-8), 11q23.1 (rs7111520; P = 1.44 × 10-11), 16p11.2 (rs6565176; P = 4.00 × 10-8), and 20q13.12 (rs2425752; P = 2.01 × 10-8). Integration of gene expression, histone modification, and in situ promoter capture Hi-C data at the 5 new and 13 known risk loci implicates dysfunction of the germinal center reaction, disrupted T-cell differentiation and function, and constitutive NF-κB activation as mechanisms of predisposition. These data provide further insights into the genetic susceptibility and biology of HL.

Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes.

BACKGROUND: While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and search for novel risk regions, we performed a multi-tissue transcriptome-wide association study (TWAS). RESULTS: GWAS data on 7319 MM cases and 234,385 controls was integrated with Genotype-Tissue Expression Project (GTEx) data assayed in 48 tissues (sample sizes, N = 80-491), including lymphocyte cell lines and whole blood, to predict gene expression. We identified 108 genes at 13 independent regions associated with MM risk, all of which were in 1 Mb of known MM GWAS risk variants. Of these, 94 genes, located in eight regions, had not previously been considered as a candidate gene for that locus. CONCLUSIONS: Our findings highlight the value of leveraging expression data from multiple tissues to identify candidate genes responsible for GWAS associations which provide insight into MM tumorigenesis. Among the genes identified, a number have plausible roles in MM biology, notably APOBEC3C, APOBEC3H, APOBEC3D, APOBEC3F, APOBEC3G, or have been previously implicated in other malignancies. The genes identified in this TWAS can be explored for follow-up and validation to further understand their role in MM biology.

Regions of homozygosity as risk factors for multiple myeloma.

Genomic regions of homozygosity (ROH), detectable in outbred populations, have been implicated as determinants of inherited risk. To examine whether ROH is associated with risk of multiple myeloma (MM), we performed whole-genome homozygosity analysis using single-nucleotide polymorphism genotype data from 2,282 MM cases and 5,197 controls, with replication in an additional 878 MM cases and 7,083 controls. Globally, the distribution of ROH between cases and controls was not significantly different. However, one ROH at chromosome 9q21, harboring the B-cell transcription factor gene KLF9, showed evidence of a consistent association and may therefore warrant further investigation as a candidate risk factor for MM. Overall, our analysis provides little support for a homozygosity signature being a significant factor in MM risk.

Second primary cancers in patients with acute lymphoblastic, chronic lymphocytic and hairy cell leukaemia.

Improvement of survival in lymphocytic leukaemia has been accompanied by the occurrence of second primary cancer (SPCs). Based on Swedish Family Cancer Database, we applied bi-directional analyses in which relative risks (RRs) were calculated for any SPCs in patients with chronic lymphocytic leukaemia (CLL), acute lymphoblastic leukaemia (ALL) and hairy cell leukaemia (HCL) and the risks of these leukaemias as SPCs. After CLL, RRs were significant for 20 SPCs, and high for skin squamous cell cancer (24·58 for in situ and 7·63 for invasive), Merkel cell carcinoma (14·36), Hodgkin lymphoma (7·16) and Kaposi sarcoma (6·76). Conversely, 15 CLL cancer pairs were reciprocally increased. The increased risks were reciprocal for ALL and four cancers. RR for ALL was 15·35 after myeloid neoplasia. HCL showed reciprocally increased RRs with non-Hodgkin lymphoma and melanoma. The concordance between RRs for bi-directional associations between CLL and different cancers, and HCL and different cancers was highly significant. For CLL (also for HCL), the bi-directional risks with skin cancers and other immune-related cancers suggest the probable involvement of immune dysfunction. For ALL, treatment may contribute to risks of multiple SPCs. Increased risk of ALL after haematological neoplasms may indicate bone marrow dysfunction. These findings may help guide treatment decisions and prognostic assessment.

Second primary cancers in non-Hodgkin lymphoma: Bidirectional analyses suggesting role for immune dysfunction.

Second primary cancers (SPCs) account for an increasing proportion of all cancer diagnoses. It is unlikely that prior therapy is solely responsible for SPC risk. To investigate risk of SPC after diagnosis of non-Hodgkin lymphoma (NHL) and 10 of its subtypes we conducted a novel bidirectional analysis, SPCs after NHL and NHL as SPC. Using the Swedish Family-Cancer Database, we identified 19,833 individuals with primary NHL diagnosed between 1993 and 2015. We calculated relative risks (RRs) of SPCs in NHL survivors and, for bi-directional analysis, risk of NHL as SPC. The overall RRs were significantly bidirectionally increased for NHL and 7 cancers. After diagnosis of NHL risks were increased for upper aerodigestive tract (RR = 1.96), colorectal (1.35), kidney (3.10), bladder (1.54) and squamous cell skin cancer (SCC) (4.12), melanoma (1.98) and Hodgkin lymphoma (9.38). The concordance between RRs for each bidirectional association between NHL and 31 different cancers was highly significant (r = 0.86, p < 0.0001). Melanoma was bidirectionally associated with all 10 subtypes of NHL. The observed bidirectional associations between NHL and cancer suggest that therapy-related carcinogenic mechanisms cannot solely explain the findings. Considering that skin SCC and melanoma are usually treated by surgery and that these cancers and NHL are most responsive of any cancer to immune suppression, the consistent bidirectional results provide population-level evidence that immune suppressed state is a key underlying mechanism in the context of SPCs. Furthermore, the quantified risks for NHL subtypes have direct clinical application in the management of NHL patients.

Influence of obesity-related risk factors in the aetiology of glioma.

BACKGROUND: Obesity and related factors have been implicated as possible aetiological factors for the development of glioma in epidemiological observation studies. We used genetic markers in a Mendelian randomisation framework to examine whether obesity-related traits influence glioma risk. This methodology reduces bias from confounding and is not affected by reverse causation. METHODS: Genetic instruments were identified for 10 key obesity-related risk factors, and their association with glioma risk was evaluated using data from a genome-wide association study of 12,488 glioma patients and 18,169 controls. The estimated odds ratio of glioma associated with each of the genetically defined obesity-related traits was used to infer evidence for a causal relationship. RESULTS: No convincing association with glioma risk was seen for genetic instruments for body mass index, waist-to-hip ratio, lipids, type-2 diabetes, hyperglycaemia or insulin resistance. Similarly, we found no evidence to support a relationship between obesity-related traits with subtypes of glioma-glioblastoma (GBM) or non-GBM tumours. CONCLUSIONS: This study provides no evidence to implicate obesity-related factors as causes of glioma.

Impact of atopy on risk of glioma: a Mendelian randomisation study.

BACKGROUND: An inverse relationship between allergies with glioma risk has been reported in several but not all epidemiological observational studies. We performed an analysis of genetic variants associated with atopy to assess the relationship with glioma risk using Mendelian randomisation (MR), an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations. METHODS: Two-sample MR was undertaken using genome-wide association study data. We used single nucleotide polymorphisms (SNPs) associated with atopic dermatitis, asthma and hay fever, IgE levels, and self-reported allergy as instrumental variables. We calculated MR estimates for the odds ratio (OR) for each risk factor with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighting (IVW), maximum likelihood estimation (MLE), weighted median estimate (WME) and mode-based estimate (MBE) methods. Violation of MR assumptions due to directional pleiotropy were sought using MR-Egger regression and HEIDI-outlier analysis. RESULTS: Under IVW, MLE, WME and MBE methods, associations between glioma risk with asthma and hay fever, self-reported allergy and IgE levels were non-significant. An inverse relationship between atopic dermatitis and glioma risk was found by IVW (OR 0.96, 95% confidence interval (CI) 0.93-1.00, P = 0.041) and MLE (OR 0.96, 95% CI 0.94-0.99, P = 0.003), but not by WME (OR 0.96, 95% CI 0.91-1.01, P = 0.114) or MBE (OR 0.97, 95% CI 0.92-1.02, P = 0.194). CONCLUSIONS: Our investigation does not provide strong evidence for relationship between atopy and the risk of developing glioma, but findings do not preclude a small effect in relation to atopic dermatitis. Our analysis also serves to illustrate the value of using several MR methods to derive robust conclusions.

Mendelian randomisation implicates hyperlipidaemia as a risk factor for colorectal cancer.

While elevated blood cholesterol has been associated with an increased risk of colorectal cancer (CRC) in observational studies, causality is uncertain. Here we apply a Mendelian randomisation (MR) analysis to examine the potential causal relationship between lipid traits and CRC risk. We used single nucleotide polymorphisms (SNPs) associated with blood levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) as instrumental variables (IV). We calculated MR estimates for each risk factor with CRC using SNP-CRC associations from 9,254 cases and 18,386 controls. Genetically predicted higher TC was associated with an elevated risk of CRC (odds ratios (OR) per unit SD increase = 1.46, 95% confidence interval [CI]: 1.20-1.79, p = 1.68 × 10-4 ). The pooled ORs for LDL, HDL, and TG were 1.05 (95% CI: 0.92-1.18, p = 0.49), 0.94 (95% CI: 0.84-1.05, p = 0.27), and 0.98 (95% CI: 0.85-1.12, p = 0.75) respectively. A genetic risk score for 3-hydoxy-3-methylglutaryl-coenzyme A reductase (HMGCR) to mimic the effects of statin therapy was associated with a reduced CRC risk (OR = 0.69, 95% CI: 0.49-0.99, p = 0.046). This study supports a causal relationship between higher levels of TC with CRC risk, and a further rationale for implementing public health strategies to reduce the prevalence of hyperlipidaemia.

Candidate gene association studies and risk of Hodgkin lymphoma: a systematic review and meta-analysis.

To evaluate the contribution of association studies of candidate polymorphisms to inherited predisposition to Hodgkin lymphoma (HL), we conducted a systematic review and meta-analysis of published case-control studies. Of the variants examined more than once in candidate gene association studies, we identified 21 studies that reported on 12 polymorphic variants in 10 genes. Data were also extracted from a published genome wide association study to allow analysis of an additional 47 variants in a further 30 genes. Promising associations were seen in nine of the variants (p < 0.05). Given that the estimated false positive report probabilities (FPRPs) for all associations are high (i.e. FPRP > 0.2), these findings should be interpreted with caution. While studies of candidate polymorphisms may be an attractive means of identifying risk factors for HL, future studies should employ sample sizes adequately powered to identify variants having only modest effects on HL risk. Furthermore, because of aetiological heterogeneity within HL, stratification of genotyping according to age, tumour Epstein-Barr virus status and histology is essential. Copyright © 2015 John Wiley & Sons, Ltd.

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.

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.