PIK3CA mutation enrichment and quantitation from blood and tissue

PIK3CA is one of the two most frequently mutated genes in breast cancers, occurring in 30-40% of cases. Four frequent 'hotspot' PIK3CA mutations (E542K, E545K, H1047R and H1047L) account for 80-90% of all PIK3CA mutations in human malignancies and represent predictive biomarkers. Here we describe a PIK3CA mutation specific nuclease-based enrichment assay, which combined with a low-cost real-time qPCR detection method, enhances assay detection sensitivity from 5% for E542K and 10% for E545K to 0.6%, and from 5% for H1047R to 0.3%. Moreover, we present a novel flexible prediction method to calculate initial mutant allele frequency in tissue biopsy and blood samples with low mutant fraction. These advancements demonstrated a quick, accurate and simple detection and quantitation of PIK3CA mutations in two breast cancer cohorts (first cohort n = 22, second cohort n = 25). Hence this simple, versatile and informative workflow could be applicable for routine diagnostic testing where quantitative results are essential, e.g. disease monitoring subject to validation in a substantial future study

Genomic profile of advanced breast cancer in circulating tumour DNA.

The genomics of advanced breast cancer (ABC) has been described through tumour tissue biopsy sequencing, although these approaches are limited by geographical and temporal heterogeneity. Here we use plasma circulating tumour DNA sequencing to interrogate the genomic profile of ABC in 800 patients in the plasmaMATCH trial. We demonstrate diverse subclonal resistance mutations, including enrichment of HER2 mutations in HER2 positive disease, co-occurring ESR1 and MAP kinase pathway mutations in HR + HER2- disease that associate with poor overall survival (p = 0.0092), and multiple PIK3CA mutations in HR + disease that associate with short progression free survival on fulvestrant (p = 0.0036). The fraction of cancer with a mutation, the clonal dominance of a mutation, varied between genes, and within hotspot mutations of ESR1 and PIK3CA. In ER-positive breast cancer subclonal mutations were enriched in an APOBEC mutational signature, with second hit PIK3CA mutations acquired subclonally and at sites characteristic of APOBEC mutagenesis. This study utilises circulating tumour DNA analysis in a large clinical trial to demonstrate the subclonal diversification of pre-treated advanced breast cancer, identifying distinct mutational processes in advanced ER-positive breast cancer, and novel therapeutic opportunities

Results of the c-TRAK TN trial: a clinical trial utilising ctDNA mutation tracking to detect molecular residual disease and trigger intervention in patients with moderate and high-risk early stage triple negative breast cancer

Background: Post-treatment detection of circulating tumour DNA (ctDNA) in early-stage triple negative breast cancer (TNBC) patients predicts high risk of relapse. c-TRAK-TN assessed the utility of prospective ctDNA surveillance in TNBC and the activity of pembrolizumab in patients with ctDNA detected (ctDNA+). Patients and methods: c-TRAK-TN, a multi-centre phase II trial, with integrated prospective ctDNA surveillance by digital PCR, enrolled patients with early-stage TNBC and residual disease following neoadjuvant chemotherapy, or, stage II/III with adjuvant chemotherapy. ctDNA surveillance comprised three monthly blood sampling to 12 months (18 months if samples were missed due to COVID), and ctDNA+ patients were randomised 2:1; intervention:observation. ctDNA results were blinded unless patients were allocated to intervention, when staging scans were done and those free of recurrence were offered pembrolizumab. A protocol amendment (16/09/2020) closed the observation group; all subsequent ctDNA+ patients were allocated to intervention. Co-primary endpoints were i) ctDNA detection rate ii) sustained ctDNA clearance rate on pembrolizumab (NCT03145961). Results: 208 patients registered between 30/01/18 - 06/12/19, 185 had tumour sequenced, 171 (92·4%) had trackable mutations, and 161 entered ctDNA surveillance. Rate of ctDNA detection by 12 months was 27·3% (44/161,95%CI:20·6-34·9). Seven patients relapsed without prior ctDNA detection. 45 patients entered the therapeutic component (intervention n=31; observation n=14; 1 observation patient was re-allocated to intervention following protocol amendment). Of patients allocated intervention, 72% (23/32) had metastases on staging at time of ctDNA+, and 4 patients declined pembrolizumab. Of the five patients who commenced pembrolizumab, none achieved sustained ctDNA clearance. Conclusion: c-TRAK-TN is the first prospective study to assess whether ctDNA assays have clinical utility in guiding therapy in TNBC. Patients had a high rate of metastatic disease on ctDNA detection. Findings have implications for future trial design, emphasising the importance of commencing ctDNA testing early, with more sensitive and/or frequent ctDNA testing regimes

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Reproducibility of Digital PCR Assays for Circulating Tumor DNA Analysis in Advanced Breast Cancer

<div><p>Circulating tumor DNA (ctDNA) analysis has the potential to allow non-invasive analysis of tumor mutations in advanced cancer. In this study we assessed the reproducibility of digital PCR (dPCR) assays of circulating tumor DNA in a cohort of patients with advanced breast cancer and assessed delayed plasma processing using cell free DNA preservative tubes. We recruited a cohort of 96 paired samples from 71 women with advanced breast cancer who had paired blood samples processed either immediately or delayed in preservative tubes with processing 48–72 hours after collection. Plasma DNA was analysed with multiplex digital PCR (mdPCR) assays for hotspot mutations in <i>PIK3CA</i>, <i>ESR1</i> and <i>ERBB2</i>, and for <i>AKT1</i> E17K. There was 94.8% (91/96) agreement in mutation calling between immediate and delayed processed tubes, kappa 0.88 95% CI 0.77–0.98). Discordance in mutation calling resulted from low allele frequency and likely stochastic effects. In concordant samples there was high correlation in mutant copies per ml plasma (r² = 0.98; p<0.0001). There was elevation of total cell free plasma DNA concentrations in 10.3% of delayed processed tubes, although overall quantification of total cell free plasma DNA had similar prognostic effects in immediate (HR 3.6) and delayed (HR 3.0) tubes. There was moderate agreement in changes in allele fraction between sequential samples in quantitative mutation tracking (r = 0.84, p = 0.0002). Delayed processing of samples using preservative tubes allows for centralized ctDNA digital PCR mutation screening in advanced breast cancer. The potential of preservative tubes in quantitative mutation tracking requires further research.</p></div

Early circulating tumor DNA dynamics and clonal selection with palbociclib and fulvestrant for breast cancer

Circulating tumor DNA (ctDNA) may provide a prediction of treatment response, but could be impacted by tumor heterogeneity. Here, the authors investigate ctDNA in CDK4/6 inhibitor treatment in advanced breast cancer, finding ctDNA levels predict progression-free survival and anticipate clonal selection

Genomic profile of advanced breast cancer in circulating tumour DNA.

The genomics of advanced breast cancer (ABC) has been described through tumour tissue biopsy sequencing, although these approaches are limited by geographical and temporal heterogeneity. Here we use plasma circulating tumour DNA sequencing to interrogate the genomic profile of ABC in 800 patients in the plasmaMATCH trial. We demonstrate diverse subclonal resistance mutations, including enrichment of HER2 mutations in HER2 positive disease, co-occurring ESR1 and MAP kinase pathway mutations in HR + HER2- disease that associate with poor overall survival (p = 0.0092), and multiple PIK3CA mutations in HR + disease that associate with short progression free survival on fulvestrant (p = 0.0036). The fraction of cancer with a mutation, the clonal dominance of a mutation, varied between genes, and within hotspot mutations of ESR1 and PIK3CA. In ER-positive breast cancer subclonal mutations were enriched in an APOBEC mutational signature, with second hit PIK3CA mutations acquired subclonally and at sites characteristic of APOBEC mutagenesis. This study utilises circulating tumour DNA analysis in a large clinical trial to demonstrate the subclonal diversification of pre-treated advanced breast cancer, identifying distinct mutational processes in advanced ER-positive breast cancer, and novel therapeutic opportunities

Agreement in change in mutation abundance in sequential samples between immediate EDTA and delayed Streck samples.

<p>A. Agreement in fold change in mutation allele frequency between immediate and delayed samples in sequential samples from 6 patients (r = 0.85, p = 0.0002). B. Agreement in fold change in mutant copies per ml between immediate and delayed samples in sequential samples from 6 patients (r = 0.84, p = 0.0003).</p