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Background Survival rates for ovarian cancer remain poor, and monitoring and prediction of therapeutic response may benefit from additional markers. Ovarian cancers frequently overexpress Folate Receptor alpha (FRα) and the soluble receptor (sFRα) is measurable in blood. Here we investigated sFRα as a potential biomarker. Methods We evaluated sFRα longitudinally, before and during neo-adjuvant, adjuvant and palliative therapies, and tumour FRα expression status by immunohistrochemistry. The impact of free FRα on the efficacy of anti-FRα treatments was evaluated by an antibody-dependent cellular cytotoxicity assay. Results Membrane and/or cytoplasmic FRα staining were observed in 52.7% tumours from 316 ovarian cancer patients with diverse histotypes. Circulating sFRα levels were significantly higher in patients, compared to healthy volunteers, specifically in patients sampled prior to neoadjuvant and palliative treatments. sFRα was associated with FRα cell membrane expression in the tumour. sFRα levels decreased alongside concurrent tumour burden in patients receiving standard therapies. High concentrations of sFRα partly reduced anti-FRα antibody tumour cell killing, an effect overcome by increased antibody doses. Conclusions sFRα may present a non-invasive marker for tumour FRα expression, with the potential for monitoring patient response to treatment. Larger, prospective studies should evaluate FRα for assessing disease burden and response to systemic treatments.

Genome sequencing of cancers often reveals mosaics of different subclones present in the same tumour1–3. Although these are believed to arise according to the principles of somatic evolution, the exact spatial growth patterns and underlying mechanisms remain elusive4,5. Here, to address this need, we developed a workflow that generates detailed quantitative maps of genetic subclone composition across whole-tumour sections. These provide the basis for studying clonal growth patterns, and the histological characteristics, microanatomy and microenvironmental composition of each clone. The approach rests on whole-genome sequencing, followed by highly multiplexed base-specific in situ sequencing, single-cell resolved transcriptomics and dedicated algorithms to link these layers. Applying the base-specific in situ sequencing workflow to eight tissue sections from two multifocal primary breast cancers revealed intricate subclonal growth patterns that were validated by microdissection. In a case of ductal carcinoma in situ, polyclonal neoplastic expansions occurred at the macroscopic scale but segregated within microanatomical structures. Across the stages of ductal carcinoma in situ, invasive cancer and lymph node metastasis, subclone territories are shown to exhibit distinct transcriptional and histological features and cellular microenvironments. These results provide examples of the benefits afforded by spatial genomics for deciphering the mechanisms underlying cancer evolution and microenvironmental ecology.

Supplementary Figure S1. Frequency of genomic aberrations in the KCL TNBC cohort. Supplementary Figure S2. Conceptual diagrams of Scores of Chromosomal Instability Scarring (SCINS). Supplementary Figure S3. Extent and location of SCINS in TNBC. Supplementary Figure S4. Chromosome-wise distribution of SCINS across four TNBC cohorts. Supplementary Figure S5. SCINS-defined tumour classes identify HORMAD1 to be among the top genes linked with Hi-AiCNA/Hi-CnLOH in PrECOG TNBCs. Supplementary Figure S6. Gene expression signatures and HORMAD1 expression. Supplementary Figure S7. Immunofluorescent localisation of HORMAD1 in cell lines. Supplementary Figure S8. Expression of HORMAD1 in breast cancer cell lines and tumour samples. Supplementary Figure S9. HORMAD1 inhibits activity of the DR-GFP HR reporter. Supplementary Figure S10. Effect of HORMAD1 overexpression and knockdown on cell growth and proliferation. Supplementary Figure S11. HORMAD1 promotes activity of the EJ5 NHEJ reporter. Supplementary Figure S12. Effect of HORMAD1 knockdown on 53BP1 and RAD51 foci in HCC1143. Supplementary Figure S13. BRCA1/2 mutation, platinum sensitivity and genomic scarring or HORMAD1 expression. Supplementary Figure S14. Effect of HORMAD1 knockdown on drug sensitivity in HCC1143. Supplementary Figure S15. ROC analysis of PrECOG TNBCs. Supplementary Figure S16. HORMAD1 expression in unselected and BRCA1/2 wildtype TNBCs.

Supplementary Methods, Figure Legends, Table Legends

Supplementary Table S1. KCL TNBC and breast cell line cohort characteristics. Supplementary Table S2. Categories of genomic segment used as the basis for measuring SCINS. Supplementary Table S3. Genes expressed in a SAM of different SCINS clusters. Supplementary Table S4. Gene expression signatures of genomic instability.

SWEAVE document. R code for SCINS analysis.

Background: Disparity between mammographic and pathological sizing of DCIS can lead to surgical overtreatment, with poor cosmetic outcomes of breast conservation surgery (BCS) or inappropriate mastectomy versus undertreatment, with subsequent need for re-excision. In addition, where mammographic size is smaller than pathological size, this may reflect an increased risk of mammographically occult residual disease post surgery; where pathological size is smaller than mammographic size there is a possibility of pathological underestimation or missed positive margins, with both scenarios resulting in increased risk of recurrence. Methods: The Sloane Project, within the UK NHS Breast Screening Programme, is a prospective cohort study of screen detected DCIS (2003-2012), with recurrence data for a median follow-up of 9 years. The NHS Breast Screening Programme screens women from age 50-70. We assessed factors associated with mammographic/pathology disparity, leading to i) 'downsizing' from pre-operative mammographic size estimation to final surgically resected pathological size or ii) 'upsizing' from pre-operative mammographic size to surgically resected pathological size. We defined 'downsizing' as pathological size 10mm or >5mm larger than mammographic size. Ipsilateral recurrence rates were determined in patients with mammographic/pathology disparity (downsized or upsized) compared to those with accurate preoperative sizing. Results: Using a 10mm size disparity, among 10829 patients, DCIS was downsized (pathological size smaller than mammographic size) in 26%, upsized in 19% and similar in 54%. Mastectomy was associated with marked mammographic/pathology disparity, with a 3.90RR of downsizing (p The results remained similar when patients prescribed endocrine therapy or radiotherapy were excluded. Re-excision (but not completion mastectomy) is associated with increased recurrence, with recurrence occurring in 237 of 5157 not requiring re-excision but 99 of 1488 requiring re-excision; RR: 1.45 (1.15-1.82). Conclusion: Large mammographic size, microcalcification casting features and young age (size overestimation) versus microcalcification and high density (size underestimation) should be considered in selecting surgery for DCIS. Mammographic/pathology disparity of only 5mm, whether this leads to downsizing or upsizing, is associated with an increased risk of ipsilateral recurrence after breast conservation. Table 1.In patients undergoing breast conservation, impact of 10mm and 5 mm mammographic/pathology disparity on ipsilateral recurrence rateTotalIpsilateral recurrence, n (%)RR (CI)Change in size of >10mmNo change3062158 (5.2%)1downsized111666 (5.9%)1.15 (0.87-1.51)upsized52036 (6.9%)1.34 (0.95-1.90)unknown19112 (6.3%)1.22 (0.69-2.15)TOTAL4889272 (5.6%)Change in size of >5mmNo change2783118 (4.2%)1downsized1953115 (5.9%)1.39 (1.08-1.78)upsized139580 (5.7%)1.35 (1.03-1.78)unknown23814 (5.9%)1.39 (0.81-2.38)TOTAL6369327 (5.1%) Citation Format: Cliona Clare Kirwan, Bridget Hilton, Karen Clements, Hilary Stobart, Matthew Wallis, Senthurun Mylvaganam, Elena Provenzano, Anthony Maxwell, Nisha Sharma, Abeer Shaaban, David Dodwell, Joanne Dulson-Cox, Elinor Sawyer, Olive Kearins, Samantha Brace-McDonnell, Sarah Pinder, Alastair M Thompson. Predictors of inaccurate pre-operative size assessment of screen detected DCIS and impact on recurrence rates [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-22-01.

Background:. Mammographic screening programmes have been shown to reduce breast cancer mortality. However, they detect many small tumours with favourable biological features which may not progress during a woman’s lifetime. These are treated with standard surgery and adjuvant therapies, which have associated morbidities. Thus, there is a need to reduce overtreatment of good prognosis tumours found by screening. Minimally invasive treatment approaches have been described but there is no prospective randomised evidence to support their routine use. Vacuum-assisted excision (VAE) is in widespread use for management of benign lesions and lesions of uncertain malignant potential. SMALL (ISRCTN 12240119) is designed to determine the feasibility of using this approach for treatment of small invasive tumours detected within the UK NHS Breast Screening Programme (BSP). Methods:. SMALL is a phase III multicentre randomised trial comparing standard surgery with VAE for screen-detected good prognosis breast cancers. The main eligibility criteria are age ≥47 years, screen-detected unifocal grade 1 tumours with maximum diameter 15mm, which are strongly ER/PR+ve and HER2-ve, with negative clinical/radiological axillary staging. Patients are randomised 2:1 in favour of VAE or surgery; with no axillary surgery in the VAE arm. Completeness of excision is assessed radiologically, and if excision is incomplete, patients undergo open surgery. Adjuvant radiotherapy and endocrine therapy are mandated in the VAE arm but may be omitted following surgery. Co-primary end-points are:1.Non-inferiority comparison of the requirement for a second procedure following excision2.Single arm analysis of local recurrence (LR) at 5 years following VAE. Recruitment of 800 patients over 4 years will permit demonstration of 10% non-inferiority of VAE for requirement of a second procedure. This ensures sufficient patients for single arm analysis of LR rates, where expected LR free survival is 99% at 5 years, with an undesirable survival probability after VAE of 97%. To ensure that the trial as a whole only has 5% alpha, the significance level for each co-primary outcome is set at 2.5% with 90% power. The Data Monitoring Committee will monitor LR events to ensure these do not exceed 3% per year. Secondary outcome measures include time to ipsilateral recurrence, overall survival, complications, quality of life and health economic analysis. A QuinteT Recruitment Intervention (QRI) is integrated throughout SMALL to optimise recruitment and informed consent. Recruitment challenges are identified by analysing recruiter/patient interviews and audio-recordings of trial discussions, and by review of screening, eligibility and recruitment data and study documentation. Solutions to address these are developed collaboratively, including individual/group recruiter feedback and recruitment tips documents. Results:. SMALL opened in December 2019, but recruitment halted in 2020 due to suspension of the NHS BSP for 5 months due to COVID-19. As of 1st July 2021, 55 patients had been approached in 10 centres, with 33 patients randomised (randomisation rate 60%). A further 23 centres are in set-up, with 8 suspended due to the pandemic. Drawing from preliminary QRI findings and insights from patient representatives, a recruitment tips document has been circulated (on introducing and discussing SMALL, providing balanced information. on treatment options and explaining randomisation). individual recruiter feedback has commenced, with wider feedback planned shortly. Conclusion:. Despite pandemic-related challenges, SMALL has an excellent recruitment rate to date and is expected to have a global impact on treatment of breast cancer within mammographic screening programmes. SMALL is funded by the UK NIHR HTA programme, award 17/42/32 Citation Format: Stuart A McIntosh, Charlotte E Coles, Carmel Conefrey, David Dodwell, Kenneth Elder, Jessica Foster, Claire Gaunt, Amanda Kirkham, Iain Lyburn, Jenna Morgan, Sangeetha Paramasivan, Sarah Pinder, Sarah Pirrie, Shelley Potter, Tracy Roberts, Nisha Sharma, Hilary Stobart, Elizabeth Southgate, Sian Taylor-Phillips, Matthew Wallis, Daniel Rea. SMALL - Open surgery versus minimally invasive vacuum-assisted excision for small screen detected breast cancer: A phase 3 randomised trial [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr OT1-06-02.

Background/objectives The natural history of microinvasive carcinoma of the breast (one or more foci of invasion of 1mm or less) and its optimal management remain controversial. We analysed the frequency and outcome of patients with DCIS plus microinvasion within a large prospective cohort of screen-detected DCIS. Methods Patients with screen-detected DCIS diagnosed between 2003 and 2012 with or without microinvasion in the final surgical specimen were identified from the UK Sloane Project database. Comprehensive imaging, surgical, pathology, oncology and subsequent outcome data were collected with a median follow-up of 9 years. Results Among 11285 DCIS patients diagnosed in the UK, microinvasion was reported in 521 (4.6%). The frequency of reported microinvasion varied considerably among screening units (0-25%) but overall decreased from 7% in 2003/04 to 3% in 2011/12.As reported elsewhere, microinvasion was significantly associated with high grade DCIS (5.9% of 7182 cases) compared to 2.9% of intermediate grade and 40mm had microinvasive foci reported. Microinvasion was also associated with the presence of comedo necrosis (p Citation Format: Abeer M Shaaban, Bridget Hilton, Karen Clements, David Dodwell, Nisha Sharma, Cliona Kirwan, Elinor Sawyer, Anthony Maxwell, Matthew Wallis, Hilary Stobart, Senthurun Mylvaganam, Janet.Litherland Litherland, Samantha Brace-Mcdonnell, Joanne Dulson-Cox, Olive Kearins, Elena Provenzano, Sarah Pinder, Alastair Thompson. The diagnosis and prognosis of ductal carcinoma in situ (DCIS) with microinvasion - Results from the United Kingdom Sloane project [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-12-36.

Background The variable natural history of ductal carcinoma in situ (DCIS) is poorly understood. The aim of this retrospective cohort study was to determine the outcomes of women who were diagnosed through the English National Health Service Breast Screening Programme (NHS BSP) and had no surgery for screen-detected DCIS. Method English NHS BSP databases were searched for women diagnosed with DCIS without invasive cancer on needle biopsy between 1 April 2001 and 31 March 2018 inclusive, who had no record of surgery within 6 months of diagnosis. These were cross-referenced with cancer registry data for further treatment, event information and mortality records. Details of potentially eligible women were sent to the relevant breast screening units for verification and for completion of data forms detailing clinical, radiological and pathological findings, non-surgical treatment, subsequent clinical course and outcomes. Results Data for 311 eligible women (median age 62 years) were included, with median follow-up (primary DCIS diagnosis to either surgery, development of invasive disease, death or last known to be alive) of 4.1 years (range 0.5 to 17.4 years). The median age at diagnosis was 64 years (range 47 to 90 years). Sixty (19%) women developed invasive breast cancer, 56 ipsilateral and 4 contralateral. Twenty-two women (7%) underwent surgery for DCIS (>6 months after diagnosis) and 86 (28%) died of other causes. Women with high or intermediate grade DCIS were significantly more likely to develop ipsilateral invasive breast cancer (iIBC) than those with low grade DCIS. 28/123 (23%) with high grade DCIS, 21/105 (20%) with intermediate grade DCIS, 5/76 (7%) with low grade DCIS and 2/7 (29%) with an unknown grade of DCIS developed iIBC. Ipsilateral invasion risk increased approximately linearly with time for at least 10 years. Women who developed iIBC were significantly younger than those who did not. This was driven primarily by a strong association among those with high grade DCIS. There was no significant difference in age between those with intermediate and low grade DCIS respectively who did or did not develop iIBC. The median baseline size of DCIS in women who developed iIBC was higher than in women who did not develop iIBC, both overall and in each of the three grade categories (median sizes - high grade 38 mm vs 29 mm, p=0.19; intermediate grade 35 mm vs 18 mm, p=0.31; low grade 18 mm vs 15 mm, p=0.38). This reached statistical significance for all grades combined: 37 mm (range 3-95) v 20 mm (range 3-200), p=0.02. Of the 262 women with a known microinvasion status, 8/25 (32%) with definite or possible microinvasion were subsequently diagnosed with ipsilateral invasive cancer compared to 38/237 (16%) without microinvasion (p=0.027). There was no significant association on univariable analysis between risk of iIBC and microcalcification as the predominant radiological feature (iIBC and microcalcification 47/258 vs iIBC and other radiological feature 7/46; p=0.83), the presence of histological necrosis (iIBC and necrosis, 14/89 vs iIBC and no necrosis, 31/157; p=0.49) or the use of ET (iIBC and ET 11/67 vs iIBC and no ET 45/244; p=0.86). Of the 51 invasive cancers that developed with a known grade, 46 (90%) were grade 2 or 3. Conclusion The findings suggest that women diagnosed with high or intermediate grade DCIS and those with microinvasion should continue to be offered surgery. For those with low grade DCIS there is a need for shared decision-making in the choice of surgery or active surveillance based on a discussion of the risks and benefits of the options as currently understood, and in the light of the low reproducibility of DCIS grading. Citation Format: Karen Clements, Anthony Maxwell, Bridget Hilton, Matthew Wallis, Cliona Kirwan, Hilary Stobart, Elena Provenzano, Nisha Sharma, Janet Litherland, Abeer Shaaban, David Dodwell, Joanne Dulson-Cox, Elinor Sawyer, Senthurun Mylvaganam, Olive Kearins, Samantha Brace-McDonnell, Sarah Pinder, Alastair Thompson. A longitudinal cohort study of outcomes in 311 women with unresected ductal carcinoma in situ detected through the English breast screening programme [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-22-06.

Supplementary Figure 4. Multivariable Cox proportional hazards regression analyses for disease free survival (DFS; left panel) and corresponding forest plots (Right panel).

Supplementary Figure 2. Receiver operating characteristic (ROC) analysis of pathological complete response (pCR), revised pathological TNM stage (yp-TNM stage), Clinical-Pathologic Scoring System (CPS) score and CPS-Oestrogen receptor-histological grade (CPS-EG) were performed for predicting breast cancer specific survival in the training (A), internal validation (B), external validation (C) and combined three cohorts (D).

supplemental figure legend.

Purpose: Highly aggressive triple-negative breast cancers (TNBCs) lack validated therapeutic targets and have high risk of metastatic disease. Folate receptor alpha (FRα) is a central mediator of cell growth regulation that could serve as an important target for cancer therapy.Experimental Design: We evaluated FRα expression in breast cancers by genomic (n = 3,414) and IHC (n = 323) analyses and its association with clinical parameters and outcomes. We measured the functional contributions of FRα in TNBC biology by RNA interference and the antitumor functions of an antibody recognizing FRα (MOv18-IgG1), in vitro, and in human TNBC xenograft models.Results: FRα is overexpressed in significant proportions of aggressive basal like/TNBC tumors, and in postneoadjuvant chemotherapy–residual disease associated with a high risk of relapse. Expression is associated with worse overall survival. TNBCs show dysregulated expression of thymidylate synthase, folate hydrolase 1, and methylenetetrahydrofolate reductase, involved in folate metabolism. RNA interference to deplete FRα decreased Src and ERK signaling and resulted in reduction of cell growth. An anti-FRα antibody (MOv18-IgG1) conjugated with a Src inhibitor significantly restricted TNBC xenograft growth. Moreover, MOv18-IgG1 triggered immune-dependent cancer cell death in vitro by human volunteer and breast cancer patient immune cells, and significantly restricted orthotopic and patient-derived xenograft growth.Conclusions: FRα is overexpressed in high-grade TNBC and postchemotherapy residual tumors. It participates in cancer cell signaling and presents a promising target for therapeutic strategies such as ADCs, or passive immunotherapy priming Fc-mediated antitumor immune cell responses. Clin Cancer Res; 24(20); 5098–111. ©2018 AACR.

Supplementary Figure 5. Kaplan Meier curves and lifetime table showing disease free survival (DFS) in the training (A), internal validation (B), and external validation (C) cohorts stratified according to Nottingham clinicopathological response index prognostic groups (NPRI-PGs).

Supplementary Figure 1. Kaplan Meier curves showing disease free survival (DFS) in the training (upper panels), internal validation (middle panels) and external validation (lower panels) cohorts stratified according to the number of lymph node (LN) metastases (i), presence of lympho-vascular invasion (LVI; ii), absence of fibrosis (iii) the percentage reduction in primary tumour size (iv).

Supplementary Tables 1 to 5. Table (S1): Clinico-pathological characteristics of all three individual cohorts and the sum of all three together. Table (S2): Summery of pathological features that have been reviewed Table (S3): Univariate and multivariate backward step-wise analysis for factors associated with disease free survival (DFS) in the training cohort. Table (S4): Summery of the code system that has been used for calculation of Nottingham clinico-pathological response index (NPRI) Table (S5): Univariate analysis for clinicopathological features associated with disease free survival (DFS) and breast cancer specific survival (BCSS) in the training, internal and external validation cohorts.

Supplementary Figure Legends, Materials and Methods

Purpose: There is a need to identify more sensitive clinicopathologic criteria to assess the response to neoadjuvant chemotherapy (Neo-ACT) and guide subsequent adjuvant therapy.Experimental Design: We performed a clinicopathologic assessment of 426 patients who had completed Neo-ACT for locally advanced breast cancer (LABC) with a median follow-up of 70 months. Patients were divided into a training set treated with anthracycline combination chemotherapy (n = 172); an internal validation set treated with anthracycline and taxane (n = 129); and an external validation set treated with anthracycline with or without taxane (n = 125).Results: A multivariate Cox regression model demonstrated the absence of fibrosis, presence of lymphovascular invasion, increasing number of lymph node metastases, and administration of hormone therapy were significantly associated with short breast cancer–specific survival (BCSS) and disease-free survival (DFS); Ps < 0.01, while reduction of tumor size was associated with DFS (P = 0.022). Nottingham Clinico-Pathological Response Indexes (NPRI) were calculated, and four prognostic groups (NPRI-PG) were identified. Patients in prognostic group 2 (NPRI-PG2) for BCSS (66 of 172; 38.4%) have the same prognosis as those who achieved pathologic complete response (pCR; NPRI-PG1; 15%). Receiver-operating characteristic (ROC) curves indicated that the NPRI outperformed the currently used prognostic factors and adding the NPRI improved their performance as a predictor for both BCSS (area under the curve [AUC], 0.88) and DFS (AUC, 0.87).Conclusions: The NPRI predicts BCSS and DFS, with a higher sensitivity than pCR. The NPRI can also improve the sensitivity and specificity of clinicopathologic response as a study endpoint, for assessing response to Neo-ACT, and can serve as a valuable tool for the discovery of future predictive molecular markers. Clin Cancer Res; 21(5); 1052–62. ©2014 AACR.

Supplementary figures

Supplementary Figure 3. Multivariable Cox proportional hazards regression analyses for disease free survival (DFS; left panel) and corresponding forest plots (Right panel).

Supplementary Figure 6. Receiver operating characteristic (ROC) analysis of Nottingham clinico-pathological response index (NPRI) score and other clinico-pathological covariates were performed for predicting disease free survival in the training (A), internal validation (B), external validation (C) and combined three cohorts (D).

Objectives: The importance of consistent terminology in describing the appearance of breast calcifications in mammography is well recognised. Imaging of calcifications using electron microscopy is a globally growing field of research. We therefore suggest that the time is ripe to develop a lexicon of terms for classifying the micromorphology of breast calcifications. Methods: Calcifications within a wide range of histological sections of breast tissue, both benign and malignant, were imaged by Scanning Electron Microscopy (SEM). These images were examined, and the micromorphology of calcifications present was grouped to create a classification system. Results: Based on the appearance of the calcifications observed, we propose five main categories for classification of the micromorphology of breast calcifications, namely, Dense Homogenous, Punctulate, Banded, Spongy and Aggregate. Conclusions: Use of the descriptive categories outlined here will help to ensure consistency and comparability of published observations on the micromorphology of breast calcifications. Advances in knowledge: This is the first time a lexicon and classification system has been proposed for the micromorphology of breast calcifications, as observed by scanning electron microscopy of histological sections. This will facilitate comparability of observed relationships between micromorphology, mammographic appearance, chemistry and pathology.

Ductal carcinoma in situ (DCIS) is frequently associated with breast calcification. This study combines multiple analytical techniques to investigate the heterogeneity of these calcifications at the micrometre scale. X-ray diffraction, scanning electron microscopy and Raman and Fourier-transform infrared spectroscopy were used to determine the physicochemical and crystallographic properties of type II breast calcifications located in formalin fixed paraffin embedded DCIS breast tissue samples. Multiple calcium phosphate phases were identified across the calcifications, distributed in different patterns. Hydroxyapatite was the dominant mineral, with magnesium whitlockite found at the calcification edge. Amorphous calcium phosphate and octacalcium phosphate were also identified close to the calcification edge at the apparent mineral/matrix barrier. Crystallographic features of hydroxyapatite also varied across the calcifications, with higher crystallinity centrally, and highest carbonate substitution at the calcification edge. Protein was also differentially distributed across the calcification and the surrounding soft tissue, with collagen and β-pleated protein features present to differing extents. Combination of analytical techniques in this study was essential to understand the heterogeneity of breast calcifications and how this may link crystallographic and physicochemical properties of calcifications to the surrounding tissue microenvironment. Cancer Research UK and by KWF Kankerbestrijding: C38317/A24043

IntroductionThe National Health Service (NHS) Breast Screening Programme aims to detect cancer earlier when treatment is more effective but can harm women by over diagnosing and overtreating cancers which would never have become symptomatic. As well as breast cancer, a spectrum of atypical epithelial proliferations (atypia) can also be detected as part of screening. This spectrum of changes, while not cancer, may mean that a woman is more likely to develop breast cancer in the future. Follow-up of atypia is not evidence based. We currently do not know which atypia should be detected to avoid future cancer. This study will explore how atypia develops into breast cancer in terms of number of women, time of cancer development, cancer type and severity, and whether this varies for different types of atypia.Methods and analysisThe Sloane cohort study began in April 2003 with ongoing data collection including atypia diagnosed through screening at screening units in the UK. The database for England has 3645 cases (24 September 2020) of epithelial atypia, with follow-up from 1 to 15 years. The outcomes include subsequent invasive breast cancer and the nature of subsequent cancer. Descriptive statistics will be produced. The observed rates of breast cancer at 1, 3 and 6 years for types of atypia will be reported with CIs, to enable comparison to women in the general population. Time to event methods will be used to describe the time to breast cancer diagnosis for the types of atypia, including flexible parametric modelling if appropriate. Patient representatives from Independent Cancer Patients’ Voice are included at every stage of the research.Ethics and disseminationThe study has received research ethics approval from the University of Warwick Biomedical and Scientific Research Ethics Committee (BSREC 10/20–21, 8 October 2020), Public Health England office for data release approvals (ODR1718_313) and approval from the English Breast Research Advisory Committee (BSPRAC_031). The findings will be disseminated to breast screening clinicians (via journal publication and conference presentation), to the NHS Breast Screening Programme to update their guidelines on how women with atypia should be followed up, and to the general public.

Peer reviewed: True, PURPOSE: The introduction of breast screening in the UK led to an increase in the detection of non-invasive breast neoplasia, predominantly ductal carcinoma in situ (DCIS), a non-obligatory precursor of invasive breast cancer. The Sloane Project, a UK prospective cohort study of screen-detected non-invasive breast neoplasia, commenced in 2003 to evaluate the radiological assessment, surgical management, pathology, adjuvant therapy and outcomes for non-invasive breast neoplasia. Long-term follow-up and accurate data collection are essential to examine the clinical impact. Here, we describe the establishment, development and analytical processes for this large UK cohort study. PARTICIPANTS: Women diagnosed with non-invasive breast neoplasia via the UK National Health Service Breast Screening Programme (NHSBSP) from 01 April 2003 are eligible, with a minimum age of 46 years. Diagnostic, therapeutic and follow-up data collected via proformas, complement date and cause of death from national data sources. Accrual for patients with DCIS ceased in 2012 but is ongoing for patients with epithelial atypia/in situ neoplasia, while follow-up for all continues long term. FINDINGS TO DATE: To date, patients within the Sloane cohort comprise one-third of those diagnosed with DCIS within the NHSBSP and are representative of UK practice. DCIS has a variable outcome and confirms the need for longer-term follow-up for screen-detected DCIS. However, the radiology and pathology features of DCIS can be used to inform patient management. We demonstrate validation of follow-up information collected from national datasets against traditional, manual methods. FUTURE PLANS: Conclusions derived from the Sloane Project are generalisable to women in the UK with screen-detected DCIS. The follow-up methodology may be extended to other UK cohort studies and routine clinical follow-up. Data from English patients entered into the Sloane Project are available on request to researchers under data sharing agreement. Annual follow-up data collection will continue for a minimum of 20 years.

Introduction: Ductal carcinoma in situ (DCIS) is considered a non-obligate precursor of invasive ductal carcinoma. With the aim of preventing a subsequent invasive cancer, all DCIS lesions are currently treated with surgical excision often supplemented with radiotherapy (RT). To prevent DCIS over- or undertreatment, a reliable marker of DCIS invasiveness risk is urgently needed. Methods: We studied two large DCIS cohorts: the Sloane cohort, a prospective breast screening cohort from the UK (median follow-up of 11 years), and a Dutch population-based cohort (NKI, median follow-up of 13 years). FFPE tissue specimens from patients with pure primary DCIS after breast-conserving surgery (BCS) +/- RT that did develop a subsequent ipsilateral event (DCIS or invasive) were considered as cases, whereas patients that did not develop any form of recurrence up to the last follow-up or death were considered as controls. We performed copy number analysis (CNA) and RNAseq analysis on 229 cases (80 DCIS only recurrences) and 344 controls. Results: DCIS was classified into the PAM50 subtypes using RNAseq data which revealed an enrichment of luminal A phenotype in DCIS that did not recur (P = 0.01, Fisher Exact test). No single copy number aberration was more common in cases compared to controls. RNAseq data did not reveal any genes significantly over/under-expressed in cases versus controls after FDR correction. However, by limiting the analysis to samples that had not had RT and excluding pure DCIS recurrences, we could develop a penalized Cox model from RNAseq data. The model was trained on weighted samples (to correct for the biased sampling of the case-control dataset) from the NKI series with double loop cross-validation. The genes were selected using the Elastic net framework of penalization. Using this predicted hazard ratio, the samples were split into high, medium, and low-risk quantiles, with a recurrence risk of 23%, 7% and 2%, respectively at 5 years (p = 10-10, Wald test). The NKI-trained predictor was independently validated in the Sloane No RT no DCIS recurrence cohort (p = 0.02, Wald test). GSEA analysis revealed proliferation hallmarks enriched in the recurrence predictor (FDR = 0.058). The RNAseq predictor was more predictive of recurrence than PAM50, clinical features (Grade, Her2 and ER) and the 12-gene Oncotype DCIS score (p < 0.001, permutation test using the Wald statistic) in both the NKI and Sloane series. Conclusion: Genomic profiling of two independent series of DCIS with outcome data did not reveal any clear associations with recurrence until analysis was limited to a set of samples who had not had radiotherapy and DCIS recurrences were excluded. We then identified an RNAseq-based classifier that could differentiate primary DCIS in low-, medium-, and high-risk groups, and validated it in an independent cohort. This classifier, if validated in other datasets, will allow us to identify women who do not need intensive treatment for their DCIS. Citation Format: Maria Roman Escorza, Michael Sheinman, Tycho Bismeijer, Ahmed A. Ahmed, Vandna Shah, Jeffrey R. Marks, Lorraine M. King, Anargyros Megalios, Lindy L. Visser, Marlous Hoogstrat, Helen R. Davies, Tapsi Kumar, Deborah Collyar, Hilary Stobart, Sarah Pinder, Nicholas N. Navin, Andrew Futreal, Serena Nik-Zainal, E. Shelley Hwang, Esther H. Lips, Alastair Thompson, Lodewyk F.A. Wessels, Jelle Wesseling, Elinor J. Sawyer. Genomic predictor can discriminate between high- and low-risk DCIS [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr PR002.

Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive disease. A fundamental biologic question is whether the invasive disease arises from tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial DCIS lesion and paired invasive recurrent tumors in 95 patients together with single-cell DNA sequencing in a subset of cases. Our data show that in 75% of cases the invasive recurrence was clonally related to the initial DCIS, suggesting that tumor cells were not eliminated during the initial treatment. Surprisingly, however, 18% were clonally unrelated to the DCIS, representing new independent lineages and 7% of cases were ambiguous. This knowledge is essential for accurate risk evaluation of DCIS, treatment de-escalation strategies and the identification of predictive biomarkers.

With the widespread adoption of breast cancer screening the incidence of pure ductal carcinoma in situ (DCIS) has increased. As DCIS is considered a non-obligate precursor of invasive ductal carcinoma most women with pure DCIS are treated with breast conserving surgery (BCS) +/- radiotherapy. However, for many this is likely to be overtreatment as only a minority will develop a subsequent ipsilateral recurrence. Studies also show that only ~60% of these ipsilateral recurrences are invasive disease with the remainder being pure DCIS. To predict which women are most likely to benefit from interventions, there is a need to identify biomarkers that are associated with invasive recurrence. Our aim was to assess whether copy number aberrations (CNAs) could be used to identify DCIS that was likely to recur as invasive disease or remain recurrence-free during long-time follow up. We performed somatic copy number profiling on 309 pure DCIS samples that had not developed an ipsilateral event (controls), 198 that had developed subsequent ipsilateral invasive disease (INV-cases) and 58 that had developed subsequent ipsilateral pure DCIS (DCIS-cases). The samples were obtained from two large nation-wide cohorts: the Sloane cohort, a prospective breast screening cohort from the UK with a median follow up of 12.5 years and a Dutch population based cohort, with a median follow up of 13 years. CNAs were assessed using the CytoSNP array or low pass whole genome sequencing and analyzed using GISTIC. Integrative cluster (IntClust) subtyping revealed that only 5 subtypes were well represented in DCIS compared to 10 in invasive disease and the distribution of clusters between INV-cases and controls was similar with the exception of IntClust 4, which was significantly more common in controls (P= 0.025, Fishers exact test). IntClust 4 is characterized to have low levels of genomic instability and a CNA-devoid. INV-cases were globally more aberrant than controls (P = 0.006, Wilcoxon test) as assessed by the chromosomal instability index (CIN) score. GISTIC identified 17 recurrent amplifications, 21 recurrent gains and 22 recurrent losses in the whole cohort. Six of these regions were more common in INV-cases compared to controls: amplifications at 17q24.1 and 8p11.23, losses at 1p36.13 and 11q23.2 ​and gains at 17q21.33​ and 16p (Nominal P < 0.05 and FDR < 0.1, Fishers exact test). Subgroup analysis of ER+, Her2- INV-cases versus controls revealed an additional differential CNA, amplification at 11q13.3 more common in cases. DCIS-cases had similar CNAs to INV-cases and were more aberrant than controls in terms of CIN score (P < 0.037, Wilcoxon test) but not as aberrant as INV-cases. In conclusion, we have identified potential CNAs that are associated with invasive recurrence. Further analysis will integrate gene expression with copy number data to identify which genes are being targeted by these CNAs in order to identify pathways important in progression of DCIS. Citation Format: Ahmed A. Ahmed, Maria Roman-Escorza, Tycho Bismeijer, Michael Sheinman, Vandna Shah, Rana Shami, Jeffrey R. Marks, Lorraine M. King, Anargyros Megalios, Lindy L. Visser, Marlous Hoogstraat, Helen R. Davies, Tapsi Kumar, Deborah Collyar, Hilary Stobart, Sarah Pinder, Nicholas N. Navin, Andrew Futreal, Serena Nik-Zainal, E. Shelley Hwang, Lodewyk F. Wessels, Esther H. Lips, Alastair Thompson, Jelle Wesseling, Elinor J. Sawyer. Copy number analysis of pure DCIS and association with recurrence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5108.

MC3 Working Group: Rehan Akbani21, Pavana Anur22, Matthew H. Bailey1,2,3, Alex Buchanan9, Kami Chiotti9, Kyle Covington12,23, Allison Creason9, Li Ding1,2,3,20, Kyle Ellrott9, Yu Fan21, Steven Foltz1,2, Gad Getz8,14,15,16, Walker Hale12, David Haussler24,25, Julian M. Hess8,26, Carolyn M. Hutter27, Cyriac Kandoth28, Katayoon Kasaian29,30, Melpomeni Kasapi27, Dave Larson1 , Ignaty Leshchiner8, John Letaw31, Singer Ma32, Michael D. McLellan1,3,20, Yifei Men32, Gordon B. Mills33,34, Beifang Niu35, Myron Peto22, Amie Radenbaugh24, Sheila M. Reynolds36, Gordon Saksena8, Heidi Sofia27, Chip Stewart8, Adam J. Struck31, Joshua M. Stuart24,37, Wenyi Wang21, John N. Weinstein38, David A. Wheeler12,13, Christopher K. Wong24,39, Liu Xi12 & Kai Ye40,41 21Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 22Molecular and Medical Genetics, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 23Castle Biosciences Inc, Friendswood, TX 77546, USA. 24UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 25Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 26Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02114, USA. 27National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA. 28Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. 29Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada. 30Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada. 31Computational Biology Program, School of Medicine, Oregon Health and Science University, Portland, OR 97239, USA. 32DNAnexus Inc, Mountain View, CA 94040, USA. 33Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA. 34Precision Oncology, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 35Computer Network Information Center, Chinese Academy of Sciences, Beijing, China. 36Institute for Systems Biology, Seattle, WA 98109, USA. 37Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 38Department of Bioinformatics and Computational Biology and Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 39Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 40School of Elect, PCAWG novel somatic mutation calling methods working group: Matthew H. Bailey1,2,3, Beifang Niu35, Matthias Bieg42,43, Paul C. Boutros6,44,45,46, Ivo Buchhalter43,47,48, Adam P. Butler49, Ken Chen50, Zechen Chong51, Li Ding1,2,3,20, Oliver Drechsel52,53, Lewis Jonathan Dursi6,7, Roland Eils47,48,54,55, Kyle Ellrott9, Shadrielle M. G. Espiritu6, Yu Fan21, Robert S. Fulton1,3,20, Shengjie Gao56, Josep L. l. Gelpi57,58, Mark B. Gerstein5,18,19, Gad Getz8,14,15,16, Santiago Gonzalez59,60, Ivo G. Gut52,61, Faraz Hach62,63, Michael C. Heinold47,48, Julian M. Hess8,26, Jonathan Hinton49, Taobo Hu64, Vincent Huang6, Yi Huang65,66, Barbara Hutter43,67,68, David R. Jones49, Jongsun Jung69, Natalie Jäger47, Hyung-Lae Kim70, Kortine Kleinheinz47,48, Sushant Kumar5,19, Yogesh Kumar64, Christopher M. Lalansingh6, Ignaty Leshchiner8, Ivica Letunic71, Dimitri Livitz8, Eric Z. Ma64, Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Michael D. McLellan1,3,20, Andrew Menzies49, Ana Milovanovic57, Morten Muhlig Nielsen73, Stephan Ossowski52,53,74, Nagarajan Paramasivam43,47, Jakob Skou Pedersen73,75, Marc D. Perry76,77, Montserrat Puiggròs57, Keiran M. Raine49, Esther Rheinbay8,14,72, Romina Royo57, S. Cenk Sahinalp62,78,79, Gordon Saksena8, Iman Sarrafi62,78, Matthias Schlesner47,80, Jared T. Simpson6,17, Lucy Stebbings49, Chip Stewart8, Miranda D. Stobbe52,61, Jon W. Teague49, Grace Tiao8, David Torrents57,81, Jeremiah A. Wala8,14,82, Jiayin Wang1,40,66, Wenyi Wang21, Sebastian M. Waszak60, Joachim Weischenfeldt60,83,84, Michael C. Wendl1,10,11, Johannes Werner47,85, Zhenggang Wu64, Hong Xue64, Sergei Yakneen60, Takafumi N. Yamaguchi6, Kai Ye40,41, Venkata D. Yellapantula20,86, Christina K. Yung76 & Junjun Zhang76, PCAWG Consortium: Lauri A. Aaltonen87, Federico Abascal49, Adam Abeshouse88, Hiroyuki Aburatani89, David J. Adams49, Nishant Agrawal90, Keun Soo Ahn91, Sung-Min Ahn92, Hiroshi Aikata93, Rehan Akbani21, Kadir C. Akdemir50, Hikmat Al-Ahmadie88, Sultan T. Al-Sedairy94, Fatima Al-Shahrour95, Malik Alawi96,97, Monique Albert98, Kenneth Aldape99,100, Ludmil B. Alexandrov49,101,102, Adrian Ally30, Kathryn Alsop103, Eva G. Alvarez104,105,106, Fernanda Amary107, Samirkumar B. Amin108,109,110, Brice Aminou76, Ole Ammerpohl111,112, Matthew J. Anderson113, Yeng Ang114, Davide Antonello115, Pavana Anur22, Samuel Aparicio116, Elizabeth L. Appelbaum1,117, Yasuhito Arai118, Axel Aretz119, Koji Arihiro93, Shun-ichi Ariizumi120, Joshua Armenia121, Laurent Arnould122, Sylvia Asa123,124, Yassen Assenov125, Gurnit Atwal6,126,127, Sietse Aukema112,128, J. Todd Auman129, Miriam R. Aure130, Philip Awadalla6,126, Marta Aymerich131, Gary D. Bader126, Adrian Baez-Ortega132, Matthew H. Bailey1,2,3, Peter J. Bailey133, Miruna Balasundaram30, Saianand Balu134, Pratiti Bandopadhayay8,135,136, Rosamonde E. Banks137, Stefano Barbi138, Andrew P. Barbour139,140, Jonathan Barenboim6, Jill Barnholtz-Sloan141,142, Hugh Barr143, Elisabet Barrera59, John Bartlett98,144, Javier Bartolome57, Claudio Bassi115, Oliver F. Bathe145,146, Daniel Baumhoer147, Prashant Bavi148, Stephen B. Baylin149,150, Wojciech Bazant59, Duncan Beardsmore151, Timothy A. Beck152,153, Sam Behjati49, Andreas Behren154, Beifang Niu35, Cindy Bell155, Sergi Beltran52,61, Christopher Benz156, Andrew Berchuck157, Anke K. Bergmann158, Erik N. Bergstrom101,102, Benjamin P. Berman159,160,161, Daniel M. Berney162, Stephan H. Bernhart163,164,165, Rameen Beroukhim8,14,82, Mario Berrios166, Samantha Bersani167, Johanna Bertl73,168, Miguel Betancourt169, Vinayak Bhandari6,44, Shriram G. Bhosle49, Andrew V. Biankin133,170,171,172, Matthias Bieg42,43, Darell Bigner173, Hans Binder163,164, Ewan Birney59, Michael Birrer72, Nidhan K. Biswas174, Bodil Bjerkehagen147,175, Tom Bodenheimer134, Lori Boice176, Giada Bonizzato177, Johann S. De Bono178, Arnoud Boot179,180, Moiz S. Bootwalla166, Ake Borg181, Arndt Borkhardt182, Keith A. Boroevich183,184, Ivan Borozan6, Christoph Borst185, Marcus Bosenberg186, Mattia Bosio52,53,57, Jacqueline Boultwood187, Guillaume Bourque188,189, Paul C. Boutros6,44,45,46, G. Steven Bova190, David T. Bowen49,191, Reanne Bowlby30, David D. L. Bowtell103, Sandrine Boyault192, Rich Boyce59, Jeffrey Boyd193, Alvis Brazma59, Paul Brennan194, Daniel S. Brewer195,196, Arie B. Brinkman197, Robert G. Bristow44,198,199,200,201, Russell R. Broaddus99, Jane E. Brock202, Malcolm Brock203, Annegien Broeks204, Angela N. Brooks8,24,37,82, Denise Brooks30, Benedikt Brors67,205,206, Søren Brunak207,208, Timothy J. C. Bruxner113,209, Alicia L. Bruzos104,105,106, Alex Buchanan9, Ivo Buchhalter43,47,48, Christiane Buchholz210, Susan Bullman8,82, Hazel Burke211, Birgit Burkhardt212, Kathleen H. Burns213,214, John Busanovich8,215, Carlos D. Bustamante216,217, Adam P. Butler49, Atul J. Butte218, Niall J. Byrne76, Anne-Lise Børresen-Dale130,219, Samantha J. Caesar-Johnson220, Andy Cafferkey59, Declan Cahill221, Claudia Calabrese59,60, Carlos Caldas222,223, Fabien Calvo224, Niedzica Camacho178, Peter J. Campbell49,225, Elias Campo226,227, Cinzia Cantù177, Shaolong Cao21, Thomas E. Carey228, Joana Carlevaro-Fita229,230,231, Rebecca Carlsen30, Ivana Cataldo167,177, Mario Cazzola232, Jonathan Cebon154, Robert Cerfolio233, Dianne E. Chadwick234, Dimple Chakravarty235, Don Chalmers236, Calvin Wing Yiu Chan47,237, Kin Chan238, Michelle Chan-Seng-Yue148, Vishal S. Chandan239, David K. Chang133,170, Stephen J. Chanock240, Lorraine A. Chantrill170,241, Aurélien Chateigner76,242, Nilanjan Chatterjee149,243, Kazuaki Chayama93, Hsiao-Wei Chen114,121, Jieming Chen218, Ken Chen50, Yiwen Chen21, Zhaohong Chen244, Andrew D. Cherniack8,82, Jeremy Chien245, Yoke-Eng Chiew246,247, Suet-Feung Chin222,223, Juok Cho8, Sunghoon Cho248, Jung Kyoon Choi249, Wan Choi250, Christine Chomienne251, Zechen Chong51, Su Pin Choo252, Angela Chou170,246, Angelika N. Christ113, Elizabeth L. Christie103, Eric Chuah30, Carrie Cibulskis8, Kristian Cibulskis8, Sara Cingarlini253, Peter Clapham49, Alexander Claviez254, Sean Cleary148,255, Nicole Cloonan256, Marek Cmero257,258,259, Colin C. Collins62, Ashton A. Connor255,260, Susanna L. Cooke133, Colin S. Cooper178,196,261, Leslie Cope149, Vincenzo Corbo138,177, Matthew G. Cordes1,262, Stephen M. Cordner263, Isidro Cortés-Ciriano264,265,266, Kyle Covington12,23, Prue A. Cowin267, Brian Craft24, David Craft8,268, Chad J. Creighton269, Yupeng Cun270, Erin Curley271, Ioana Cutcutache179,180, Karolina Czajka272, Bogdan Czerniak99,273, Rebecca A. Dagg274, Ludmila Danilova149, Maria Vittoria Davi275, Natalie R. Davidson276,277,278,279,280, Helen Davies49,281,282, Ian J. Davis283, Brandi N. Davis-Dusenbery284, Kevin J. Dawson49, Francisco M. De La Vega216,217,285, Ricardo De Paoli-Iseppi211, Timothy Defreitas8, Angelo P. Dei Tos286, Olivier Delaneau287,288,289, John A. Demchok220, Jonas Demeulemeester290,291, German M. Demidov52,53,74, Deniz Demircioğlu292,293, Nening M. Dennis221, Robert E. Denroche148, Stefan C. Dentro49,290,294, Nikita Desai76, Vikram Deshpande72, Amit G. Deshwar295, Christine Desmedt296,297, Jordi Deu-Pons298,299, Noreen Dhalla30, Neesha C. Dhani300, Priyanka Dhingra301,302, Rajiv Dhir303, Anthony DiBiase304, Klev Diamanti305, Li Ding1,2,3,20, Shuai Ding306, Huy Q. Dinh159, Luc Dirix307, HarshaVardhan Doddapaneni12, Nilgun Donmez62,78, Michelle T. Dow244, Ronny Drapkin308, Oliver Drechsel52,53, Ruben M. Drews223, Serge Serge49, Tim Dudderidge150,221, Ana Dueso-Barroso57, Andrew J. Dunford8, Michael Dunn309, Lewis Jonathan Dursi6,7, Fraser R. Duthie133,310, Ken Dutton-Regester311, Jenna Eagles272, Douglas F. Easton312,313, Stuart Edmonds314, Paul A. Edwards223,315, Sandra E. Edwards178, Rosalind A. Eeles178,221, Anna Ehinger316, Juergen Eils54,55, Roland Eils47,48,54,55, Adel El-Naggar99,273, Matthew Eldridge223, Kyle Ellrott9, Serap Erkek60, Georgia Escaramis53,317,318, Shadrielle M. G. Espiritu6, Xavier Estivill53,319, Dariush Etemadmoghadam103, Jorunn E. Eyfjord320, Bishoy M. Faltas280, Daiming Fan321, Yu Fan21, William C. Faquin72, Claudiu Farcas244, Matteo Fassan322, Aquila Fatima323, Francesco Favero324, Nodirjon Fayzullaev76, Ina Felau220, Sian Fereday103, Martin L. Ferguson325, Vincent Ferretti76,326, Lars Feuerbach205, Matthew A. Field327, J. Lynn Fink57,113, Gaetano Finocchiaro328, Cyril Fisher221, Matthew W. Fittall290, Anna Fitzgerald329, Rebecca C. Fitzgerald282, Adrienne M. Flanagan330, Neil E. Fleshner331, Paul Flicek59, John A. Foekens332, Kwun M. Fong333, Nuno A. Fonseca59,334, Christopher S. Foster335,336, Natalie S. Fox6, Michael Fraser6, Scott Frazer8, Milana Frenkel-Morgenstern337, William Friedman338, Joan Frigola298, Catrina C. Fronick1,262, Akihiro Fujimoto184, Masashi Fujita184, Masashi Fukayama339, Lucinda A. Fulton1 , Robert S. Fulton1,3,20, Mayuko Furuta184, P. Andrew Futreal340, Anja Füllgrabe59, Stacey B. Gabriel8, Steven Gallinger148,255,260, Carlo Gambacorti-Passerini341, Jianjiong Gao121, Shengjie Gao56, Levi Garraway82, Øystein Garred342, Erik Garrison49, Dale W. Garsed103, Nils Gehlenborg8,343, Josep L. l. Gelpi57,58, Joshy George110, Daniela S. Gerhard344, Clarissa Gerhauser345, Jeffrey E. Gershenwald346,347, Mark B. Gerstein5,18,19, Moritz Gerstung59,60, Gad Getz8,14,15,16, Mohammed Ghori49, Ronald Ghossein348, Nasra H. Giama349, Richard A. Gibbs12, Anthony J. Gill170,350, Pelvender Gill351, Dilip D. Giri348, Dominik Glodzik49, Vincent J. Gnanapragasam352,353, Maria Elisabeth Goebler354, Mary J. Goldman24, Carmen Gomez355, Santiago Gonzalez59,60, Abel Gonzalez-Perez298,299,356, Dmitry A. Gordenin357, James Gossage358, Kunihito Gotoh359, Ramaswamy Govindan3, Dorthe Grabau360, Janet S. Graham133,361, Robert C. Grant148,260, Anthony R. Green315, Eric Green27, Liliana Greger59, Nicola Grehan282, Sonia Grimaldi177, Sean M. Grimmond362, Robert L. Grossman363, Adam Grundhoff97,364, Gunes Gundem88, Qianyun Guo75, Manaswi Gupta8, Shailja Gupta365, Ivo G. Gut52,61, Marta Gut52,61, Jonathan Göke292,366, Gavin Ha8, Andrea Haake111, David Haan37, Siegfried Haas185, Kerstin Haase290, James E. Haber367, Nina Habermann60, Faraz Hach62,63, Syed Haider6, Natsuko Hama118, Freddie C. Hamdy351, Anne Hamilton267, Mark P. Hamilton368, Leng Han369, George B. Hanna370, Martin Hansmann371, Nicholas J. Haradhvala8,72, Olivier Harismendy102,372, Ivon Harliwong113, Arif O. Harmanci5,373, Eoghan Harrington374, Takanori Hasegawa375, David Haussler24,25, Steve Hawkins223, Shinya Hayami376, Shuto Hayashi375, D. Neil Hayes134,377,378, Stephen J. Hayes379,380, Nicholas K. Hayward211,311, Steven Hazell221, Yao He381, Allison P. Heath382, Simon C. Heath52,61, David Hedley300, Apurva M. Hegde38, David I. Heiman8, Michael C. Heinold47,48, Zachary Heins88, Lawrence E. Heisler152, Eva Hellstrom-Lindberg383, Mohamed Helmy384, Seong Gu Heo385, Austin J. Hepperla134, José María Heredia-Genestar386, Carl Herrmann47,48,387, Peter Hersey211, Julian M. Hess8,26, Holmfridur Hilmarsdottir320, Jonathan Hinton49, Satoshi Hirano388, Nobuyoshi Hiraoka389, Katherine A. Hoadley134,390, Asger Hobolth75,168, Ermin Hodzic78, Jessica I. Hoell182, Steve Hoffmann163,164,165,391, Oliver Hofmann392, Andrea Holbrook166, Aliaksei Z. Holik53, Michael A. Hollingsworth393, Oliver Holmes209,311, Robert A. Holt30, Chen Hong205,237, Eun Pyo Hong385, Jongwhi H. Hong394, Gerrit K. Hooijer395, Henrik Hornshøj73, Fumie Hosoda118, Yong Hou56,396, Volker Hovestadt397, William Howat352, Alan P. Hoyle134, Ralph H. Hruban149, Jianhong Hu12, Taobo Hu64, Xing Hua240, Kuan-lin Huang1,398, Mei Huang176, Mi Ni Huang179,180, Vincent Huang6, Yi Huang65,66, Wolfgang Huber60, Thomas J. Hudson272,399, Michael Hummel400, Jillian A. Hung246,247, David Huntsman401, Ted R. Hupp402, Jason Huse88, Matthew R. Huska403, Barbara Hutter43,67,68, Carolyn M. Hutter27, Daniel Hübschmann48,54,404,405,406, Christine A. Iacobuzio-Donahue348, Charles David Imbusch205, Marcin Imielinski407,408, Seiya Imoto375, William B. Isaacs409, Keren Isaev6,44, Shumpei Ishikawa410, Murat Iskar397, S. M. Ashiqul Islam244, Michael Ittmann411,412,413, Sinisa Ivkovic284, Jose M. G. Izarzugaza414, Jocelyne Jacquemier415, Valerie Jakrot211, Nigel B. Jamieson133,172,416, Gun Ho Jang148, Se Jin Jang417, Joy C. Jayaseelan12, Reyka Jayasinghe1 , Stuart R. Jefferys134, Karine Jegalian418, Jennifer L. Jennings419, Seung-Hyup Jeon250, Lara Jerman60,420, Yuan Ji421,422, Wei Jiao6, Peter A. Johansson311, Amber L. Johns170, Jeremy Johns272, Rory Johnson230,423, Todd A. Johnson183, Clemency Jolly290, Yann Joly424, Jon G. Jonasson320, Corbin D. Jones425, David R. Jones49, David T. W. Jones426,427, Nic Jones428, Steven J. M. Jones30, Jos Jonkers204, Young Seok Ju49,249, Hartmut Juhl429, Jongsun Jung69, Malene Juul73, Randi Istrup Juul73, Sissel Juul374, Natalie Jäger47, Rolf Kabbe47, Andre Kahles276,277,278,279,430, Abdullah Kahraman431,432,433, Vera B. Kaiser434, Hojabr Kakavand211, Sangeetha Kalimuthu148, Christof von Kalle405, Koo Jeong Kang91, Katalin Karaszi351, Beth Karlan435, Rosa Karlić436, Dennis Karsch437, Katayoon Kasaian29,30, Karin S. Kassahn113,438, Hitoshi Katai439, Mamoru Kato440, Hiroto Katoh410, Yoshiiku Kawakami93, Jonathan D. Kay117, Stephen H. Kazakoff209,311, Marat D. Kazanov441,442,443, Maria Keays59, Electron Kebebew444,445, Richard F. Kefford446, Manolis Kellis8,447, James G. Kench170,350,448, Catherine J. Kennedy246,247, Jules N. A. Kerssemakers47, David Khoo273, Vincent Khoo221, Narong Khuntikeo115,449, Ekta Khurana301,302,450,451, Helena Kilpinen117, Hark Kyun Kim452, Hyung-Lae Kim70, Hyung-Yong Kim415, Hyunghwan Kim250, Jaegil Kim8, Jihoon Kim453, Jong K. Kim454, Youngwook Kim455,456, Tari A. King457,458,459, Wolfram Klapper128, Kortine Kleinheinz47,48, Leszek J. Klimczak460, Stian Knappskog49,461, Michael Kneba437, Bartha M. Knoppers424, Youngil Koh462,463, Jan Komorowski305,464, Daisuke Komura410, Mitsuhiro Komura375, Gu Kong415, Marcel Kool426,465, Jan O. Korbel59,60, Viktoriya Korchina12, Andrey Korshunov465, Michael Koscher465, Roelof Koster466, Zsofia Kote-Jarai178, Antonios Koures244, Milena Kovacevic284, Barbara Kremeyer49, Helene Kretzmer164,165, Markus Kreuz467, Savitri Krishnamurthy99,468, Dieter Kube469, Kiran Kumar8, Pardeep Kumar221, Sushant Kumar5,19, Yogesh Kumar64, Ritika Kundra114,121, Kirsten Kübler8,14,72, Ralf Küppers470, Jesper Lagergren383,471, Phillip H. Lai166, Peter W. Laird472, Sunil R. Lakhani473, Christopher M. Lalansingh6, Emilie Lalonde6, Fabien C. Lamaze6, Adam Lambert351, Eric Lander8, Pablo Landgraf474,475, Luca Landoni115, Anita Langerød130, Andrés Lanzós230,231,423, Denis Larsimont476, Erik Larsson477, Mark Lathrop189, Loretta M. S. Lau478, Chris Lawerenz55, Rita T. Lawlor177, Michael S. Lawrence8,72,183, Alexander J. Lazar99,108, Xuan Le479, Darlene Lee30, Donghoon Lee5, Eunjung Alice Lee480, Hee Jin Lee417, Jake June-Koo Lee264,266, Jeong-Yeon Lee481, Juhee Lee482, Ming Ta Michael Lee340, Henry Lee-Six49, Kjong-Van Lehmann276,277,278,279,430, Hans Lehrach483, Dido Lenze400, Conrad R. Leonard209,311, Daniel A. Leongamornlert49,178, Ignaty Leshchiner8, Louis Letourneau484, Ivica Letunic71, Douglas A. Levine88,485, Lora Lewis12, Tim Ley486, Chang Li56,396, Constance H. Li6,44, Haiyan Irene Li30, Jun Li21, Lin Li56, Shantao Li5, Siliang Li56,396, Xiaobo Li56,396, Xiaotong Li5, Xinyue Li56, Yilong Li49, Han Liang21, Sheng-Ben Liang234, Peter Lichter68,397, Pei Lin8, Ziao Lin8,487, W. M. Linehan488, Ole Christian Lingjærde489, Dongbing Liu56,396, Eric Minwei Liu88,301,302, Fei-Fei Liu201,490, Fenglin Liu381,491, Jia Liu492, Xingmin Liu56,396, Julie Livingstone6, Dimitri Livitz8, Naomi Livni221, Lucas Lochovsky5,19,110, Markus Loeffler467, Georgina V. Long211, Armando Lopez-Guillermo493, Shaoke Lou5,19, David N. Louis72, Laurence B. Lovat117, Yiling Lu38, Yong-Jie Lu162,494, Youyong Lu495,496,497, Claudio Luchini167, Ilinca Lungu144,148, Xuemei Luo152, Hayley J. Luxton117, Andy G. Lynch223,315,498, Lisa Lype36, Cristina López111,112, Carlos López-Otín499, Eric Z. Ma64, Yussanne Ma30, Gaetan MacGrogan500, Shona MacRae501, Geoff Macintyre223, Tobias Madsen73, Kazuhiro Maejima184, Andrea Mafficini177, Dennis T. Maglinte166,502, Arindam Maitra174, Partha P. Majumder174, Luca Malcovati232, Salem Malikic62,78, Giuseppe Malleo115, Graham J. Mann211,246,503, Luisa Mantovani-Löffler504, Kathleen Marchal505,506, Giovanni Marchegiani115, Elaine R. Mardis1,193,507, Adam A. Margolin31, Maximillian G. Marin37, Florian Markowetz223,315, Julia Markowski403, Jeffrey Marks508, Tomas Marques-Bonet61,81,386,509, Marco A. Marra30, Luke Marsden351, John W. M. Martens332, Sancha Martin49,510, Jose I. Martin-Subero81,511, Iñigo Martincorena49, Alexander Martinez-Fundichely301,302,451 Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Charlie E. Massie223, Thomas J. Matthew37, Lucy Matthews178, Erik Mayer221,512, Simon Mayes513, Michael Mayo30, Faridah Mbabaali272, Karen McCune514, Ultan McDermott49, Patrick D. McGillivray19, Michael D. McLellan1,3,20, John D. McPherson148,272,515, John R. McPherson179,180, Treasa A. McPherson260, Samuel R. Meier8, Alice Meng516, Shaowu Meng134, Andrew Menzies49, Neil D. Merrett115,517, Sue Merson178, Matthew Meyerson8,14,82, William U. Meyerson4,5, Piotr A. Mieczkowski518, George L. Mihaiescu76, Sanja Mijalkovic284, Ana Mijalkovic Mijalkovic-Lazic284, Tom Mikkelsen519, Michele Milella253, Linda Mileshkin103, Christopher A. Miller1 , David K. Miller113,170, Jessica K. Miller272, Gordon B. Mills33,34, Ana Milovanovic57, Sarah Minner520, Marco Miotto115, Gisela Mir Arnau267, Lisa Mirabello240, Chris Mitchell103, Thomas J. Mitchell49,315,352, Satoru Miyano375, Naoki Miyoshi375, Shinichi Mizuno521, Fruzsina Molnár-Gábor522, Malcolm J. Moore300, Richard A. Moore30, Sandro Morganella49, Quaid D. Morris127,490, Carl Morrison523,524, Lisle E. Mose134, Catherine D. Moser349, Ferran Muiños298,299, Loris Mularoni298,299, Andrew J. Mungall30, Karen Mungall30, Elizabeth A. Musgrove133, Ville Mustonen525,526,527, David Mutch528, Francesc Muyas52,53,74, Donna M. Muzny12, Alfonso Muñoz59, Jerome Myers529, Ola Myklebost461, Peter Möller530, Genta Nagae89, Adnan M. Nagrial170, Hardeep K. Nahal-Bose76, Hitoshi Nakagama531, Hidewaki Nakagawa184, Hiromi Nakamura118, Toru Nakamura388, Kaoru Nakano184, Tannistha Nandi532, Jyoti Nangalia49, Mia Nastic284, Arcadi Navarro61,81,386, Fabio C. P. Navarro19, David E. Neal223,352, Gerd Nettekoven533, Felicity Newell209,311, Steven J. Newhouse59, Yulia Newton37, Alvin Wei Tian Ng534, Anthony Ng535, Jonathan Nicholson49, David Nicol221, Yongzhan Nie321,536, G. Petur Nielsen72, Morten Muhlig Nielsen73, Serena Nik-Zainal49,281,282,537, Michael S. Noble8, Katia Nones209,311, Paul A. Northcott538, Faiyaz Notta148,539, Brian D. O’Connor76,540, Peter O’Donnell541, Maria O’Donovan282, Sarah O’Meara49, Brian Patrick O’Neill542, J. Robert O’Neill543, David Ocana59, Angelica Ochoa88, Layla Oesper544, Christopher Ogden221, Hideki Ohdan93, Kazuhiro Ohi375, Lucila Ohno-Machado244, Karin A. Oien523,545, Akinyemi I. Ojesina546,547,548, Hidenori Ojima549, Takuji Okusaka550, Larsson Omberg551, Choon Kiat Ong552, Stephan Ossowski52,53,74, German Ott553, B. F. Francis Ouellette76,554, Christine P’ng6, Marta Paczkowska6, Salvatore Paiella115, Chawalit Pairojkul523, Marina Pajic170, Qiang Pan-Hammarström56,555, Elli Papaemmanuil49, Irene Papatheodorou59, Nagarajan Paramasivam43,47, Ji Wan Park385, Joong-Won Park556, Keunchil Park557,558, Kiejung Park559, Peter J. Park264,266, Joel S. Parker518, Simon L. Parsons124, Harvey Pass560, Danielle Pasternack272, Alessandro Pastore276, Ann-Marie Patch209,311, Iris Pauporté251, Antonio Pea115, John V. Pearson209,311, Chandra Sekhar Pedamallu8,14,82, Jakob Skou Pedersen73,75, Paolo Pederzoli115, Martin Peifer270, Nathan A. Pennell561, Charles M. Perou129,518, Marc D. Perry76,77, Gloria M. Petersen562, Myron Peto22, Nicholas Petrelli563, Robert Petryszak59, Stefan M. Pfister426,465,564, Mark Phillips424, Oriol Pich298,299, Hilda A. Pickett478, Todd D. Pihl565, Nischalan Pillay566, Sarah Pinder567, Mark Pinese170, Andreia V. Pinho568, Esa Pitkänen60, Xavier Pivot569, Elena Piñeiro-Yáñez95, Laura Planko533, Christoph Plass345, Paz Polak8,14,15, Tirso Pons570, Irinel Popescu571, Olga Potapova572, Aparna Prasad52, Shaun R. Preston573, Manuel Prinz47, Antonia L. Pritchard311, Stephenie D. Prokopec6, Elena Provenzano574, Xose S. Puente499, Sonia Puig176, Montserrat Puiggròs57, Sergio Pulido-Tamayo505,506, Gulietta M. Pupo246, Colin A. Purdie575, Michael C. Quinn209,311, Raquel Rabionet52,53,576, Janet S. Rader577, Bernhard Radlwimmer397, Petar Radovic284, Benjamin Raeder60, Keiran M. Raine49, Manasa Ramakrishna49, Kamna Ramakrishnan49, Suresh Ramalingam578, Benjamin J. Raphael579, W. Kimryn Rathmell580, Tobias Rausch60, Guido Reifenberger475, Jüri Reimand6,44, Jorge Reis-Filho348, Victor Reuter348, Iker Reyes-Salazar298, Matthew A. Reyna579, Sheila M. Reynolds36, Esther Rheinbay8,14,72, Yasser Riazalhosseini189, Andrea L. Richardson323, Julia Richter111,128, Matthew Ringel581, Markus Ringnér181, Yasushi Rino582, Karsten Rippe405, Jeffrey Roach583, Lewis R. Roberts349, Nicola D. Roberts49, Steven A. Roberts584, A. Gordon Robertson30, Alan J. Robertson113, Javier Bartolomé Rodriguez57, Bernardo Rodriguez-Martin104,105,106, F. Germán Rodríguez-González83,332, Michael H. A. Roehrl44,123,148,234,585,586, Marius Rohde587, Hirofumi Rokutan440, Gilles Romieu588, Ilse Rooman170, Tom Roques262, Daniel Rosebrock8, Mara Rosenberg8,72, Philip C. Rosenstiel589, Andreas Rosenwald590, Edward W. Rowe221,591, Romina Royo57, Steven G. Rozen179,180,592, Yulia Rubanova17,127, Mark A. Rubin423,593,594,595,596, Carlota Rubio-Perez298,299,597, Vasilisa A. Rudneva60, Borislav C. Rusev177, Andrea Ruzzenente598, Gunnar Rätsch276,277,278,279,280,430, Radhakrishnan Sabarinathan298,299,599, Veronica Y. Sabelnykova6, Sara Sadeghi30, S. Cenk Sahinalp62,78,79, Natalie Saini357, Mihoko Saito-Adachi440, Gordon Saksena8, Adriana Salcedo6, Roberto Salgado600, Leonidas Salichos5,19, Richard Sallari8, Charles Saller601, Roberto Salvia115, Michelle Sam272, Jaswinder S. Samra115,602, Francisco Sanchez-Vega114,121, Chris Sander276,603,604, Grant Sanders134, Rajiv Sarin605, Iman Sarrafi62,78, Aya Sasaki-Oku184, Torill Sauer489, Guido Sauter520, Robyn P. M. Saw211, Maria Scardoni167, Christopher J. Scarlett170,606, Aldo Scarpa177, Ghislaine Scelo194, Dirk Schadendorf68,607, Jacqueline E. Schein30, Markus B. Schilhabel589, Matthias Schlesner47,80, Thorsten Schlomm84,608, Heather K. Schmidt1 , Sarah-Jane Schramm246, Stefan Schreiber609, Nikolaus Schultz121, Steven E. Schumacher8,323, Roland F. Schwarz59,403,405,610, Richard A. Scolyer211,448,602, David Scott428, Ralph Scully611, Raja Seethala612, Ayellet V. Segre8,613, Iris Selander260, Colin A. Semple434, Yasin Senbabaoglu276, Subhajit Sengupta614, Elisabetta Sereni115, Stefano Serra585, Dennis C. Sgroi72, Mark Shackleton103, Nimish C. Shah352, Sagedeh Shahabi234, Catherine A. Shang329, Ping Shang211, Ofer Shapira8,323, Troy Shelton271, Ciyue Shen603,604, Hui Shen615, Rebecca Shepherd49, Ruian Shi490, Yan Shi134, Yu-Jia Shiah6, Tatsuhiro Shibata118,616, Juliann Shih8,82, Eigo Shimizu375, Kiyo Shimizu617, Seung Jun Shin618, Yuichi Shiraishi375, Tal Shmaya285, Ilya Shmulevich36, Solomon I. Shorser6, Charles Short59, Raunak Shrestha62, Suyash S. Shringarpure217, Craig Shriver619, Shimin Shuai6,126, Nikos Sidiropoulos83, Reiner Siebert112,620, Anieta M. Sieuwerts332, Lina Sieverling205,237, Sabina Signoretti202,621, Katarzyna O. Sikora177, Michele Simbolo138, Ronald Simon520, Janae V. Simons134, Jared T. Simpson6,17, Peter T. Simpson473, Samuel Singer115,458, Nasa Sinnott-Armstrong8,217, Payal Sipahimalani30, Tara J. Skelly390, Marcel Smid332, Jaclyn Smith622, Karen Smith-McCune514, Nicholas D. Socci276, Heidi J. Sofia27, Matthew G. Soloway134, Lei Song240, Anil K. Sood623,624,625, Sharmila Sothi626, Christos Sotiriou244, Cameron M. Soulette37, Paul N. Span627, Paul T. Spellman22, Nicola Sperandio177, Andrew J. Spillane211, Oliver Spiro8, Jonathan Spring628, Johan Staaf181, Peter F. Stadler163,164,165, Peter Staib629, Stefan G. Stark277,279,618,630, Lucy Stebbings49, Ólafur Andri Stefánsson631, Oliver Stegle59,60,632, Lincoln D. Stein6,126, Alasdair Stenhouse633, Chip Stewart8, Stephan Stilgenbauer634, Miranda D. Stobbe52,61, Michael R. Stratton49, Jonathan R. Stretch211, Adam J. Struck31, Joshua M. Stuart24,37, Henk G. Stunnenberg396,635, Hong Su56,396, Xiaoping Su99, Ren X. Sun6, Stephanie Sungalee60, Hana Susak52,53, Akihiro Suzuki89,636, Fred Sweep637, Monika Szczepanowski128, Holger Sültmann67,638, Takashi Yugawa617, Angela Tam30, David Tamborero298,299, Benita Kiat Tee Tan639, Donghui Tan518, Patrick Tan180,532,592,640, Hiroko Tanaka375, Hirokazu Taniguchi616, Tomas J. Tanskanen641, Maxime Tarabichi49,290, Roy Tarnuzzer220, Patrick Tarpey642, Morgan L. Taschuk152, Kenji Tatsuno89, Simon Tavaré223,643, Darrin F. Taylor113, Amaro Taylor-Weiner8, Jon W. Teague49, Bin Tean Teh180,592,640,644,645, Varsha Tembe246, Javier Temes104,105, Kevin Thai76, Sarah P. Thayer393, Nina Thiessen30, Gilles Thomas646, Sarah Thomas221, Alan Thompson221, Alastair M. Thompson633, John F. Thompson211, R. Houston Thompson647, Heather Thorne103, Leigh B. Thorne176, Adrian Thorogood424, Grace Tiao8, Nebojsa Tijanic284, Lee E. Timms272, Roberto Tirabosco648, Marta Tojo106, Stefania Tommasi649, Christopher W. Toon170, Umut H. Toprak48,650, David Torrents57,81, Giampaolo Tortora651,652, Jörg Tost653, Yasushi Totoki118, David Townend654, Nadia Traficante103, Isabelle Treilleux655,656, Jean-Rémi Trotta61, Lorenz H. P. Trümper469, Ming Tsao124,539, Tatsuhiko Tsunoda183,657,658,659, Jose M. C. Tubio104,105,106, Olga Tucker660, Richard Turkington661, Daniel J. Turner513, Andrew Tutt323, Masaki Ueno376, Naoto T. Ueno662, Christopher Umbricht151,213,663, Husen M. Umer305,664, Timothy J. Underwood665, Lara Urban59,60, Tomoko Urushidate616, Tetsuo Ushiku339, Liis Uusküla-Reimand666,667, Alfonso Valencia57,81, David J. Van Den Berg166, Steven Van Laere307, Peter Van Loo290,291, Erwin G. Van Meir668, Gert G. Van den Eynden307, Theodorus Van der Kwast123, Naveen Vasudev137, Miguel Vazquez57,669, Ravikiran Vedururu267, Umadevi Veluvolu518, Shankar Vembu490,670, Lieven P. C. Verbeke506,671, Peter Vermeulen307, Clare Verrill351,672, Alain Viari177, David Vicente57, Caterina Vicentini177, K. Vijay Raghavan365, Juris Viksna673, Ricardo E. Vilain674, Izar Villasante57, Anne Vincent-Salomon635, Tapio Visakorpi190, Douglas Voet8, Paresh Vyas311,351, Ignacio Vázquez-García49,86,675,676, Nick M. Waddell209, Nicola Waddell209,311, Claes Wadelius677, Lina Wadi6, Rabea Wagener111,112, Jeremiah A. Wala8,14,82, Jian Wang56, Jiayin Wang1,40,66, Linghua Wang12, Qi Wang465, Wenyi Wang21, Yumeng Wang21, Zhining Wang220, Paul M. Waring523, Hans-Jörg Warnatz483, Jonathan Warrell5,19, Anne Y. Warren352,678, Sebastian M. Waszak60, David C. Wedge49,294,679, Dieter Weichenhan345, Paul Weinberger680, John N. Weinstein38, Joachim Weischenfeldt60,83,84, Daniel J. Weisenberger166, Ian Welch681, Michael C. Wendl1,10,11, Johannes Werner47,85, Justin P. Whalley61,682, David A. Wheeler12,13, Hayley C. Whitaker117, Dennis Wigle683, Matthew D. Wilkerson518, Ashley Williams244, James S. Wilmott211, Gavin W. Wilson6,148, Julie M. Wilson148, Richard K. Wilson1,684, Boris Winterhoff685, Jeffrey A. Wintersinger17,127,384, Maciej Wiznerowicz686,687, Stephan Wolf688, Bernice H. Wong689, Tina Wong1,30, Winghing Wong690, Youngchoon Woo250, Scott Wood209,311, Bradly G. Wouters44, Adam J. Wright6, Derek W. Wright133,691, Mark H. Wright217, Chin-Lee Wu72, Dai-Ying Wu285, Guanming Wu692, Jianmin Wu170, Kui Wu56,396, Yang Wu179,180, Zhenggang Wu64, Liu Xi12, Tian Xia693, Qian Xiang76, Xiao Xiao66, Rui Xing497, Heng Xiong56,396, Qinying Xu209,311, Yanxun Xu694, Hong Xue64, Shinichi Yachida118,695, Sergei Yakneen60, Rui Yamaguchi375, Takafumi N. Yamaguchi6, Masakazu Yamamoto120, Shogo Yamamoto89, Hiroki Yamaue376, Fan Yang490, Huanming Yang56, Jean Y. Yang696, Liming Yang220, Lixing Yang697, Shanlin Yang306, Tsun-Po Yang270, Yang Yang369, Xiaotong Yao408,698, Marie-Laure Yaspo483, Lucy Yates49, Christina Yau156, Chen Ye56,396, Kai Ye40,41, Venkata D. Yellapantula20,86, Christopher J. Yoon249, Sung-Soo Yoon463, Fouad Yousif6, Jun Yu699, Kaixian Yu700, Willie Yu701, Yingyan Yu702, Ke Yuan223,510,703, Yuan Yuan21, Denis Yuen6, Takashi Yugawa617, Christina K. Yung76, Olga Zaikova704, Jorge Zamora49,104,105,106, Marc Zapatka397, Jean C. Zenklusen220, Thorsten Zenz67, Nikolajs Zeps705,706, Cheng-Zhong Zhang8,707, Fan Zhang381, Hailei Zhang8, Hongwei Zhang494, Hongxin Zhang121, Jiashan Zhang220, Jing Zhang5, Junjun Zhang76, Xiuqing Zhang56, Xuanping Zhang66,369, Yan Zhang5,708,709, Zemin Zhang381,710, Zhongming Zhao711, Liangtao Zheng381, Xiuqing Zheng381, Wanding Zhou615, Yong Zhou56, Bin Zhu240, Hongtu Zhu700,712, Jingchun Zhu24, Shida Zhu56,396, Lihua Zou713, Xueqing Zou49, Anna deFazio246,247,714, Nicholas van As221, Carolien H. M. van Deurzen715, Marc J. van de Vijver523, L. van’t Veer716 & Christian von Mering433,717, The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.

This paper (re)tells the story of a sports coach who was accused of emotional abuse of a child athlete and, following an investigation by his club, cleared of the allegation. Accounts of such allegations are rare and no research to date has explored coaches’ lived experiences of this. Such stories are ‘dangerous’ and remain largely unrecognised and undebated as they represent a challenge to the meta-narrative of child protection. Using the stance of a ‘storyteller’, the coach-participant’s story is presented as a monologue crafted using his words and embellished with literary techniques. The story is purposefully largely left open for interpretation in an attempt to encourage readers to engage cognitively and emotionally with it. Telling such a ‘dangerous’ story aims to add to the narrative repertoires available to those working in this field and expand understandings of child protection in sport.