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Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response to targeted and immune therapies from the inferred expression values. We show that DeepPT successfully predicts transcriptomics in all 16 The Cancer Genome Atlas cohorts tested and generalizes well to two independent datasets. ENLIGHT-DeepPT successfully predicts true responders in five independent patient cohorts involving four different treatments spanning six cancer types, with an overall odds ratio of 2.28 and a 39.5% increased response rate among predicted responders versus the baseline rate. Notably, its prediction accuracy, obtained without any training on the treatment data, is comparable to that achieved by directly predicting the response from the images, which requires specific training on the treatment evaluation cohorts., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

The tumor microenvironment (TME) is a complex ecosystem of diverse cell types whose interactions govern tumor growth and clinical outcome. While the TME's impact on immunotherapy has been extensively studied, its role in chemotherapy response remains less explored. To address this, we developed DECODEM (DEcoupling Cell-type-specific Outcomes using DEconvolution and Machine learning), a generic computational framework leveraging cellular deconvolution of bulk transcriptomics to associate the gene expression of individual cell types in the TME with clinical response. Employing DECODEM to analyze the gene expression of breast cancer (BC) patients treated with neoadjuvant chemotherapy, we find that the gene expression of specific immune cells ( myeloid , plasmablasts , B-cells ) and stromal cells ( endothelial , normal epithelial , CAFs ) are highly predictive of chemotherapy response, going beyond that of the malignant cells. These findings are further tested and validated in a single-cell cohort of triple negative breast cancer. To investigate the possible role of immune cell-cell interactions (CCIs) in mediating chemotherapy response, we extended DECODEM to DECODEMi to identify such CCIs, validated in single-cell data. Our findings highlight the importance of active pre-treatment immune infiltration for chemotherapy success. The tools developed here are made publicly available and are applicable for studying the role of the TME in mediating response from readily available bulk tumor expression in a wide range of cancer treatments and indications., Competing Interests: COMPETING INTERESTS E.R. is a co-founder of Medaware Ltd. (https://www.medaware.com/), Metabomed (https://www.metabomed.com/), and Pangea Biomed (https://pangeamedicine.com/). He has divested and serves as an unpaid scientific consultant to the latter company. The rest of the authors declare no conflicts of interest.

B cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer., (© 2024. The Author(s).)

Analysis of circulating tumor DNA (ctDNA) to monitor cancer dynamics and detect minimal residual disease has been an area of increasing interest. Multiple methods have been proposed but few studies have compared the performance of different approaches. Here, we compare detection of ctDNA in serial plasma samples from patients with breast cancer using different tumor-informed and tumor-naïve assays designed to detect structural variants (SVs), single nucleotide variants (SNVs), and/or somatic copy-number aberrations, by multiplex PCR, hybrid capture, and different depths of whole-genome sequencing. Our results demonstrate that the ctDNA dynamics and allele fractions (AFs) were highly concordant when analyzing the same patient samples using different assays. Tumor-informed assays showed the highest sensitivity for detection of ctDNA at low concentrations. Hybrid capture sequencing targeting between 1,347 and 7,491 tumor-identified mutations at high depth was the most sensitive assay, detecting ctDNA down to an AF of 0.00024% (2.4 parts per million, ppm). Multiplex PCR targeting 21-47 tumor-identified SVs per patient detected ctDNA down to 0.00047% AF (4.7 ppm) and has potential as a clinical assay., (© 2023 The Authors. Published under the terms of the CC BY 4.0 license.)

The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international pan-cancer registry with the goal to inform cancer research and clinical care worldwide. Founded in late 2015, the milestone GENIE 9.1-public release contains data from >110,000 tumors from >100,000 people treated at 19 cancer centers from the United States, Canada, the United Kingdom, France, the Netherlands, and Spain. Here, we demonstrate the use of these real-world data, harmonized through a centralized data resource, to accurately predict enrollment on genome-guided trials, discover driver alterations in rare tumors, and identify cancer types without actionable mutations that could benefit from comprehensive genomic analysis. The extensible data infrastructure and governance framework support additional deep patient phenotyping through biopharmaceutical collaborations and expansion to include new data types such as cell-free DNA sequencing. AACR Project GENIE continues to serve a global precision medicine knowledge base of increasing impact to inform clinical decision-making and bring together cancer researchers internationally., Significance: AACR Project GENIE has now accrued data from >110,000 tumors, placing it among the largest repository of publicly available, clinically annotated genomic data in the world. GENIE has emerged as a powerful resource to evaluate genome-guided clinical trial design, uncover drivers of cancer subtypes, and inform real-world use of genomic data. This article is highlighted in the In This Issue feature, p. 2007., (©2022 The Authors; Published by the American Association for Cancer Research.)

Background: Previous studies have independently validated the prognostic relevance of residual cancer burden (RCB) after neoadjuvant chemotherapy. We used results from several independent cohorts in a pooled patient-level analysis to evaluate the relationship of RCB with long-term prognosis across different phenotypic subtypes of breast cancer, to assess generalisability in a broad range of practice settings., Methods: In this pooled analysis, 12 institutes and trials in Europe and the USA were identified by personal communications with site investigators. We obtained participant-level RCB results, and data on clinical and pathological stage, tumour subtype and grade, and treatment and follow-up in November, 2019, from patients (aged ≥18 years) with primary stage I-III breast cancer treated with neoadjuvant chemotherapy followed by surgery. We assessed the association between the continuous RCB score and the primary study outcome, event-free survival, using mixed-effects Cox models with the incorporation of random RCB and cohort effects to account for between-study heterogeneity, and stratification to account for differences in baseline hazard across cancer subtypes defined by hormone receptor status and HER2 status. The association was further evaluated within each breast cancer subtype in multivariable analyses incorporating random RCB and cohort effects and adjustments for age and pretreatment clinical T category, nodal status, and tumour grade. Kaplan-Meier estimates of event-free survival at 3, 5, and 10 years were computed for each RCB class within each subtype., Findings: We analysed participant-level data from 5161 patients treated with neoadjuvant chemotherapy between Sept 12, 1994, and Feb 11, 2019. Median age was 49 years (IQR 20-80). 1164 event-free survival events occurred during follow-up (median follow-up 56 months [IQR 0-186]). RCB score was prognostic within each breast cancer subtype, with higher RCB score significantly associated with worse event-free survival. The univariable hazard ratio (HR) associated with one unit increase in RCB ranged from 1·55 (95% CI 1·41-1·71) for hormone receptor-positive, HER2-negative patients to 2·16 (1·79-2·61) for the hormone receptor-negative, HER2-positive group (with or without HER2-targeted therapy; p<0·0001 for all subtypes). RCB score remained prognostic for event-free survival in multivariable models adjusted for age, grade, T category, and nodal status at baseline: the adjusted HR ranged from 1·52 (1·36-1·69) in the hormone receptor-positive, HER2-negative group to 2·09 (1·73-2·53) in the hormone receptor-negative, HER2-positive group (p<0·0001 for all subtypes)., Interpretation: RCB score and class were independently prognostic in all subtypes of breast cancer, and generalisable to multiple practice settings. Although variability in hormone receptor subtype definitions and treatment across patients are likely to affect prognostic performance, the association we observed between RCB and a patient's residual risk suggests that prospective evaluation of RCB could be considered to become part of standard pathology reporting after neoadjuvant therapy., Funding: National Cancer Institute at the US National Institutes of Health., Competing Interests: Declaration of interests AKG reports personal fees from Sinochips Diagnostics. CC reports institutional funding from Genentech, Roche, Servier, and AstraZeneca; and participation in a data and safety monitoring advisory board for iMED External Science Panel. CY reports institutional funding from Quantum Leap Healthcare Collaborative. DC reports institutional research funding from Novartis, AstraZeneca, Pfizer, Roche, Eli-Lilly, Puma Biotechnology, Daiichi Sankyo, Synthon, Seagen, Zymeworks, Elsevier, European Cancer Organisation, Celgene, Succinct Medical Communications, Prima BioMed (now Immutep), Oncolytics Biotech (US), Celldex Therapeutics, San Antonio Breast Cancer Consortium, Highfield Communication, Samsung Bioepis, prIME Oncology, Merck Sharp & Dohme, Prima BioMed (now Immutep), RTI Health Solutions, and Eisai. WFS owns stocks in Delphi Diagnostics; and reports the patent “method of measuring residual cancer and predicting patient survival” (US Patent and Trademark Office [USPTO] number 7711494B2). GSS reports institutional research funding from AstraZeneca, Merck, Novartis, and Roche. HE reports institutional research funding from Roche Sanofi-Aventis; is a consultant for Daiichi-Sankyo, AstraZeneca, Intas Pharmaceuticals, and prIME Oncology; and reports travel support from Daiichi-Sankyo, AstraZeneca, Intas Pharmaceuticals, Pfizer, and Amgen. JEA reports institutional research funding from AstraZeneca; and honoraria from Pfizer and Eisai. JMSB reports grants from Thermo Fisher Scientific, Geoptix, Agendia, NanoString Technologies, Stratifyer, and Biotheranostics; is a consultant for Insight Genetics, BioNTech, Biotheranostics, Pfizer, RNA Diagnostics, and OncoXchange; reports honoraria from NanoString Technology, Oncology Education, and Biotheranostics; reports travel support from Biotheranostics and Nanostring Technologies; reports patents “histone gene module predicts anthracycline benefit” (Patent Cooperation Treaty [PCT] number CA2016/000247); “95-gene signature of residual risk following endocrine treatment” (PCT number CA2016/000304); “immune gene signature predicts anthracycline benefit” (PCT number CA2016/000305); and applied for patents “methods and devices for predicting anthracycline treatment efficacy” (USPTO application number 15/325,472; European Patent Office number 15822898.1; Canada, not yet assigned) and “systems, devices and methods for constructing and using a biomarker” (USPTO application number 15/328,108; European Patent Office number 15824751.0; Canada, not yet assigned). JCB reports institutional research funding from Eli Lilly. LP is a consultant for and receives honoraria from AstraZeneca, Merck, Novartis, Genentech, Eisai, Pieris, Immunomedics, Seattle Genetics, Almac, H3 Biomedicine, Clovis, and Syndax; and reports the patent “method of measuring residual cancer and predicting patient survival” (US Patent Number 7711494B2). LaH reports individual research grants from Roche and Sanofi-Aventis; and travel support from Roche, AstraZeneca, Pfizer, and Sanofi-Aventis. LJE reports institutional research funding from Merck; participation in an advisory board for Blue Cross Blue Shield; and personal fees from UpToDate. LJvV is an employee of and owns stock in Agendia. MPG reports individual research grants from Pfizer, Sermonix, and Eli Lilly; and is a consultant for Pfizer, Eli Lilly, Novartis, Biotheranostics, Sermonix, Context Therapeutics, and Eagle Therapeutics. MM reports grants from Roche, Puma, and Novartis; is a consultant for AstraZeneca, Amgen, Glaxo, Taiho Oncology, Roche, Novartis, PharmaMar, Eli Lilly, Puma Biotechnology, Daiichi Sankyo, and Pfizer; reports honoraria from AstraZeneca, Amgen, Roche, Novartis, and Pfizer; and reports personal fees from Pfizer and Eli Lilly. PS reports institutional research funding from Novartis, Merck, and Bristol Myers Squibb; and is a consultant for Merck, Novartis, Seattle Genetics, Gilead Immunomedics, AstraZeneca, and ExactSciences. SL-T has received consulting fees from AstraZeneca, Novartis, Roche, Pfizer, Celgene, Pierre-Fabre, Eisai, and Eli Lilly; reports honoraria from Eli Lilly; and reports travel support from Novartis, Celgene, Merck Sharp & Dohme, Roche, and Pfizer. SBE reports institutional research funding from Pfizer. All other authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment 1 . The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy 2 . Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded by ERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery 3 were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers., (© 2021. The Author(s).)

DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, reduced representation bisulfite sequencing (RRBS) profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, this study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors., (© 2021. The Author(s).)

The biology of breast cancer response to neoadjuvant therapy is underrepresented in the literature and provides a window-of-opportunity to explore the genomic and microenvironment modulation of tumours exposed to therapy. Here, we characterised the mutational, gene expression, pathway enrichment and tumour-infiltrating lymphocytes (TILs) dynamics across different timepoints of 35 HER2-negative primary breast cancer patients receiving neoadjuvant eribulin therapy (SOLTI-1007 NEOERIBULIN-NCT01669252). Whole-exome data (N = 88 samples) generated mutational profiles and candidate neoantigens and were analysed along with RNA-Nanostring 545-gene expression (N = 96 samples) and stromal TILs (N = 105 samples). Tumour mutation burden varied across patients at baseline but not across the sampling timepoints for each patient. Mutational signatures were not always conserved across tumours. There was a trend towards higher odds of response and less hazard to relapse when the percentage of subclonal mutations was low, suggesting that more homogenous tumours might have better responses to neoadjuvant therapy. Few driver mutations (5.1%) generated putative neoantigens. Mutation and neoantigen load were positively correlated (R 2  = 0.94, p = <0.001); neoantigen load was weakly correlated with stromal TILs (R 2  = 0.16, p = 0.02). An enrichment in pathways linked to immune infiltration and reduced programmed cell death expression were seen after 12 weeks of eribulin in good responders. VEGF was downregulated over time in the good responder group and FABP5, an inductor of epithelial mesenchymal transition (EMT), was upregulated in cases that recurred (p < 0.05). Mutational heterogeneity, subclonal architecture and the improvement of immune microenvironment along with remodelling of hypoxia and EMT may influence the response to neoadjuvant treatment.

Molecular profiling of breast cancer has enabled the development of more robust molecular prognostic signatures and therapeutic options for breast cancer patients. However, non-Caucasian populations remain understudied. Here, we present the mutational, transcriptional, and copy number profiles of 560 Malaysian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to breast tumours in Caucasian women, we show an increased prevalence of HER2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. We also observe elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst HER2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.

Longitudinal analysis of circulating tumor DNA (ctDNA) has shown promise for monitoring treatment response. However, most current methods lack adequate sensitivity for residual disease detection during or after completion of treatment in patients with nonmetastatic cancer. To address this gap and to improve sensitivity for minute quantities of residual tumor DNA in plasma, we have developed targeted digital sequencing (TARDIS) for multiplexed analysis of patient-specific cancer mutations. In reference samples, by simultaneously analyzing 8 to 16 known mutations, TARDIS achieved 91 and 53% sensitivity at mutant allele fractions (AFs) of 3 in 10 4 and 3 in 10 5 , respectively, with 96% specificity, using input DNA equivalent to a single tube of blood. We successfully analyzed up to 115 mutations per patient in 80 plasma samples from 33 women with stage I to III breast cancer. Before treatment, TARDIS detected ctDNA in all patients with 0.11% median AF. After completion of neoadjuvant therapy, ctDNA concentrations were lower in patients who achieved pathological complete response (pathCR) compared to patients with residual disease (median AFs, 0.003 and 0.017%, respectively, P = 0.0057, AUC = 0.83). In addition, patients with pathCR showed a larger decrease in ctDNA concentrations during neoadjuvant therapy. These results demonstrate high accuracy for assessment of molecular response and residual disease during neoadjuvant therapy using ctDNA analysis. TARDIS has achieved up to 100-fold improvement beyond the current limit of ctDNA detection using clinically relevant blood volumes, demonstrating that personalized ctDNA tracking could enable individualized clinical management of patients with cancer treated with curative intent., (Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Aim: To validate a coding system implemented to summarise computed tomography colonography (CTC) findings for the detection of suspected colorectal cancer (CRC) by assessing interobserver variability and also to evaluate any weaknesses through qualitative analysis., Materials and Methods: All CTC investigations over a 6-month period (01/07/2016 to 31/12/2016) were analysed retrospectively. Each study was read initially by an advanced practitioner radiographer with a final report issued by a consultant gastrointestinal radiologist. Rates of interobserver agreement, using the kappa statistic, provided a quantitative assessment of levels of agreement. Areas of poor interobserver agreement were identified for further qualitative assessment., Results: The present study included 1,321 CTC procedures and the mean age of patients was 68.4 years (range 28-96 years). Percentage agreement for colonic coding was 90% and for extra-colonic coding 47%. This corresponds to kappa scores of 0.69 (substantial agreement) and 0.22 (fair agreement), respectively. Reasons and examples of disagreement in the colonic coding are highlighted., Conclusions: High interobserver agreement was observed for C coding, suggesting it is a reproducible method of classifying intra-colonic CTC findings. Some of the difference in classifying extra-colonic findings is the perceived importance of incidental findings between readers, as well as differences in skill set; however, some themes recurred in areas of disagreement and recommendations for refining and improving the coding system are provided., (Copyright © 2019 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.)

Background: Tumor-infiltrating lymphocytes (TILs) represent a prognostic factor for survival in primary breast cancer (BC). Nonetheless, neoepitope load and TILs cytolytic activity are modest in BC, compromising the efficacy of immune-activating antibodies, which do not yet compete against immunogenic chemotherapy., Patients and Methods: We analyzed by functional flow cytometry the immune dynamics of primary and metastatic axillary nodes [metastatic lymph nodes (mLN)] in early BC (EBC) after exposure to T-cell bispecific antibodies (TCB) bridging CD3ε and human epidermal growth factor receptor 2 (HER2) or Carcinoembryonic Antigen-Related Cell Adhesion Molecule 5 (CEACAM5), before and after chemotherapy. Human leukocyte antigen (HLA) class I loss was assessed by whole exome sequencing and immunohistochemistry. One hundred primary BC, 64 surrounding 'healthy tissue' and 24 mLN-related parameters were analyzed., Results: HLA loss of heterozygosity was observed in EBC, at a clonal and subclonal level and was associated with regulatory T cells and T-cell immunoglobulin and mucin-domain-3 expression restraining the immuno-stimulatory effects of neoadjuvant chemotherapy. TCB bridging CD3ε and HER2 or CEACAM5 could bypass major histocompatibility complex (MHC) class I loss, partially rescuing T-cell functions in mLN., Conclusion: TCB should be developed in BC to circumvent low MHC/peptide complexes., (© The Author(s) 2019. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

The detailed molecular characterization of lethal cancers is a prerequisite to understanding resistance to therapy and escape from cancer immunoediting. We performed extensive multi-platform profiling of multi-regional metastases in autopsies from 10 patients with therapy-resistant breast cancer. The integrated genomic and immune landscapes show that metastases propagate and evolve as communities of clones, reveal their predicted neo-antigen landscapes, and show that they can accumulate HLA loss of heterozygosity (LOH). The data further identify variable tumor microenvironments and reveal, through analyses of T cell receptor repertoires, that adaptive immune responses appear to co-evolve with the metastatic genomes. These findings reveal in fine detail the landscapes of lethal metastatic breast cancer., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

The rates and routes of lethal systemic spread in breast cancer are poorly understood owing to a lack of molecularly characterized patient cohorts with long-term, detailed follow-up data. Long-term follow-up is especially important for those with oestrogen-receptor (ER)-positive breast cancers, which can recur up to two decades after initial diagnosis 1-6 . It is therefore essential to identify patients who have a high risk of late relapse 7-9 . Here we present a statistical framework that models distinct disease stages (locoregional recurrence, distant recurrence, breast-cancer-related death and death from other causes) and competing risks of mortality from breast cancer, while yielding individual risk-of-recurrence predictions. We apply this model to 3,240 patients with breast cancer, including 1,980 for whom molecular data are available, and delineate spatiotemporal patterns of relapse across different categories of molecular information (namely immunohistochemical subtypes; PAM50 subtypes, which are based on gene-expression patterns 10,11 ; and integrative or IntClust subtypes, which are based on patterns of genomic copy-number alterations and gene expression 12,13 ). We identify four late-recurring integrative subtypes, comprising about one quarter (26%) of tumours that are both positive for ER and negative for human epidermal growth factor receptor 2, each with characteristic tumour-driving alterations in genomic copy number and a high risk of recurrence (mean 47-62%) up to 20 years after diagnosis. We also define a subgroup of triple-negative breast cancers in which cancer rarely recurs after five years, and a separate subgroup in which patients remain at risk. Use of the integrative subtypes improves the prediction of late, distant relapse beyond what is possible with clinical covariates (nodal status, tumour size, tumour grade and immunohistochemical subtype). These findings highlight opportunities for improved patient stratification and biomarker-driven clinical trials.

Circulating tumour DNA (ctDNA) detection and monitoring have enormous potential clinical utility in oncology. We describe here a fast, flexible and cost-effective method to profile multiple genes simultaneously in low input cell-free DNA (cfDNA): Next Generation-Targeted Amplicon Sequencing (NG-TAS). We designed a panel of 377 amplicons spanning 20 cancer genes and tested the NG-TAS pipeline using cell-free DNA from two HapMap lymphoblastoid cell lines. NG-TAS consistently detected mutations in cfDNA when mutation allele fraction was > 1%. We applied NG-TAS to a clinical cohort of metastatic breast cancer patients, demonstrating its potential in monitoring the disease. The computational pipeline is available at https://github.com/cclab-brca/NGTAS&#95;pipeline .

Pathology archives with linked clinical data are an invaluable resource for translational research, with the limitation that most cancer samples are formalin-fixed paraffin-embedded (FFPE) tissues. Therefore, FFPE tissues are an important resource for genomic profiling studies but are under-utilised due to the low amount and quality of extracted nucleic acids. We profiled the copy number landscape of 356 breast cancer patients using DNA extracted FFPE tissues by shallow whole genome sequencing. We generated a total of 491 sequencing libraries from 2 kits and obtained data from 98.4% of libraries with 86.4% being of good quality. We generated libraries from as low as 3.8 ng of input DNA and found that the success was independent of input DNA amount and quality, processing site and age of the fixed tissues. Since copy number alterations (CNA) play a major role in breast cancer, it is imperative that we are able to use FFPE archives and we have shown in this study that sWGS is a robust method to do such profiling., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Patient-Derived Tumour Xenografts (PDTXs) have emerged as the pre-clinical models that best represent clinical tumour diversity and intra-tumour heterogeneity. The molecular characterization of PDTXs using High-Throughput Sequencing (HTS) is essential; however, the presence of mouse stroma is challenging for HTS data analysis. Indeed, the high homology between the two genomes results in a proportion of mouse reads being mapped as human., Results: In this study we generated Whole Exome Sequencing (WES), Reduced Representation Bisulfite Sequencing (RRBS) and RNA sequencing (RNA-seq) data from samples with known mixtures of mouse and human DNA or RNA and from a cohort of human breast cancers and their derived PDTXs. We show that using an In silico Combined human-mouse Reference Genome (ICRG) for alignment discriminates between human and mouse reads with up to 99.9% accuracy and decreases the number of false positive somatic mutations caused by misalignment by >99.9%. We also derived a model to estimate the human DNA content in independent PDTX samples. For RNA-seq and RRBS data analysis, the use of the ICRG allows dissecting computationally the transcriptome and methylome of human tumour cells and mouse stroma. In a direct comparison with previously reported approaches, our method showed similar or higher accuracy while requiring significantly less computing time., Conclusions: The computational pipeline we describe here is a valuable tool for the molecular analysis of PDTXs as well as any other mixture of DNA or RNA species.

Purpose The glomerular filtration rate (GFR) is essential for carboplatin chemotherapy dosing; however, the best method to estimate GFR in patients with cancer is unknown. We identify the most accurate and least biased method. Methods We obtained data on age, sex, height, weight, serum creatinine concentrations, and results for GFR from chromium-51 ( 51 Cr) EDTA excretion measurements ( 51 Cr-EDTA GFR) from white patients ≥ 18 years of age with histologically confirmed cancer diagnoses at the Cambridge University Hospital NHS Trust, United Kingdom. We developed a new multivariable linear model for GFR using statistical regression analysis. 51 Cr-EDTA GFR was compared with the estimated GFR (eGFR) from seven published models and our new model, using the statistics root-mean-squared-error (RMSE) and median residual and on an internal and external validation data set. We performed a comparison of carboplatin dosing accuracy on the basis of an absolute percentage error > 20%. Results Between August 2006 and January 2013, data from 2,471 patients were obtained. The new model improved the eGFR accuracy (RMSE, 15.00 mL/min; 95% CI, 14.12 to 16.00 mL/min) compared with all published models. Body surface area (BSA)-adjusted chronic kidney disease epidemiology (CKD-EPI) was the most accurate published model for eGFR (RMSE, 16.30 mL/min; 95% CI, 15.34 to 17.38 mL/min) for the internal validation set. Importantly, the new model reduced the fraction of patients with a carboplatin dose absolute percentage error > 20% to 14.17% in contrast to 18.62% for the BSA-adjusted CKD-EPI and 25.51% for the Cockcroft-Gault formula. The results were externally validated. Conclusion In a large data set from patients with cancer, BSA-adjusted CKD-EPI is the most accurate published model to predict GFR. The new model improves this estimation and may present a new standard of care.

The use of circulating DNA(ctDNA) to provide a non-invasive, personalised genomic snapshot of a patients' tumour has huge potential. Over the past five years this area of research has gained huge momentum. A number of studies in metastatic breast cancer have shown the potential of ctDNA to predict prognosis and treatment response using ctDNA. Further developments have included deeper sequencing using whole exome and shallow whole genome approaches which has the potential to identify new mutations and chromosomal copy number changes which appear upon resistance to treatment. In early breast cancer, recent work utilising personalised digital PCR probes has shown huge potential in predicting disease relapse and the detection of micrometastatic disease which could lead to improved treatment and outcome for these patients. Specific pathways of resistance can also be monitored and liquid biopsy approaches for the detection of ESR1 mutations have been used which could identify patients who have become resistant to particular endocrine therapies. The identification of PIK3CA mutations in plasma has also been shown to predict a higher response rate to specific PI3K inhibitors and could be used as a non-invasive screening tool prior to treatment. Further work on the detection of exosomal miRNA and hypermethylated DNA in plasma have shown promise in terms of specificity for early breast cancer detection and could be used to monitor treatment response. This review will focus on technological advances in the field, early detection of relapse and the detection of tumour-specific genomic alterations which could predict treatment response and resistance in patients with breast cancer., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Bioinformatic analysis of genomic sequencing data to identify somatic mutations in cancer samples is far from achieving the required robustness and standardisation. In this study we generated a whole exome sequencing benchmark dataset using the platinum genome sample NA12878 and developed an intersect-then-combine (ITC) approach to increase the accuracy in calling single nucleotide variants (SNVs) and indels in tumour-normal pairs. We evaluated the effect of alignment, base quality recalibration, mutation caller and filtering on sensitivity and false positive rate. The ITC approach increased the sensitivity up to 17.1%, without increasing the false positive rate per megabase (FPR/Mb) and its validity was confirmed in a set of clinical samples.

Background: MammaPrint® is a microarray-based gene expression test cleared by the US Food and Drug Administration to assess recurrence risk in early-stage breast cancer, aimed to guide physicians in making neoadjuvant and adjuvant treatment decisions. The increase in the incidence of invasive lobular carcinomas (ILCs) over the past decades and the modest representation of ILC in the MammaPrint development data set calls for a stratified survival analysis dedicated to this specific subgroup., Study Aim: The current study aimed to validate the prognostic value of the MammaPrint test for breast cancer patients with early-stage ILCs., Materials and Methods: Univariate and multivariate survival associations for overall survival (OS), distant metastasis-free interval (DMFI), and distant metastasis-free survival (DMFS) were studied in a study population of 217 early-stage ILC breast cancer patients from five different clinical studies., Results and Discussion: A significant association between MammaPrint High Risk and poor clinical outcome was shown for OS, DMFI, and DMFS. A subanalysis was performed on the lymph node-negative study population. In the lymph node-negative study population, we report an up to 11 times higher change in the diagnosis of an event in the MammaPrint High Risk group. For DMFI, the reported hazard ratio is 11.1 (95% confidence interval = 2.3-53.0)., Conclusion: Study results validate MammaPrint as an independent factor for breast cancer patients with early-stage invasive lobular breast cancer. Hazard ratios up to 11 in multivariate analyses emphasize the independent value of MammaPrint, specifically in lymph node-negative ILC breast cancers., Competing Interests: Authors (IJB, MP, AW, CD, MS, RB, LJvtV, and AMG) are employed by Agendia, the commercial entity that markets the 70-gene signature as MammaPrint. LJvtV and RB are the named inventors on a patent application for the 70-gene signature used in this study. S-FC, S-JC and CC have no conflicts of interest. SL discloses, outside the work presented here, drugs supplied for a clinical study from AstraZeneca, advisory board memberships with Novartis, Cergentis, Philips Health BV, Roche and AstraZeneca, drugs supplied and a research grant to her institution from AstraZeneca, a research grant from Roche, a research grant from Genentech, and two patents pending for means and methods for molecular classification of BRCA-like breast and/or ovarian cancer. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.

The inter- and intra-tumor heterogeneity of breast cancer needs to be adequately captured in pre-clinical models. We have created a large collection of breast cancer patient-derived tumor xenografts (PDTXs), in which the morphological and molecular characteristics of the originating tumor are preserved through passaging in the mouse. An integrated platform combining in vivo maintenance of these PDTXs along with short-term cultures of PDTX-derived tumor cells (PDTCs) was optimized. Remarkably, the intra-tumor genomic clonal architecture present in the originating breast cancers was mostly preserved upon serial passaging in xenografts and in short-term cultured PDTCs. We assessed drug responses in PDTCs on a high-throughput platform and validated several ex vivo responses in vivo. The biobank represents a powerful resource for pre-clinical breast cancer pharmacogenomic studies (http://caldaslab.cruk.cam.ac.uk/bcape), including identification of biomarkers of response or resistance., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2,433 primary breast tumours that have copy number aberration (CNA), gene expression and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intra-tumour heterogeneity using mutant-allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13-14 or 8q24). High levels of intra-tumour heterogeneity are in general associated with a worse outcome, but highly aggressive tumours with 11q13-14 amplification have low levels of intra-tumour heterogeneity. These results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies.

Normal homeostasis of adult intestinal epithelium and repair following tissue damage is maintained by a balance of stem and differentiated cells, many of which are still only poorly characterised. Enteroendocrine cells of the gut are a small population of differentiated, secretory cells that are critical for integrating nutrient sensing with metabolic responses, dispersed amongst other epithelial cells. Recent evidence suggests that sub-sets of secretory enteroendocrine cells can act as reserve stem cells. Given the link between cells with stem-like properties and cancer, it is important that we identify factors that might provide a bridge between the two. Here, we identify a sub-set of chromogranin A-positive enteroendocrine cells that are positive for the developmental and cancer-associated transcription factor Brachyury in normal human small intestinal and colonic crypts. Whilst chromogranin A-positive enteroendocrine cells are also Brachyury-positive in colorectal tumours, expression of Brachyury becomes more diffuse in these samples, suggesting a more widespread function in cancer. The finding of the developmental transcription factor Brachyury in normal adult human intestinal crypts may extend the functional complexity of enteroendocrine cells and serves as a platform for assessment of the molecular processes of intestinal homeostasis that underpins our understanding of human health, cancer and aging.

Invasive lobular carcinoma (ILC) is the second most frequently occurring histological breast cancer subtype after invasive ductal carcinoma (IDC), accounting for around 10% of all breast cancers. The molecular processes that drive the development of ILC are still largely unknown. We have performed a comprehensive genomic, transcriptomic and proteomic analysis of a large ILC patient cohort and present here an integrated molecular portrait of ILC. Mutations in CDH1 and in the PI3K pathway are the most frequent molecular alterations in ILC. We identified two main subtypes of ILCs: (i) an immune related subtype with mRNA up-regulation of PD-L1, PD-1 and CTLA-4 and greater sensitivity to DNA-damaging agents in representative cell line models; (ii) a hormone related subtype, associated with Epithelial to Mesenchymal Transition (EMT), and gain of chromosomes 1q and 8q and loss of chromosome 11q. Using the somatic mutation rate and eIF4B protein level, we identified three groups with different clinical outcomes, including a group with extremely good prognosis. We provide a comprehensive overview of the molecular alterations driving ILC and have explored links with therapy response. This molecular characterization may help to tailor treatment of ILC through the application of specific targeted, chemo- and/or immune-therapies.

We propose a robust imaging technique that makes it possible to distinguish vortices from antivortices in quasi-two-dimensional Bose-Einstein condensates from a single image of the density of the atoms. Tilting the planar condensate prior to standard absorption imaging excites a generalized gyroscopic mode of the condensate, revealing the sign and location of each vortex. This technique is anticipated to enable experimental measurement of the incompressible kinetic energy spectrum of the condensate and the observation of a negative-temperature phase transition of the vortex gas, driven by two-dimensional superfluid turbulence.

Blood cells derive from hematopoietic stem cells through stepwise fating events. To characterize gene expression programs driving lineage choice, we sequenced RNA from eight primary human hematopoietic progenitor populations representing the major myeloid commitment stages and the main lymphoid stage. We identified extensive cell type-specific expression changes: 6711 genes and 10,724 transcripts, enriched in non-protein-coding elements at early stages of differentiation. In addition, we found 7881 novel splice junctions and 2301 differentially used alternative splicing events, enriched in genes involved in regulatory processes. We demonstrated experimentally cell-specific isoform usage, identifying nuclear factor I/B (NFIB) as a regulator of megakaryocyte maturation-the platelet precursor. Our data highlight the complexity of fating events in closely related progenitor populations, the understanding of which is essential for the advancement of transplantation and regenerative medicine., (Copyright © 2014, American Association for the Advancement of Science.)

The T-box transcription factor Brachyury is expressed in a number of tumour types and has been demonstrated to have cancer inducing properties. To date, it has been linked to cancer associated induction of epithelial to mesenchymal transition, tumour metastasis and expression of markers for cancer stem-like cells. Taken together, these findings indicate that Brachyury plays an important role in the progression of cancer, although the mechanism through which it functions is poorly understood. Here we show that Brachyury regulates the potential of Brachyury-positive colorectal cancer cells to proliferate and reduced levels of Brachyury result in inhibition of proliferation, with features consistent with the cells entering a quiescent-like state. This inhibition of proliferation is dependent upon p27Kip1 demonstrating that Brachyury acts to modulate cellular proliferative fate in colorectal cancer cells in a p27Kip1-dependent manner. Analysis of patient derived colorectal tumours reveals a heterogeneous localisation of Brachyury (in the nucleolus, nucleus and cytoplasm) indicating the potential complexity of the regulatory role of Brachyury in solid colorectal tumours.

The identification of cancer-specific biomolecules is of fundamental importance to the development of diagnostic and/or prognostic markers, which may also serve as therapeutic targets. Some antigenic proteins are only normally present in male gametogenic tissues in the testis and not in normal somatic cells. When these proteins are aberrantly produced in cancer they are referred to as cancer/testis (CT) antigens (CTAs). Some CTA genes have been proven to encode immunogenic proteins that have been used as successful immunotherapy targets for various forms of cancer and have been implicated as drug targets. Here, a targeted in silico analysis of cancer expressed sequence tag (EST) data sets resulted in the identification of a significant number of novel CT genes. The expression profiles of these genes were validated in a range of normal and cancerous cell types. Subsequent meta-analysis of gene expression microarray data sets demonstrates that these genes are clinically relevant as cancer-specific biomarkers, which could pave the way for the discovery of new therapies and/or diagnostic/prognostic monitoring technologies.

A significant proportion of biomedical resources carries information that cross references to anatomical structures across multiple scales. To improve the visualization of such resources in their anatomical context, we developed an automated methodology that produces anatomy schematics in a consistent manner,and provides for the overlay of anatomy-related resource information onto the same diagram. This methodology, called ApiNATOMY, draws upon the topology of ontology graphs to automatically lay out treemaps representing body parts as well as semantic metadata linking to such ontologies. More generally, ApiNATOMY treemaps provide an efficient and manageable way to visualize large biomedical ontologies in a meaningful and consistent manner. In the anatomy domain, such treemaps will allow epidemiologists, clinicians, and biomedical scientists to review, and interact with, anatomically aggregated heterogeneous data and model resources. Such an approach supports the visual identification of functional relations between anatomically colocalized resources that may not be immediately amenable to automation by ontology-based inferencing. We also describe the application of ApiNATOMY schematics to integrate, and add value to, human phenotype-related information—results are found at http://apinatomy.org. The long-term goal for the ApiNATOMY toolkit is to support clinical and scientific graphical user interfaces and dashboards for biomedical resource management and data analytics., ((c) 2012 Wiley Periodicals, Inc.)

Background: Neutropenic fever in patients receiving chemotherapy is a medical emergency and should be treated promptly within 1 h with antibiotics as specified within the 2009 NCAG report on chemotherapy services., Aim: To determine door-to-assessment, door-to-treatment and door-to-investigation intervals for patients with febrile neutropenia who presented to the inpatient Oncology Ward, the outpatient Oncology Day Unit and the Emergency Department in Addenbrooke's Hospital, Cambridge., Design: Retrospective observational audit., Methods: Thirty-two patients on treatment for solid cancers who were admitted with febrile neutropenia between January and December 2010 were identified, and paper and electronic medical records were analysed to determine door to: assessment, treatment and investigation intervals., Results and Conclusions: Patients in this series were assessed quicker and received the first dose of antibiotics faster when they presented to an oncology ward rather than the emergency department. However, imaging was performed faster and blood results issued quicker if performed in the emergency department due to a better infrastructure that has been tailored to comply with national targets. Nonetheless, compliance with optimum standards of care was poor, with only 9% of sampled patients getting antibiotics within 1 h of presenting to hospital, and 53% within 1 h of being assessed by a clinician.

Plasminogen activator inhibitor (PAI)-1 is associated with cancer progression, fibrosis and thrombosis. It is expressed in the stomach but the mechanisms controlling its expression there, and its biological role, are uncertain. We sought to define the role of gastrin in regulating PAI-1 expression and to determine the relevance for gastrin-stimulated cell migration and invasion. In gastric biopsies from subjects with elevated plasma gastrin, the abundances of PAI-1, urokinase plasminogen activator (uPA), and uPA receptor (uPAR) mRNAs measured by quantitative PCR were increased compared with subjects with plasma concentrations in the reference range. In patients with hypergastrinemia due to autoimmune chronic atrophic gastritis, there was increased abundance of PAI-1, uPA, and uPAR mRNAs that was reduced by octreotide or antrectomy. Immunohistochemistry revealed localization of PAI-1 to parietal cells and enterochromaffin-like cells in micronodular neuroendocrine tumors in hypergastrinemic subjects. Transcriptional mechanisms were studied by using a PAI-1-luciferase promoter-reporter construct transfected into AGS-G(R) cells. There was time- and concentration-dependent increase of PAI-1-luciferase expression in response to gastrin that was reversed by inhibitors of the PKC and MAPK pathways. In Boyden chamber assays, recombinant PAI-1 inhibited gastrin-stimulated AGS-G(R) cell migration and invasion, and small interfering RNA treatment increased responses to gastrin. We conclude that elevated plasma gastrin concentrations are associated with increased expression of gastric PAI-1, which may act to restrain gastrin-stimulated cell migration and invasion.

The gastric pathogen Helicobacter pylori (H. pylori) is linked to peptic ulcer and gastric cancer, but the relevant pathophysiological mechanisms are unclear. We now report that H. pylori stimulates the expression of plasminogen activator inhibitor (PAI)-1, urokinase plasminogen activator (uPA), and its receptor (uPAR) in gastric epithelial cells and the consequences for epithelial cell proliferation. Real-time PCR of biopsies from gastric corpus, but not antrum, showed significantly increased PAI-1, uPA, and uPAR in H. pylori-positive patients. Transfection of primary human gastric epithelial cells with uPA, PAI-1, or uPAR promoters in luciferase reporter constructs revealed expression of all three in H+/K+ATPase- and vesicular monoamine transporter 2-expressing cells; uPA was also expressed in pepsinogen- and uPAR-containing trefoil peptide-1-expressing cells. In each case expression was increased in response to H. pylori and for uPA, but not PAI-1 or uPAR, required the virulence factor CagE. H. pylori also stimulated soluble and cell surface-bound uPA activity, and both were further increased by PAI-1 knockdown, consistent with PAI-1 inhibition of endogenous uPA. H. pylori stimulated epithelial cell proliferation, which was inhibited by uPA immunoneutralization and uPAR knockdown; exogenous uPA also stimulated proliferation that was further increased after PAI-1 knockdown. The proliferative effects of uPA were inhibited by immunoneutralization of the EGF receptor and of heparin-binding EGF (HB-EGF) by the mutant diphtheria toxin CRM197 and an EGF receptor tyrosine kinase inhibitor. H. pylori induction of uPA therefore leads to epithelial proliferation through activation of HB-EGF and is normally inhibited by concomitant induction of PAI-1; treatments directed at inhibition of uPA may slow the progression to gastric cancer.

Warts are a common skin complaint in childhood. We describe 3 unusual cases in which inadvertent tissue injury was caused during the treatment of viral warts by a commercially available cryotherapy device. In each case there was a failure to follow the instructions provided correctly. If such devices are to remain available for public use we feel changes should be implemented to reduce the risk of such injuries occurring again in the future. Alternatively, cryotherapy as a treatment modality should remain in the realm of the trained health care professional.

Classifications of proteins into groups of related sequences are in some respects like a periodic table for biology, allowing us to understand the underlying molecular biology of any organism. Pfam is a large collection of protein domains and families. Its scientific goal is to provide a complete and accurate classification of protein families and domains. The next release of the database will contain over 10,000 entries, which leads us to reflect on how far we are from completing this work. Currently Pfam matches 72% of known protein sequences, but for proteins with known structure Pfam matches 95%, which we believe represents the likely upper bound. Based on our analysis a further 28,000 families would be required to achieve this level of coverage for the current sequence database. We also show that as more sequences are added to the sequence databases the fraction of sequences that Pfam matches is reduced, suggesting that continued addition of new families is essential to maintain its relevance.

Introduction: We describe a case of a 9-year-old girl who developed progressive severe retro-orbital pain and partial visual loss in association with left optic-nerve compression due to polyostotic fibrous dysplasia of the skull., Materials and Methods: Intradural decompression of the optic nerve resulted in immediate and complete resolution of the pain as well as a vast visual improvement., Conclusion: In cases of fibrous dysplasia of the skull with evidence of optic-nerve compression, relief of retro-orbital pain should be an additional consideration when deciding to proceed with surgical management.

Pfam is a comprehensive collection of protein domains and families, represented as multiple sequence alignments and as profile hidden Markov models. The current release of Pfam (22.0) contains 9318 protein families. Pfam is now based not only on the UniProtKB sequence database, but also on NCBI GenPept and on sequences from selected metagenomics projects. Pfam is available on the web from the consortium members using a new, consistent and improved website design in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/), as well as from mirror sites in France (http://pfam.jouy.inra.fr/) and South Korea (http://pfam.ccbb.re.kr/).