Ptychographic Nanoscale Imaging of the Magnetoelectric Coupling in Freestanding BiFeO3

Understanding the magnetic and ferroelectric ordering of magnetoelectric multiferroic materials at the nanoscale necessitates a versatile imaging method with high spatial resolution. Here, soft X-ray ptychography is employed to simultaneously image the ferroelectric and antiferromagnetic domains in an 80 nm thin freestanding film of the room-temperature multiferroic BiFeO3 (BFO). The antiferromagnetic spin cycloid of period 64 nm is resolved by reconstructing the corresponding resonant elastic X-ray scattering in real space and visualized together with mosaic-like ferroelectric domains in a linear dichroic contrast image at the Fe L3 edge. The measurements reveal a near perfect coupling between the antiferromagnetic and ferroelectric ordering by which the propagation direction of the spin cycloid is locked orthogonally to the ferroelectric polarization. In addition, the study evinces both a preference for in-plane propagation of the spin cycloid and changes of the ferroelectric polarization by 71° between multiferroic domains in the epitaxial strain-free, freestanding BFO film. The results provide a direct visualization of the strong magnetoelectric coupling in BFO and of its fine multiferroic domain structure, emphasizing the potential of ptychographic imaging for the study of multiferroics and non-collinear magnetic materials with soft X-rays.

In vivo low-dose phase-contrast CT for quantification of functional and anatomical alterations in lungs of an experimental allergic airway disease mouse model

Introduction

Synchrotron-based propagation-based imaging (PBI) is ideally suited for lung imaging and has successfully been applied in a variety of in vivo small animal studies. Virtually all these experiments were tailored to achieve extremely high spatial resolution close to the alveolar level while delivering high x-ray doses that would not permit longitudinal studies. However, the main rationale for performing lung imaging studies in vivo in small animal models is the ability to follow disease progression or monitor treatment response in the same animal over time. Thus, an in vivo imaging strategy should ideally allow performing longitudinal studies.

Methods

Here, we demonstrate our findings of using PBI-based planar and CT imaging with two different detectors-MÖNCH 0.3 direct conversion detector and a complementary metal-oxide-semiconductor (CMOS) detector (Photonics Science)-in an Ovalbumin induced experimental allergic airway disease mouse model in comparison with healthy controls. The mice were imaged free breathing under isoflurane anesthesia.

Results

At x-ray dose levels below those once used by commercial small animal CT devices at similar spatial resolutions, we were able to resolve structural changes at a pixel size down to 25 μm and demonstrate the reduction in elastic recoil in the asthmatic mice in cinematic planar x-ray imaging with a frame rate of up to 100 fps.

Discussion

Thus, we believe that our approach will permit longitudinal small animal lung disease studies, closely following the mice over longer time spans.

Quantum Efficiency Measurement and Modeling of Silicon Sensors Optimized for Soft X-ray Detection

Hybrid pixel detectors have become indispensable at synchrotron and X-ray free-electron laser facilities thanks to their large dynamic range, high frame rate, low noise, and large area. However, at energies below 3 keV, the detector performance is often limited because of the poor quantum efficiency of the sensor and the difficulty in achieving single-photon resolution due to the low signal-to-noise ratio. In this paper, we address the quantum efficiency of silicon sensors by refining the design of the entrance window, mainly by passivating the silicon surface and optimizing the dopant profile of the n+ region. We present the measurement of the quantum efficiency in the soft X-ray energy range for silicon sensors with several process variations in the fabrication of planar sensors with thin entrance windows. The quantum efficiency for 250 eV photons is increased from almost 0.5% for a standard sensor to up to 62% as a consequence of these developments, comparable to the quantum efficiency of backside-illuminated scientific CMOS sensors. Finally, we discuss the influence of the various process parameters on quantum efficiency and present a strategy for further improvement.

Epigenomic Blood-Based Early Detection of Pancreatic Cancer Employing Cell-Free DNA

BACKGROUND & AIMS

Early detection of pancreatic cancer (PaC) can drastically improve survival rates. Approximately 25% of subjects with PaC have type 2 diabetes diagnosed within 3 years prior to the PaC diagnosis, suggesting that subjects with type 2 diabetes are at high risk of occult PaC. We have developed an early-detection PaC test, based on changes in 5-hydroxymethylcytosine (5hmC) signals in cell-free DNA from plasma.

METHODS

Blood was collected from 132 subjects with PaC and 528 noncancer subjects to generate epigenomic and genomic feature sets yielding a predictive PaC signal algorithm. The algorithm was validated in a blinded cohort composed of 102 subjects with PaC, 2048 noncancer subjects, and 1524 subjects with non-PaCs.

RESULTS

5hmC differential profiling and additional genomic features enabled the development of a machine learning algorithm capable of distinguishing subjects with PaC from noncancer subjects with high specificity and sensitivity. The algorithm was validated with a sensitivity for early-stage (stage I/II) PaC of 68.3% (95% confidence interval [CI], 51.9%-81.9%) and an overall specificity of 96.9% (95% CI, 96.1%-97.7%).

CONCLUSIONS

The PaC detection test showed robust early-stage detection of PaC signal in the studied cohorts with varying type 2 diabetes status. This assay merits further clinical validation for the early detection of PaC in high-risk individuals.

Early detection of pancreatic cancer using 5-hydroxymethylation profiles in plasma-derived cell-free DNA

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Background: Pancreatic cancer is one of the deadliest cancers, with approximately 15-20% of patients who present at diagnosis with a resectable disease. The major barrier to better outcomes is the lack of early-detection molecular tools to enable timely intervention. We have developed a test that enables the detection of pancreatic cancer from a simple blood draw. The test incorporates a novel, genome-wide sequencing-based epigenomics detection method that enriches for DNA loci that undergo active de-methylation. The measurement of 5-hydroxymethylcytosine (5hmC) provides a unique and stable biomarker for the early detection of cancer including pancreatic cancer. Methods: Whole-blood was obtained from a training cohort of 660 individuals (consisting of 132 pancreatic cancers (PaCa) and 528 non-cancers) and a validation cohort of 2,150 individuals (consisting of 102 PaCa and 2,048 non-cancers). Cell-free DNA (cfDNA) was isolated from plasma from which 5hmC and whole-genome libraries were generated and sequenced. Logistic regression algorithms were employed using 5hmC feature sets combined with physical characteristics of DNA fragments to optimally partition cancer from non-cancer samples. Results: Cross validation of the training model yielded an overall sensitivity of 65.9%,(95% CI, 57.2%–73.9%), early-stage (stage I-II) sensitivity of 57.1% (95% CI, 44%–69.5%) and a specificity of 98%. The model was further validated in a separate, non-overlapping set of blinded and independently processed samples and yielded an early-stage sensitivity of 68.3% (95% CI, 51.9%–81.9%) and a specificity of 96.9% (95% CI, 96.0%–97.6%). Conclusions: Our results demonstrate that plasma-derived cfDNA 5hmC profiles enable the accurate detection of early-stage PaCa, providing a valuable non-invasive tool especially for those individuals at high risk for the disease, including individuals with genetic predisposition and newly diagnosed type 2 diabetes. A larger clinical study (NODMED - NCT05188586) is ongoing and will provide clinical validation for the detection in individuals at high risk for this deadly disease.

The 5-Hydroxymethylcytosine Landscape of Prostate Cancer

Analysis of DNA methylation is a valuable tool to understand disease progression and is increasingly being used to create diagnostic and prognostic clinical biomarkers. While conversion of cytosine to 5-methylcytosine (5mC) commonly results in transcriptional repression, further conversion to 5-hydroxymethylcytosine (5hmC) is associated with transcriptional activation. Here we perform the first study integrating whole-genome 5hmC with DNA, 5mC, and transcriptome sequencing in clinical samples of benign, localized, and advanced prostate cancer. 5hmC is shown to mark activation of cancer drivers and downstream targets. Furthermore, 5hmC sequencing revealed profoundly altered cell states throughout the disease course, characterized by increased proliferation, oncogenic signaling, dedifferentiation, and lineage plasticity to neuroendocrine and gastrointestinal lineages. Finally, 5hmC sequencing of cell-free DNA from patients with metastatic disease proved useful as a prognostic biomarker able to identify an aggressive subtype of prostate cancer using the genes TOP2A and EZH2, previously only detectable by transcriptomic analysis of solid tumor biopsies. Overall, these findings reveal that 5hmC marks epigenomic activation in prostate cancer and identify hallmarks of prostate cancer progression with potential as biomarkers of aggressive disease.

SIGNIFICANCE

In prostate cancer, 5-hydroxymethylcytosine delineates oncogene activation and stage-specific cell states and can be analyzed in liquid biopsies to detect cancer phenotypes. See related article by Wu and Attard, p. 3880.

The cell type specific 5hmC landscape and dynamics of healthy human hematopoiesis and TET2-mutant pre-leukemia

The conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) is a key step in DNA demethylation that is mediated by ten-eleven-translocation (TET) enzymes, which require ascorbate/vitamin C. Here, we report the 5hmC landscape of normal hematopoiesis and identify cell type-specific 5hmC profiles associated with active transcription and chromatin accessibility of key hematopoietic regulators. We utilized CRISPR/Cas9 to model TET2 loss-of-function mutations in primary human HSPCs. Disrupted cells exhibited increased colonies in serial replating, defective erythroid/megakaryocytic differentiation, and in vivo competitive advantage and myeloid skewing coupled with reduction of 5hmC at erythroid-associated gene loci. Azacitidine and ascorbate restored 5hmC abundance and slowed or reverted the expansion of TET2-mutant clones in vivo. These results demonstrate the key role of 5hmC in normal hematopoiesis and TET2-mutant phenotypes and raise the possibility of utilizing these agents to further our understanding of pre-leukemia/clonal hematopoiesis.

Pancreatic cancer detection using 5-hydroxymethylation signatures in plasma-derived cell free DNA in high-risk patients with new onset diabetes

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Background: Pancreatic cancer (PaCa) is the third leading cause of cancer death in the United States despite a low incidence rate. It is often diagnosed when cancer has already metastasized to distant organs. Late diagnosis deprives patients of potentially curative treatments such as surgery and impacts survival rates. People with new onset diabetes (NOD) are at 6-8 fold increased risk for PaCa compared to the general population. Indeed, 0.85% of patients with NOD will be diagnosed with PaCa within 3 years. This population of PaCa patients with NOD constitute 25% of all new pancreatic cancer diagnoses. Surveillance of the NOD population for PaCa presents an opportunity to shift PaCa diagnosis to earlier stage. Methods: Whole blood was obtained from a cohort of 167 PaCa patients and 490 patients with cancers other than PaCa as well as 836 non-cancer controls with and without NOD. Plasma was processed to isolate cfDNA and 5hmC libraries were generated and sequenced. 5hmC data is used to generate models for PaCa detection using Bluestar Genomics’s technology platform. Results: To investigate whether PaCa can be detected in plasma, we interrogated plasma-derived cfDNA hydroxymethylation in PaCa patients and non-cancer controls. Models trained using 5hmC-based biomarkers from cfDNA consistently performed with a mean test sensitivity of 61.1% [95% confidence interval (CI): 35.7% to 82.7%] and a test specificity of 97.6% (CI: 93% to 99.5%) measured across 50 cross validation iterations within the training data set, which was composed of 48.3% early stage (Stages I & II) disease. The final model was trained using all of the training data, yielding 58.4% (CI: 47.5% to 68.8%) sensitivity at 98% (CI: 96.5% to 99.0%) specificity. This model was then tested on an independent test set with 22 PaCa patients (51.7% early stage, 15 of which was NOD) and 123 non-cancer control patients (53 of which were NOD) and yielded a classification performance of 59.1% (CI: 36.4% to 79.3%) sensitivity at 95.9% (CI: 90.8% to 98.7%) specificity. The model performance in the subset of patient cohort with NOD was 53.3% (CI: 26.6% to 78.7%) sensitivity at 94.3% (CI: 84.3% to 98.8%) specificity. Lastly, sensitivity observed on an independent validation set, composed of 56 PaCa and 117 ITTP samples, was 46.4% (CI: 33.0% to 60.2%) with 100% (CI: 96.8 to 100%) specificity. Conclusions: Our results demonstrate PaCa detection in plasma-derived cfDNA using 5hmC profiles. Overall, the model performed consistently between the training and independent validation datasets. A larger clinical study is under development to clinically validate the model described in this study with the goal of identifying occult PaCa within the NOD population in order to enable earlier detection and thus improve patient outcomes.

Comparison of hygiene levels in metal-ceramic and stratified zirconia in prosthetic rehabilitation on teeth and implants: a retrospective clinical study of a three-year follow-up

The aim of this retrospective clinical study was to evaluate and compare oral hygiene levels in patients subjected to fixed metal-ceramic or stratified zirconia prostheses, either on teeth or on dental implants. Twenty patients, including 10 with metal-ceramic prostheses and 10 with stratified zirconia, were engaged for the study. Considering the prosthesis positioning phase as zero time, all patients were examined twice a year for a follow-up period of 3 years. During each session, to assess oral cavity state of health, both the Plaque Index (IP) and the Bleeding Index (BOP) were recorded. All patients were instructed in home hygiene maintenance and subjected to professional oral hygiene sessions customized according to prothesis type (on natural teeth or dental implants) and materials (metal ceramic or stratified zirconia). Statistically significant evidence was found in IP values, with an increase in the initial stages in zirconia prostheses and in the final stages in metal-ceramic ones. BOP levels showed a reduction during the follow-up period, but no statistically significant differences were found between examined groups. An adequate patient education in hygiene maintenance associated with professional oral hygiene sessions with special tools could positively affect fixed prostheses' maintenance, both on natural teeth and on dental implants.

Pancreatic cancer detection using EpiDetect signatures in plasma-derived cell free DNA in high-risk patients with new onset diabetes

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Background: Pancreatic cancer (PaCa) is the third leading cause of cancer death in the United States despite its low incidence rate, owing to a 5-year survival rate of 10%. It is often asymptomatic in early stage, resulting in the majority of diagnoses occurring when cancer has already metastasized to distant organs. Late diagnosis deprives patients of potentially curative treatments such as surgery and impacts survival rates. Diabetes can be an early symptom of PaCa. Indeed, 25% of PaCa patients had a preceding diabetes diagnosis. Among all people with new onset diabetes (NOD), 0.85% will be diagnosed with PaCa within 3 years, which represents 6-8 fold increased risk for PaCa compared to the general population. Surveillance of the NOD population for PaCa presents an opportunity to shift PaCa diagnosis to earlier stage by finding it sooner. Methods: Whole blood was obtained from a cohort of 117 PaCa patients as well as 800 non-cancer controls with and without NOD. Plasma was processed to isolate cfDNA and 5hmC and low pass whole genome libraries were generated and sequenced. The EpiDetect assay combines 5hmC and whole genome sequencing data and were generated using Bluestar Genomics’s technology platform. Results: To investigate whether PaCa can be detected in plasma, we interrogated plasma-derived cfDNA epigenomic and genomic signal from PaCa patients and non-cancer controls. We first trained stacked ensemble models on PaCa and non-cancer samples utilizing 5hmC, fragmentation and CNV-based biomarkers from cfDNA. These models performed stably with a median of 72.8% sensitivity and 90.1% specificity measured across 25 outer fold iterations using the training data set, which was composed of 50% early stage (Stages I & II) disease. The final binomial ensemble model was trained using all of the training data, yielding an area under the receiver operating characteristic curve (auROC) of 0.9, with 75% sensitivity and 89% specificity. This model was then tested on an independent validation data set from 33 PaCa patients (24 with diabetes, 15 of which was NOD) and 202 non-cancer control patients (76 with diabetes, 51 of which was NOD) and yielded a classification performance auROC of 0.9 with 67% sensitivity at 92% specificity. Lastly, model performance in the subset of patient cohort with NOD only had an auROC of 0.87 with 60% sensitivity at 88% specificity. Conclusions: Our results indicate that 5hmC profiles along with CNV and fragmentation patterns from cfDNA can be used to detect PaCa in plasma-derived cfDNA. Overall, model performance was stable and consistent between the training and independent validation datasets. A larger clinical study is under development to investigate the utility of the model described in this pilot study in identifying occult PaCa within the NOD population, with the aim of shifting diagnosis to early stage and potentially improving patient outcomes.

Genome-wide 5hmC profiles to enable cancer detection and tissue of origin classification in breast, colorectal, lung, ovarian, and pancreatic cancers

3044

Background: Epigenomics assays have recently become popular tools for identification of molecular biomarkers, both in tissue and in plasma. In particular 5-hydroxymethyl-cytosine (5hmC) method, has been shown to enable the epigenomic regulation of gene expression and subsequent gene activity, with different patterns, across several tumor and normal tissues types. In this study we show that 5hmC profiles enable discrete classification of tumor and normal tissue for breast, colorectal, lung ovary and pancreas. Such classification was also recapitulated in cfDNA from patient with breast, colorectal, lung, ovarian and pancreatic cancers. Methods: DNA was isolated from 176 fresh frozen tissues from breast, colorectal, lung, ovary and pancreas (44 per tumor per tissue type and up to 11 tumor tissues for each stage (I-IV)) and up to 10 normal tissues per tissue type. cfDNA was isolated from plasma from 783 non-cancer individuals and 569 cancer patients. Plasma-isolated cfDNA and tumor genomic DNA, were enriched for the 5hmC fraction using chemical labelling, sequenced, and aligned to a reference genome to construct features sets of 5hmC patterns. Results: 5hmC multinomial logistic regression analysis was employed across tumor and normal tissues and identified a set of specific and discrete tumor and normal tissue gene-based features. This indicates that we can classify samples regardless of source, with a high degree of accuracy, based on tissue of origin and also distinguish between normal and tumor status.Next, we employed a stacked ensemble machine learning algorithm combining multiple logistic regression models across diverse feature sets to the cfDNA dataset composed of 783 non cancers and 569 cancers comprising 67 breast, 118 colorectal, 210 Lung, 71 ovarian and 100 pancreatic cancers. We identified a genomic signature that enable the classification of non-cancer versus cancers with an outer fold cross validation sensitivity of 49% (CI 45%-53%) at 99% specificity. Further, individual cancer outer fold cross validation sensitivity at 99% specificity, was measured as follows: breast 30% (CI 119% -42%); colorectal 41% (CI 32%-50%); lung 49% (CI 42%-56%); ovarian 72% (CI 60-82%); pancreatic 56% (CI 46%-66%). Conclusions: This study demonstrates that 5hmC profiles can distinguish cancer and normal tissues based on their origin. Further, 5hmC changes in cfDNA enables detection of the several cancer types: breast, colorectal, lung, ovarian and pancreatic cancers. Our technology provides a non-invasive tool for cancer detection with low risk sample collection enabling improved compliance than current screening methods. Among other utilities, we believe our technology could be applied to asymptomatic high-risk individuals thus enabling enrichment for those subjects that most need a diagnostic imaging follow up.

Characterization of Chromium Compensated GaAs Sensors with the Charge-Integrating JUNGFRAU Readout Chip by Means of a Highly Collimated Pencil Beam

Chromium compensated GaAs or GaAs:Cr sensors provided by the Tomsk State University (Russia) were characterized using the low noise, charge integrating readout chip JUNGFRAU with a pixel pitch of 75 × 75 µm2 regarding its application as an X-ray detector at synchrotrons sources or FELs. Sensor properties such as dark current, resistivity, noise performance, spectral resolution capability and charge transport properties were measured and compared with results from a previous batch of GaAs:Cr sensors which were produced from wafers obtained from a different supplier. The properties of the sample from the later batch of sensors from 2017 show a resistivity of 1.69 × 109 Ω/cm, which is 47% higher compared to the previous batch from 2016. Moreover, its noise performance is 14% lower with a value of (101.65 ± 0.04) e- ENC and the resolution of a monochromatic 60 keV photo peak is significantly improved by 38% to a FWHM of 4.3%. Likely, this is due to improvements in charge collection, lower noise, and more homogeneous effective pixel size. In a previous work, a hole lifetime of 1.4 ns for GaAs:Cr sensors was determined for the sensors of the 2016 sensor batch, explaining the so-called "crater effect" which describes the occurrence of negative signals in the pixels around a pixel with a photon hit due to the missing hole contribution to the overall signal causing an incomplete signal induction. In this publication, the "crater effect" is further elaborated by measuring GaAs:Cr sensors using the sensors from 2017. The hole lifetime of these sensors was 2.5 ns. A focused photon beam was used to illuminate well defined positions along the pixels in order to corroborate the findings from the previous work and to further characterize the consequences of the "crater effect" on the detector operation.

A human tissue map of 5-hydroxymethylcytosines exhibits tissue specificity through gene and enhancer modulation

DNA 5-hydroxymethylcytosine (5hmC) modification is known to be associated with gene transcription and frequently used as a mark to investigate dynamic DNA methylation conversion during mammalian development and in human diseases. However, the lack of genome-wide 5hmC profiles in different human tissue types impedes drawing generalized conclusions about how 5hmC is implicated in transcription activity and tissue specificity. To meet this need, we describe the development of a 5hmC tissue map by characterizing the genomic distributions of 5hmC in 19 human tissues derived from ten organ systems. Subsequent sequencing results enabled the identification of genome-wide 5hmC distributions that uniquely separates samples by tissue type. Further comparison of the 5hmC profiles with transcriptomes and histone modifications revealed that 5hmC is preferentially enriched on tissue-specific gene bodies and enhancers. Taken together, the results provide an extensive 5hmC map across diverse human tissue types that suggests a potential role of 5hmC in tissue-specific development; as well as a resource to facilitate future studies of DNA demethylation in pathogenesis and the development of 5hmC as biomarkers.

Detection of early stage pancreatic cancer using 5-hydroxymethylcytosine signatures in circulating cell free DNA

Pancreatic cancer is often detected late, when curative therapies are no longer possible. Here, we present non-invasive detection of pancreatic ductal adenocarcinoma (PDAC) by 5-hydroxymethylcytosine (5hmC) changes in circulating cell free DNA from a PDAC cohort (n = 64) in comparison with a non-cancer cohort (n = 243). Differential hydroxymethylation is found in thousands of genes, most significantly in genes related to pancreas development or function (GATA4, GATA6, PROX1, ONECUT1, MEIS2), and cancer pathogenesis (YAP1, TEAD1, PROX1, IGF1). cfDNA hydroxymethylome in PDAC cohort is differentially enriched for genes that are commonly de-regulated in PDAC tumors upon activation of KRAS and inactivation of TP53. Regularized regression models built using 5hmC densities in genes perform with AUC of 0.92 (discovery dataset, n = 79) and 0.92-0.94 (two independent test sets, n = 228). Furthermore, tissue-derived 5hmC features can be used to classify PDAC cfDNA (AUC = 0.88). These findings suggest that 5hmC changes enable classification of PDAC even during early stage disease.

Abstract 783: Epigenomic detection of multiple cancers in plasma derived cell free DNA

Background: Our feasibility study employed a novel genomic detection methodology that enriches 5-hydroxymethylcytosine (5hmC) loci in cell free DNA (cfDNA) from the plasma of cancer patients using click chemistry coupled with sequencing and machine learning based classification methods. These classification methods were developed to detect the presence of disease in the plasma of cancer and control subjects. Cancer and control patient cfDNA cohorts were accrued from multiple sites consisting of 48 breast, 55 lung, 32 prostate and 2 pancreatic datasets consisting of 41 and 53 cancer subjects (Set 1 and 2). In addition, a control cohort of 260 subjects (non-cancer) was employed to match cancer patient demographics (age, sex and smoking status) in a case-control study design.

Methods: Machine learning methods, applied to each cancer case cohort individually, with a balancing non-cancer cohort, were able to classify cancer and control samples. Measures of predictive performance using 5-fold cross validation coupled with out-of-fold Area Under the Receiver Operating Characteristic Curve (AUROC) measures were employed. Gene sets selected as part of biomarker discovery were further analyzed for disease relevance using pathway analysis tools (GSEA, mSigDB).

Results: 260 controls and 229 cancers from four disease types (breast, lung, pancreas and prostate) were analyzed; more than 60% of cancer patients had early stage disease (I or II). Predictive performance, employing AUROC measures, was established for breast (0.89), lung (0.84), pancreas (set 1 - 0.95 and 2 - 0.93) and prostate (0.83). The genes defining each of these predictive models were enriched for pathways relevant to disease specific etiology, notably in the control of gene regulation in these same pathways. The breast cancer cohort consisted primarily of stage I and II patients including tumors < 2 cm and these samples exhibited a higher prediction probability score. The prostate cancer cohort consisted of both indolent and aggressive disease sample and prediction performance was equally high for both (AUROC for indolent vs aggressive was 0.81 and 0.77, respectively).

Conclusions: These findings suggest that 5hmC changes in cfDNA enable non-invasive detection of early stage breast, pancreatic, prostate, and lung cancers. Furthermore, 5hmC profiling in cfDNA may enable the prediction of clinically relevant features such as tumor size in breast adenocarcinoma or indolent disease in prostate cancer. Finally, this study identified a suite of 5hmC biomarkers that may be further validated in larger, and more diverse, patient cohorts.

Citation Format: Anna Bergamaschi, Jeremy Ku, Yuhong Ning, Francois Collin, Chris Ellison, Tierney Phillips, Erin McCarthy, Wendy Wang, Michael Antoine, David Haan, Aaron Scott, Paul Lloyd, Gulfem Guler, Alan Ashworth, Stephen Quake, Samuel Levy. Epigenomic detection of multiple cancers in plasma derived cell free DNA [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 783.

Monitoring immunotherapy response in non-small cell lung cancer patients using 5-hydroxymethylcytosine signatures in circulating cell free DNA

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Background: Liquid biopsies are gaining prominence for not only cancer diagnosis but also patient monitoring. Mutational signals derived from cell-free DNA (cfDNA) show promise to assess response to cancer treatment, including immunotherapy. However, reliance of these methods on mutational data from tissue biopsies limit their applicability when a tumor biopsy is unavailable, or when mutational landscape of tumor changes under the selective pressures of cancer drug treatment. Epigenomic approaches have the potential to address these shortcomings. Methods: Blood draws were obtained from a cohort of non-small cell lung cancer (NSCLC) patients (n = 19) who went on to anti-PD1 treatment prior to therapy start and while on therapy. cfDNA was isolated from plasma and was subsequently processed to generate 5hmC genome-wide profiles. Results: We analyzed cfDNA from NSCLC patients undergoing anti-PD1 therapy to investigate whether immunotherapy response can be detected from plasma. Using a predictive model trained on lung cancer and non-cancer samples, we were able to detect changes in prediction scores in patient treated with immunotherapy that were consistent with RECIST. Patients with progressive disease (n = 3), determined by RECIST, had prediction scores that increased while they received treatment. On the other hand, majority of the patients that exhibited partial response to treatment (n = 12) had predictive scores that decreased with treatment, again consistent with RECIST. Furthermore, score changes consistent with RECIST was observed one cycle prior to the RECIST timepoint in all except one patient, where an extra blood draw after baseline was available (n = 7). Annotation of the regions that account for differential scoring identified enhancer, 5’UTR and promoter regions. Comparison of partial responders to patients with progressive disease revealed genes involved in metastasis, oncogenes and tumor suppressors that change in opposing directions between these patient groups, consistent with the underlying biology. Conclusions: Our results suggest that 5hmC profiles from cfDNA can be used to determine immunotherapy response in non-small cell lung cancer patients. Compared with mutation based liquid biopsy methods to assess response, epigenomics-based methods have the advantage of being agnostic to starting tumor mutations, and not relying on a mutational analysis from tumor biopsy. Future work will help determine applicability of this method to other kinds of therapies and cancer types.

Effect of detection of epigenomic changes in plasma-derived cell-free DNA on multicancer classification

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Background: Epigenomic changes in DNA methylation patterns are more precisely delineated by active demethylation events as marked by 5-hydroxymethylation (5hmC) of cytosine residues. 5hmC appears to be dynamically modulated in tumor tissues and can be employed as a cancer biomarker. Strategies which interrogate 5hmC genome-wide patterns in a liquid biopsy context may provide efficient and precise technology for early cancer screening and detection. In this study we identified genome-wide 5hmC changes in plasma based circulating free DNA (cfDNA) from breast, colorectal, lung, pancreatic and prostate cancer patients versus non-cancer individuals. Methods: cfDNA was isolated from plasma, enriched for the 5hmC fraction using novel click-chemistry protocol for labelling followed by sequencing and alignment to a reference genome to construct features sets of 5hmC patterns. Regularized classification models were constructed to classify cancer samples apart from non-cancer. Results: > 500 non-cancer individuals and > 500 cancer patients across five cancer types (breast, colorectal, lung, pancreas and prostate) were included in this study. About 60% of the cancer samples were early stage disease (I or II). The ability to classify non-cancer versus cancer patients was evaluated by 5-fold cross validation of our trained prediction models. Our models were able to classify all breast cancer with a test auROC of 0.86 while prediction model classification for ER negative samples had an auROC of 0.92. Colorectal performance auROC was 0.9; lung auROC = 0.92, pancreatic auROC = 0.97 and prostate auROC = 0.91. Overall sensitivity range, when allowing 2% false positive, was between 85% and 52%. Further using 5hmC signal in blood we were able to identify several signaling pathways specifically relevant to the biology of the cancers investigated. Conclusions: These findings further demonstrate that 5hmC changes in cfDNA enable non-invasive detection of breast, colorectal, lung pancreatic, and prostate cancers. Further, 5hmC signals enabled the identification of a suite of cancer signaling pathways differentially enriched in cancers versus non-cancers. These data suggest that dynamic changes in tumor cell methylation, detectable through 5-hydroxymethylation, are contained in the circulating blood and signal active disease biology.

Spectral µCT with an energy resolving and interpolating pixel detector

A main challenge in x-ray µCT with laboratory radiation derives from the broad spectral content, which in contrast to monochromatic synchrotron radiation gives rise to reconstruction artifacts and impedes quantitative reconstruction. Due to the low spectral brightness of these sources, monochromatization is unfavorable and parallel recording of a broad bandpath is practically indispensable. While conventional CT sums up all spectral components into a single detector value, spectral CT discriminates the data in several spectral bins. Here we show that a new generation of charge integrating and interpolating pixel detectors is ideally suited to implement spectral CT with a resolution in the range of 10 µm. We find that the information contained in several photon energy bins largely facilitates automated classification of materials, as demonstrated for of a mouse cochlea. Bones, soft tissues, background and metal implant materials are discriminated automatically. Importantly, this includes taking a better account of phase contrast effects, based on tailoring reconstruction parameters to specific energy bins.

Development of low-energy X-ray detectors using LGAD sensors

Recent advances in segmented low-gain avalanche detectors (LGADs) make them promising for the position-sensitive detection of low-energy X-ray photons thanks to their internal gain. LGAD microstrip sensors fabricated by Fondazione Bruno Kessler have been investigated using X-rays with both charge-integrating and single-photon-counting readout chips developed at the Paul Scherrer Institut. In this work it is shown that the charge multiplication occurring in the sensor allows the detection of X-rays with improved signal-to-noise ratio in comparison with standard silicon sensors. The application in the tender X-ray energy range is demonstrated by the detection of the sulfur K_α and K_β lines (2.3 and 2.46 keV) in an energy-dispersive fluorescence spectrometer at the Swiss Light Source. Although further improvements in the segmentation and in the quantum efficiency at low energy are still necessary, this work paves the way for the development of single-photon-counting detectors in the soft X-ray energy range.

Changes in DNA hydroxymethylation for the detection of multiple cancers in plasma cell-free DNA

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Background: Methylation and hydroxymethylation of cytosines enable the epigenomic regulation of gene suppression and activation. 5-hydroxymethyl-cytosine (5hmC) is globally decreased in tumor tissue. However, genome-wide analysis using precise 5hmC labelling techniques reveals more nuanced changes upon tumorigenesis and raises the possibility that this loss could be exploited for developing a cancer biomarker. This suggests that 5hmC profiles might enable discrete classification of not only tumor tissue but also of tumor cell-free DNA (cfDNA). We sought to identify genome-wide 5hmC changes in plasma based cfDNA from cancer patients representing multiple disease types, stages and clinical characteristics in comparison with non-cancer patients. Methods: cfDNA was isolated from plasma, enriched for the 5hmC fraction using chemical labelling, sequenced, and aligned to the genome to determine 5hmC counts per genomic feature. Regularized regression models were constructed to classify cancer samples (age matched or corrected for smoking status) on non-overlapping training (80% of all samples) and test sample sets (20% of all samples). Results: 226 non-cancer patients and 278 cancers across four cancer types (breast, colorectal, lung-squamous and pancreas) were included in this study, where more than 60% of cancer samples were early stage disease (I or II). Upon comparison with non-cancer samples, 5hmC peaks have reduced enrichment in exons in breast, colorectal and lung cancer but not in pancreatic cancer. Further, 5hmC peaks in pancreas show different patterns of enrichment in 3’UTR, translational termination sites, promoters and LTR. Overall 5hmC signal density was reduced in late stage cancers across all four diseases. The ability to classify non-cancer versus cancer patients was evaluated via cross-validation of out of fold prediction in the training set with AUC > 0.84 for all four cancer types. Further, test set sensitivity across all four cancer types was found to be > 66% with 98% specificity. Conclusions: These findings suggest that 5hmC changes in plasma cfDNA enable classification of early stages of breast, colorectal, lung-squamous and pancreas cancer and are promising biomarkers for disease detection.

X-ray Fourier ptychography

To a large extent, the performance of imaging systems is determined by their objectives, which affect properties as varied as collection efficiency, resolving power, and image distortions. Such limitations can be addressed by so-called aperture synthesis, a technique used, for instance, in radar, astronomy, and, increasingly, microscopy. Here, we apply such techniques to x-ray imaging and demonstrate how Fourier ptychography can be used at transmission x-ray microscopes to increase resolution, provide quantitative absorption and phase contrast, and allow for corrections of lens aberrations. We anticipate that such methods will find common and frequent applications, alleviating a number of limitations imposed by x-ray optical elements, offering an alternative approach to phase contrast imaging, and providing novel opportunities to mitigate radiation damage.

MÖNCH detector enables fast and low-dose free-propagation phase-contrast computed tomography of in situ mouse lungs

Due to the complexity of the underlying pathomechanism, in vivo mouse lung-disease models continue to be of great importance in preclinical respiratory research. Longitudinal studies following the cause of a disease or evaluating treatment efficacy are of particular interest but challenging due to the small size of the mouse lung and the fast breathing rate. Synchrotron-based in-line phase-contrast computed tomography imaging has been successfully applied in lung research in various applications, but mostly at dose levels that forbid longitudinal in vivo studies. Here, the novel charge-integrating hybrid detector MÖNCH is presented, which enables imaging of mouse lungs at a pixel size of 25 µm, in less than 10 s and with an entrance dose of about 70 mGy, which therefore will allow longitudinal lung disease studies to be performed in mouse models.

The EIGER detector for low-energy electron microscopy and photoemission electron microscopy

EIGER is a single-photon-counting hybrid pixel detector developed at the Paul Scherrer Institut, Switzerland. It is designed for applications at synchrotron light sources with photon energies above 5 keV. Features of EIGER include a small pixel size (75 µm × 75 µm), a high frame rate (up to 23 kHz), a small dead-time between frames (down to 3 µs) and a dynamic range up to 32-bit. In this article, the use of EIGER as a detector for electrons in low-energy electron microscopy (LEEM) and photoemission electron microscopy (PEEM) is reported. It is demonstrated that, with only a minimal modification to the sensitive part of the detector, EIGER is able to detect electrons emitted or reflected by the sample and accelerated to 8-20 keV. The imaging capabilities are shown to be superior to the standard microchannel plate detector for these types of applications. This is due to the much higher signal-to-noise ratio, better homogeneity and improved dynamic range. In addition, the operation of the EIGER detector is not affected by radiation damage from electrons in the present energy range and guarantees more stable performance over time. To benchmark the detector capabilities, LEEM experiments are performed on selected surfaces and the magnetic and electronic properties of individual iron nanoparticles with sizes ranging from 8 to 22 nm are detected using the PEEM endstation at the Surface/Interface Microscopy (SIM) beamline of the Swiss Light Source.

The EIGER detector for low-energy electron microscopy and photoemission electron microscopy

EIGER is a single-photon-counting hybrid pixel detector developed at the Paul Scherrer Institut, Switzerland. It is designed for applications at synchrotron light sources with photon energies above 5 keV. Features of EIGER include a small pixel size (75 µm × 75 µm), a high frame rate (up to 23 kHz), a small dead-time between frames (down to 3 µs) and a dynamic range up to 32-bit. In this article, the use of EIGER as a detector for electrons in low-energy electron microscopy (LEEM) and photoemission electron microscopy (PEEM) is reported. It is demonstrated that, with only a minimal modification to the sensitive part of the detector, EIGER is able to detect electrons emitted or reflected by the sample and accelerated to 8-20 keV. The imaging capabilities are shown to be superior to the standard microchannel plate detector for these types of applications. This is due to the much higher signal-to-noise ratio, better homogeneity and improved dynamic range. In addition, the operation of the EIGER detector is not affected by radiation damage from electrons in the present energy range and guarantees more stable performance over time. To benchmark the detector capabilities, LEEM experiments are performed on selected surfaces and the magnetic and electronic properties of individual iron nanoparticles with sizes ranging from 8 to 22 nm are detected using the PEEM endstation at the Surface/Interface Microscopy (SIM) beamline of the Swiss Light Source.

Abstract PD7-07: Discovery of molecular predictors of late breast cancer specific events (BCSE) in ER+, node+ breast cancer – new transcriptome expression whole gene analysis of the phase III adjuvant trial SWOG S8814

BACKGROUND: Unique genes and pathways were identified for prognosis on tamoxifen (T, 5 yrs) and prediction on CAF-T vs T in S8814 using whole transcriptome RNA-Seq from archival FFPE tissue. (Albain, et al; Cherbavaz, et al; SABCS 2015) Discovery was robust for early DFS events but sparse for late. The aims of this new analysis were to 1) utilize a new endpoint BCSE for gene discovery of late events, prognosis and prediction and 2) add intronic counts to the previous exonic results to define whole genes impacting on late BCSE.

METHODS: Charts of patients (pts) on CAF-T (212) vs T (142) were reviewed to define the BCSE endpoint (local/regional, contralateral, distant). Deaths without BC were treated as competing risks. BCSE models (including metagenes) of late prognosis and prediction used cumulative incidence functions. Consolidated intronic regions counts within genes were added to exonic regions counts. Using these “whole gene” (WG) counts, association of gene expression with time to BCSE was assessed by Cox regression. A multiple WG score (MWGS) for BCSE prognosis beyond 5 yrs (to 12.5 yrs) was constructed and evaluated for 1-3 and 4+ node (N) groups. False discovery rate was controlled at 10%.

RESULTS: More exons and WG were discovered for prognosis on T alone over 12.5 yrs with the BCSE endpoint than DFS. For prognosis of late BCSE after 5 yrs, more genes were discovered using WG (n=111) than by exons (n=9). There were significantly fewer genes for late BCSE on CAF-T (8, WG; 0, exons). The functions of WG prognostic for late BCSE were: cell cycle/proliferation-26 genes, chromosome segregation/mitotic spindle-22, DNA repair/maintenance-10, transcriptional/translational control-5, cell adhesion/migration-4, immune-3, diverse/unknown-32 and growth factor/hormone receptor signaling-9 (this group was only found by WGs, not exons). Of these 111 WG, a MWGS prognostic for late BCSE on T used 57 previously discovered genes pre-specified for this analysis. Probability of BCSE beyond 5 yrs for low vs high MWGS was 8% vs 21% in N1-3+ and 17% vs 42% in N4+. Late prognosis on T differed by low vs high risk defined in a metagene model: cumulative BCSE at year 10 was 0% vs 47% (low vs high risk, p=0.001). Prediction of 10-yr incidence of BCSE varied by risk level by treatment in a metagene model: low risk- CAF-T=47%, T=0% (p=0.045); high risk- CAF-T=35%, T=45% (p=0.027).

CONCLUSIONS: Gene discovery for prognosis of late BCSE is enhanced with a novel WG transcriptome expression approach. Use of chemotherapy (CT) before T significantly attenuated gene discovery, so that molecular tools for decisions on extending endocrine therapy (ET) may not be reliable in a setting of prior CT. Some pts on ET for 5 yrs may not require either longer ET or CT, given a N+ cohort was defined with no BCSE observed over 12.5 yrs. For prediction of CT benefit, CAF-T appeared to be inferior to T in a low risk metagene model for BCSE. In sum, these results add more evidence that ET alone may be sufficient (perhaps better) in select N+ settings. Validation in SWOG S1007 (RxPONDER) is planned.

SUPPORT: NCI CA180888, 180819, 180821, 180820, 180863; in part, Genomic Health, Inc.

Citation Format: Albain KS, Crager MR, Barlow WE, Baehner FL, Bergamaschi A, Rae JM, Ravdin PM, Tripathy D, Gralow JR, Livingston RB, Osborne CK, Ingle JN, Pritchard KI, Davidson NE, Carey LA, Cherbavaz DB, Sing AP, Shak S, Hortobagyi GN, Hayes DF. Discovery of molecular predictors of late breast cancer specific events (BCSE) in ER+, node+ breast cancer – new transcriptome expression whole gene analysis of the phase III adjuvant trial SWOG S8814 [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr PD7-07.

Micrometer-resolution imaging using MÖNCH: towards G2-less grating interferometry

MÖNCH is a 25 µm-pitch charge-integrating detector aimed at exploring the limits of current hybrid silicon detector technology. The small pixel size makes it ideal for high-resolution imaging. With an electronic noise of about 110 eV r.m.s., it opens new perspectives for many synchrotron applications where currently the detector is the limiting factor, e.g. inelastic X-ray scattering, Laue diffraction and soft X-ray or high-resolution color imaging. Due to the small pixel pitch, the charge cloud generated by absorbed X-rays is shared between neighboring pixels for most of the photons. Therefore, at low photon fluxes, interpolation algorithms can be applied to determine the absorption position of each photon with a resolution of the order of 1 µm. In this work, the characterization results of one of the MÖNCH prototypes are presented under low-flux conditions. A custom interpolation algorithm is described and applied to the data to obtain high-resolution images. Images obtained in grating interferometry experiments without the use of the absorption grating G2 are shown and discussed. Perspectives for the future developments of the MÖNCH detector are also presented.

Towards hybrid pixel detectors for energy-dispersive or soft X-ray photon science

JUNGFRAU (adJUstiNg Gain detector FoR the Aramis User station) is a two-dimensional hybrid pixel detector for photon science applications at free-electron lasers and synchrotron light sources. The JUNGFRAU 0.4 prototype presented here is specifically geared towards low-noise performance and hence soft X-ray detection. The design, geometry and readout architecture of JUNGFRAU 0.4 correspond to those of other JUNGFRAU pixel detectors, which are charge-integrating detectors with 75 µm × 75 µm pixels. Main characteristics of JUNGFRAU 0.4 are its fixed gain and r.m.s. noise of as low as 27 e(-) electronic noise charge (<100 eV) with no active cooling. The 48 × 48 pixels JUNGFRAU 0.4 prototype can be combined with a charge-sharing suppression mask directly placed on the sensor, which keeps photons from hitting the charge-sharing regions of the pixels. The mask consists of a 150 µm tungsten sheet, in which 28 µm-diameter holes are laser-drilled. The mask is aligned with the pixels. The noise and gain characterization, and single-photon detection as low as 1.2 keV are shown. The performance of JUNGFRAU 0.4 without the mask and also in the charge-sharing suppression configuration (with the mask, with a `software mask' or a `cluster finding' algorithm) is tested, compared and evaluated, in particular with respect to the removal of the charge-sharing contribution in the spectra, the detection efficiency and the photon rate capability. Energy-dispersive and imaging experiments with fluorescence X-ray irradiation from an X-ray tube and a synchrotron light source are successfully demonstrated with an r.m.s. energy resolution of 20% (no mask) and 14% (with the mask) at 1.2 keV and of 5% at 13.3 keV. The performance evaluation of the JUNGFRAU 0.4 prototype suggests that this detection system could be the starting point for a future detector development effort for either applications in the soft X-ray energy regime or for an energy-dispersive detection system.

Abstract S3-02: Molecular predictors of outcome on adjuvant CAF plus tamoxifen (T) vs T in postmenopausal patients (pts) with ER+, node+ breast cancer – Transcriptome expression analysis of the phase III trial SWOG-8814

BACKGROUND: In SWOG-8814A, pts with ER+ node+ breast cancer and low 21 gene recurrence scores (RS) had good prognosis and no CAF benefit, but high RS predicted longer survival from CAF followed by T (CAF-T) vs T (Albain, Lancet Oncol 2010). The aims of SWOG-8814B were to identify novel genes and networks for 1) prognosis of early and late relapse and 2) prediction of CAF benefit, using whole transcriptome expression analysis with next generation RNA sequencing (NGS).

METHODS: Stored RNA previously extracted for SWOG-8814A (T, CAF-T arms; T, 5 yrs) was analyzed for RNA/library yield (see companion abstract Cherbavaz et al. for methods). Genes were sequenced and expression of mRNA species was related to disease-free survival (DFS) using Cox proportional hazards. Discovery analyses controlled false discovery rate (FDR) at 10%. Genes were identified for prognosis on T and prediction on CAF-T vs T. Networks of genes/pathways were explored. Early (0-5 yrs) and late (5-13+ yrs) time periods were studied. Gene Ontology, Cytoscape, pathway and hierarchical clustering were used for functional gene and metagene analyses.

RESULTS: Of 367 samples, 354 (96%; 142 T, 212 CAF-T; 141 DFS events) had sufficient RNA/library yield, with 20,101 genes sequenced. For prognosis on T, there were 2327 and 568 genes discovered in early and all-yrs follow-up, with only 9 genes prognostic after 5 yrs. Prognosis analyses for residual risk after CAF-T were uninformative. Functional mapping found that genes prognostic for worse DFS were enriched for proliferation (G2M, M-phase), cellular metabolism, DNA repair, stress response and EMT; whereas, those with better DFS involved transcription regulation/repression via zinc finger proteins. Hierarchical clustering (T arm) found significant DFS prognostic metagene signatures for ER-related genes, immune response, ECM/stroma, chromatin remodeling-transcription factor activity and TGFb pathway. All varied for early vs late DFS events. For example, low ER/high stroma expression signatures correlated with high proliferation gene expression and were strongly associated with early events (standardized [st] HR 2.94, p&lt;0.001). Late recurrence was associated with high proliferation, both individually (stHR 1.51, p=.035) and in combination with higher ER expression (stHR 1.51, p=0.09). Fifteen genes predicted CAF benefit (9 better DFS, 6 worse), or 129 genes if FDR relaxed to 20%. Cluster analysis for CAF prediction is ongoing.

CONCLUSIONS: Unique genes, clusters and pathways were identified by NGS of archival material in ER+ N+ breast cancer, including previously unreported signatures. While ER, stroma and proliferation-related signatures were associated with early prognosis, proliferation best predicted worse DFS after 5 yrs. NGS of the primary tumor is most informative for early events in pts with only 5 years of T, with few genes selecting only for late relapse. If validated, these signatures may identify pts with excellent DFS despite positive nodes for endocrine therapy alone as well as others for whom chemotherapy and/or biologics are also required

.

SUPPORT: NCI CA 180888, 180819, 180821, 180820, 180863; in part, Genomic Health, Inc.

Citation Format: Albain KS, Crager MR, Barlow WE, Baehner FL, Bergamaschi A, Rae JM, Ravdin PM, Tripathy D, Gralow JR, Livingston RB, Osborne CK, Ingle JN, Pritchard KI, Davidson NE, Carey LA, Cherbavaz DB, Sing AP, Shak S, Hortobagyi GN, Hayes DF. Molecular predictors of outcome on adjuvant CAF plus tamoxifen (T) vs T in postmenopausal patients (pts) with ER+, node+ breast cancer – Transcriptome expression analysis of the phase III trial SWOG-8814. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr S3-02.

PI3K inhibition results in enhanced estrogen receptor function and dependence in hormone receptor-positive breast cancer

Activating mutations of PIK3CA are the most frequent genomic alterations in estrogen receptor (ER)-positive breast tumors, and selective phosphatidylinositol 3-kinase α (PI3Kα) inhibitors are in clinical development. The activity of these agents, however, is not homogeneous, and only a fraction of patients bearing PIK3CA-mutant ER-positive tumors benefit from single-agent administration. Searching for mechanisms of resistance, we observed that suppression of PI3K signaling results in induction of ER-dependent transcriptional activity, as demonstrated by changes in expression of genes containing ER-binding sites and increased occupancy by the ER of promoter regions of up-regulated genes. Furthermore, expression of ESR1 mRNA and ER protein were also increased upon PI3K inhibition. These changes in gene expression were confirmed in vivo in xenografts and patient-derived models and in tumors from patients undergoing treatment with the PI3Kα inhibitor BYL719. The observed effects on transcription were enhanced by the addition of estradiol and suppressed by the anti-ER therapies fulvestrant and tamoxifen. Fulvestrant markedly sensitized ER-positive tumors to PI3Kα inhibition, resulting in major tumor regressions in vivo. We propose that increased ER transcriptional activity may be a reactive mechanism that limits the activity of PI3K inhibitors and that combined PI3K and ER inhibition is a rational approach to target these tumors.

Radiation hardness assessment of the charge-integrating hybrid pixel detector JUNGFRAU 1.0 for photon science

JUNGFRAU (adJUstiNg Gain detector FoR the Aramis User station) is a two-dimensional hybrid pixel detector for photon science applications in free electron lasers, particularly SwissFEL, and synchrotron light sources. JUNGFRAU is an automatic gain switching, charge-integrating detector which covers a dynamic range of more than 10(4) photons of an energy of 12 keV with a good linearity, uniformity of response, and spatial resolving power. The JUNGFRAU 1.0 application-specific integrated circuit (ASIC) features a 256 × 256 pixel matrix of 75 × 75 μm(2) pixels and is bump-bonded to a 320 μm thick Si sensor. Modules of 2 × 4 chips cover an area of about 4 × 8 cm(2). Readout rates in excess of 2 kHz enable linear count rate capabilities of 20 MHz (at 12 keV) and 50 MHz (at 5 keV). The tolerance of JUNGFRAU to radiation is a key issue to guarantee several years of operation at free electron lasers and synchrotrons. The radiation hardness of JUNGFRAU 1.0 is tested with synchrotron radiation up to 10 MGy of delivered dose. The effect of radiation-induced changes on the noise, baseline, gain, and gain switching is evaluated post-irradiation for both the ASIC and the hybridized assembly. The bare JUNGFRAU 1.0 chip can withstand doses as high as 10 MGy with minor changes to its noise and a reduction in the preamplifier gain. The hybridized assembly, in particular the sensor, is affected by the photon irradiation which mainly shows as an increase in the leakage current. Self-healing of the system is investigated during a period of 11 weeks after the delivery of the radiation dose. Annealing radiation-induced changes by bake-out at 100 °C is investigated. It is concluded that the JUNGFRAU 1.0 pixel is sufficiently radiation-hard for its envisioned applications at SwissFEL and synchrotron beam lines.

Current and future detector developments at the Swiss Light Source

The detector group of the Swiss Light Source (SLS) at the Paul Scherrer Institut (PSI) has a long history of x-ray detector developments for synchrotrons. Initially these detectors were all single photon counting systems. In the last years the focus at PSI was moving towards charge integrating systems mainly driven by the detector needs for the upcoming XFELs. Charge integrating systems however also solve some of the problems of single photon counting systems. Charge integrating systems have an almost infinite linear count rate capability, allow systems with smallest pixel sizes and for low photon energies. In this presentation we give an overview of the detector developments at PSI and focus on Jungfrau, Mönch and Eiger. Eiger is a single photon counting system specifically developed for high frame rates. It has a 75 micron pixel size and can run at frame rates up to 24 kHz. A 9M Eiger detector will be installed in a few months at the cSAXS beamline of the SLS. Jungfrau uses the same sensor as Eiger (about 4cm x 8 cm with a pixel size of 75 microns). It has a charge integrating architecture with dynamic gain switching to achieve a dynamic range of 10^4 photons (at 12 keV). With a frame rate of up to 2 kHz Jungfrau is currently being developed for applications at both XFELs and synchrotrons. 16M Jungfrau detectors are foreseen at the SwissFEL. Mönch is currently a research project. A first prototype with 160x160 pixels and a pixel size of 25 microns was designed and is currently characterised. It offers the smallest pixel size of current hybrid pixel detectors and also has a very low noise allowing hybrid pixel detectors to be used down to about 400eV. We present measurement results for Jungfrau, Mönch and Eiger and give an outlook on future possible systems.

Integration of molecular profiling and chemical imaging to elucidate fibroblast-microenvironment impact on cancer cell phenotype and endocrine resistance in breast cancer

The tumor microenvironment is known to play a key role in altering the properties and behavior of nearby cancer cells. Its influence on resistance to endocrine therapy and cancer relapse, however, is poorly understood. Here we investigate the interaction of mammary fibroblasts and estrogen receptor-positive breast cancer cells in three-dimensional culture models in order to characterize gene expression, cellular changes, and the secreted protein factors involved in the cellular cross-talk. We show that fibroblasts, which are the predominant cell type found in the stroma adjacent to the cancer cells in a tumor, induce an epithelial-to-mesenchymal transition in the cancer cells, leading to hormone-independent growth, a more invasive phenotype, and resistance to endocrine therapy. Here, we applied a label-free chemical imaging modality, Fourier transform infrared (FT-IR) spectroscopic imaging, to identify cells that had transitioned to hormone-independent growth. Both the molecular and chemical profiles identified here were translated from cell culture to patient samples: a secreted protein signature was used to stratify patient populations based on gene expression and FT-IR was used to characterize breast tumor patient biopsies. Our findings underscore the role of mammary fibroblasts in promoting aggressiveness and endocrine therapy resistance in ER-positive breast cancers and highlight the utility of FT-IR for the further characterization of breast cancer samples.

PTSD prevalence and associated risk factors after a fire disaster that broke out in a paediatric hospital: a cross-sectional study

BACKGROUND

Several studies have shown a higher risk of psychological problems in health care workers exposed to serious occupational stressors.

OBJECTIVES

The aim of the present study was to assess the presence of Post-traumatic Stress Disorder (PTSD) and possible risk factors in a sample of 32 workers who were at the same time rescuers and victims of a fire that broke out in the neonatal intensive care unit of a large paediatric hospital.

METHODS

Immediately and six months after the event, the subjects underwent a study protocol aimed at the diagnostic assessment of PTSD, investigated via the Clinician-Administered PTSD Scale (CAPS) and the Impact of Event Scale-Revised (IES-R).

RESULTS

Out of the 30 subjects examined (two were missing), six showed the diagnostic criteria for a current PTSD. Risk factors for PTSD onset were a prior psychiatric disorder, the level of involvement in the fire disaster and the presence of phobias in the days immediately after the event. Gender and level of education approached statistical significance.

CONCLUSIONS

The high prevalence of PTSD found in this sample was due to the fact that the risk of death or serious injury involved infants.

Antagonism of EGFR and HER3 enhances the response to inhibitors of the PI3K-Akt pathway in triple-negative breast cancer

Both abundant epidermal growth factor receptor (EGFR or ErbB1) and high activity of the phosphatidylinositol 3-kinase (PI3K)-Akt pathway are common and therapeutically targeted in triple-negative breast cancer (TNBC). However, activation of another EGFR family member [human epidermal growth factor receptor 3 (HER3) (or ErbB3)] may limit the antitumor effects of these drugs. We found that TNBC cell lines cultured with the EGFR or HER3 ligand EGF or heregulin, respectively, and treated with either an Akt inhibitor (GDC-0068) or a PI3K inhibitor (GDC-0941) had increased abundance and phosphorylation of HER3. The phosphorylation of HER3 and EGFR in response to these treatments was reduced by the addition of a dual EGFR and HER3 inhibitor (MEHD7945A). MEHD7945A also decreased the phosphorylation (and activation) of EGFR and HER3 and the phosphorylation of downstream targets that occurred in response to the combination of EGFR ligands and PI3K-Akt pathway inhibitors. In culture, inhibition of the PI3K-Akt pathway combined with either MEHD7945A or knockdown of HER3 decreased cell proliferation compared with inhibition of the PI3K-Akt pathway alone. Combining either GDC-0068 or GDC-0941 with MEHD7945A inhibited the growth of xenografts derived from TNBC cell lines or from TNBC patient tumors, and this combination treatment was also more effective than combining either GDC-0068 or GDC-0941 with cetuximab, an EGFR-targeted antibody. After therapy with EGFR-targeted antibodies, some patients had residual tumors with increased HER3 abundance and EGFR/HER3 dimerization (an activating interaction). Thus, we propose that concomitant blockade of EGFR, HER3, and the PI3K-Akt pathway in TNBC should be investigated in the clinical setting.

Highly sensitive quantitative imaging for monitoring single cancer cell growth kinetics and drug response

The detection and treatment of cancer has advanced significantly in the past several decades, with important improvements in our understanding of the fundamental molecular and genetic basis of the disease. Despite these advancements, drug-screening methodologies have remained essentially unchanged since the introduction of the in vitro human cell line screen in 1990. Although the existing methods provide information on the overall effects of compounds on cell viability, they are restricted by bulk measurements, large sample sizes, and lack capability to measure proliferation kinetics at the individual cell level. To truly understand the nature of cancer cell proliferation and to develop personalized adjuvant therapies, there is a need for new methodologies that provide quantitative information to monitor the effect of drugs on cell growth as well as morphological and phenotypic changes at the single cell level. Here we show that a quantitative phase imaging modality known as spatial light interference microscopy (SLIM) addresses these needs and provides additional advantages over existing proliferation assays. We demonstrate these capabilities through measurements on the effects of the hormone estradiol and the antiestrogen ICI182,780 (Faslodex) on the growth of MCF-7 breast cancer cells. Along with providing information on changes in the overall growth, SLIM provides additional biologically relevant information. For example, we find that exposure to estradiol results in rapidly growing cells with lower dry mass than the control population. Subsequently blocking the estrogen receptor with ICI results in slower growing cells, with lower dry masses than the control. This ability to measure changes in growth kinetics in response to environmental conditions provides new insight on growth regulation mechanisms. Our results establish the capabilities of SLIM as an advanced drug screening technology that provides information on changes in proliferation kinetics at the cellular level with greater sensitivity than any existing method.

The Materials Science beamline upgrade at the Swiss Light Source

The Materials Science beamline at the Swiss Light Source has been operational since 2001. In late 2010, the original wiggler source was replaced with a novel insertion device, which allows unprecedented access to high photon energies from an undulator installed in a medium-energy storage ring. In order to best exploit the increased brilliance of this new source, the entire front-end and optics had to be redesigned. In this work, the upgrade of the beamline is described in detail. The tone is didactic, from which it is hoped the reader can adapt the concepts and ideas to his or her needs.

Abstract 503: Mammary fibroblasts induce hormone-independent growth in estrogen receptor-positive breast cancer cells via an epithelial-to-mesenchymal transition in a 3D cell culture model

The majority of breast cancers diagnosed in the United States are estrogen receptor positive (ER+). These patients may respond to targeted endocrine therapies, but up to 30% of patients experience a cancer recurrence. We hypothesized that the molecular interaction of ER+ breast cancer cells with mammary fibroblasts might lead to endocrine resistance and, eventually, breast cancer relapse. We developed a three-dimensional (3D) co-culture model representing cancer cell-fibroblast interactions during early tumor invasion. We show that the proliferation of MCF7 ER+ cells switches from hormone-dependent to growth factor-dependent in the presence of human mammary fibroblasts. Further, we determine that this transition is associated with gene and protein hallmarks of the epithelial-mesenchymal transition (EMT) in tumor cells, in particular upregulation of SNAIL and SLUG mRNA and loss of E-Cadherin protein. We identified the secreted proteins that arise from epithelial-fibroblast interactions in this system using an antibody-based array. The proteins secreted into the conditioned medium are sufficient to induce EMT markers in primary normal human mammary epithelial cells (HMECs). Our report demonstrates that estrogen receptor activity is dynamic and therefore is not best assessed with immunohistochemical techniques alone. For the facile and rapid determination of ER activity in a clinical setting, we propose the use of an emerging imaging method, highly sensitive label-free Fourier Transform infrared (FT-IR) spectroscopic imaging. We validate this technology in predicting endocrine sensitivity in breast cancer here, by detecting significant changes in spectroscopic peaks correlated with proliferation and metabolism of MCF7 cells grown in 3D culture.

(Supported by grants from The Breast Cancer Research Foundation to BSK, DOD postdoctoral fellowship W81XWH-09-1-0398 to AB, NIH NCI Alliance for Nanotechnology in Cancer ‘Midwest Cancer Nanotechnology Training Center R25 CA154015A to SEH, and National Institutes of Health RO1CA138882 to RB.)

Citation Format: Sarah E. Holton, Anna Bergamaschi, Benita S. Katzenellenbogen, Rohit Bhargava. Mammary fibroblasts induce hormone-independent growth in estrogen receptor-positive breast cancer cells via an epithelial-to-mesenchymal transition in a 3D cell culture model. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 503. doi:10.1158/1538-7445.AM2013-503

Abstract 1316: Estrogen receptor-α dictates the subcellular localization of ERK5 to control differential proliferation and invasion programs of breast cancer cells

Mitogen activated protein kinases (MAPKs) are key players in relaying extracellular signals to the cell nucleus and are often overexpressed in aggressive and endocrine-resistant breast cancers. Our previous studies (Madak-Erdogan et al. Mol Cell Biol 31:226,2011) revealed that one such kinase, ERK2, was recruited to distal enhancers of estradiol(E2)-regulated genes together with estrogen receptor alpha (ERα) and collaborated with ERα to regulate gene expression and cell proliferation programs in response to hormone. In the current study, we identified ERK5, a close relative of ERK2, as a factor that is recruited to the transcription start site (TSS) of E2-stimulated genes. Use of dominant negative and constitutively active forms, as well as small molecule inhibitors of ERK5 and MEK5, revealed that activation of ERK5 by upstream kinase MEK5 and activity of ERK5 itself was required for recruitment of the kinase to the chromatin. Immunofluorescence studies demonstrated that ERK5 localized to transcription factories in the nucleus upon cell treatment with E2. Inhibitors of ERK5 completely abrogated E2-dependent cell proliferation and colony formation for all of the ERα-positive breast cancer cell lines studied. In contrast to what we observed in ERα-positive cells, in ERα-negative breast cancer cell lines we did not detect any nuclear ERK5; instead, we found ERK5 localized to the actin cytoskeleton, especially to sites where substantial remodeling takes place. Upon expression of ERα in these ERα-negative cells, we observed re-localization of ERK5 to the nucleus and a decrease in actin reorganization associated with reduced cell motility and invasion. Abrogation of ERα expression using siRNA in ERα-positive cell lines caused loss of nuclear ERK5 and relocalized this kinase to the actin cytoskeleton. Our studies with tamoxifen resistant cell lines revealed that ERK5 localization to the nucleus was reduced and localization to the actin cytoskeleton increased as resistance progressed, suggesting a correlation between ERα activity, ERK5 localization and motility of breast cancer cells. Our data reveal that ERα elicits nuclear localization of ERK5, diminishing ERK5 localization to regions of high actin remodeling, thereby possibly accounting for the generally lower metastatic potential that is characteristic of many ERα-positive breast cancer cells.

(Supported by grants T32 ES007326 and P50 AT006268 from NIH, and a grant from The Breast Cancer Research Foundation.)

Citation Format: Zeynep Madak Erdogan, Anna Bergamaschi, Rosa Ventrella, Hailing Lu, Benita S. Katzenellenbogen. Estrogen receptor-α dictates the subcellular localization of ERK5 to control differential proliferation and invasion programs of breast cancer cells. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1316. doi:10.1158/1538-7445.AM2013-1316

Abstract C85: FOXM1-dependent gene expression program controls cancer stem cell and metastasis properties of breast cancer cells

The transcription factor FOXM1 coordinates expression of late cell cycle-related genes. Elevated expression of FOXM1 in breast cancer correlates with a more aggressive tumor phenotype and, as we have previously shown, is associated with resistance to endocrine treatment via 14-3-3ζ protein signaling (Bergamaschi A. et al. Breast Cancer Research 2011, 13:R7). To better understand the role that FOXM1 plays in endocrine resistance and aggressiveness, we analyzed its genome-wide DNA binding and effects on gene expression. We mapped genome-wide FOXM1 binding events, by chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq), in breast cancer cell lines after estrogen or tamoxifen treatments. We also investigated the relationship between FOXM1, estrogen receptor-α and MAPK chromatin binding events by clustering analysis of Chip-seq data and identified specific clusters of colocalized binding events as identifiers for different functional gene classes. Clusters enriched in colocalized factor binding sites were associated with genes involved in maintenance of stem cell properties and genes involved in invasion and metastasis (Rho-GTPases). Binding profiles were also integrated with expression data from FOXM1 knockdown experiments, to reveal specific FOXM1 transcriptional networks.

Cell studies showed the relevance of FOXM1 in breast cancer endocrine resistance and development of metastasis. We modulated the levels of FOXM1 and some newly discovered FOXM1 regulated genes in MCF7 cells and assessed their roles in hormone resistance and breast cancer aggressiveness by several functional studies. Increased expression levels of FOXM1 were associated with an increase in the cancer stem cell population. Moreover, FOXM1 overexpressing cell lines exhibited invadopodia which correlated with an increased invasion potential. The use of a specific and selective FOXM1 inhibitor proved to be especially effective in restoring endocrine sensitivity and in decreasing breast cancer aggressiveness. Collectively, our findings define FOXM1 as a master regulator of Rho-GTPase and stem cell marker expression. Dysregulation of the FOXM1 pathway promotes breast cancer progression and therefore makes FOXM1 a relevant therapeutic target to be considered for reducing invasiveness and enhancing response to endocrine and other therapies.

Citation Format: Anna Bergamaschi, Zeynep Madak-Erdogan, Hailing Lu, Benita S. Katzenellenbogen. FOXM1-dependent gene expression program controls cancer stem cell and metastasis properties of breast cancer cells. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Invasion and Metastasis; Jan 20-23, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;73(3 Suppl):Abstract nr C85.

14-3-3ζ as a predictor of early time to recurrence and distant metastasis in hormone receptor-positive and -negative breast cancers

The 14-3-3ζ gene, on 8q22, is often amplified in breast cancer and encodes a survival factor that interacts with and stabilizes many key signaling proteins. We examined the relationship between the expression of 14-3-3ζ, estrogen receptor α (ERα), and other parameters ( tumor size, grade, nodal status, progesterone receptor, HER2, EGFR, and p53) in matched primary and recurrence tumor tissue and how these factors impact time to recurrence, properties of the recurred tumors, and site of metastasis. In this cohort of over 100 patients, median time to recurrence was 3 years (range 1-17 years). Our analyses of primary tumor microarray cores revealed that 14-3-3ζ status was significantly correlated with tumor grade, size, and ERα. Women with 14-3-3ζ-positive and ERα-negative tumors had the earliest time to recurrence (median 1 yr, p < 0.001, hazard ratio 2.89), while median time to recurrence was 7 years for 14-3-3ζ-negative and ER-positive tumors. Of recurred tumors, 70-75 % were positive for 14-3-3ζ, up from the 45 % positivity of primary tumors. High expression of 14-3-3ζ also correlated with site of recurrence and showed a propensity for distant metastases to lung and chest wall. Multifactor correlation regression analysis revealed 14-3-3ζ to be a non-redundant, independent variable that adds clinical strength in predicting risk for early recurrence in ER-positive and -negative breast cancers, providing information beyond that of all other clinical pathological features examined. Thus, high expression of 14-3-3ζ in the primary tumor was significantly associated with earlier time to recurrence and with distant metastasis. Furthermore, even when the primary breast cancers were negative-low for 14-3-3ζ, the majority acquired increased expression in the recurrence. The findings underscore the detrimental role played by 14-3-3ζ in tumor aggressiveness and suggest that reducing its expression or interfering with its actions might substantially improve the clinical outcome for breast cancer patients.

Capturing dynamics with Eiger, a fast-framing X-ray detector

Eiger is the next-generation single-photon-counting pixel detector following the widely used Pilatus detector. Its smaller pixel size of 75 µm × 75 µm, higher frame rate of up to 22 kHz, and practically zero dead-time (~4 µs) between exposures will further various measurement methods at synchrotron sources. In this article Eiger's suitability for X-ray photon correlation spectroscopy (XPCS) is demonstrated. By exploiting its high frame rate, complementary small-angle X-ray scattering (SAXS) and XPCS data are collected in parallel to determine both the structure factor and collective diffusion coefficient of a nano-colloid suspension. For the first time, correlation times on the submillisecond time scale are accessible with a large-area pixel detector.

A von Hamos x-ray spectrometer based on a segmented-type diffraction crystal for single-shot x-ray emission spectroscopy and time-resolved resonant inelastic x-ray scattering studies

We report on the design and performance of a wavelength-dispersive type spectrometer based on the von Hamos geometry. The spectrometer is equipped with a segmented-type crystal for x-ray diffraction and provides an energy resolution in the order of 0.25 eV and 1 eV over an energy range of 8000 eV-9600 eV. The use of a segmented crystal results in a simple and straightforward crystal preparation that allows to preserve the spectrometer resolution and spectrometer efficiency. Application of the spectrometer for time-resolved resonant inelastic x-ray scattering and single-shot x-ray emission spectroscopy is demonstrated.

MiR-30e and miR-181d control radial glia cell proliferation via HtrA1 modulation

The precise mechanisms by which microRNAs (miRNAs) contribute to the dynamic regulation of gene expression during the forebrain development are still partly elusive. Here we show that the depletion of miRNAs in the cerebral cortex and hippocampus, via genetic inactivation of Dicer after the onset of forebrain neurogenesis, profoundly impairs the morphological and proliferative characteristics of neural stem and progenitor cells. The cytoarchitecture and self-renewal potential of radial glial (RG) cells located within the cerebral cortex and the hippocampus were profoundly altered, thus causing a significant derangement of both the post natal dorsal sub-ventricular zone and the dentate gyrus. This effect was attributed to the High-temperature requirement A serine peptidase 1 (HtrA1) gene product whose overexpression in the developing forebrain recapitulated some of the aspects of the Dicer^−/− phenotype. MiR-30e and miR-181d were identified as posttranscriptional negative regulators of HtrA1 by binding to its 3′ untranslated region. In vivo overexpression of miR-30e and miR-181d in Dicer^−/− forebrain rescued RG proliferation defects.

[Cardiovascular prevention in the workplace: scientific evidence for the role of health promotion]

Cardiovascular disorders represent the leading cause of mortality and morbidity in the western world. A large number of working subjects is potentially involved. On this basis, the work environment may be considered an ideal place for health promotion in this field. The recently involvement of Occupational Medicine in health promotion programs represent an ideal condition for the effective implementation of these programs, Scientific literature convincingly show that well characterized interventions, acting on key factors of the cardiovascular risk, such as smoking, diet, physical activity, hypertension, hyperlipidemia, obesity and work-related stress may prevent the development of overt cardiovascular diseases. A proper administration and presentation of these programs is however an essential requisite for their success. Last but not least, the participation of workers, especially of those of low socioeconomic status should be obtained. In order to reach this goal, adequate incentives need to be proposed to workers, including employer-provided paid time off during the work-day for exercise health screenings, or prevention/wellness programs. Although seemingly costly, this approach seems to be fruitful in terms of financial returns in the mid-long term perspective.

Micrometre resolution of a charge integrating microstrip detector with single photon sensitivity

A synchrotron beam has been used to test the spatial resolution of a single-photon-resolving integrating readout-chip coupled to a 320 µm-thick silicon strip sensor with a dedicated readout system. Charge interpolation methods have yielded a spatial resolution of σ(x) ≃ 1.8 µm for a 20 µm-pitch strip.