Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer.

High-grade serous ovarian cancer (HGSC) exhibits extensive malignant clonal diversity with widespread but non-random patterns of disease dissemination. We investigated whether local immune microenvironment factors shape tumor progression properties at the interface of tumor-infiltrating lymphocytes (TILs) and cancer cells. Through multi-region study of 212 samples from 38 patients with whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T and B cell receptor sequencing, we identified three immunologic subtypes across samples and extensive within-patient diversity. Epithelial CD8+ TILs negatively associated with malignant diversity, reflecting immunological pruning of tumor clones inferred by neoantigen depletion, HLA I loss of heterozygosity, and spatial tracking between T cell and tumor clones. In addition, combinatorial prognostic effects of mutational processes and immune properties were observed, illuminating how specific genomic aberration types associate with immune response and impact survival. We conclude that within-patient spatial immune microenvironment variation shapes intraperitoneal malignant spread, provoking new evolutionary perspectives on HGSC clonal dispersion.

Multi-vendor evaluation of artificial intelligence as an independent reader for double reading in breast cancer screening on 275,900 mammograms.

BACKGROUND: Double reading (DR) in screening mammography increases cancer detection and lowers recall rates, but has sustainability challenges due to workforce shortages. Artificial intelligence (AI) as an independent reader (IR) in DR may provide a cost-effective solution with the potential to improve screening performance. Evidence for AI to generalise across different patient populations, screening programmes and equipment vendors, however, is still lacking. METHODS: This retrospective study simulated DR with AI as an IR, using data representative of real-world deployments (275,900 cases, 177,882 participants) from four mammography equipment vendors, seven screening sites, and two countries. Non-inferiority and superiority were assessed for relevant screening metrics. RESULTS: DR with AI, compared with human DR, showed at least non-inferior recall rate, cancer detection rate, sensitivity, specificity and positive predictive value (PPV) for each mammography vendor and site, and superior recall rate, specificity, and PPV for some. The simulation indicates that using AI would have increased arbitration rate (3.3% to 12.3%), but could have reduced human workload by 30.0% to 44.8%. CONCLUSIONS: AI has potential as an IR in the DR workflow across different screening programmes, mammography equipment and geographies, substantially reducing human reader workload while maintaining or improving standard of care. TRIAL REGISTRATION: ISRCTN18056078 (20/03/2019; retrospectively registered).

Rational Design of Azothiophenes-Substitution Effects on the Switching Properties.

A series of substituted azothiophenes was prepared and investigated toward their isomerization behavior. Compared to azobenzene (AB), the presented compounds showed red-shifted absorption and almost quantitative photoisomerization to their (Z) states. Furthermore, it was found that electron-withdrawing substitution on the phenyl moiety increases, while electron-donating substitution decreases the thermal half-lives of the (Z)-isomers due to higher or lower stabilization by a lone pair-π interaction. Additionally, computational analysis of the isomerization revealed that a pure singlet state transition state is unlikely in azothiophenes. A pathway via intersystem crossing to a triplet energy surface of lower energy than the singlet surface provided a better fit with experimental data of the (Z)→(E) isomerization. The insights gained in this study provide the necessary guidelines to design effective thiophenylazo-photoswitches for applications in photopharmacology, material sciences, or solar energy harvesting applications.

Thiophenylazobenzene: An Alternative Photoisomerization Controlled by Lone-Pair⋠⋠⋠π Interaction.

Azoheteroarene photoswitches have attracted attention due to their unique properties. We present the stationary photochromism and ultrafast photoisomerization mechanism of thiophenylazobenzene (TphAB). It demonstrates impressive fatigue resistance and photoisomerization efficiency, and shows favorably separated (E)- and (Z)-isomer absorption bands, allowing for highly selective photoconversion. The (Z)-isomer of TphAB adopts an unusual orthogonal geometry where the thiophenyl group is perfectly perpendicular to the phenyl group. This geometry is stabilized by a rare lone-pair⋅⋅⋅π interaction between the S atom and the phenyl group. The photoisomerization of TphAB occurs on the sub-ps to ps timescale and is governed by this interaction. Therefore, the adoption and disruption of the orthogonal geometry requires significant movement along the inversion reaction coordinates (CNN and NNC angles). Our results establish TphAB as an excellent photoswitch with versatile properties that expand the application possibilities of AB derivatives.

Starazo triple switches - synthesis of unsymmetrical 1,3,5-tris(arylazo)benzenes.

Multistate switches allow to drastically increase the information storage capacity and complexity of smart materials. In this context, unsymmetrical 1,3,5-tris(arylazo)benzenes - 'starazos' - which merge three photoswitches on one benzene ring, were successfully prepared. Two different synthetic strategies, one based on Baeyer-Mills reactions and the other based on Pd-catalyzed coupling reactions of arylhydrazides and aryl halides, followed by oxidation, were investigated. The Pd-catalyzed route efficiently led to the target compounds, unsymmetrical tris(arylazo)benzenes. These triple switches were preliminarily characterized in terms of their isomerization behavior using UV-vis and 1H NMR spectroscopy. The efficient synthesis of this new class of unsymmetrical tris(arylazo)benzenes opened new avenues to novel multistate switching materials.

London dispersion as important factor for the stabilization of (Z)-azobenzenes in the presence of hydrogen bonding.

The understanding and control of the light-induced isomerization of azobenzenes as one of the most important classes of molecular switches is crucial for the design of light-responsive materials using this entity. Herein, we present the stabilization of metastable (Z)-azobenzenes by London dispersion interactions, even in the presence of comparably stronger hydrogen bonds in various solvents. The Z→E isomerization rates of several N-substituted 4,4'-bis(4-aminobenzyl)azobenzenes were measured. An intramolecular stabilization was observed and explained by the interplay of intramolecular amide and carbamate hydrogen bonds as well as London dispersion interactions. Whereas in toluene, 1,4-dioxane and tert-butyl methyl ether the hydrogen bonds dominate, the variation in stabilization of the different substituted azobenzenes in dimethyl sulfoxide can be rationalized by London dispersion interactions. These findings were supported by conformational analysis and DFT computations and reveal low-energy London dispersion forces to be a significant factor, even in the presence of hydrogen bonds.

An air-stable bisboron complex: a practical bidentate Lewis acid catalyst.

We report an air-stable bisboron complex as an efficient catalyst for the inverse electron-demand Diels-Alder (IEDDA) reaction of 1,2-diazine as well as 1,2,4,5-tetrazine. Its stability towards air and moisture was demonstrated by NMR studies enabling its application in organic transformations without glovebox. A one-pot procedure for its synthesis was developed starting from 1,2-bis(trimethylsilyl)benzene greatly enhancing its practicality. Comparative reactions were carried out to evaluate its catalytic activity in IEDDA reactions of diazine including phthalazine as well as 1,2,4,5-tetrazine.

Diffusion-weighted MRI for early detection and characterization of prostate cancer in the transgenic adenocarcinoma of the mouse prostate model.

PURPOSE: To improve early diagnosis of prostate cancer to aid clinical decision-making. Diffusion-weighted magnetic resonance imaging (DW-MRI) is sensitive to water diffusion throughout tissues, which correlates with Gleason score, a histological measure of prostate cancer aggressiveness. In this study the ability of DW-MRI to detect prostate cancer onset and development was evaluated in transgenic adenocarcinoma of the mouse prostate (TRAMP) mice. MATERIALS AND METHODS: T2 -weighted and DW-MRI were acquired using a 7T MR scanner, 200 mm bore diameter; 10 TRAMP and 6 C57BL/6 control mice were scanned every 4 weeks from 8 weeks of age until sacrifice at 28-30 weeks. After sacrifice, the genitourinary tract was excised and sectioned for histological analysis. Histology slides registered with DW-MR images allowed for validation of DW-MR images and the apparent diffusion coefficient (ADC) as tools for cancer detection and disease stratification. An automated early assessment tool based on ADC threshold values was developed to aid cancer detection and progression monitoring. RESULTS: The ADC differentiated between control prostate ((1.86 ± 0.20) × 10(-3) mm(2) /s) and normal TRAMP prostate ((1.38 ± 0.10) × 10(-3) mm(2) /s) (P = 0.0001), between TRAMP prostate and well-differentiated cancer ((0.93 ± 0.18) × 10(-3) mm(2) /s) (P = 0.0006), and between well-differentiated cancer and poorly differentiated cancer ((0.63 ± 0.06) × 10(-3) mm(2) /s) (P = 0.02). CONCLUSION: DW-MRI is a tool for early detection of cancer, and discrimination between cancer stages in the TRAMP model. The incorporation of DW-MRI-based prostate cancer stratification and monitoring could increase the accuracy of preclinical trials using TRAMP mice.

Mapping spatial heterogeneity in the tumor microenvironment: a new era for digital pathology.

The emergent field of digital pathology employing automated image analysis techniques is to revolutionize traditional pathology at the center of clinical diagnostics. Histological images provide important tumor features unavailable in molecular profiling or omics data- the spatial context of tumor and stromal cells at single-cell resolution. Methods to map the spatial and morphological patterns of cancer and normal cells can contribute to a more comprehensive understanding of the highly heterogeneous tumor microenvironment. This review focuses on methods that help expand our knowledge of intra-tumoral spatial heterogeneity of the tumor microenvironment and their potential synergies with molecular profiling technologies.

Beyond immune density: critical role of spatial heterogeneity in estrogen receptor-negative breast cancer.

The abundance of tumor-infiltrating lymphocytes has been associated with a favorable prognosis in estrogen receptor-negative breast cancer. However, a high degree of spatial heterogeneity in lymphocytic infiltration is often observed and its clinical implication remains unclear. Here we combine automated histological image processing with methods of spatial statistics used in ecological data analysis to quantify spatial heterogeneity in the distribution patterns of tumor-infiltrating lymphocytes. Hematoxylin and eosin-stained sections from two cohorts of estrogen receptor-negative breast cancer patients (discovery: n=120; validation: n=125) were processed with our automated cell classification algorithm to identify the location of lymphocytes and cancer cells. Subsequently, hotspot analysis (Getis-Ord Gi*) was applied to identify statistically significant hotspots of cancer and immune cells, defined as tumor regions with a significantly high number of cancer cells or immune cells, respectively. We found that the amount of co-localized cancer and immune hotspots weighted by tumor area, rather than number of cancer or immune hotspots, correlates with a better prognosis in estrogen receptor-negative breast cancer in univariate and multivariate analysis. Moreover, co-localization of cancer and immune hotspots further stratified patients with immune cell-rich tumors. Our study demonstrates the importance of quantifying not only the abundance of lymphocytes but also their spatial variation in the tumor specimen for which methods from other disciplines such as spatial statistics can be successfully applied.

Automated REcognition of tissue-associated erythrocytes (ARETE)-a new tool in tissue cytometry.

Automated microscopic image analysis of immunofluorescence-stained targets on tissue sections is challenged by autofluorescent elements such as erythrocytes, which might interfere with target segmentation and quantification. Therefore, we developed an automated system (Automated REcognition of Tissue-associated Erythrocytes; ARETE) for in silico exclusion of erythrocytes. To detect erythrocytes in transmission images, a cascade of boosted decision trees of Haar-like features was trained on 8,640/4,000 areas (15 × 15 pixels) with/without erythrocytes from images of placental sections (4 µm). Ground truth data were generated on 28 transmission images. At least two human experts labelled the area covered by erythrocytes. For validation, output masks of human experts and ARETE were compared pixel-wise against a mask obtained from majority voting of human experts. F1 score, specificity, and Cohen's κ coefficients were calculated. To study the influence of erythrocyte-derived autofluorescence, we investigated the expression levels of a protein (receptor for advanced glycated end products; RAGE) in placenta and number of Ki-67-positive/cytokeratin 8-positive epithelial cells in colon sections. ARETE exhibited high sensitivity (99.87%) and specificity (99.81%) on a training-subset and processed transmission images (1,392 × 1,024 pixels) within 4 sec. ARETE and human expert's F1-scores were 0.55 versus 0.76, specificities 0.85 versus 0.92 and Cohen's κ coefficients 0.41 versus 0.68. A ranking of Cohen's κ coefficient by the scale of Fleiss certified "good agreement" between ARETE and the human experts. Applying ARETE, we demonstrated 4-14% false-positive RAGE-expression in placenta, and 18% falsely detected proliferative epithelial cells in colon, caused by erythrocyte-autofluorescence. ARETE is a fast system for in silico reduction of erythrocytes, which improves automated image analysis in research and diagnostic pathology.

Electrochemically Triggered Energy Release from an Azothiophene-Based Molecular Solar Thermal System.

Molecular solar thermal (MOST) systems combine solar energy conversion, storage, and release in simple one-photon one-molecule processes. Here, we address the electrochemically triggered energy release from an azothiophene-based MOST system by photoelectrochemical infrared reflection absorption spectroscopy (PEC-IRRAS) and density functional theory (DFT). Specifically, the electrochemically triggered back-reaction from the energy rich (Z)-3-cyanophenylazothiophene to its energy lean (E)-isomer using highly oriented pyrolytic graphite (HOPG) as the working electrode was studied. Theory predicts that two reaction channels are accessible, an oxidative one (hole-catalyzed) and a reductive one (electron-catalyzed). Experimentally it was found that the photo-isomer decomposes during hole-catalyzed energy release. Electrochemically triggered back-conversion was possible, however, through the electron-catalyzed reaction channel. The reaction rate could be tuned by the electrode potential within two orders of magnitude. It was shown that the MOST system withstands 100 conversion cycles without detectable decomposition of the photoswitch. After 100 cycles, the photochemical conversion was still quantitative and the electrochemically triggered back-reaction reached 94 % of the original conversion level.

Perceived Realism of High-Resolution Generative Adversarial Network-derived Synthetic Mammograms.

PURPOSE: To explore whether generative adversarial networks (GANs) can enable synthesis of realistic medical images that are indiscernible from real images, even by domain experts. MATERIALS AND METHODS: In this retrospective study, progressive growing GANs were used to synthesize mammograms at a resolution of 1280 × 1024 pixels by using images from 90 000 patients (average age, 56 years ± 9) collected between 2009 and 2019. To evaluate the results, a method to assess distributional alignment for ultra-high-dimensional pixel distributions was used, which was based on moment plots. This method was able to reveal potential sources of misalignment. A total of 117 volunteer participants (55 radiologists and 62 nonradiologists) took part in a study to assess the realism of synthetic images from GANs. RESULTS: A quantitative evaluation of distributional alignment shows 60%-78% mutual-information score between the real and synthetic image distributions, and 80%-91% overlap in their support, which are strong indications against mode collapse. It also reveals shape misalignment as the main difference between the two distributions. Obvious artifacts were found by an untrained observer in 13.6% and 6.4% of the synthetic mediolateral oblique and craniocaudal images, respectively. A reader study demonstrated that real and synthetic images are perceptually inseparable by the majority of participants, even by trained breast radiologists. Only one out of the 117 participants was able to reliably distinguish real from synthetic images, and this study discusses the cues they used to do so. CONCLUSION: On the basis of these findings, it appears possible to generate realistic synthetic full-field digital mammograms by using a progressive GAN architecture up to a resolution of 1280 × 1024 pixels.Supplemental material is available for this article.© RSNA, 2020.

Selective switching of multiple azobenzenes.

Multi-state photoswitchable compounds are highly attractive for application in data storage or multi-responsive materials. In this work, a trisazobenzene macrocycle capable of three-state isomerization is presented. The compound can be switched into each of the states with more than 70% of the isomer solely by light and heat as stimuli representing the first example for an oligo-azobenzene containing identical photochromic units which can be selectively adressed. Detailed spectroscopic, crystallographic, HPLC as well as computational investigations and the comparison to a less and a higher strained derivative revealed macrocyclic ring strain to be responsible for the compounds unique isomerization behavior.

Intermolecular London Dispersion Interactions of Azobenzene Switches for Tuning Molecular Solar Thermal Energy Storage Systems.

The performance of molecular solar thermal energy storage systems (MOST) depends amongst others on the amount of energy stored. Azobenzenes have been investigated as high-potential materials for MOST applications. In the present study it could be shown that intermolecular attractive London dispersion interactions stabilize the (E)-isomer in bisazobenzene that is linked by different alkyl bridges. Differential scanning calorimetry (DSC) measurements revealed, that this interaction leads to an increased storage energy per azo-unit of more than 3 kcal/mol compared to the parent azobenzene. The origin of this effect has been supported by computation as well as X-ray analysis. In the solid state structure attractive London dispersion interactions between the C-H of the alkyl bridge and the π-system of the azobenzene could be clearly assigned. This concept will be highly useful in designing more effective MOST systems in the future.

Analysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer.

BACKGROUND: Despite treatment advances, there remains a significant risk of recurrence in ovarian cancer, at which stage it is usually incurable. Consequently, there is a clear need for improved patient stratification. However, at present clinical prognosticators remain largely unchanged due to the lack of reproducible methods to identify high-risk patients. METHODS: In high-grade serous ovarian cancer patients with advanced disease, we spatially define a tumour ecological balance of stromal resource and immune hazard using high-throughput image and spatial analysis of routine histology slides. On this basis an EcoScore is developed to classify tumours by a shift in this balance towards cancer-favouring or inhibiting conditions. FINDINGS: The EcoScore provides prognostic value stronger than, and independent of, known risk factors. Crucially, the clinical relevance of mutational burden and genomic instability differ under different stromal resource conditions, suggesting that the selective advantage of these cancer hallmarks is dependent on the context of stromal spatial structure. Under a high resource condition defined by a high level of geographical intermixing of cancer and stromal cells, selection appears to be driven by point mutations; whereas, in low resource tumours featured with high hypoxia and low cancer-immune co-localization, selection is fuelled by aneuploidy. INTERPRETATION: Our study offers empirical evidence that cancer fitness depends on tumour spatial constraints, and presents a biological basis for developing better assessments of tumour adaptive strategies in overcoming ecological constraints including immune surveillance and hypoxia.

Investigating the Contribution of Collagen to the Tumor Biomechanical Phenotype with Noninvasive Magnetic Resonance Elastography.

Increased stiffness in the extracellular matrix (ECM) contributes to tumor progression and metastasis. Therefore, stromal modulating therapies and accompanying biomarkers are being developed to target ECM stiffness. Magnetic resonance (MR) elastography can noninvasively and quantitatively map the viscoelastic properties of tumors in vivo and thus has clear clinical applications. Herein, we used MR elastography, coupled with computational histopathology, to interrogate the contribution of collagen to the tumor biomechanical phenotype and to evaluate its sensitivity to collagenase-induced stromal modulation. Elasticity (G d) and viscosity (G l) were significantly greater for orthotopic BT-474 (G d = 5.9 ± 0.2 kPa, G l = 4.7 ± 0.2 kPa, n = 7) and luc-MDA-MB-231-LM2-4 (G d = 7.9 ± 0.4 kPa, G l = 6.0 ± 0.2 kPa, n = 6) breast cancer xenografts, and luc-PANC1 (G d = 6.9 ± 0.3 kPa, G l = 6.2 ± 0.2 kPa, n = 7) pancreatic cancer xenografts, compared with tumors associated with the nervous system, including GTML/Trp53KI/KI medulloblastoma (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 7), orthotopic luc-D-212-MG (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 7), luc-RG2 (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 5), and luc-U-87-MG (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 8) glioblastoma xenografts, intracranially propagated luc-MDA-MB-231-LM2-4 (G d = 3.7 ± 0.2 kPa, G l = 2.2 ± 0.1 kPa, n = 7) breast cancer xenografts, and Th-MYCN neuroblastomas (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 5). Positive correlations between both elasticity (r = 0.72, P < 0.0001) and viscosity (r = 0.78, P < 0.0001) were determined with collagen fraction, but not with cellular or vascular density. Treatment with collagenase significantly reduced G d (P = 0.002) and G l (P = 0.0006) in orthotopic breast tumors. Texture analysis of extracted images of picrosirius red staining revealed significant negative correlations of entropy with G d (r = -0.69, P < 0.0001) and G l (r = -0.76, P < 0.0001), and positive correlations of fractal dimension with G d (r = 0.75, P < 0.0001) and G l (r = 0.78, P < 0.0001). MR elastography can thus provide sensitive imaging biomarkers of tumor collagen deposition and its therapeutic modulation. SIGNIFICANCE: MR elastography enables noninvasive detection of tumor stiffness and will aid in the development of ECM-targeting therapies.

Relevance of Spatial Heterogeneity of Immune Infiltration for Predicting Risk of Recurrence After Endocrine Therapy of ER+ Breast Cancer.

Background: Despite increasing evidence supporting the clinical utility of immune infiltration in the estrogen receptor-negative (ER-) subtype, the prognostic value of immune infiltration for ER+ disease is not well defined. Methods: Quantitative immune scores of cell abundance and spatial heterogeneity were computed using a fully automated hematoxylin and eosin-stained image analysis algorithm and spatial statistics for 1178 postmenopausal patients with ER+ breast cancer treated with five years' tamoxifen or anastrozole. The prognostic significance of immune scores was compared with Oncotype DX 21-gene recurrence score (RS), PAM50 risk of recurrence (ROR) score, IHC4, and clinical treatment score, available for 963 patients. Statistical tests were two-sided. Results: Scores of immune cell abundance were not associated with recurrence-free survival. In contrast, high immune spatial scores indicating increased cell spatial clustering were associated with poor 10-year, early (0-5 years), and late (5-10 years) recurrence-free survival (Immune Hotspot: LR-χ2 = 14.06, P < .001, for 0-10 years; LR-χ2 = 6.24, P = .01, for 0-5 years; LR-χ2 = 7.89, P = .005, for 5-10 years). The prognostic value of spatial scores for late recurrence was similar to that of IHC4 and RS in both populations, but was not as strong as other tests in comparison for recurrence across 10 years. Conclusions: These results provide a missing link between tumor immunity and disease outcome in ER+ disease by examining tumor spatial architecture. The association between spatial scores and late recurrence suggests a lasting memory of protumor immunity that may impact disease progression and evolution of endocrine treatment resistance, which may be exploited for therapeutic advances.

Twist and Return-Induced Ring Strain Triggers Quick Relaxation of a ( Z)-Stabilized Cyclobisazobenzene.

Continuous irradiation of the thermodynamically stable ( Z, Z)-cyclobisazobenzene does not lead to accumulation of a ( Z, E) or ( E, E) isomer as one might expect. Our combined experimental and computational investigation reveals that Z → E photoisomerization still takes place on an ultrafast time scale but induces large ring strain in the macrocycle, which leads to a very fast thermal back-isomerization, preventing photostationary accumulation of ( E)-isomers.