The CrowdGleason dataset: Learning the Gleason grade from crowds and experts.

BACKGROUND: Currently, prostate cancer (PCa) diagnosis relies on the human analysis of prostate biopsy Whole Slide Images (WSIs) using the Gleason score. Since this process is error-prone and time-consuming, recent advances in machine learning have promoted the use of automated systems to assist pathologists. Unfortunately, labeled datasets for training and validation are scarce due to the need for expert pathologists to provide ground-truth labels. METHODS: This work introduces a new prostate histopathological dataset named CrowdGleason, which consists of 19,077 patches from 1045 WSIs with various Gleason grades. The dataset was annotated using a crowdsourcing protocol involving seven pathologists-in-training to distribute the labeling effort. To provide a baseline analysis, two crowdsourcing methods based on Gaussian Processes (GPs) were evaluated for Gleason grade prediction: SVGPCR, which learns a model from the CrowdGleason dataset, and SVGPMIX, which combines data from the public dataset SICAPv2 and the CrowdGleason dataset. The performance of these methods was compared with other crowdsourcing and expert label-based methods through comprehensive experiments. RESULTS: The results demonstrate that our GP-based crowdsourcing approach outperforms other methods for aggregating crowdsourced labels (κ=0.7048±0.0207) for SVGPCR vs.(κ=0.6576±0.0086) for SVGP with majority voting). SVGPCR trained with crowdsourced labels performs better than GP trained with expert labels from SICAPv2 (κ=0.6583±0.0220) and outperforms most individual pathologists-in-training (mean κ=0.5432). Additionally, SVGPMIX trained with a combination of SICAPv2 and CrowdGleason achieves the highest performance on both datasets (κ=0.7814±0.0083 and κ=0.7276±0.0260). CONCLUSION: The experiments show that the CrowdGleason dataset can be successfully used for training and validating supervised and crowdsourcing methods. Furthermore, the crowdsourcing methods trained on this dataset obtain competitive results against those using expert labels. Interestingly, the combination of expert and non-expert labels opens the door to a future of massive labeling by incorporating both expert and non-expert pathologist annotators.

Tumor evolution metrics predict recurrence beyond 10 years in locally advanced prostate cancer.

Cancer evolution lays the groundwork for predictive oncology. Testing evolutionary metrics requires quantitative measurements in controlled clinical trials. We mapped genomic intratumor heterogeneity in locally advanced prostate cancer using 642 samples from 114 individuals enrolled in clinical trials with a 12-year median follow-up. We concomitantly assessed morphological heterogeneity using deep learning in 1,923 histological sections from 250 individuals. Genetic and morphological (Gleason) diversity were independent predictors of recurrence (hazard ratio (HR) = 3.12 and 95% confidence interval (95% CI) = 1.34-7.3; HR = 2.24 and 95% CI = 1.28-3.92). Combined, they identified a group with half the median time to recurrence. Spatial segregation of clones was also an independent marker of recurrence (HR = 2.3 and 95% CI = 1.11-4.8). We identified copy number changes associated with Gleason grade and found that chromosome 6p loss correlated with reduced immune infiltration. Matched profiling of relapse, decades after diagnosis, confirmed that genomic instability is a driving force in prostate cancer progression. This study shows that combining genomics with artificial intelligence-aided histopathology leads to the identification of clinical biomarkers of evolution.

Nitrate reduction enables safer aryldiazonium chemistry.

Aryldiazonium salts remain a staple in organic synthesis and are still prepared largely in accord with the protocol developed in the 19th century. Because of the favorable reactivity that often cannot be achieved with other aryl(pseudo)halides, diazonium chemistry continues to grow. Facile extrusion of dinitrogen contributes to the desired reactivity but is also reason for safety concerns. Explosions have occurred since the discovery of these reagents and still result in accidents. In this study, we report a diazonium chemistry paradigm shift based on nitrate reduction using thiosulfate or dihalocuprates as electron donors that avoids diazonium accumulation. Because nitrate reduction is rate-limiting, aryldiazoniums are produced as fleeting intermediates, which results in a safer and often more efficient deaminative halogenation in a single step from anilines.

Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset.

Digital Pathology (DP) has experienced a significant growth in recent years and has become an essential tool for diagnosing and prognosis of tumors. The availability of Whole Slide Images (WSIs) and the implementation of Deep Learning (DL) algorithms have paved the way for the appearance of Artificial Intelligence (AI) systems that support the diagnosis process. These systems require extensive and varied data for their training to be successful. However, creating labeled datasets in histopathology is laborious and time-consuming. We have developed a crowdsourcing-multiple instance labeling/learning protocol that is applied to the creation and use of the CR-AI4SkIN dataset.2 CR-AI4SkIN contains 271 WSIs of 7 Cutaneous Spindle Cell (CSC) neoplasms with expert and non-expert labels at region and WSI levels. It is the first dataset of these types of neoplasms made available. The regions selected by the experts are used to learn an automatic extractor of Regions of Interest (ROIs) from WSIs. To produce the embedding of each WSI, the representations of patches within the ROIs are obtained using a contrastive learning method, and then combined. Finally, they are fed to a Gaussian process-based crowdsourcing classifier, which utilizes the noisy non-expert WSI labels. We validate our crowdsourcing-multiple instance learning method in the CR-AI4SkIN dataset, addressing a binary classification problem (malign vs. benign). The proposed method obtains an F1 score of 0.7911 on the test set, outperforming three widely used aggregation methods for crowdsourcing tasks. Furthermore, our crowdsourcing method also outperforms the supervised model with expert labels on the test set (F1-score = 0.6035). The promising results support the proposed crowdsourcing multiple instance learning annotation protocol. It also validates the automatic extraction of interest regions and the use of contrastive embedding and Gaussian process classification to perform crowdsourcing classification tasks.

Contribution of pks+ E. coli mutations to colorectal carcinogenesis.

The dominant mutational signature in colorectal cancer genomes is C > T deamination (COSMIC Signature 1) and, in a small subgroup, mismatch repair signature (COSMIC signatures 6 and 44). Mutations in common colorectal cancer driver genes are often not consistent with those signatures. Here we perform whole-genome sequencing of normal colon crypts from cancer patients, matched to a previous multi-omic tumour dataset. We analyse normal crypts that were distant vs adjacent to the cancer. In contrast to healthy individuals, normal crypts of colon cancer patients have a high incidence of pks + (polyketide synthases) E.coli (Escherichia coli) mutational and indel signatures, and this is confirmed by metagenomics. These signatures are compatible with many clonal driver mutations detected in the corresponding cancer samples, including in chromatin modifier genes, supporting their role in early tumourigenesis. These results provide evidence that pks + E.coli is a potential driver of carcinogenesis in the human gut.

Catalytic asymmetric defluorinative allylation of silyl enol ethers.

The stereocontrolled installation of alkyl fragments at the alpha position of ketones is a fundamental yet unresolved transformation in organic chemistry. Herein we report a new catalytic methodology able to construct α-allyl ketones via defluorinative allylation of silyl enol ethers in a regio-, diastereo- and enantioselective manner. The protocol leverages the unique features of the fluorine atom to simultaneously act as a leaving group and to activate the fluorophilic nucleophile via a Si-F interaction. A series of spectroscopic, electroanalytic and kinetic experiments demonstrate the crucial interplay of the Si-F interaction for successful reactivity and selectivity. The generality of the transformation is demonstrated by synthesising a wide set of structurally diverse α-allylated ketones bearing two contiguous stereocenters. Remarkably, the catalytic protocol is amenable for the allylation of biologically significant natural products.

Unveiling the impact of the light-source and steric factors on [2+2] heterocycloaddition reactions.

Information gained from in-depth mechanistic investigations can be used to control the selectivity of reactions, leading to the expansion of the generality of synthetic processes and the discovery of new reactivity. Here, we investigate the mechanism of light-driven [2+2] heterocycloadditions (Paternò-Büchi reactions) between indoles and ketones to develop insight into these processes. Using ground-state UV-Vis absorption and transient absorption spectroscopy (TAS), together with DFT calculations, we found that the reactions can proceed via an exciplex or electron-donor-acceptor (EDA) complex, which are key intermediates in determining the stereoselectivity of the reactions. We used this discovery to control the diastereoselectivity of the reactions, gaining access to previously inaccessible diastereoisomeric variants. When moving from 370 to 456 nm irradiation, the EDA complex is increasingly favoured, and the diastereomeric ratio (d.r.) of the product moves from >99:<1 to 47:53. In contrast, switching from methyl to ipropyl substitution favours the exciplex intermediate, reversing the d.r. from 89:11 to 16:84. Our study shows how light and steric parameters can be rationally used to control the diastereoselectivity of photoreactions, creating mechanistic pathways to previously inaccessible stereochemical variants.

Halloysite Nanotubes as Bimodal Lewis/Brønsted Acid Heterogeneous Catalysts for the Synthesis of Heterocyclic Compounds.

Halloysite nanotubes can be used for the preparation of solid catalysts. Owing to their natural availability at low-cost as well as to their large and easy-to-functionalize surface, they can be conveniently activated with mineral acids or derivatized with acidic groups. Nevertheless, the use of HNTs as catalysts in complex transformations is still limited. Herein, we report two strategies to utilize HNT-based materials as solid acidic catalysts for the Biginelli reaction. To this aim, two methods for increasing the number of acidic sites on the HNTs were explored: (i) the treatment with piranha solution (Pir-HNTs) and (ii) the functionalization with phenylboronic acid (in particular with benzene-1,4-diboronic acid: the sample is denoted as HNT-BOA). Interestingly, both strategies enhance the performance of the multicomponent reaction. Pir-HNTs and HNT-BOA show an increased reactivity (72% and 89% yield, respectively) in comparison with pristine HNTs (52%). Additionally, Pir-HNTs can be reused up to five times without significant performance loss. Moreover, the method also displays good reaction scope, as demonstrated by the preparation of 12 different 3,4-dihydropyrimidinones in up to 71% yield. Therefore, the described strategies are promising for enhancing the acidity of the HNTs as catalysts for the organic reaction.

The co-evolution of the genome and epigenome in colorectal cancer.

Colorectal malignancies are a leading cause of cancer-related death1 and have undergone extensive genomic study2,3. However, DNA mutations alone do not fully explain malignant transformation4-7. Here we investigate the co-evolution of the genome and epigenome of colorectal tumours at single-clone resolution using spatial multi-omic profiling of individual glands. We collected 1,370 samples from 30 primary cancers and 8 concomitant adenomas and generated 1,207 chromatin accessibility profiles, 527 whole genomes and 297 whole transcriptomes. We found positive selection for DNA mutations in chromatin modifier genes and recurrent somatic chromatin accessibility alterations, including in regulatory regions of cancer driver genes that were otherwise devoid of genetic mutations. Genome-wide alterations in accessibility for transcription factor binding involved CTCF, downregulation of interferon and increased accessibility for SOX and HOX transcription factor families, suggesting the involvement of developmental genes during tumourigenesis. Somatic chromatin accessibility alterations were heritable and distinguished adenomas from cancers. Mutational signature analysis showed that the epigenome in turn influences the accumulation of DNA mutations. This study provides a map of genetic and epigenetic tumour heterogeneity, with fundamental implications for understanding colorectal cancer biology.

Phenotypic plasticity and genetic control in colorectal cancer evolution.

Genetic and epigenetic variation, together with transcriptional plasticity, contribute to intratumour heterogeneity1. The interplay of these biological processes and their respective contributions to tumour evolution remain unknown. Here we show that intratumour genetic ancestry only infrequently affects gene expression traits and subclonal evolution in colorectal cancer (CRC). Using spatially resolved paired whole-genome and transcriptome sequencing, we find that the majority of intratumour variation in gene expression is not strongly heritable but rather 'plastic'. Somatic expression quantitative trait loci analysis identified a number of putative genetic controls of expression by cis-acting coding and non-coding mutations, the majority of which were clonal within a tumour, alongside frequent structural alterations. Consistently, computational inference on the spatial patterning of tumour phylogenies finds that a considerable proportion of CRCs did not show evidence of subclonal selection, with only a subset of putative genetic drivers associated with subclone expansions. Spatial intermixing of clones is common, with some tumours growing exponentially and others only at the periphery. Together, our data suggest that most genetic intratumour variation in CRC has no major phenotypic consequence and that transcriptional plasticity is, instead, widespread within a tumour.

Genetic susceptibility to telomere shortening through the rs2293607 polymorphism is associated with a greater risk of alcohol use disorder.

Telomere shortening is usually considered a biomarker of ageing. Harmful alcohol use promotes accelerated biological ageing and alcohol use disorders (AUDs) are associated with short telomere length (TL). This study was conducted to examine the relationship of TL to AUD and determine whether single nucleotide polymorphisms (SNPs) in TERC and TERT modulate this association. For this purpose, we genotyped TERC SNPs rs2293607, rs12696304, and rs16847897 and TERT SNPs rs2735940, rs2736100, and rs2736098 in 308 male patients with AUD and 255 sex-matched healthy controls and measured TL in a subset of 99 patients and 99 controls paired by age and smoking status. Our results showed that the mean TL was shorter in patients with AUD than in controls. The area under the ROC curve was 0.70 (P < 0.001). The GG genotype of TERC rs2293607 was more common among patients with AUD than among controls (9.8% vs. 5.1%; P = 0.038). No difference was found for the other SNPs. Carriers of the GG genotype of rs2293607 had shorter telomeres than did allele A carriers. In conclusion, patients with AUD had shorter telomeres. Genetic susceptibility to telomere shortening through the rs2293607 SNP is associated with a greater risk of AUD.

Bayesian K-SVD for H and E blind color deconvolution. Applications to stain normalization, data augmentation and cancer classification.

Stain variation between images is a main issue in the analysis of histological images. These color variations, produced by different staining protocols and scanners in each laboratory, hamper the performance of computer-aided diagnosis (CAD) systems that are usually unable to generalize to unseen color distributions. Blind color deconvolution techniques separate multi-stained images into single stained bands that can then be used to reduce the generalization error of CAD systems through stain color normalization and/or stain color augmentation. In this work, we present a Bayesian modeling and inference blind color deconvolution framework based on the K-Singular Value Decomposition algorithm. Two possible inference procedures, variational and empirical Bayes are presented. Both provide the automatic estimation of the stain color matrix, stain concentrations and all model parameters. The proposed framework is tested on stain separation, image normalization, stain color augmentation, and classification problems.

Temperature and Gate-Length Dependence of Subthreshold RF Detection in GaN HEMTs.

The responsivity of AlGaN/GaN high-electron mobility transistors (HEMTs) when operating as zero-bias RF detectors in the subthreshold regime exhibits different behaviors depending on the operating temperature and gate length of the transistors. We have characterized in temperature (8-400 K) the detection performance of HEMTs with different gate lengths (75-250 nm). The detection results at 1 GHz can be reproduced by a quasi-static model, which allows us to interpret them by inspection of the output ID - VDS curves of the transistors. We explain the different behaviors observed in terms of the presence or absence of a shift in the zero-current operating point originating from the existence of the gate-leakage current jointly with temperature effects related to the ionization of bulk traps.

Radical α-Trifluoromethoxylation of Ketones under Batch and Flow Conditions by Means of Organic Photoredox Catalysis.

The first light-driven method for the α-trifluoromethoxylation of ketones is reported. Enol carbonates react with N-trifluoromethoxy-4-cyano-pyridinium, using the photoredox catalyst 4-CzIPN under 456 nm irradiation, affording the α-trifluoromethoxy ketones in ≤50% isolated yield and complete chemoselectivity. As shown by 29 examples, the reaction is general and proceeds very rapidly under batch (1 h) and flow conditions (2 min). Diverse product manipulations demonstrate the synthetic potential of the disclosed method in accessing elusive trifluoromethoxylated bioactive ingredients.

High Site Selectivity in Electrophilic Aromatic Substitutions: Mechanism of C-H Thianthrenation.

The introduction of thianthrene as a linchpin has proven to be a versatile strategy for the C-H functionalization of aromatic compounds, featuring a broad scope and fast diversification. The synthesis of aryl thianthrenium salts has displayed an unusually high para regioselectivity, notably superior to those observed in halogenation or borylation reactions for various substrates. We report an experimental and computational study on the mechanism of aromatic C-H thianthrenation reactions, with an emphasis on the elucidation of the reactive species and the nature of the exquisite site selectivity. Mechanisms involving a direct attack of arene to the isolated O-trifluoracetylthianthrene S-oxide (TT+-TFA) or to the thianthrene dication (TT2+) via electron transfer under acidic conditions are identified. A reversible interconversion of the different Wheland-type intermediates before a subsequent, irreversible deprotonation is proposed to be responsible for the exceptional para selectivity of the reaction.

A Rational Approach to Organo-Photocatalysis: Novel Designs and Structure-Property Relationships.

Organic photocatalysts are emerging as viable and more sustainable tools than metal complexes. Recently, the field of organo-photocatalysis has experienced an explosion in terms of applications, redesign of well-established systems, and identification of novel scaffolds. A rational approach to the structural modification of the different photocatalysts is key to accessing unprecedented reactivity, while improving their catalytic performances. We herein discuss the concepts underpinning the scaffold modification of some of the most recently used photocatalysts and analyze how specific structural changes alter their physicochemical and redox properties.

EGFR amplification and outcome in a randomised phase III trial of chemotherapy alone or chemotherapy plus panitumumab for advanced gastro-oesophageal cancers.

OBJECTIVE: Epidermal growth factor receptor (EGFR) inhibition may be effective in biomarker-selected populations of advanced gastro-oesophageal adenocarcinoma (aGEA) patients. Here, we tested the association between outcome and EGFR copy number (CN) in pretreatment tissue and plasma cell-free DNA (cfDNA) of patients enrolled in a randomised first-line phase III clinical trial of chemotherapy or chemotherapy plus the anti-EGFR monoclonal antibody panitumumab in aGEA (NCT00824785). DESIGN: EGFR CN by either fluorescence in situ hybridisation (n=114) or digital-droplet PCR in tissues (n=250) and plasma cfDNAs (n=354) was available for 474 (86%) patients in the intention-to-treat (ITT) population. Tissue and plasma low-pass whole-genome sequencing was used to screen for coamplifications in receptor tyrosine kinases. Interaction between chemotherapy and EGFR inhibitors was modelled in patient-derived organoids (PDOs) from aGEA patients. RESULTS: EGFR amplification in cfDNA correlated with poor survival in the ITT population and similar trends were observed when the analysis was conducted in tissue and plasma by treatment arm. EGFR inhibition in combination with chemotherapy did not correlate with improved survival, even in patients with significant EGFR CN gains. Addition of anti-EGFR inhibitors to the chemotherapy agent epirubicin in PDOs, resulted in a paradoxical increase in viability and accelerated progression through the cell cycle, associated with p21 and cyclin B1 downregulation and cyclin E1 upregulation, selectively in organoids from EGFR-amplified aGEA. CONCLUSION: EGFR CN can be accurately measured in tissue and liquid biopsies and may be used for the selection of aGEA patients. EGFR inhibitors may antagonise the antitumour effect of anthracyclines with important implications for the design of future combinatorial trials.

Noise and charge discreteness as ultimate limit for the THz operation of ultra-small electronic devices.

To manufacture faster electron devices, the industry has entered into the nanoscale dimensions and Terahertz (THz) working frequencies. The discrete nature of the few electrons present simultaneously in the active region of ultra-small devices generate unavoidable fluctuations of the current at THz frequencies. The consequences of this noise remain unnoticed in the scientific community because its accurate understanding requires dealing with consecutive multi-time quantum measurements. Here, a modeling of the quantum measurement of the current at THz frequencies is introduced in terms of quantum (Bohmian) trajectories. With this new understanding, we develop an analytic model for THz noise as a function of the electron transit time and the sampling integration time, which finally determine the maximum device working frequency for digital applications. The model is confirmed by either semi-classical or full- quantum time-dependent Monte Carlo simulations. All these results show that intrinsic THz noise increases unlimitedly when the volume of the active region decreases. All attempts to minimize the low signal-to-noise ratio of these ultra-small devices to get effective THz working frequencies are incompatible with the basic elements of the scaling strategy. One can develop THz electron devices, but they cannot have ultra-small dimensions. Or, one can fabricate ultra-small electron devices, but they cannot be used for THz working frequencies.

Oncogenic driver mutations predict outcome in a cohort of head and neck squamous cell carcinoma (HNSCC) patients within a clinical trial.

234 diagnostic formalin-fixed paraffin-embedded (FFPE) blocks from homogeneously treated patients with locally advanced head and neck squamous cell carcinoma (HNSCC) within a multicentre phase III clinical trial were characterised. The mutational spectrum was examined by next generation sequencing in the 26 most frequent oncogenic drivers in cancer and correlated with treatment response and survival. Human papillomavirus (HPV) status was measured by p16INK4a immunohistochemistry in oropharyngeal tumours. Clinicopathological features and response to treatment were measured and compared with the sequencing results. The results indicated TP53 as the most mutated gene in locally advanced HNSCC. HPV-positive oropharyngeal tumours were less mutated than HPV-negative tumours in TP53 (p < 0.01). Mutational and HPV status influences patient survival, being mutated or HPV-negative tumours associated with poor overall survival (p < 0.05). No association was found between mutations and clinicopathological features. This study confirmed and expanded previously published genomic characterization data in HNSCC. Survival analysis showed that non-mutated HNSCC tumours associated with better prognosis and lack of mutations can be identified as an important biomarker in HNSCC. Frequent alterations in PI3K pathway in HPV-positive HNSCC could define a promising pathway for pharmacological intervention in this group of tumours.