Electrospinning Nonspinnable Sols to Ceramic Fibers and Springs.

Electrospinning has been applied to produce ceramic fibers using sol gel-based spinning solutions consisting of ceramic precursors, a solvent, and a polymer to control the viscosity of the solution. However, the addition of polymers to the spinning solution makes the process more complex, increases the processing time, and results in porous mechanically weak ceramic fibers. Herein, we develop a coelectrospinning technique, where a nonspinnable sol (<10 mPa s) consisting of only the ceramic precursor(s) and solvent(s) is encapsulated inside a polymeric shell, forming core-shell precursor fibers that are further calcined into ceramic fibers with reduced porosity, decreased surface defects, uniform crystal packing, and controlled diameters. We demonstrate the versatility of this method by applying it to a series of nonspinnable sols and creating high-quality ceramic fibers containing TiO2, ZrO2, SiO2, and Al2O3. The polycrystalline TiO2 fibers possess excellent flexibility and a high Young's modulus reaching 54.3 MPa, solving the extreme brittleness problem of the previously reported TiO2 fibers. The single-component ZrO2 fibers exhibit a Young's modulus and toughness of 130.5 MPa and 11.9 KJ/m3, respectively, significantly superior to the counterparts prepared by conventional sol-gel electrospinning. We also report the creation of ceramic fibers in micro- and nanospring morphologies and examine the formation mechanisms using thermomechanical simulations. The fiber assemblies constructed by the helical fibers exhibit a density-normalized toughness of 3.5-5 times that of the straight fibers due to improved fracture strain. This work expands the selection of the electrospinning solution and enables the development of ceramic fibers with more attractive properties.

Nanoscale Rheology: Dynamic Mechanical Analysis over a Broad and Continuous Frequency Range Using Photothermal Actuation Atomic Force Microscopy.

Polymeric materials are widely used in industries ranging from automotive to biomedical. Their mechanical properties play a crucial role in their application and function and arise from the nanoscale structures and interactions of their constitutive polymer molecules. Polymeric materials behave viscoelastically, i.e., their mechanical responses depend on the time scale of the measurements; quantifying these time-dependent rheological properties at the nanoscale is relevant to develop, for example, accurate models and simulations of those materials, which are needed for advanced industrial applications. In this paper, an atomic force microscopy (AFM) method based on the photothermal actuation of an AFM cantilever is developed to quantify the nanoscale loss tangent, storage modulus, and loss modulus of polymeric materials. The method is then validated on styrene-butadiene rubber (SBR), demonstrating the method's ability to quantify nanoscale viscoelasticity over a continuous frequency range up to 5 orders of magnitude (0.2-20,200 Hz). Furthermore, this method is combined with AFM viscoelastic mapping obtained with amplitude modulation-frequency modulation (AM-FM) AFM, enabling the extension of viscoelastic quantification over an even broader frequency range and demonstrating that the novel technique synergizes with preexisting AFM techniques for quantitative measurement of viscoelastic properties. The method presented here introduces a way to characterize the viscoelasticity of polymeric materials and soft and biological matter in general at the nanoscale for any application.

End-to-end prognostication in colorectal cancer by deep learning: a retrospective, multicentre study.

BACKGROUND: Precise prognosis prediction in patients with colorectal cancer (ie, forecasting survival) is pivotal for individualised treatment and care. Histopathological tissue slides of colorectal cancer specimens contain rich prognostically relevant information. However, existing studies do not have multicentre external validation with real-world sample processing protocols, and algorithms are not yet widely used in clinical routine. METHODS: In this retrospective, multicentre study, we collected tissue samples from four groups of patients with resected colorectal cancer from Australia, Germany, and the USA. We developed and externally validated a deep learning-based prognostic-stratification system for automatic prediction of overall and cancer-specific survival in patients with resected colorectal cancer. We used the model-predicted risk scores to stratify patients into different risk groups and compared survival outcomes between these groups. Additionally, we evaluated the prognostic value of these risk groups after adjusting for established prognostic variables. FINDINGS: We trained and validated our model on a total of 4428 patients. We found that patients could be divided into high-risk and low-risk groups on the basis of the deep learning-based risk score. On the internal test set, the group with a high-risk score had a worse prognosis than the group with a low-risk score, as reflected by a hazard ratio (HR) of 4·50 (95% CI 3·33-6·09) for overall survival and 8·35 (5·06-13·78) for disease-specific survival (DSS). We found consistent performance across three large external test sets. In a test set of 1395 patients, the high-risk group had a lower DSS than the low-risk group, with an HR of 3·08 (2·44-3·89). In two additional test sets, the HRs for DSS were 2·23 (1·23-4·04) and 3·07 (1·78-5·3). We showed that the prognostic value of the deep learning-based risk score is independent of established clinical risk factors. INTERPRETATION: Our findings indicate that attention-based self-supervised deep learning can robustly offer a prognosis on clinical outcomes in patients with colorectal cancer, generalising across different populations and serving as a potentially new prognostic tool in clinical decision making for colorectal cancer management. We release all source codes and trained models under an open-source licence, allowing other researchers to reuse and build upon our work. FUNDING: The German Federal Ministry of Health, the Max-Eder-Programme of German Cancer Aid, the German Federal Ministry of Education and Research, the German Academic Exchange Service, and the EU.

Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study.

Deep learning (DL) can accelerate the prediction of prognostic biomarkers from routine pathology slides in colorectal cancer (CRC). However, current approaches rely on convolutional neural networks (CNNs) and have mostly been validated on small patient cohorts. Here, we develop a new transformer-based pipeline for end-to-end biomarker prediction from pathology slides by combining a pre-trained transformer encoder with a transformer network for patch aggregation. Our transformer-based approach substantially improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training and evaluating on a large multicenter cohort of over 13,000 patients from 16 colorectal cancer cohorts, we achieve a sensitivity of 0.99 with a negative predictive value of over 0.99 for prediction of microsatellite instability (MSI) on surgical resection specimens. We demonstrate that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem.

Oncomicrobial Community Profiling Identifies Clinicomolecular and Prognostic Subtypes of Colorectal Cancer.

BACKGROUND & AIMS: Dysbiosis of gut microbiota is linked to the development of colorectal cancer (CRC). However, microbiota-based stratification of CRC tissue and how this relates to clinicomolecular characteristics and prognosis remains to be clarified. METHODS: Tumor and normal mucosa from 423 patients with stage I to IV CRC were profiled by bacterial 16S rRNA gene sequencing. Tumors were characterized for microsatellite instability (MSI), CpG island methylator phenotype (CIMP), APC, BRAF, KRAS, PIK3CA, FBXW7, SMAD4, and TP53 mutations, subsets for chromosome instability (CIN), mutation signatures, and consensus molecular subtypes (CMS). Microbial clusters were validated in an independent cohort of 293 stage II/III tumors. RESULTS: Tumors reproducibly stratified into 3 oncomicrobial community subtypes (OCSs) with distinguishing features: OCS1 (Fusobacterium/oral pathogens, proteolytic, 21%), right-sided, high-grade, MSI-high, CIMP-positive, CMS1, BRAF V600E, and FBXW7 mutated; OCS2 (Firmicutes/Bacteroidetes, saccharolytic, 44%), and OCS3 (Escherichia/Pseudescherichia/Shigella, fatty acid ß-oxidation, 35%) both left-sided and exhibiting CIN. OCS1 was associated with MSI-related mutation signatures (SBS15, SBS20, ID2, and ID7) and OCS2 and OCS3 with SBS18 related to damage by reactive oxygen species. Among stage II/III patients, OCS1 and OCS3 both had poorer overall survival compared with OCS2 for microsatellite stable tumors (multivariate hazard ratio [HR], 1.85; 95% confidence interval [CI], 1.15-2.99; P = .012; and HR, 1.52; 95% CI 1.01-2.29; P = .044, respectively) and left-sided tumors (multivariate HR, 2.66; 95% CI, 1.45-4.86; P = .002; and HR, 1.76; 95% CI, 1.03-3.02; P = .039, respectively). CONCLUSIONS: OCS classification stratified CRCs into 3 distinct subgroups with different clinicomolecular features and outcomes. Our findings provide a framework for a microbiota-based stratification of CRC to refine prognostication and to inform the development of microbiota-targeted interventions.

Intermediate-phase engineering via dimethylammonium cation additive for stable perovskite solar cells.

Achieving the long-term stability of perovskite solar cells is arguably the most important challenge required to enable widespread commercialization. Understanding the perovskite crystallization process and its direct impact on device stability is critical to achieving this goal. The commonly employed dimethyl-formamide/dimethyl-sulfoxide solvent preparation method results in a poor crystal quality and microstructure of the polycrystalline perovskite films. In this work, we introduce a high-temperature dimethyl-sulfoxide-free processing method that utilizes dimethylammonium chloride as an additive to control the perovskite intermediate precursor phases. By controlling the crystallization sequence, we tune the grain size, texturing, orientation (corner-up versus face-up) and crystallinity of the formamidinium (FA)/caesium (FA)yCs1-yPb(IxBr1-x)3 perovskite system. A population of encapsulated devices showed improved operational stability, with a median T80 lifetime (the time over which the device power conversion efficiency decreases to 80% of its initial value) for the steady-state power conversion efficiency of 1,190 hours, and a champion device showed a T80 of 1,410 hours, under simulated sunlight at 65 °C in air, under open-circuit conditions. This work highlights the importance of material quality in achieving the long-term operational stability of perovskite optoelectronic devices.

Survival prediction in triple negative breast cancer using multiple instance learning of histopathological images.

Computational pathology is a rapidly expanding area for research due to the current global transformation of histopathology through the adoption of digital workflows. Survival prediction of breast cancer patients is an important task that currently depends on histopathology assessment of cancer morphological features, immunohistochemical biomarker expression and patient clinical findings. To facilitate the manual process of survival risk prediction, we developed a computational pathology framework for survival prediction using digitally scanned haematoxylin and eosin-stained tissue microarray images of clinically aggressive triple negative breast cancer. Our results show that the model can produce an average concordance index of 0.616. Our model predictions are analysed for independent prognostic significance in univariate analysis (hazard ratio = 3.12, 95% confidence interval [1.69,5.75], p < 0.005) and multivariate analysis using clinicopathological data (hazard ratio = 2.68, 95% confidence interval [1.44,4.99], p < 0.005). Through qualitative analysis of heatmaps generated from our model, an expert pathologist is able to associate tissue features highlighted in the attention heatmaps of high-risk predictions with morphological features associated with more aggressive behaviour such as low levels of tumour infiltrating lymphocytes, stroma rich tissues and high-grade invasive carcinoma, providing explainability of our method for triple negative breast cancer.

Characterisation of factors contributing to the performance of nonwoven fibrous matrices as substrates for adenovirus vectored vaccine stabilisation.

Adenovirus vectors offer a platform technology for vaccine development. The value of the platform has been proven during the COVID-19 pandemic. Although good stability at 2-8 °C is an advantage of the platform, non-cold-chain distribution would have substantial advantages, in particular in low-income countries. We have previously reported a novel, potentially less expensive thermostabilisation approach using a combination of simple sugars and glass micro-fibrous matrix, achieving excellent recovery of adenovirus-vectored vaccines after storage at temperatures as high as 45 °C. This matrix is, however, prone to fragmentation and so not suitable for clinical translation. Here, we report an investigation of alternative fibrous matrices which might be suitable for clinical use. A number of commercially-available matrices permitted good protein recovery, quality of sugar glass and moisture content of the dried product but did not achieve the thermostabilisation performance of the original glass fibre matrix. We therefore further investigated physical and chemical characteristics of the glass fibre matrix and its components, finding that the polyvinyl alcohol present in the glass fibre matrix assists vaccine stability. This finding enabled us to identify a potentially biocompatible matrix with encouraging performance. We discuss remaining challenges for transfer of the technology into clinical use, including reliability of process performance.

Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks.

Traditional image-based survival prediction models rely on discriminative patch labeling which make those methods not scalable to extend to large datasets. Recent studies have shown Multiple Instance Learning (MIL) framework is useful for histopathological images when no annotations are available in classification task. Different to the current image-based survival models that limit to key patches or clusters derived from Whole Slide Images (WSIs), we propose Deep Attention Multiple Instance Survival Learning (DeepAttnMISL) by introducing both siamese MI-FCN and attention-based MIL pooling to efficiently learn imaging features from the WSI and then aggregate WSI-level information to patient-level. Attention-based aggregation is more flexible and adaptive than aggregation techniques in recent survival models. We evaluated our methods on two large cancer whole slide images datasets and our results suggest that the proposed approach is more effective and suitable for large datasets and has better interpretability in locating important patterns and features that contribute to accurate cancer survival predictions. The proposed framework can also be used to assess individual patient's risk and thus assisting in delivering personalized medicine.

Generation of High Dose Inhalable Effervescent Dispersions against Pseudomonas aeruginosa Biofilms.

PURPOSE: Novel particle engineering approach was used in this study to generate high dose inhalable effervescent particles with synergistic effects against Pseudomonas aeruginosa biofilms. METHODS: Spray dried co-amorphous salt of ciprofloxacin (CFX) and tartaric acid (TA) was prepared and coated with external layer of sodium bicarbonate and silica coated silver nanobeads. Design of experiments (DOE) was used to optimize physicochemical properties of particles for enhanced lung deposition. RESULTS: Generated particles were co-amorphous CFX/TA showing that CFX lost its zwitterionic form and exhibiting distinct properties to CFX/HCl as assessed by FTIR and thermal analysis. Particles exhibited mass mean aerodynamic diameter (MMAD) of 3.3 µm, emitted dose of 78% and fine particle dose of 85%. Particles were further evaluated via antimicrobial assessment of minimum inhibitory concentrations (MIC) and minimum biofilm eradication concentration (MBEC). MIC and MBEC results showed that the hybrid particles were around 3-5 times more effective when compared to CFX signifying that synergistic effect was achieved. Diffusing wave spectroscopy results showed that the silver containing particles had a disruptive effect on rheological properties as opposed to silver free particles. CONCLUSIONS: Overall, these results showed the potential to use particle engineering to generate particles that are highly disruptive of bacterial biofilms.

Tumour infiltrating lymphocyte status is superior to histological grade, DNA mismatch repair and BRAF mutation for prognosis of colorectal adenocarcinomas with mucinous differentiation.

Mucinous colorectal adenocarcinoma (CRC) is conventionally defined by extracellular mucin comprising >50% of the tumour area, while tumours with ≤50% mucin are designated as having a mucinous component. However, these definitions are largely arbitrary and comparisons of clinico-molecular features and outcomes by proportion of mucinous component are limited. A cohort of 1643 patients with stage II/III cancer was examined for tumour mucinous component, DNA mismatch repair (MMR) status, BRAF mutation and tumour infiltrating lymphocytes (TILs). Tumours with ≤50% mucinous component exhibited similar characteristics as mucinous tumours, including association with female gender, proximal location, high grade, TIL-high, defective MMR (dMMR) and BRAF mutation. Proportion of mucinous component did not stratify disease-free survival (DFS). In univariate analysis dMMR status, but not histological grade, stratified survival for mucinous and mucinous component tumours; however, in multivariate analysis dMMR status was not an independent predictor. BRAF mutation prognostic value depended on mucinous differentiation and MMR status, with poor prognosis limited to non-mucinous pMMR tumours (HR 2.61, 95% CI 1.69-4.03; p < 0.001). TIL status was a strong independent predictor of DFS in mucinous/mucinous component tumours (HR 0.40, 95% CI 0.23-0.67; p < 0.001), and a superior predictor of prognosis compared with histological grade, MMR and BRAF mutation. Mucinous component and mucinous stage II/III CRCs exhibit clinico-molecular resemblances, with histological grade and BRAF mutation lacking prognostic value. Prognosis for these tumours was instead strongly associated with TIL status, with the most favourable outcomes in TIL-high dMMR tumours, whilst TIL-low tumours had poor outcomes irrespective of MMR status.

Scarcity of Recurrent Regulatory Driver Mutations in Colorectal Cancer Revealed by Targeted Deep Sequencing.

BACKGROUND: Genetic testing of cancer samples primarily focuses on protein-coding regions, despite most mutations arising in noncoding DNA. Noncoding mutations can be pathogenic if they disrupt gene regulation, but the benefits of assessing promoter mutations in driver genes by panel testing has not yet been established. This is especially the case in colorectal cancer, for which few putative driver variants at regulatory elements have been reported. METHODS: We designed a unique target capture sequencing panel of 39 colorectal cancer driver genes and their promoters, together with more than 35 megabases of regulatory elements focusing on gene promoters. Using this panel, we sequenced 95 colorectal cancer and matched normal samples at high depth, averaging 170× and 82× coverage, respectively. RESULTS: Our target capture sequencing design enabled improved coverage and variant detection across captured regions. We found cases with hereditary defects in mismatch and base excision repair due to deleterious germline coding variants, and we identified mutational spectra consistent with these repair deficiencies. Focusing on gene promoters and other regulatory regions, we found little evidence for base or region-specific recurrence of functional somatic mutations. Promoter elements, including TERT, harbored few mutations, with none showing strong functional evidence. Recurrent regulatory mutations were rare in our sequenced regions in colorectal cancer, though we highlight some candidate mutations for future functional studies. CONCLUSIONS: Our study supports recent findings that regulatory driver mutations are rare in many cancer types and suggests that the inclusion of promoter regions into cancer panel testing is currently likely to have limited clinical utility in colorectal cancer.

Evaluation of the transferability of survival calculators for stage II/III colon cancer across healthcare systems.

Adjuvant! Online Inc (A!O), the Memorial Sloan Kettering Cancer Center (MSKCC), MD Anderson (MDA) and Mayo Clinic (MC) provide calculators to predict survival probabilities for patients with resected early-stage colon cancer, trained on data from United States (US) patient cohorts or patients enrolled in international clinical trials. Limited data exist on the transferability of calculators across healthcare systems. Calculator transferability to Australian community practice was evaluated for 1,401 stage II/III patients. Calibration and discrimination were assessed for overall (OS), cancer-specific (CSS) or recurrence-free survival (RFS). The US patient cohort-based calculators, A!O, MSKCC and MDA, significantly overestimated risks of recurrence and death in Australian patients, with 5-year OS, CSS and RFS prediction differences of -6.5% to -9.9%, -9.1% to -14.4% and - 3.8% to -6.8%, respectively (p < 0.001). Significant heterogeneity in calibration was observed for subgroups by tumor stage and treatment, age, gender, tumor location, ECOG and ASA score. Calibration appeared acceptable for the clinical trial patient-based MC calculator, but restricted tool applicability (stage III patients, ≥12 examined lymph nodes, receiving adjuvant treatment) limited the sample size. Compared to AJCC 7th edition tumor staging, calculators showed improved discrimination for OS, but no improvement for CSS and RFS. In conclusion, deficiencies in calibration limited transferability of US patient cohort-based survival calculators for early-stage colon cancer to the setting of Australian community practice. Our results demonstrate the utility for multi-feature survival calculators to improve OS predictions but highlight the importance for performance assessment of tools prior to implementation in an external health care setting.

Lymphocytic response to tumour and deficient DNA mismatch repair identify subtypes of stage II/III colorectal cancer associated with patient outcomes.

OBJECTIVE: Tumour-infiltrating lymphocyte (TIL) response and deficient DNA mismatch repair (dMMR) are determinants of prognosis in colorectal cancer. Although highly correlated, evidence suggests that these are independent predictors of outcome. However, the prognostic significance of combined TIL/MMR classification and how this compares to the major genomic and transcriptomic subtypes remain unclear. DESIGN: A prospective cohort of 1265 patients with stage II/III cancer was examined for TIL/MMR status and BRAF/KRAS mutations. Consensus molecular subtype (CMS) status was determined for 142 cases. Associations with 5-year disease-free survival (DFS) were evaluated and validated in an independent cohort of 602 patients. RESULTS: Tumours were categorised into four subtypes based on TIL and MMR status: TIL-low/proficient-MMR (pMMR) (61.3% of cases), TIL-high/pMMR (14.8%), TIL-low/dMMR (8.6%) and TIL-high/dMMR (15.2%). Compared with TIL-high/dMMR tumours with the most favourable prognosis, both TIL-low/dMMR (HR=3.53; 95% CI=1.88 to 6.64; Pmultivariate<0.001) and TIL-low/pMMR tumours (HR=2.67; 95% CI=1.47 to 4.84; Pmultivariate=0.001) showed poor DFS. Outcomes of patients with TIL-low/dMMR and TIL-low/pMMR tumours were similar. TIL-high/pMMR tumours showed intermediate survival rates. These findings were validated in an independent cohort. TIL/MMR status was a more significant predictor of prognosis than National Comprehensive Cancer Network high-risk features and was a superior predictor of prognosis compared with genomic (dMMR, pMMR/BRAFwt /KRASwt , pMMR/BRAFmut /KRASwt , pMMR/BRAFwt /KRASmut ) and transcriptomic (CMS 1-4) subtypes. CONCLUSION: TIL/MMR classification identified subtypes of stage II/III colorectal cancer associated with different outcomes. Although dMMR status is generally considered a marker of good prognosis, we found this to be dependent on the presence of TILs. Prognostication based on TIL/MMR subtypes was superior compared with histopathological, genomic and transcriptomic subtypes.

Differential Scanning Calorimetry of Native Silk Feedstock.

Native silk proteins, extracted directly from the silk gland prior to spinning, offer access to a naturally hydrated protein that has undergone little to no processing. Combined with differential scanning calorimetry (DSC), it is possible to probe the thermal stability and hydration status of silk and thus investigate its denaturation and solidification, echoing that of the natural spinning process. It is found that native silk is stable between -10 °C and 55 °C, and both the high-temperature enthalpy of denaturation (measured via modulated temperature DSC) and a newly reported low-temperature ice-melting transition may serve as useful quality indicators in the future for artificial silks. Finally, compared to albumin, silk's denaturation enthalpy is much lower than expected, which is interpreted within a recently proposed entropic desolvation framework which can serve to unveil the low-energy aquamelt processing pathway.

Mutation burden and other molecular markers of prognosis in colorectal cancer treated with curative intent: results from the QUASAR 2 clinical trial and an Australian community-based series.

BACKGROUND: Molecular indicators of colorectal cancer prognosis have been assessed in several studies, but most analyses have been restricted to a handful of markers. We aimed to identify prognostic biomarkers for colorectal cancer by sequencing panels of multiple driver genes. METHODS: In stage II or III colorectal cancers from the QUASAR 2 open-label randomised phase 3 clinical trial and an Australian community-based series, we used targeted next-generation sequencing of 82 and 113 genes, respectively, including the main colorectal cancer drivers. We investigated molecular pathways of tumorigenesis, and analysed individual driver gene mutations, combinations of mutations, or global measures such as microsatellite instability (MSI) and mutation burden (total number of non-synonymous mutations and coding indels) for associations with relapse-free survival in univariable and multivariable models, principally Cox proportional hazards models. FINDINGS: In QUASAR 2 (511 tumours), TP53, KRAS, BRAF, and GNAS mutations were independently associated with shorter relapse-free survival (p<0·035 in all cases), and total somatic mutation burden with longer survival (hazard ratio [HR] 0·81 [95% CI 0·68-0·96]; p=0·014). MSI was not independently associated with survival (HR 1·12 [95% CI 0·57-2·19]; p=0·75). We successfully validated these associations in the Australian sample set (296 tumours). In a combined analysis of both the QUASAR 2 and the Australian sample sets, mutation burden was also associated with longer survival (HR 0·84 [95% CI 0·74-0·94]; p=0·004) after exclusion of MSI-positive and POLE mutant tumours. In an extended analysis of 1732 QUASAR 2 and Australian colorectal cancers for which KRAS, BRAF, and MSI status were available, KRAS and BRAF mutations were specifically associated with poor prognosis in MSI-negative cancers. MSI-positive cancers with KRAS or BRAF mutations had better prognosis than MSI-negative cancers that were wild-type for KRAS or BRAF. Mutations in the genes NF1 and NRAS from the MAPK pathway co-occurred, and mutations in the DNA damage-response genes TP53 and ATM were mutually exclusive. We compared a prognostic model based on the gold standard of clinicopathological variables and MSI with our new model incorporating clinicopathological variables, mutation burden, and driver mutations in KRAS, BRAF, and TP53. In both QUASAR 2 and the Australian cohort, our new model was significantly better (p=0·00004 and p=0·0057, respectively, based on a likelihood ratio test). INTERPRETATION: Multigene panels identified two previously unreported prognostic associations in colorectal cancer involving TP53 mutation and total mutation burden, and confirmed associations with KRAS and BRAF. Even a modest-sized gene panel can provide important information for use in clinical practice and outperform MSI-based prognostic models. FUNDING: UK Technology Strategy Board, National Institute for Health Research Oxford Biomedical Research Centre, Cancer Australia Project, Cancer Council Victoria, Ludwig Institute for Cancer Research, Victorian Government.

MACROD2 Haploinsufficiency Impairs Catalytic Activity of PARP1 and Promotes Chromosome Instability and Growth of Intestinal Tumors.

ADP-ribosylation is an important posttranslational protein modification that regulates diverse biological processes, controlled by dedicated transferases and hydrolases. Here, we show that frequent deletions (∼30%) of the MACROD2 mono-ADP-ribosylhydrolase locus in human colorectal cancer cause impaired PARP1 transferase activity in a gene dosage-dependent manner. MACROD2 haploinsufficiency alters DNA repair and sensitivity to DNA damage and results in chromosome instability. Heterozygous and homozygous depletion of Macrod2 enhances intestinal tumorigenesis in ApcMin/+ mice and the growth of human colorectal cancer xenografts. MACROD2 deletion in sporadic colorectal cancer is associated with the extent of chromosome instability, independent of clinical parameters and other known genetic drivers. We conclude that MACROD2 acts as a haploinsufficient tumor suppressor, with loss of function promoting chromosome instability, thereby driving cancer evolution.Significance: Chromosome instability (CIN) is a hallmark of cancer. We identify MACROD2 deletion as a cause of CIN in human colorectal cancer. MACROD2 loss causes repression of PARP1 activity, impairing DNA repair. MACROD2 haploinsufficiency promotes CIN and intestinal tumor growth. Our results reveal MACROD2 as a major caretaker tumor suppressor gene. Cancer Discov; 8(8); 988-1005. ©2018 AACR.See related commentary by Jin and Burkard, p. 921This article is highlighted in the In This Issue feature, p. 899.

Disruption of a -35 kb Enhancer Impairs CTCF Binding and MLH1 Expression in Colorectal Cells.

Purpose:MLH1 is a major tumor suppressor gene involved in the pathogenesis of Lynch syndrome and various sporadic cancers. Despite their potential pathogenic importance, genomic regions capable of regulating MLH1 expression over long distances have yet to be identified.Experimental Design: Here, we use chromosome conformation capture (3C) to screen a 650-kb region flanking the MLH1 locus to identify interactions between the MLH1 promoter and distal regions in MLH1-expressing and nonexpressing cells. Putative enhancers were functionally validated using luciferase reporter assays, chromatin immunoprecipitation, and CRISPR-Cas9-mediated deletion of endogenous regions. To evaluate whether germline variants in the enhancer might contribute to impaired MLH1 expression in patients with suspected Lynch syndrome, we also screened germline DNA from a cohort of 74 patients with no known coding mutations or epimutations at the MLH1 promoter.Results: A 1.8-kb DNA fragment, 35 kb upstream of the MLH1 transcription start site enhances MLH1 gene expression in colorectal cells. The enhancer was bound by CTCF and CRISPR-Cas9-mediated deletion of a core binding region impairs endogenous MLH1 expression. A total of 5.4% of suspected Lynch syndrome patients have a rare single-nucleotide variant (G > A; rs143969848; 2.5% in gnomAD European, non-Finnish) within a highly conserved CTCF-binding motif, which disrupts enhancer activity in SW620 colorectal carcinoma cells.Conclusions: A CTCF-bound region within the MLH1-35 enhancer regulates MLH1 expression in colorectal cells and is worthy of scrutiny in future genetic screening strategies for suspected Lynch syndrome associated with loss of MLH1 expression. Clin Cancer Res; 24(18); 4602-11. ©2018 AACR.

Analysing the structure and glass transition behaviour of silks for archaeology and conservation.

Silk is an iconic material in many cultures. Silk archaeology and conservation is affected by silk production technology as well as subsequent environmental effects such as humidity, temperature, UV radiation and ageing. The complex interactions and various effects on silk materials affect the practical use of silk, for example, in the conservation of ancient manuscripts. This study examines the various influences of silk provenance and processing, adhesive coatings and chemical treatments as well as natural and artificial ageing of the silk material. We use infrared spectroscopy (FTIR) and dynamic mechanical thermal analysis to investigate the glass transition behaviours in a range of archaeological and control silk samples. This allows us to establish structural differences in century-old museum silks and predict the effects of silk ageing and degradation.