Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning

Objective Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning. Design Training and evaluation of a neural network were performed using a total of n=1206 tissue sections with comprehensive multi-omic data from three independent datasets (training on FOCUS trial, n=278 patients; test on rectal cancer biopsies, GRAMPIAN cohort, n=144 patients; and The Cancer Genome Atlas (TCGA), n=430 patients). Ground truth CMS calls were ascertained by matching random forest and single sample predictions from CMS classifier. Results Image-based CMS (imCMS) accurately classified slides in unseen datasets from TCGA (n=431 slides, AUC)=0.84) and rectal cancer biopsies (n=265 slides, AUC=0.85). imCMS spatially resolved intratumoural heterogeneity and provided secondary calls correlating with bioinformatic prediction from molecular data. imCMS classified samples previously unclassifiable by RNA expression profiling, reproduced the expected correlations with genomic and epigenetic alterations and showed similar prognostic associations as transcriptomic CMS. Conclusion This study shows that a prediction of RNA expression classifiers can be made from H&E images, opening the door to simple, cheap and reliable biological stratification within routine workflows

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning

OBJECTIVE Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning. DESIGN Training and evaluation of a neural network were performed using a total of n=1206 tissue sections with comprehensive multi-omic data from three independent datasets (training on FOCUS trial, n=278 patients; test on rectal cancer biopsies, GRAMPIAN cohort, n=144 patients; and The Cancer Genome Atlas (TCGA), n=430 patients). Ground truth CMS calls were ascertained by matching random forest and single sample predictions from CMS classifier. RESULTS Image-based CMS (imCMS) accurately classified slides in unseen datasets from TCGA (n=431 slides, AUC)=0.84) and rectal cancer biopsies (n=265 slides, AUC=0.85). imCMS spatially resolved intratumoural heterogeneity and provided secondary calls correlating with bioinformatic prediction from molecular data. imCMS classified samples previously unclassifiable by RNA expression profiling, reproduced the expected correlations with genomic and epigenetic alterations and showed similar prognostic associations as transcriptomic CMS. CONCLUSION This study shows that a prediction of RNA expression classifiers can be made from H&E images, opening the door to simple, cheap and reliable biological stratification within routine workflows

Germline MBD4-deficiency causes a multi-tumor predisposition syndrome

We report an autosomal recessive, multi-organ tumor predisposition syndrome, caused by bi-allelic loss-of-function germline variants in the base excision repair (BER) gene MBD4. We identified five individuals with bi-allelic MBD4 variants within four families and these individuals had a personal and/or family history of adenomatous colorectal polyposis, acute myeloid leukemia, and uveal melanoma. MBD4 encodes a glycosylase involved in repair of G:T mismatches resulting from deamination of 5′-methylcytosine. The colorectal adenomas from MBD4-deficient individuals showed a mutator phenotype attributable to mutational signature SBS1, consistent with the function of MBD4. MBD4-deficient polyps harbored somatic mutations in similar driver genes to sporadic colorectal tumors, although AMER1 mutations were more common and KRAS mutations less frequent. Our findings expand the role of BER deficiencies in tumor predisposition. Inclusion of MBD4 in genetic testing for polyposis and multi-tumor phenotypes is warranted to improve disease management

Whole genome methylation analysis of nondysplastic barrett esophagus that progresses to invasive cancer

OBJECTIVE: To investigate differences in methylation between patients with nondysplastic Barrett esophagus who progress to invasive adenocarcinoma and those who do not.BACKGROUND: Identifying patients with nondysplastic Barrett esophagus who progress to invasive adenocarcinoma remains a challenge. Previous studies have demonstrated the potential utility of epigenetic markers for identifying this group.METHODS: A whole genome methylation interrogation using the Illumina HumanMethylation 450 array of patients with nondysplastic Barrett esophagus who either develop adenocarcinoma or remain static, with validation of findings by bisulfite pyrosequencing.RESULTS: In all, 12 patients with "progressive" versus 12 with "nonprogressive" nondysplastic Barrett esophagus were analyzed via methylation array. Forty-four methylation markers were identified that may be able to discriminate between nondysplastic Barrett esophagus that either progress to adenocarcinoma or remain static. Hypomethylation of the recently identified tumor suppressor OR3A4 (probe cg09890332) validated in a separate cohort of samples (median methylation in progressors 67.8% vs 96.7% in nonprogressors; P = 0.0001, z = 3.85, Wilcoxon rank-sum test) and was associated with the progression to adenocarcinoma. There were no differences in copy number between the 2 groups, but a global trend towards hypomethylation in the progressor group was observed.CONCLUSION: Hypomethylation of OR3A4 has the ability to risk stratify the patient with nondysplastic Barrett esophagus and may form the basis of a future surveillance program.</p

Mechanisms of synthetic lethality between BRCA1/2 and 53BP1 deficiencies and DNA polymerase theta targeting

Abstract A synthetic lethal relationship exists between disruption of polymerase theta (Polθ), and loss of either 53BP1 or homologous recombination (HR) proteins, including BRCA1; however, the mechanistic basis of these observations are unclear. Here we reveal two distinct mechanisms of Polθ synthetic lethality, identifying dual influences of 1) whether Polθ is lost or inhibited, and 2) the underlying susceptible genotype. Firstly, we find that the sensitivity of BRCA1/2- and 53BP1-deficient cells to Polθ loss, and 53BP1-deficient cells to Polθ inhibition (ART558) requires RAD52, and appropriate reduction of RAD52 can ameliorate these phenotypes. We show that in the absence of Polθ, RAD52 accumulations suppress ssDNA gap-filling in G2/M and encourage MRE11 nuclease accumulation. In contrast, the survival of BRCA1-deficient cells treated with Polθ inhibitor are not restored by RAD52 suppression, and ssDNA gap-filling is prevented by the chemically inhibited polymerase itself. These data define an additional role for Polθ, reveal the mechanism underlying synthetic lethality between 53BP1, BRCA1/2 and Polθ loss, and indicate genotype-dependent Polθ inhibitor mechanisms

Ultrarapid detection of SARS-CoV-2 RNA using a reverse transcription-free exponential amplification reaction, RTF-EXPAR.

A rapid isothermal method for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, is reported. The procedure uses an unprecedented reverse transcription-free (RTF) approach for converting genomic RNA into DNA. This involves the formation of an RNA/DNA heteroduplex whose selective cleavage generates a short DNA trigger strand, which is then rapidly amplified using the exponential amplification reaction (EXPAR). Deploying the RNA-to-DNA conversion and amplification stages of the RTF-EXPAR assay in a single step results in the detection, via a fluorescence read-out, of single figure copy numbers per microliter of SARS-CoV-2 RNA in under 10 min. In direct three-way comparison studies, the assay has been found to be faster than both RT-qPCR and reverse transcription loop-mediated isothermal amplification (RT-LAMP), while being just as sensitive. The assay protocol involves the use of standard laboratory equipment and is readily adaptable for the detection of other RNA-based pathogens

Patient Derived Organoids Confirm That PI3K/AKT Signalling Is an Escape Pathway for Radioresistance and a Target for Therapy in Rectal Cancer

OBJECTIVES: Partial or total resistance to preoperative chemoradiotherapy occurs in more than half of locally advanced rectal cancer patients. Several novel or repurposed drugs have been trialled to improve cancer cell sensitivity to radiotherapy, with limited success. We aimed to understand the mechanisms of resistance to chemoradiotherapy in rectal cancer using patient derived organoid models. DESIGN: To understand the mechanisms underlying this resistance, we compared the pre-treatment transcriptomes of patient-derived organoids (PDO) with measured radiotherapy sensitivity to identify biological pathways involved in radiation resistance coupled with single cell sequencing, genome wide CRISPR-Cas9 and targeted drug screens. RESULTS: RNA sequencing enrichment analysis revealed upregulation of PI3K/AKT/mTOR and epithelial mesenchymal transition pathway genes in radioresistant PDOs. Single-cell sequencing of pre & post-irradiation PDOs showed mTORC1 and PI3K/AKT upregulation, which was confirmed by a genome-wide CRSIPR-Cas9 knockout screen using irradiated colorectal cancer (CRC) cell lines. We then tested the efficiency of dual PI3K/mTOR inhibitors in improving cancer cell sensitivity to radiotherapy. After irradiation, significant AKT phosphorylation was detected (p=0.027) which was abrogated with dual PI3K/mTOR inhibitors and lead to significant radiosensitisation of the HCT116 cell line and radiation resistant PDO lines. CONCLUSIONS: The PI3K/AKT/mTOR pathway upregulation contributes to radioresistance and its targeted pharmacological inhibition leads to significant radiosensitisation in CRC organoids, making it a potential target for clinical trials

Rapid implementation and validation of a cold-chain free SARS-CoV-2 diagnostic testing workflow to support surge capacity.

BACKGROUND In January 2020 reports of unidentified severe respiratory illness were described in Wuhan, China. A rapid expansion in cases affecting most countries around the globe led to major changes in the way people live their daily lives. In the United Kingdom, the Department of Health and Social Care directed healthcare providers to establish additional resources to manage the anticipated surge in cases that could overwhelm the health services. A priority area was testing for SARS-CoV-2 RNA and its detection by qualitative RT-PCR. DESIGN A laboratory workflow twinning research environment with clinical laboratory capabilities was implemented and validated in the University of Birmingham within 4 days of the project initiation. The diagnostic capability was centred on an IVD CE-marked RT-PCR kit and designed to provide surge capacity to the nearby Queen Elizabeth Hospital. The service was initially tasked with testing healthcare workers (HCW) using throat swabs, and subsequently the process investigated the utility of using saliva as an alternative sample type. RESULTS Between the 8th April 2020 and the 30th April 2020, the laboratory tested a total of 1282 HCW for SARS-CoV-2 RNA in throat swabs. RNA was detected in 54 % of those who reported symptoms compatible with COVID-19, but in only 4% who were asymptomatic. CONCLUSION This capability was established rapidly and utilised a cold-chain free methodology, applicable to a wide range of settings, and which can provide surge capacity and support to clinical laboratories facing increasing pressure during periods of national crisis

Combined exome and transcriptome sequencing of non-muscle-invasive bladder cancer:associations between genomic changes, expression subtypes, and clinical outcomes

BACKGROUND: Three-quarters of bladder cancer patients present with early-stage disease (non-muscle-invasive bladder cancer, NMIBC, UICC TNM stages Ta, T1 and Tis); however, most next-generation sequencing studies to date have concentrated on later-stage disease (muscle-invasive BC, stages T2+). We used exome and transcriptome sequencing to comprehensively characterise NMIBCs of all grades and stages to identify prognostic genes and pathways that could facilitate treatment decisions. Tumour grading is based upon microscopy and cellular appearances (grade 1 BCs are less aggressive, and grade 3 BCs are most aggressive), and we chose to also focus on the most clinically complex NMIBC subgroup, those patients with grade 3 pathological stage T1 (G3 pT1) disease. METHODS: Whole-exome and RNA sequencing were performed in total on 96 primary NMIBCs including 22 G1 pTa, 14 G3 pTa and 53 G3 pT1s, with both exome and RNA sequencing data generated from 75 of these individual samples. Associations between genomic alterations, expression profiles and progression-free survival (PFS) were investigated. RESULTS: NMIBCs clustered into 3 expression subtypes with different somatic alteration characteristics. Amplifications of ARNT and ERBB2 were significant indicators of worse PFS across all NMIBCs. High APOBEC mutagenesis and high tumour mutation burden were both potential indicators of better PFS in G3pT1 NMIBCs. The expression of individual genes was not prognostic in BCG-treated G3pT1 NMIBCs; however, downregulated interferon-alpha and gamma response pathways were significantly associated with worse PFS (adjusted p-value < 0.005). CONCLUSIONS: Multi-omic data may facilitate better prognostication and selection of therapeutic interventions in patients with G3pT1 NMIBC. These findings demonstrate the potential for improving the management of high-risk NMIBC patients and warrant further prospective validation