Mutational signature in colorectal cancer caused by genotoxic pks+ E. coli.

Various species of the intestinal microbiota have been associated with the development of colorectal cancer1,2, but it has not been demonstrated that bacteria have a direct role in the occurrence of oncogenic mutations. Escherichia coli can carry the pathogenicity island pks, which encodes a set of enzymes that synthesize colibactin3. This compound is believed to alkylate DNA on adenine residues4,5 and induces double-strand breaks in cultured cells3. Here we expose human intestinal organoids to genotoxic pks+ E. coli by repeated luminal injection over five months. Whole-genome sequencing of clonal organoids before and after this exposure revealed a distinct mutational signature that was absent from organoids injected with isogenic pks-mutant bacteria. The same mutational signature was detected in a subset of 5,876 human cancer genomes from two independent cohorts, predominantly in colorectal cancer. Our study describes a distinct mutational signature in colorectal cancer and implies that the underlying mutational process results directly from past exposure to bacteria carrying the colibactin-producing pks pathogenicity island.

Analysis of an Indian colorectal cancer faecal microbiome collection demonstrates universal colorectal cancer-associated patterns, but closest correlation with other Indian cohorts.

It is increasingly being recognised that changes in the gut microbiome have either a causative or associative relationship with colorectal cancer (CRC). However, most of this research has been carried out in a small number of developed countries with high CRC incidence. It is unknown if lower incidence countries such as India have similar microbial associations.Having previously established protocols to facilitate microbiome research in regions with developing research infrastructure, we have now collected and sequenced microbial samples from a larger cohort study of 46 Indian CRC patients and 43 healthy volunteers.When comparing to previous global collections, these samples resemble other Asian samples, with relatively high levels of Prevotella. Predicting cancer status between cohorts shows good concordance. When compared to a previous collection of Indian CRC patients, there was similar concordance, despite different sequencing technologies between cohorts.These results show that there does seem to be a global CRC microbiome, and that some inference between studies is reasonable. However, we also demonstrate that there is definite regional variation, with more similarities between location-matched comparisons. This emphasises the importance of developing protocols and advancing infrastructure to allow as many countries as possible to contribute to microbiome studies of their own populations.

Characterisation of dysplastic liver nodules using low-pass DNA sequencing and detection of chromosome arm-level abnormalities in blood-derived cell-free DNA.

High-grade dysplasia carries significant risk of transformation to hepatocellular carcinoma (HCC). Despite this, at the current standard of care, all non-malignant hepatic nodules including high-grade dysplastic nodules are managed similarly. This is partly related to difficulties in distinguishing high-risk pathology in the liver. We aimed to identify chromosome arm-level somatic copy number alterations (SCNAs) that characterise the transition of liver nodules along the cirrhosis-dysplasia-carcinoma axis. We validated our findings on an independent cohort using blood-derived cell-free DNA. A repository of non-cancer DNA sequences obtained from patients with HCC (n = 389) was analysed to generate cut-off thresholds aiming to minimise false-positive SCNAs. Tissue samples representing stages from the multistep process of hepatocarcinogenesis (n = 184) were subjected to low-pass whole genome sequencing. Chromosome arm-level SCNAs were identified in liver cirrhosis, dysplastic nodules, and HCC to assess their discriminative capacity. Samples positive for 1q+ or 8q+ arm-level duplications were likely to be either HCC or high-grade dysplastic nodules as opposed to low-grade dysplastic nodules or cirrhotic tissue with an odds ratio (OR) of 35.5 (95% CI 11.5-110) and 16 (95% CI 6.4-40.2), respectively (p < 0.0001). In an independent cohort of patients recruited from Nottingham, UK, at least two out of four alterations (1q+, 4q-, 8p-, and 8q+) were detectable in blood-derived cell-free DNA of patients with HCC (n = 22) but none of the control patients with liver cirrhosis (n = 9). Arm-level SCNAs on 1q+ or 8q+ are associated with high-risk liver pathology. These can be detected using low-pass sequencing of cell-free DNA isolated from blood, which may be a future early cancer screening tool for patients with liver cirrhosis. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Sparse modelling of cancer patients' survival based on genomic copy number alterations.

Copy number alterations (CNA) are structural variation in the genome, in which some regions exhibit more or less than the normal two chromosomal copies. This genomic CNA profile provides critical information in tumour progression and is therefore informative for patients' survival. It is currently a statistical challenge to model patients' survival using their genomic CNA profiles while at the same time identify regions in the genome that are associated with patients' survival. Some methods have been proposed, including Cox proportional hazard (PH) model with ridge, lasso, or elastic net penalties. However, these methods do not take the general dependencies between genomic regions into account and produce results that are difficult to interpret. In this paper, we extend the elastic net penalty by introducing additional penalty that takes into account general dependencies between genomic regions. This new model produces smooth parameter estimates while simultaneously performs variable selection via sparse solution. The results indicate that the proposed method shows a better prediction performance than other models in our simulation study, while enabling us to investigate regions in the genome that are associated with the patients' survival with sensible interpretation. We illustrate the method using a real dataset from a lung cancer cohort and simulated data.

Luminal Bioavailability of Orally Administered ω-3 PUFAs in the Distal Small Intestine, and Associated Changes to the Ileal Microbiome, in Humans with a Temporary Ileostomy.

BACKGROUND: Oral administration of purified omega-3 (ω-3) PUFAs is associated with changes to the fecal microbiome. However, it is not known whether this effect is associated with increased PUFA concentrations in the gut. OBJECTIVES: We investigated the luminal bioavailability of oral ω-3 PUFAs (daily dose 1 g EPA and 1g DHA free fatty acid equivalents as triglycerides in soft-gel capsules, twice daily) and changes to the gut microbiome, in the ileum. METHODS: Ileostomy fluid (IF) and blood were obtained at baseline, after first capsule dosing (median 2 h), and at a similar time after final dosing on day 28, in 11 individuals (median age 63 y) with a temporary ileostomy. Fatty acids were measured by LC-tandem MS. The ileal microbiome was characterized by 16S rRNA PCR and Illumina sequencing. RESULTS: There was a mean 6.0 ± 9.8-fold and 6.6 ± 9.6-fold increase in ileal EPA and DHA concentrations (primary outcome), respectively, at 28 d, which was associated with increased RBC ω-3 PUFA content (P ≤ 0.05). The first oral dose did not increase the ileal ω-3 PUFA concentration except in 4 individuals, who displayed high luminal EPA and DHA concentrations, which reduced to concentrations similar to the overall study population at day 28, suggesting physiological adaptation. Bacteroides, Clostridium, and Streptococcus were abundant bacterial genera in the ileum. Ileal microbiome variability over time and between individuals was large, with no consistent change associated with acute ω-3 PUFA dosing. However, high concentrations of EPA and DHA in IF on day 28 were associated with higher abundance of Bacteroides (r2 > 0.86, P < 0.05) and reduced abundance of other genera, including Actinomyces (r2 > 0.94, P < 0.05). CONCLUSIONS: Oral administration of ω-3 PUFAs leads to increased luminal ω-3 PUFA concentrations and changes to the microbiome, in the ileum of individuals with a temporary ileostomy. This study is registered on the ISRCTN registry as ISRCTN14530452.

Correction: Developing a Raman spectroscopy-based tool to stratify patient response to pre-operative radiotherapy in rectal cancer.

Correction for 'Developing a Raman spectroscopy-based tool to stratify patient response to pre-operative radiotherapy in rectal cancer' by Chloe J. Kirkby et al., Analyst, 2021, 146, 581-589, DOI: .

Developing a Raman spectroscopy-based tool to stratify patient response to pre-operative radiotherapy in rectal cancer.

Rectal cancer patients frequently receive pre-operative radiotherapy (RT), prior to surgical resection. However, colorectal cancer is heterogeneous and the degree of tumour response to pre-operative RT is highly variable. There are currently no clinically approved methods of predicting response to RT, and a significant proportion of patients will show no clinical benefit, despite enduring the side-effects. We evaluated the use of Raman spectroscopy (RS), a non-destructive technique able to provide the unique chemical fingerprint of tissues, as a potential tool to stratify patient response to pre-operative RT. Raman measurements were obtained from the formalin-fixed, paraffin-embedded (FFPE) pre-treatment biopsy specimens of 20 rectal cancer patients who received pre-operative RT. A principal component analysis and linear discriminant analysis algorithm was able to classify patient response to pre-operative RT as good or poor, with an accuracy of 86.04 ± 0.14% (standard error). Patients with a good response to RT showed greater contributions from protein-associated peaks, whereas patients who responded poorly showed greater lipid contributions. These results demonstrate that RS is able to reliably classify tumour response to pre-operative RT from FFPE biopsies and highlights its potential to guide personalised cancer patient treatment.

A randomised trial of the effect of omega-3 polyunsaturated fatty acid supplements on the human intestinal microbiota.

OBJECTIVE: Omega-3 polyunsaturated fatty acids (PUFAs) have anticolorectal cancer (CRC) activity. The intestinal microbiota has been implicated in colorectal carcinogenesis. Dietary omega-3 PUFAs alter the mouse intestinal microbiome compatible with antineoplastic activity. Therefore, we investigated the effect of omega-3 PUFA supplements on the faecal microbiome in middle-aged, healthy volunteers (n=22). DESIGN: A randomised, open-label, cross-over trial of 8 weeks' treatment with 4 g mixed eicosapentaenoic acid/docosahexaenoic acid in two formulations (soft-gel capsules and Smartfish drinks), separated by a 12-week 'washout' period. Faecal samples were collected at five time-points for microbiome analysis by 16S ribosomal RNA PCR and Illumina MiSeq sequencing. Red blood cell (RBC) fatty acid analysis was performed by liquid chromatography tandem mass spectrometry. RESULTS: Both omega-3 PUFA formulations induced similar changes in RBC fatty acid content, except that drinks were associated with a larger, and more prolonged, decrease in omega-6 PUFA arachidonic acid than the capsule intervention (p=0.02). There were no significant changes in α or ß diversity, or phyla composition, associated with omega-3 PUFA supplementation. However, a reversible increased abundance of several genera, including Bifidobacterium, Roseburia and Lactobacillus was observed with one or both omega-3 PUFA interventions. Microbiome changes did not correlate with RBC omega-3 PUFA incorporation or development of omega-3 PUFA-induced diarrhoea. There were no treatment order effects. CONCLUSION: Omega-3 PUFA supplementation induces a reversible increase in several short-chain fatty acid-producing bacteria, independently of the method of administration. There is no simple relationship between the intestinal microbiome and systemic omega-3 PUFA exposure. TRIAL REGISTRATION NUMBER: ISRCTN18662143.

Stratifying tumour subtypes based on copy number alteration profiles using next-generation sequence data.

MOTIVATION: The role of personalized medicine and target treatment in the clinical management of cancer patients has become increasingly important in recent years. This has made the task of precise histological substratification of cancers crucial. Increasingly, genomic data are being seen as a valuable classifier. Specifically, copy number alteration (CNA) profiles generated by next-generation sequencing (NGS) can become a determinant for tumours subtyping. The principle purpose of this study is to devise a model with good prediction capability for the tumours histological subtypes as a function of both the patients covariates and their genome-wide CNA profiles from NGS data. RESULTS: We investigate a logistic regression for modelling tumour histological subtypes as a function of the patients' covariates and their CNA profiles, in a mixed model framework. The covariates, such as age and gender, are considered as fixed predictors and the genome-wide CNA profiles are considered as random predictors. We illustrate the application of this model in lung and oral cancer datasets, and the results indicate that the tumour histological subtypes can be modelled with a good fit. Our cross-validation indicates that the logistic regression exhibits the best prediction relative to other classification methods we considered in this study. The model also exhibits the best agreement in the prediction between smooth-segmented and circular binary-segmented CNA profiles. AVAILABILITY AND IMPLEMENTATION: An R package to run a logistic regression is available in http://www1.maths.leeds.ac.uk/~arief/R/CNALR/. CONTACT: a.gusnanto@leeds.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The clonal relationships between pre-cancer and cancer revealed by ultra-deep sequencing.

The study of the relationships between pre-cancer and cancer and identification of early driver mutations is becoming increasingly important as the value of molecular markers of early disease and personalised drug targets is recognized, especially now the extent of clonal heterogeneity in fully invasive disease is being realized. It has been assumed that pre-cancerous lesions exhibit a fairly passive progression to invasive disease; the degree to which they, too, are heterogeneous is unknown. We performed ultra-deep sequencing of thousands of selected mutations, together with copy number analysis, from multiple, matched pre-invasive lesions, primary tumours and metastases from five patients with oral cancer, some with multiple primary tumours presenting either synchronously or metachronously, totalling 75 samples. This allowed the clonal relationships between the samples to be observed for each patient. We expose for the first time the unexpected variety and complexity of the relationships between this group of oral dysplasias and their associated carcinomas and, ultimately, the diversity of processes by which tumours are initiated, spread and metastasize. Instead of a series of genomic precursors of their adjacent invasive disease, we have shown dysplasia to be a distinct dynamic entity, refuting the belief that pre-cancer and invasive tumours with a close spatial relationship always have linearly related genomes. We show that oral pre-cancer exhibits considerable subclonal heterogeneity in its own right, that mutational changes in pre-cancer do not predict the onset of invasion, and that the genomic pathway to invasion is neither unified nor predictable. Sequence data from this study have been deposited in the European Nucleotide Archive, Accession No. PRJEB6588.

A novel genomic signature reclassifies an oral cancer subtype.

Verrucous carcinoma of the oral cavity (OVC) is considered a subtype of classical oral squamous cell carcinoma (OSCC). Diagnosis is problematic, and additional biomarkers are needed to better stratify patients. To investigate their molecular signature, we performed low-coverage copy number (CN) sequencing on 57 OVC and exome and RNA sequencing on a subset of these and compared the data to the same OSCC parameters. CN results showed that OVC lacked any of the classical OSCC patterns such as gain of 3q and loss of 3p and demonstrated considerably fewer genomic rearrangements compared to the OSCC cohort. OVC and OSCC samples could be clearly differentiated. Exome sequencing showed that OVC samples lacked mutations in genes commonly associated with OSCC (TP53, NOTCH1, NOTCH2, CDKN2A and FAT1). RNA sequencing identified genes that were differentially expressed between the groups. In silico functional analysis showed that the mutated and differentially expressed genes in OVC samples were involved in cell adhesion and keratinocyte proliferation, while those in the OSCC cohort were enriched for cell death and apoptosis pathways. This is the largest and most detailed genomic and transcriptomic analysis yet performed on this tumour type, which, as an example of non-metastatic cancer, may shed light on the nature of metastases. These three independent investigations consistently show substantial differences between the cohorts. Taken together, they lead to the conclusion that OVC is not a subtype of OSCC, but should be classified as a distinct entity.

Estimating optimal window size for analysis of low-coverage next-generation sequence data.

MOTIVATION: Current high-throughput sequencing has greatly transformed genome sequence analysis. In the context of very low-coverage sequencing (<0.1×), performing 'binning' or 'windowing' on mapped short sequences ('reads') is critical to extract genomic information of interest for further evaluation, such as copy-number alteration analysis. If the window size is too small, many windows will exhibit zero counts and almost no pattern can be observed. In contrast, if the window size is too wide, the patterns or genomic features will be 'smoothed out'. Our objective is to identify an optimal window size in between the two extremes. RESULTS: We assume the reads density to be a step function. Given this model, we propose a data-based estimation of optimal window size based on Akaike's information criterion (AIC) and cross-validation (CV) log-likelihood. By plotting the AIC and CV log-likelihood curve as a function of window size, we are able to estimate the optimal window size that minimizes AIC or maximizes CV log-likelihood. The proposed methods are of general purpose and we illustrate their application using low-coverage next-generation sequence datasets from real tumour samples and simulated datasets. AVAILABILITY AND IMPLEMENTATION: An R package to estimate optimal window size is available at http://www1.maths.leeds.ac.uk/∼arief/R/win/.

Correcting for cancer genome size and tumour cell content enables better estimation of copy number alterations from next-generation sequence data.

MOTIVATION: Comparison of read depths from next-generation sequencing between cancer and normal cells makes the estimation of copy number alteration (CNA) possible, even at very low coverage. However, estimating CNA from patients' tumour samples poses considerable challenges due to infiltration with normal cells and aneuploid cancer genomes. Here we provide a method that corrects contamination with normal cells and adjusts for genomes of different sizes so that the actual copy number of each region can be estimated. RESULTS: The procedure consists of several steps. First, we identify the multi-modality of the distribution of smoothed ratios. Then we use the estimates of the mean (modes) to identify underlying ploidy and the contamination level, and finally we perform the correction. The results indicate that the method works properly to estimate genomic regions with gains and losses in a range of simulated data as well as in two datasets from lung cancer patients. It also proves a powerful tool when analysing publicly available data from two cell lines (HCC1143 and COLO829). AVAILABILITY: An R package, called CNAnorm, is available at http://www.precancer.leeds.ac.uk/cnanorm or from Bioconductor. CONTACT: a.gusnanto@leeds.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A computational index derived from whole-genome copy number analysis is a novel tool for prognosis in early stage lung squamous cell carcinoma.

Squamous cell carcinoma of the lung is remarkable for the extent to which the same chromosomal abnormalities are detected in individual tumours. We have used next generation sequencing at low coverage to produce high resolution copy number karyograms of a series of 89 non-small cell lung tumours specifically of the squamous cell subtype. Because this methodology is able to create karyograms from formalin-fixed paraffin-embedded material, we were able to use archival stored samples for which survival data were available and correlate frequently occurring copy number changes with disease outcome. No single region of genomic change showed significant correlation with survival. However, adopting a whole-genome approach, we devised an algorithm that relates to total genomic damage, specifically the relative ratios of copy number states across the genome. This algorithm generated a novel index, which is an independent prognostic indicator in early stage squamous cell carcinoma of the lung.

The risk of colorectal cancer in individuals with mutations of the cystic fibrosis transmembrane conductance regulator (CFTR) gene: An English population-based study.

BACKGROUND: Studies have demonstrated a higher risk of developing colorectal cancer (CRC) in individuals with Cystic Fibrosis (CF), and also a potentially increased risk in carriers of cystic fibrosis transmembrane conductance regulator (CFTR) mutations. Life expectancy for those with CF is rising, increasing the number at risk of developing CRC. METHODS: The incidence of CRC amongst individuals with CF was calculated using data from CORECT-R and linked UK CF Registry and Secondary User Services (SUS) data. Crude, age-specific and age-standardised rates were compared to those without CF. The presence of CFTR mutations in individuals with CRC was assessed using 100,000 Genomes Project data. FINDINGS: The crude incidence rate of CRC in the CF population was 0.29 per 1,000 person-years (28 cases). The CF population were significantly younger than those without (median age at CRC diagnosis 52 years versus 73 years; p<0·01). When age-adjusted, there was a 5-fold increased CRC incidence amongst individuals with CF compared to those without (SIR 5.0 95%CI 3.2-6.9). When compared to other population studies the overall prevalence of CFTR mutations in the CRC population was significantly higher than expected (p<0·01). INTERPRETATION: CF is linked to an increased risk of CRC. The incidence of CFTR mutations in the CRC population is higher than would be expected, suggesting an association between CFTR function and CRC risk. Further research is needed to develop effective screening strategies for these populations. FUNDING: Cancer Research UK (grants C23434/A23706 & C10674/A27140).

Associations between AI-Assisted Tumor Amphiregulin and Epiregulin IHC and Outcomes from Anti-EGFR Therapy in the Routine Management of Metastatic Colorectal Cancer.

PURPOSE: High tumor production of the EGFR ligands, amphiregulin (AREG) and epiregulin (EREG), predicted benefit from anti-EGFR therapy for metastatic colorectal cancer (mCRC) in a retrospective analysis of clinical trial data. Here, AREG/EREG IHC was analyzed in a cohort of patients who received anti-EGFR therapy as part of routine care, including key clinical contexts not investigated in the previous analysis. EXPERIMENTAL DESIGN: Patients who received panitumumab or cetuximab ± chemotherapy for treatment of RAS wild-type mCRC at eight UK cancer centers were eligible. Archival formalin-fixed paraffin-embedded tumor tissue was analyzed for AREG and EREG IHC in six regional laboratories using previously developed artificial intelligence technologies. Primary endpoints were progression-free survival (PFS) and overall survival (OS). RESULTS: A total of 494 of 541 patients (91.3%) had adequate tissue for analysis. A total of 45 were excluded after central extended RAS testing, leaving 449 patients in the primary analysis population. After adjustment for additional prognostic factors, high AREG/EREG expression (n = 360; 80.2%) was associated with significantly prolonged PFS [median: 8.5 vs. 4.4 months; HR, 0.73; 95% confidence interval (CI), 0.56-0.95; P = 0.02] and OS [median: 16.4 vs. 8.9 months; HR, 0.66 95% CI, 0.50-0.86; P = 0.002]. The significant OS benefit was maintained among patients with right primary tumor location (PTL), those receiving cetuximab or panitumumab, those with an oxaliplatin- or irinotecan-based chemotherapy backbone, and those with tumor tissue obtained by biopsy or surgical resection. CONCLUSIONS: High tumor AREG/EREG expression was associated with superior survival outcomes from anti-EGFR therapy in mCRC, including in right PTL disease. AREG/EREG IHC assessment could aid therapeutic decisions in routine practice. See related commentary by Randon and Pietrantonio, p. 4021.

Using next-generation sequencing for high resolution multiplex analysis of copy number variation from nanogram quantities of DNA from formalin-fixed paraffin-embedded specimens.

The use of next-generation sequencing technologies to produce genomic copy number data has recently been described. Most approaches, however, reply on optimal starting DNA, and are therefore unsuitable for the analysis of formalin-fixed paraffin-embedded (FFPE) samples, which largely precludes the analysis of many tumour series. We have sought to challenge the limits of this technique with regards to quality and quantity of starting material and the depth of sequencing required. We confirm that the technique can be used to interrogate DNA from cell lines, fresh frozen material and FFPE samples to assess copy number variation. We show that as little as 5 ng of DNA is needed to generate a copy number karyogram, and follow this up with data from a series of FFPE biopsies and surgical samples. We have used various levels of sample multiplexing to demonstrate the adjustable resolution of the methodology, depending on the number of samples and available resources. We also demonstrate reproducibility by use of replicate samples and comparison with microarray-based comparative genomic hybridization (aCGH) and digital PCR. This technique can be valuable in both the analysis of routine diagnostic samples and in examining large repositories of fixed archival material.

Prediction of tumour pathological subtype from genomic profile using sparse logistic regression with random effects.

The purpose of this study is to highlight the application of sparse logistic regression models in dealing with prediction of tumour pathological subtypes based on lung cancer patients' genomic information. We consider sparse logistic regression models to deal with the high dimensionality and correlation between genomic regions. In a hierarchical likelihood (HL) method, it is assumed that the random effects follow a normal distribution and its variance is assumed to follow a gamma distribution. This formulation considers ridge and lasso penalties as special cases. We extend the HL penalty to include a ridge penalty (called 'HLnet') in a similar principle of the elastic net penalty, which is constructed from lasso penalty. The results indicate that the HL penalty creates more sparse estimates than lasso penalty with comparable prediction performance, while HLnet and elastic net penalties have the best prediction performance in real data. We illustrate the methods in a lung cancer study.

Adaptor Template Oligo-Mediated Sequencing (ATOM-Seq) is a new ultra-sensitive UMI-based NGS library preparation technology for use with cfDNA and cfRNA.

Liquid biopsy testing utilising Next Generation Sequencing (NGS) is rapidly moving towards clinical adoption for personalised oncology. However, before NGS can fulfil its potential any novel testing approach must identify ways of reducing errors, allowing separation of true low-frequency mutations from procedural artefacts, and be designed to improve upon current technologies. Popular NGS technologies typically utilise two DNA capture approaches; PCR and ligation, which have known limitations and seem to have reached a development plateau with only small, stepwise improvements being made. To maximise the ultimate utility of liquid biopsy testing we have developed a highly versatile approach to NGS: Adaptor Template Oligo Mediated Sequencing (ATOM-Seq). ATOM-Seq's strengths and versatility avoid the major limitations of both PCR- and ligation-based approaches. This technology is ligation free, simple, efficient, flexible, and streamlined, and it offers novel advantages that make it perfectly suited for use on highly challenging clinical material. Using reference and clinical materials, we demonstrate detection of known SNVs down to allele frequencies of 0.1% using as little as 20-25 ng of cfDNA, as well as the ability to detect fusions from RNA. We illustrate ATOM-Seq's suitability for clinical testing by showing high concordance rates between paired cfDNA and FFPE clinical samples.

Microbiome Analysis of More Than 2,000 NHS Bowel Cancer Screening Programme Samples Shows the Potential to Improve Screening Accuracy.

PURPOSE: There is potential for fecal microbiome profiling to improve colorectal cancer screening. This has been demonstrated by research studies, but it has not been quantified at scale using samples collected and processed routinely by a national screening program. EXPERIMENTAL DESIGN: Between 2016 and 2019, the largest of the NHS Bowel Cancer Screening Programme hubs prospectively collected processed guaiac fecal occult blood test (gFOBT) samples with subsequent colonoscopy outcomes: blood-negative [n = 491 (22%)]; colorectal cancer [n = 430 (19%)]; adenoma [n = 665 (30%)]; colonoscopy-normal [n = 300 (13%)]; nonneoplastic [n = 366 (16%)]. Samples were transported and stored at room temperature. DNA underwent 16S rRNA gene V4 amplicon sequencing. Taxonomic profiling was performed to provide features for classification via random forests (RF). RESULTS: Samples provided 16S amplicon-based microbial profiles, which confirmed previously described colorectal cancer-microbiome associations. Microbiome-based RF models showed potential as a first-tier screen, distinguishing colorectal cancer or neoplasm (colorectal cancer or adenoma) from blood-negative with AUC 0.86 (0.82-0.89) and AUC 0.78 (0.74-0.82), respectively. Microbiome-based models also showed potential as a second-tier screen, distinguishing from among gFOBT blood-positive samples, colorectal cancer or neoplasm from colonoscopy-normal with AUC 0.79 (0.74-0.83) and AUC 0.73 (0.68-0.77), respectively. Models remained robust when restricted to 15 taxa, and performed similarly during external validation with metagenomic datasets. CONCLUSIONS: Microbiome features can be assessed using gFOBT samples collected and processed routinely by a national colorectal cancer screening program to improve accuracy as a first- or second-tier screen. The models required as few as 15 taxa, raising the potential of an inexpensive qPCR test. This could reduce the number of colonoscopies in countries that use fecal occult blood test screening.