Differential levels of circulating RNAs prior to endometrial cancer diagnosis.

Endometrial cancer (EC) is one of the most common female cancers and there is currently no routine screening strategy for early detection. An altered abundance of circulating microRNAs (miRNAs) and other RNA classes have the potential as early cancer biomarkers. We analyzed circulating RNA levels using small RNA sequencing, targeting RNAs in the size range of 17-47 nucleotides, in EC patients with samples collected prior to diagnosis compared to cancer-free controls. The analysis included 316 cases with samples collected 1-11 years prior to EC diagnosis, and 316 matched controls, both from the Janus Serum Bank cohort in Norway. We identified differentially abundant (DA) miRNAs, isomiRs, and small nuclear RNAs between EC cases and controls. The top EC DA miRNAs were miR-155-5p, miR-200b-3p, miR-589-5p, miR-151a-5p, miR-543, miR-485-5p, miR-625-p, and miR-671-3p. miR-200b-3p was previously reported to be among one of the top miRNAs with higher abundance in EC cases. We observed 47, 41, and 32 DA miRNAs for EC interacting with BMI, smoking status, and physical activity, respectively, including two miRNAs (miR-223-3p and miR-29b-3p) interacting with all three factors. The circulating RNAs are altered and show temporal dynamics prior to EC diagnosis. Notably, DA miRNAs for EC had the lowest q-value 4.39-6.66 years before diagnosis. Enrichment analysis of miRNAs showed that signaling pathways Fc epsilon RI, prolactin, toll-like receptor, and VEGF had the strongest associations.

Changes in intrahost genetic diversity according to lesion severity in longitudinal HPV16 samples.

Human papillomavirus type 16 (HPV16) is the most common cause of cervical cancer, but most infections are transient with lesions not progressing to cancer. There is a lack of specific biomarkers for early cancer risk stratification. This study aimed to explore the intrahost HPV16 genomic variation in longitudinal samples from HPV16-infected women with different cervical lesion severity (normal, low-grade, and high-grade). The TaME-seq deep sequencing protocol was used to generate whole genome HPV16 sequences of 102 samples collected over time from 40 individuals. Single nucleotide variants (SNVs) and intrahost SNVs (iSNVs) were identified in the viral genomes. A majority of individuals had a unique set of SNVs and these SNVs were stable over time. Overall, the number of iSNVs and APOBEC3-induced iSNVs were significantly lower in high-grade relative to normal and low-grade samples. A significant increase in the number of APOBEC3-induced iSNVs over time was observed for normal samples when compared to high-grade. Our results indicates that the lower incidence of iSNVs and APOBEC3-induced iSNVs in high-grade lesions may have implications for novel biomarkers discoveries, potentially aiding early stratification of HPV-induced cervical precancerous lesions.

Exploring the gut DNA virome in fecal immunochemical test stool samples reveals associations with lifestyle in a large population-based study.

Stool samples for fecal immunochemical tests (FIT) are collected in large numbers worldwide as part of colorectal cancer screening programs. Employing FIT samples from 1034 CRCbiome participants, recruited from a Norwegian colorectal cancer screening study, we identify, annotate and characterize more than 18000 DNA viruses, using shotgun metagenome sequencing. Only six percent of them are assigned to a known taxonomic family, with Microviridae being the most prevalent viral family. Linking individual profiles to comprehensive lifestyle and demographic data shows 17/25 of the variables to be associated with the gut virome. Physical activity, smoking, and dietary fiber consumption exhibit strong and consistent associations with both diversity and relative abundance of individual viruses, as well as with enrichment for auxiliary metabolic genes. We demonstrate the suitability of FIT samples for virome analysis, opening an opportunity for large-scale studies of this enigmatic part of the gut microbiome. The diverse viral populations and their connections to the individual lifestyle uncovered herein paves the way for further exploration of the role of the gut virome in health and disease.

HoCoRT: host contamination removal tool.

BACKGROUND: Shotgun metagenome sequencing data obtained from a host environment will usually be contaminated with sequences from the host organism. Host sequences should be removed before further analysis to avoid biases, reduce downstream computational load, or ensure privacy in the case of a human host. The tools that we identified, as designed specifically to perform host contamination sequence removal, were either outdated, not maintained, or complicated to use. Consequently, we have developed HoCoRT, a fast and user-friendly tool that implements several methods for optimised host sequence removal. We have evaluated the speed and accuracy of these methods. RESULTS: HoCoRT is an open-source command-line tool for host contamination removal. It is designed to be easy to install and use, offering a one-step option for genome indexing. HoCoRT employs a variety of well-known mapping, classification, and alignment methods to classify reads. The user can select the underlying classification method and its parameters, allowing adaptation to different scenarios. Based on our investigation of various methods and parameters using synthetic human gut and oral microbiomes, and on assessment of publicly available data, we provide recommendations for typical datasets with short and long reads. CONCLUSIONS: To decontaminate a human gut microbiome with short reads using HoCoRT, we found the optimal combination of speed and accuracy with BioBloom, Bowtie2 in end-to-end mode, and HISAT2. Kraken2 consistently demonstrated the highest speed, albeit with a trade-off in accuracy. The same applies to an oral microbiome, but here Bowtie2 was notably slower than the other tools. For long reads, the detection of human host reads is more difficult. In this case, a combination of Kraken2 and Minimap2 achieved the highest accuracy and detected 59% of human reads. In comparison to the dedicated DeconSeq tool, HoCoRT using Bowtie2 in end-to-end mode proved considerably faster and slightly more accurate. HoCoRT is available as a Bioconda package, and the source code can be accessed at https://github.com/ignasrum/hocort along with the documentation. It is released under the MIT licence and is compatible with Linux and macOS (except for the BioBloom module).

Profiling small RNAs in fecal immunochemical tests: is it possible?

Fecal microRNAs represent promising molecules with potential clinical interest as non-invasive diagnostic and prognostic biomarkers. Colorectal cancer (CRC) screening based on the fecal immunochemical test (FIT) is an effective tool for prevention of cancer development. However, due to the poor sensitivity of FIT especially for premalignant lesions, there is a need for implementation of complementary tests. Improving the identification of individuals who would benefit from further investigation with colonoscopy using molecular analysis, such as miRNA profiling of FIT samples, would be ideal due to their widespread use. In the present study, we assessed the feasibility of applying small RNA sequencing to measure human miRNAs in FIT leftover buffer in samples from two European screening populations. We showed robust detection of miRNAs with profiles similar to those obtained from specimens sampled using the established protocol of RNA stabilizing buffers, or in long-term archived samples. Detected miRNAs exhibited differential abundances for CRC, advanced adenoma, and control samples that were consistent for FIT and RNA-stabilizing buffers. Interestingly, the sequencing data also allowed for concomitant evaluation of small RNA-based microbial profiles. We demonstrated that it is possible to explore the human miRNome in FIT leftover samples across populations and envision that the analysis of small RNA biomarkers can complement the FIT in large scale screening settings.

Accurate microRNA annotation of animal genomes using trained covariance models of curated microRNA complements in MirMachine.

The annotation of microRNAs depends on the availability of transcriptomics data and expert knowledge. This has led to a gap between the availability of novel genomes and high-quality microRNA complements. Using >16,000 microRNAs from the manually curated microRNA gene database MirGeneDB, we generated trained covariance models for all conserved microRNA families. These models are available in our tool MirMachine, which annotates conserved microRNAs within genomes. We successfully applied MirMachine to a range of animal species, including those with large genomes and genome duplications and extinct species, where small RNA sequencing is hard to achieve. We further describe a microRNA score of expected microRNAs that can be used to assess the completeness of genome assemblies. MirMachine closes a long-persisting gap in the microRNA field by facilitating automated genome annotation pipelines and deeper studies into the evolution of genome regulation, even in extinct organisms.

Correction: Self-collected and clinician-collected anal swabs show modest agreement for HPV genotyping.

[This corrects the article DOI: 10.1371/journal.pone.0250426.].

Long-term follow-up of colorectal cancer screening attendees identifies differences in Phascolarctobacterium spp. using 16S rRNA and metagenome sequencing.

Background: The microbiome has been implicated in the initiation and progression of colorectal cancer (CRC) in cross-sectional studies. However, there is a lack of studies using prospectively collected samples. Methods: From the Norwegian Colorectal Cancer Prevention (NORCCAP) trial, we analyzed 144 archived fecal samples from participants who were diagnosed with CRC or high-risk adenoma (HRA) at screening and from participants who remained cancer-free during 17 years of follow-up. We performed 16S rRNA sequencing of all the samples and metagenome sequencing on a subset of 47 samples. Differences in taxonomy and gene content between outcome groups were assessed for alpha and beta diversity and differential abundance. Results: Diversity and composition analyses showed no significant differences between CRC, HRA, and healthy controls. Phascolarctobacterium succinatutens was more abundant in CRC compared with healthy controls in both the 16S and metagenome data. The abundance of Bifidobacterium and Lachnospiraceae spp. was associated with time to CRC diagnosis. Conclusion: Using a longitudinal study design, we identified three taxa as being potentially associated with CRC. These should be the focus of further studies of microbial changes occurring prior to CRC diagnosis.

Associations of the 2018 World Cancer Research Fund/American Institute of Cancer Research (WCRF/AICR) cancer prevention recommendations with stages of colorectal carcinogenesis.

BACKGROUND: While adherence to cancer prevention recommendations is linked to lower risk of colorectal cancer (CRC), few have studied associations across the entire spectrum of colorectal carcinogenesis. Here, we studied the relationship of the standardized 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) Score for cancer prevention recommendations with detection of colorectal lesions in a screening setting. As a secondary objective, we examined to what extent the recommendations were being followed in an external cohort of CRC patients. METHODS: Adherence to the seven-point 2018 WCRF/AICR Score was measured in screening participants receiving a positive fecal immunochemical test and in CRC patients participating in an intervention study. Dietary intake, body fatness and physical activity were assessed using self-administered questionnaires. Multinomial logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for screen-detected lesions. RESULTS: Of 1486 screening participants, 548 were free from adenomas, 524 had non-advanced adenomas, 349 had advanced lesions and 65 had CRC. Adherence to the 2018 WCRF/AICR Score was inversely associated with advanced lesions; OR 0.82 (95% CI 0.71, 0.94) per score point, but not with CRC. Of the seven individual components included in the score, alcohol, and BMI seemed to be the most influential. Of the 430 CRC patients included in the external cohort, the greatest potential for lifestyle improvement was seen for the recommendations concerning alcohol and red and processed meat, where 10% and 2% fully adhered, respectively. CONCLUSIONS: Adherence to the 2018 WCRF/AICR Score was associated with lower probability of screen-detected advanced precancerous lesions, but not CRC. Although some components of the score seemed to be more influential than others (i.e., alcohol and BMI), taking a holistic approach to cancer prevention is likely the best way to prevent the occurrence of precancerous colorectal lesions.

TaME-seq2: tagmentation-assisted multiplex PCR enrichment sequencing for viral genomic profiling.

BACKGROUND: Previously developed TaME-seq method for deep sequencing of HPV, allowed simultaneous identification of the human papillomavirus (HPV) DNA consensus sequence, low-frequency variable sites, and chromosomal integration events. The method has been successfully validated and applied to the study of five carcinogenic high-risk (HR) HPV types (HPV16, 18, 31, 33, and 45). Here, we present TaME-seq2 with an updated laboratory workflow and bioinformatics pipeline. The HR-HPV type repertoire was expanded with HPV51, 52, and 59. As a proof-of-concept, TaME-seq2 was applied on SARS-CoV-2 positive samples showing the method's flexibility to a broader range of viruses, both DNA and RNA. RESULTS: Compared to TaME-seq version 1, the bioinformatics pipeline of TaME-seq2 is approximately 40× faster. In total, 23 HPV-positive samples and seven SARS-CoV-2 clinical samples passed the threshold of 300× mean depth and were submitted to further analysis. The mean number of variable sites per 1 kb was ~ 1.5× higher in SARS-CoV-2 than in HPV-positive samples. Reproducibility and repeatability of the method were tested on a subset of samples. A viral integration breakpoint followed by a partial genomic deletion was found in within-run replicates of HPV59-positive sample. Identified viral consensus sequence in two separate runs was > 99.9% identical between replicates, differing by a couple of nucleotides identified in only one of the replicates. Conversely, the number of identical minor nucleotide variants (MNVs) differed greatly between replicates, probably caused by PCR-introduced bias. The total number of detected MNVs, calculated gene variability and mutational signature analysis, were unaffected by the sequencing run. CONCLUSION: TaME-seq2 proved well suited for consensus sequence identification, and the detection of low-frequency viral genome variation and viral-chromosomal integrations. The repertoire of TaME-seq2 now encompasses seven HR-HPV types. Our goal is to further include all HR-HPV types in the TaME-seq2 repertoire. Moreover, with a minor modification of previously developed primers, the same method was successfully applied for the analysis of SARS-CoV-2 positive samples, implying the ease of adapting TaME-seq2 to other viruses.

Microbial dynamics with CRC progression: a study of the mucosal microbiota at multiple sites in cancers, adenomatous polyps, and healthy controls.

Accumulating evidence has related the gut microbiota to colorectal cancer (CRC). Fusobacterium nucleatum has repeatedly been linked to colorectal tumorigenesis. The aim of this study was to investigate microbial composition in different sampling sites, in order to profile the microbial dynamics with CRC progression. Further, we characterized the tumor-associated F. nucleatum subspecies. Here, we conducted Illumina Miseq next-generation sequencing of the 16S rRNA V4 region in biopsy samples, to investigate microbiota alterations in cancer patients, patients with adenomatous polyp, and healthy controls in Norway. Further, Fusobacterium positive tumor biopsies were subjected to MinION nanopore sequencing of Fusobacterium-specific amplicons to characterize the Fusobacterium species and subspecies. We found enrichment of oral biofilm-associated bacteria, Fusobacterium, Gemella, Parvimonas, Granulicatella, Leptotrichia, Peptostreptococcus, Campylobacter, Selenomonas, Porphyromonas, and Prevotella in cancer patients compared to adenomatous polyp patients and control patients. Higher abundance of amplicon sequence variants (ASVs) classified as Phascolarctobacterium, Bacteroides vulgatus, Bacteroides plebeius, Bacteroides eggerthii, Tyzzerella, Desulfovibrio, Frisingicoccus, Eubacterium coprostanoligenes group, and Lachnospiraceae were identified in cancer and adenomatous polyp patients compared to healthy controls. F. nucleatum ssp. animalis was the dominating subspecies. F. nucleatum ssp. nucleatum, F. nucleatum ssp. vincentii, Fusobacterium pseudoperiodonticum, Fusobacterium necrophorum, and Fusobacterium gonidiaformans were identified in five samples. Several biofilm-associated bacteria were enriched at multiple sites in cancer patients. Another group of bacteria was enriched in both cancer and polyps, suggesting that they may have a role in polyp development and possibly early stages of CRC.

Dynamic and static circulating cancer microRNA biomarkers - a validation study.

For cancers and other pathologies, early diagnosis remains the most promising path to survival. Profiling of longitudinal cohorts facilitates insights into trajectories of biomarkers. We measured microRNA expression in 240 serum samples from patients with colon, lung, and breast cancer and from cancer-free controls. Each patient provided at least two serum samples, one prior to diagnosis and one following diagnosis. The median time interval between the samples was 11.6 years. Using computational models, we evaluated the circulating profiles of 21 microRNAs. The analysis yielded two sets of biomarkers, static ones that show an absolute difference between certain cancer types and controls and dynamic ones where the level over time provided higher diagnostic information content. In the first group, miR-99a-5p stands out for all three cancer types. In the second group, miR-155-5p allows to predict lung cancers and colon cancers. Classification in samples from cancer and non-cancer patients using gradient boosted trees reached an average accuracy of 79.9%. The results suggest that individual change over time or an absolute value at one time point may predict a disease with high specificity and sensitivity.

Differences in integration frequencies and APOBEC3 profiles of five high-risk HPV types adheres to phylogeny.

Persistent infection with Human Papillomavirus (HPV) is responsible for almost all cases of cervical cancers, and HPV16 and HPV18 associated with the majority of these. These types differ in the proportion of viral minor nucleotide variants (MNVs) caused by APOBEC3 mutagenesis as well as integration frequencies. Whether these traits extend to other types remains uncertain. This study aimed to investigate and compare genomic variability and chromosomal integration in the two phylogenetically distinct Alpha-7 and Alpha-9 clades of carcinogenic HPV types. The TaME-seq protocol was employed to sequence cervical cell samples positive for HPV31, HPV33 or HPV45 and combine these with data from a previous study on HPV16 and HPV18. APOBEC3 mutation signatures were found in Alpha-9 (HPV16/31/33) but not in Alpha-7 (HPV18/45). HPV45 had significantly more MNVs compared to the other types. Alpha-7 had higher integration frequency compared to Alpha-9. An increase in integration frequency with increased diagnostic severity was found for Alpha-7. The results highlight important differences and broaden our understanding of the molecular mechanisms behind cervical cancer induced by high-risk HPV types from the Alpha-7 and Alpha-9 clades.

Associations of red and processed meat intake with screen-detected colorectal lesions.

Limited data exist regarding the role of meat consumption in early-stage colorectal carcinogenesis. We examined associations of red and processed meat intake with screen-detected colorectal lesions in immunochemical fecal occult blood test (FIT)-positive participants, enrolled in the Norwegian CRCbiome study during 2017-2021, aged 55-77 years. Absolute and energy-adjusted intakes of red and processed meat (combined and individually) were assessed using a validated, semi-quantitative FFQ. Associations between meat intake and screen-detected colorectal lesions were examined using multinomial logistic regression analyses with adjustment for key covariates. Of 1162 participants, 319 presented with advanced colorectal lesions at colonoscopy. High v. low energy-adjusted intakes of red and processed meat combined, as well as red meat alone, were borderline to significantly positively associated with advanced colorectal lesions (OR of 1·24 (95 % CI 0·98, 1·57) and 1·34 (95 % CI 1·07, 1·69), respectively). A significant dose-response relationship was also observed for absolute intake levels (OR of 1·32 (95 % CI 1·09, 1·60) per 100 g/d increase in red and processed meat). For processed meat, no association was observed between energy-adjusted intakes and advanced colorectal lesions. A significant positive association was, however, observed for participants with absolute intake levels ≥ 100 v. < 50 g/d (OR of 1·19 (95 % CI 1·09, 1·31)). In summary, high intakes of red and processed meat were associated with presence of advanced colorectal lesions at colonoscopy in FIT-positive participants. The study demonstrates a potential role of dietary data to improve the performance of FIT-based screening.

A Role of the TEX101 Interactome in the Common Aetiology Behind Male Subfertility and Testicular Germ Cell Tumor.

Patients who develop testicular germ cell tumours (TGCT) are at higher risk to be subfertile than the general population. The conditions are believed to originate during foetal life, however, the mechanisms behind a common aetiology of TGCT and male subfertility remains unknown. Testis-expressed 101 (TEX101) is a glycoprotein that is related to male fertility, and downregulation of the TEX101 gene was shown in pre-diagnostic TGCT patients. In this review, we summarize the current knowledge of TEX101 and its interactome related to fertility and TGCT development. We searched literature and compilation of data from curated databases. There are studies from both human and animals showing that disruption of TEX101 result in abnormal semen parameters and sperm function. Members of the TEX101 interactome, like SPATA19, Ly6k, PICK1, and ODF genes are important for normal sperm function. We found only two studies of TEX101 related to TGCT, however, several genes in its interactome may be associated with TGCT development, such as PLAUR, PRSS21, CD109, and ALP1. Some of the interactome members are related to both fertility and cancer. Of special interest is the presence of the glycosylphosphatidylinositol anchored proteins TEX101 and PRSS21 in basophils that may be coupled to the immune response preventing further development of TGCT precursor cells. The findings of this review indicate that members of the TEX101 interactome could be a part of the link between TGCT and male subfertility.

Identification of Circulating lncRNAs Associated with Gallbladder Cancer Risk by Tissue-Based Preselection, Cis-eQTL Validation, and Analysis of Association with Genotype-Based Expression.

Long noncoding RNAs (lncRNAs) play key roles in cell processes and are good candidates for cancer risk prediction. Few studies have investigated the association between individual genotypes and lncRNA expression. Here we integrate three separate datasets with information on lncRNA expression only, both lncRNA expression and genotype, and genotype information only to identify circulating lncRNAs associated with the risk of gallbladder cancer (GBC) using robust linear and logistic regression techniques. In the first dataset, we preselect lncRNAs based on expression changes along the sequence "gallstones → dysplasia → GBC". In the second dataset, we validate associations between genetic variants and serum expression levels of the preselected lncRNAs (cis-lncRNA-eQTLs) and build lncRNA expression prediction models. In the third dataset, we predict serum lncRNA expression based on individual genotypes and assess the association between genotype-based expression and GBC risk. AC084082.3 and LINC00662 showed increasing expression levels (p-value = 0.009), while C22orf34 expression decreased in the sequence from gallstones to GBC (p-value = 0.04). We identified and validated two cis-LINC00662-eQTLs (r2 = 0.26) and three cis-C22orf34-eQTLs (r2 = 0.24). Only LINC00662 showed a genotyped-based serum expression associated with GBC risk (OR = 1.25 per log2 expression unit, 95% CI 1.04-1.52, p-value = 0.02). Our results suggest that preselection of lncRNAs based on tissue samples and exploitation of cis-lncRNA-eQTLs may facilitate the identification of circulating noncoding RNAs linked to cancer risk.

Serum RNAs can predict lung cancer up to 10 years prior to diagnosis.

Lung cancer (LC) prognosis is closely linked to the stage of disease when diagnosed. We investigated the biomarker potential of serum RNAs for the early detection of LC in smokers at different prediagnostic time intervals and histological subtypes. In total, 1061 samples from 925 individuals were analyzed. RNA sequencing with an average of 18 million reads per sample was performed. We generated machine learning models using normalized serum RNA levels and found that smokers later diagnosed with LC in 10 years can be robustly separated from healthy controls regardless of histology with an average area under the ROC curve (AUC) of 0.76 (95% CI, 0.68-0.83). Furthermore, the strongest models that took both time to diagnosis and histology into account successfully predicted non-small cell LC (NSCLC) between 6 and 8 years, with an AUC of 0.82 (95% CI, 0.76-0.88), and SCLC between 2 and 5 years, with an AUC of 0.89 (95% CI, 0.77-1.0), before diagnosis. The most important separators were microRNAs, miscellaneous RNAs, isomiRs, and tRNA-derived fragments. We have shown that LC can be detected years before diagnosis and manifestation of disease symptoms independently of histological subtype. However, the highest AUCs were achieved for specific subtypes and time intervals before diagnosis. The collection of models may therefore also predict the severity of cancer development and its histology. Our study demonstrates that serum RNAs can be promising prediagnostic biomarkers in an LC screening setting, from early detection to risk assessment.

The CRCbiome study: a large prospective cohort study examining the role of lifestyle and the gut microbiome in colorectal cancer screening participants.

BACKGROUND: Colorectal cancer (CRC) screening reduces CRC incidence and mortality. However, current screening methods are either hampered by invasiveness or suboptimal performance, limiting their effectiveness as primary screening methods. To aid in the development of a non-invasive screening test with improved sensitivity and specificity, we have initiated a prospective biomarker study (CRCbiome), nested within a large randomized CRC screening trial in Norway. We aim to develop a microbiome-based classification algorithm to identify advanced colorectal lesions in screening participants testing positive for an immunochemical fecal occult blood test (FIT). We will also examine interactions with host factors, diet, lifestyle and prescription drugs. The prospective nature of the study also enables the analysis of changes in the gut microbiome following the removal of precancerous lesions. METHODS: The CRCbiome study recruits participants enrolled in the Bowel Cancer Screening in Norway (BCSN) study, a randomized trial initiated in 2012 comparing once-only sigmoidoscopy to repeated biennial FIT, where women and men aged 50-74 years at study entry are invited to participate. Since 2017, participants randomized to FIT screening with a positive test result have been invited to join the CRCbiome study. Self-reported diet, lifestyle and demographic data are collected prior to colonoscopy after the positive FIT-test (baseline). Screening data, including colonoscopy findings are obtained from the BCSN database. Fecal samples for gut microbiome analyses are collected both before and 2 and 12 months after colonoscopy. Samples are analyzed using metagenome sequencing, with taxonomy profiles, and gene and pathway content as primary measures. CRCbiome data will also be linked to national registries to obtain information on prescription histories and cancer relevant outcomes occurring during the 10 year follow-up period. DISCUSSION: The CRCbiome study will increase our understanding of how the gut microbiome, in combination with lifestyle and environmental factors, influences the early stages of colorectal carcinogenesis. This knowledge will be crucial to develop microbiome-based screening tools for CRC. By evaluating biomarker performance in a screening setting, using samples from the target population, the generalizability of the findings to future screening cohorts is likely to be high. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01538550 .

HPV16 and HPV18 type-specific APOBEC3 and integration profiles in different diagnostic categories of cervical samples.

Human papillomavirus (HPV) 16 and 18 are the most predominant types in cervical cancer. Only a small fraction of HPV infections progress to cancer, indicating that additional factors and genomic events contribute to the carcinogenesis, such as minor nucleotide variation caused by APOBEC3 and chromosomal integration. We analysed intra-host minor nucleotide variants (MNVs) and integration in HPV16 and HPV18 positive cervical samples with different morphology. Samples were sequenced using an HPV whole genome sequencing protocol TaME-seq. A total of 80 HPV16 and 51 HPV18 positive samples passed the sequencing depth criteria of 300× reads, showing the following distribution: non-progressive disease (HPV16 n = 21, HPV18 n = 12); cervical intraepithelial neoplasia (CIN) grade 2 (HPV16 n = 27, HPV18 n = 9); CIN3/adenocarcinoma in situ (AIS) (HPV16 n = 27, HPV18 n = 30); cervical cancer (HPV16 n = 5). Similar numbers of MNVs in HPV16 and HPV18 samples were observed for most viral genes, with the exception of HPV18 E4 with higher numbers across clinical categories. APOBEC3 signatures were observed in HPV16 lesions, while similar mutation patterns were not detected for HPV18. The proportion of samples with integration was 13% for HPV16 and 59% for HPV18 positive samples, with a noticeable portion located within or close to cancer-related genes.

Ultralow amounts of DNA from long-term archived serum samples produce high-quality methylomes.

BACKGROUND: Long-term stored serum is considered challenging for epigenomic analyses: as there are no cells, circulating DNA is scarce, and amplification removes epigenetic signals. Additionally, pre-analytical treatments and storage might introduce biases and fragmentation to the DNA. In particular, starting with low-input DNA can result in low-diversity libraries. However, successful whole-genome bisulphite sequencing (WGBS) of such serum samples has the potential to open biobanks for epigenetic analyses and deliver novel prediagnostic biomarkers. Here, we perform WGBS using the Accel-NGS library preparation kit on ultralow amounts of DNA from long-term archived samples with diverse pretreatments from the Janus Serum Bank. RESULTS: Ninety-four of the 96 samples produced satisfactory methylation calls; an average of 578 M reads per sample generated a mean coverage of 17× and mean duplication level of 35%. Failed samples were related to poor bisulphite conversion rather than to sequencing or library preparation. We demonstrate the feasibility of WGBS on ultralow DNA yields from serum samples stored up to 48 years. CONCLUSIONS: Our results show the potential of large serum biobank collections for future epigenomic studies and biomarker discovery.