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.

Detection of colorectal-cancer-associated bacterial taxa in fecal samples using next-generation sequencing and 19 newly established qPCR assays.

We have previously identified increased levels of distinct bacterial taxa within mucosal biopsies from colorectal cancer (CRC) patients. Following prior research, the aim of this study was to investigate the detection of the same CRC-associated bacteria in fecal samples and to evaluate the suitability of fecal samples as a non-invasive material for the detection of CRC-associated bacteria. Next-generation sequencing (NGS) of the 16S ribosomal RNA (rRNA) V4 region was performed to evaluate the detection of the CRC-associated bacteria in the fecal microbiota of cancer patients, patients with adenomatous polyp and healthy controls. Furthermore, 19 novel species-specific quantitative PCR (qPCR) assays were established to detect the CRC-associated bacteria. Approximately, 75% of the bacterial taxa identified in biopsies were reflected in fecal samples. NGS failed to detect low-abundance CRC-associated taxa in fecal samples, whereas qPCR exhibited high sensitivity and specificity in identifying all targeted taxa. Comparison of fecal microbial composition between the different patient groups showed enrichment of Fusobacterium nucleatum, Parvimonas micra, and Gemella morbillorum in cancer patients. Our findings suggest that low-abundance mucosa-associated bacteria can be detected in fecal samples using sensitive qPCR assays.

Validation of miRNA signatures for ovarian cancer earlier detection in the pre-diagnosis setting using machine learning approaches.

Introduction: Effective strategies for early detection of epithelial ovarian cancer are lacking. We evaluated whether a panel of 14 previously established circulating microRNAs could discriminate between cases diagnosed <2 years after serum collection and those diagnosed 2-7 years after serum collection. miRNA sequencing data from subsequent ovarian cancer cases were obtained as part of the ongoing multi-cancer JanusRNA project, utilizing pre-diagnostic serum samples from the Janus Serum Bank and linked to the Cancer Registry of Norway for cancer outcomes. Methods: We included a total of 80 ovarian cancer cases contributing 80 serum samples and compared 40 serum samples from cases with samples collected <2 years prior to diagnosis with 40 serum samples from cases with sample collection ≥2 to 7 years. We employed the extreme gradient boosting (XGBoost) algorithm to train a binary classification model using 70% of the available data, while the model was tested on the remaining 30% of the dataset. Results: The performance of the model was evaluated using repeated holdout validation. The previously established set of miRNAs achieved a median area under the receiver operating characteristic curve (AUC) of 0.771 in the test sets. Four out of 14 miRNAs (hsa-miR-200a-3p, hsa-miR-1246, hsa-miR-203a-3p, hsa-miR-23b-3p) exhibited higher expression levels closer to diagnosis, consistent with the previously reported upregulation in cancer cases, with statistical significance observed only for hsa-miR-200a-3p (beta=0.14; p=0.04). Discussion: The discrimination potential of the selected models provides evidence of the robustness of the miRNA signature for ovarian cancer.

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.