Early detection: the impact of genomics

The multitarget faecal immunochemical test for improving stool-based colorectal cancer screening programmes: a Dutch population-based, paired-design, intervention study

BACKGROUND

The faecal immunochemical test (FIT) is widely employed for colorectal cancer screening. However, its sensitivity for advanced precursor lesions remains suboptimal. The multitarget FIT (mtFIT), measuring haemoglobin, calprotectin, and serpin family F member 2, has demonstrated enhanced sensitivity for advanced neoplasia, especially advanced adenomas, at equal specificity to FIT. This study aimed to prospectively validate and investigate the clinical utlitity of mtFIT versus FIT in a setting of population-based colorectal cancer screening.

METHODS

Individuals aged 55-75 years and who were eligible for the Dutch national FIT-based colorectal cancer screening programme were invited to submit both a FIT and mtFIT sample collected from the same bowel movement. Positive FIT (47 μg/g haemoglobin cutoff) or mtFIT (based on decision-tree algorithm) led to a colonoscopy referral. The primary outcome was the relative detection rate of mtFIT versus FIT for all advanced neoplasia. Secondary outcomes were the relative detection rates of colorectal cancer, advanced adenoma, and advanced serrated polyps individually and the long-term effect of mtFIT-based versus FIT-based programmatic screening on colorectal cancer incidence, mortality, and cost, determined with microsimulation modelling. The study has been registered in ClinicalTrials.gov, NCT05314309, and is complete.

FINDINGS

Between March 25 and Dec 7, 2022, 35 786 individuals were invited to participate in the study, of whom 15 283 (42·7%) consented, and 13 187 (86·3%) of 15 283 provided both mtFIT and FIT samples with valid results. Of the 13 187 participants, 6637 (50·3%) were male and 6550 (49·7%) were female. mtFIT showed a 9·11% (95% CI 8·62-9·61) positivity rate and 2·27% (95% CI 2·02-2·54) detection rate for advanced neoplasia, compared with a positivity rate of 4·08% (3·75-4·43) and a detection rate of 1·21% (1·03-1·41) for FIT. Detection rates of mtFIT versus FIT were 0·20% (95% CI 0·13-0·29) versus 0·17% (0·11-0·27) for colorectal cancer; 1·64% (1·43-1·87) versus 0·86% (0·72-1·04) for advanced adenoma, and 0·43% (0·33-0·56) versus 0·17% (0·11-0·26) for advanced serrated polyps. Modelling demonstrated that mtFIT-based screening could reduce colorectal cancer incidence by 21% and associated mortality by 18% compared with the current Dutch colorectal cancer screening programme, at feasible costs. Furthermore, at equal positivity rates, mtFIT outperformed FIT in terms of diagnostic yield. At an equally low positivity rate, mtFIT-based screening was predicted to further decrease colorectal cancer incidence by 5% and associated mortality by 4% compared with FIT-based screening.

INTERPRETATION

The higher detection rate of mtFIT for advanced adenoma compared with FIT holds the potential to translate into additional and clinically meaningful long-term colorectal cancer incidence and associated mortality reductions in programmatic colorectal cancer screening.

FUNDING

Stand Up to Cancer, Dutch Cancer Society, Dutch Digestive Foundation, and Health~Holland.

Integrative Analysis of DNA Methylation and Gene Expression Profiles Identifies Colorectal Cancer-Related Diagnostic Biomarkers

Background: Colorectal cancer (CRC) is a common human malignancy worldwide. The prognosis of patients is largely frustrated by delayed diagnosis or misdiagnosis. DNA methylation alterations have been previously proved to be involved in CRC carcinogenesis.

Methods: In this study, we proposed to identify CRC-related diagnostic biomarkers by analyzing DNA methylation and gene expression profiles. TCGA-COAD datasets downloaded from the Cancer Genome Atlas (TCGA) were used as the training set to screen differential expression genes (DEGs) and methylation CpG sites (dmCpGs) in CRC samples. A logistic regression model was constructed based on hyper-methylated CpG sites which were located in downregulated genes for CRC diagnosis. Another two independent datasets from the Gene Expression Omnibus (GEO) were used as a testing set to evaluate the performance of the model in CRC diagnosis.

Results: We found that CpG island methylator phenotype (CIMP) was a potential signature of poor prognosis by dividing CRC samples into CIMP and noCIMP groups based on a set of CpG sites with methylation standard deviation (sd) > 0.2 among CRC samples and low methylation levels (mean β < 0.05) in adjacent samples. Hyper-methylated CpGs tended to be more closed to CpG island (CGI) and transcription start site (TSS) relative to hypo-methylated CpGs (p-value < 0.05, Fisher exact test). A logistic regression model was finally constructed based on two hyper-methylated CpGs, which had an area under receiver operating characteristic curve of 0.98 in the training set, and 0.85 and 0.95 in the two independent testing sets.

Conclusions: In conclusion, our study identified promising DNA methylation biomarkers for CRC diagnosis.

Comprehensive Analysis of RNA Expression Correlations between Biofluids and Human Tissues

In recent years, biofluid has been considered a promising source of non-invasive biomarkers for health monitoring and disease diagnosis. However, the expression consistency between biofluid and human tissue, which is fundamental to RNA biomarker development, has not been fully evaluated. In this study, we collected expression profiles across 53 human tissues and five main biofluid types. Utilizing the above dataset, we uncovered a globally positive correlation pattern between various biofluids (including blood, urine, bile, saliva and stool) and human tissues. However, significantly varied biofluid-tissue similarity levels and tendencies were observed between mRNA and lncRNA. Moreover, a higher correlation was found between biofluid types and their functionally related and anatomically closer tissues. In particular, a highly specific correlation was discovered between urine and the prostate. The biological sex of the donor was also proved to be an important influencing factor in biofluid-tissue correlation. Moreover, genes enriched in basic biological processes were found to display low variability across biofluid types, while genes enriched in catabolism-associated pathways were identified as highly variable.

Colorectal Cancer Screening Methods and Molecular Markers for Early Detection

Colorectal cancer (CRC) is one of the most common malignant tumors in the digestive tract in humans. The development of colorectal cancer is composed of multiple stages, starting with benign adenomatous polyps in the inner wall of the large intestine and rectum, and then gradually developing. Then it developed into advanced adenomas carcinoma in situ and invasive carcinoma. Represents the distant metastasis of the most advanced development. The purpose of this review is to novel routine screening and diagnostic methods (e.g., Endoscopy and CT colonoscopy, SEPT9 methylation assay, Fecal test) and find reliable molecular markers for early diagnosis of CRC.

Multitarget Stool DNA Test Performance in an Average-Risk Colorectal Cancer Screening Population

INTRODUCTION

We set out to evaluate the performance of a multitarget stool DNA (MT-sDNA) in an average-risk colonoscopy-controlled colorectal cancer (CRC) screening population. MT-sDNA stool test results were evaluated against fecal immunochemical test (FIT) results for the detection of different lesions, including molecularly defined high-risk adenomas and several other tumor characteristics.

METHODS

Whole stool samples (n = 1,047) were prospectively collected and subjected to an MT-sDNA test, which tests for KRAS mutations, NDRG4 and BMP3 promoter methylation, and hemoglobin. Results for detecting CRC (n = 7), advanced precancerous lesions (advanced adenoma [AA] and advanced serrated polyps; n = 119), and non-AAs (n = 191) were compared with those of FIT alone (thresholds of 50, 75, and 100 hemoglobin/mL). AAs with high risk of progression were defined by the presence of specific DNA copy number events as measured by low-pass whole genome sequencing.

RESULTS

The MT-sDNA test was more sensitive than FIT alone in detecting advanced precancerous lesions (46% (55/119) vs 27% (32/119), respectively, P < 0.001). Specificities among individuals with nonadvanced or negative findings (controls) were 89% (791/888) and 93% (828/888) for MT-sDNA and FIT testing, respectively. A positive MT-sDNA test was associated with multiple lesions (P = 0.005), larger lesions (P = 0.03), and lesions with tubulovillous architecture (P = 0.04). The sensitivity of the MT-sDNA test or FIT in detecting individuals with high-risk AAs (n = 19) from individuals with low-risk AAs (n = 52) was not significantly different.

DISCUSSION

In an average-risk screening population, the MT-sDNA test has an increased sensitivity for detecting advanced precancerous lesions compared with FIT alone. AAs with a high risk of progression were not detected with significantly higher sensitivity by MT-sDNA or FIT.

Genomics of Particulate Matter Exposure Associated Cardiopulmonary Disease: A Narrative Review

Particulate matter (PM) exposure is associated with the development of cardiopulmonary disease. Our group has studied the adverse health effects of World Trade Center particulate matter (WTC-PM) exposure on firefighters. To fully understand the complex interplay between exposure, organism, and resultant disease phenotype, it is vital to analyze the underlying role of genomics in mediating this relationship. A PubMed search was performed focused on environmental exposure, genomics, and cardiopulmonary disease. We included original research published within 10 years, on epigenetic modifications and specific genetic or allelic variants. The initial search resulted in 95 studies. We excluded manuscripts that focused on work-related chemicals, heavy metals and tobacco smoke as primary sources of exposure, as well as reviews, prenatal research, and secondary research studies. Seven full-text articles met pre-determined inclusion criteria, and were reviewed. The effects of air pollution were evaluated in terms of methylation (n = 3), oxidative stress (n = 2), and genetic variants (n = 2). There is evidence to suggest that genomics plays a meditating role in the formation of adverse cardiopulmonary symptoms and diseases that surface after exposure events. Genomic modifications and variations affect the association between environmental exposure and cardiopulmonary disease, but additional research is needed to further define this relationship.