Development and validation of a blood-based assay for gastric cancer early detection: A multidimensional analysis of cell-free DNA whole methylome sequencing—protocol for an observational, case‒control study

doi:10.21203/rs.3.rs-2730560/v1

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Study protocol

Development and validation of a blood-based assay for gastric cancer early detection: A multidimensional analysis of cell-free DNA whole methylome sequencing—protocol for an observational, case‒control study

https://doi.org/10.21203/rs.3.rs-2730560/v1

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Background

Cancer-related features in cell-free DNA (cfDNA) fragments have gradually been identified and play essential roles in noninvasive early cancer detection. Integrated analysis of several cfDNA features has enhanced detection sensitivity compared to single features. To facilitate early diagnosis of gastric cancer, an assay based on assessing genomic-scale methylation and fragmentation profiles of plasma cfDNA will be developed and validated for early cancer detection.

Methods

This is an observational case‒control study. Blood samples will be prospectively collected before gastroscopy from 180 gastric cancer patients and 180 nonmalignant control subjects (healthy or with benign gastric diseases). Cases and controls will be randomly divided into a training and a testing dataset at a ratio of 2:1. Plasma cfDNA will be isolated and extracted, followed by bisulfite-free low-depth whole methylome sequencing. A multidimensional model named THorough Epigenetic Marker Integration Solution (THEMIS) including methylation, fragmentation, and chromosomal copy number alternation will be constructed in the training dataset. The performance of the model in differentiating cancer patients from noncancer controls will then be evaluated in the testing dataset.

Discussion

This is the first registered case‒control study designed to investigate a stacked ensemble model integrating several cfDNA features, including methylation pattern, fragmentation profile, and chromosomal copy number alternation, in identifying the GC population. This study will reveal whether multidimensional analysis of cfDNA will be an effective strategy for differentiating GC patients from nonmalignant individuals in a Chinese population.

Trial registration

This study was approved by the Medical Ethics Committee of the First Affiliated Hospital of the Air Force Medical University (Xi’an, China; approval No. KY20222222-F-1) and registered on the Chinese Clinical Trial Registry with registration number ChiCTR2200065623. The study was registered on clinicalTrial.gov with a registration number: NCT05668910.

Gastric cancer

circulating cell-free DNA

early detection

methylation

fragmentation

chromosomal

whole methylone sequencing

Gastric cancer (GC) is one of the most commonly diagnosed digestive tract tumours, accounting for an estimated 1.08 million new cases and an estimated 769,000 deaths in 2020 globally (7.7% of total cancer-related deaths), ranking fifth for age-standardized incidence and fourth for cancer-related mortality worldwide (1). China is among the countries with the highest incidence rate of GC, albeit a gradual decline has been observed in recent years (2, 3). Early GC detection and timely treatment are strongly associated with a better prognosis for GC patients. In Japan and South Korea, population screening has been widely performed, resulting in effective diagnosis of tumours at early stages and improved survival rates (4). Unfortunately, most patients are diagnosed with advanced GC in China, probably owing to the large population and lack of standardized screening programs. Gastroscopy (upper gastrointestinal endoscope) and biopsy taken under gastroscopy are considered the gold-standard methods for GC diagnosis. However, gastroscopy is an invasive operation with poor compliance. Moreover, insufficient endoscopy physicians and endoscopic equipment as well as the unstandardized endoscopic examination in China makes endoscopy difficult for population screening (5).

Currently available noninvasive blood biomarker-based approaches could serve as a step before endoscope diagnosis and identify the high-risk GC population, but those methods are associated with high false-positives and high false-negatives, leading to possible overdiagnosis or underdiagnosis. Serological indicators such as H. pylori (Hp) antibodies are not specific for GC detection due to their strong association with atrophic gastritis and gastric ulcers (5). Other indicators, including serum pepsinogen (PG), serum gastrin-17 (G-17), and MG7-Ag, are not recommended for use alone due to their poor sensitivity and specificity (6). A new GC score system based on age, sex, PG, G-17, and HP antibodies was developed in China’s Early GC screening Process Expert Consensus (5). Although this new GC score system might have an improved prediction performance (7), the cost‒benefit of its clinical application needs to be analysed. Plasma tumour markers such as carcinoembryonic antigen (CEA), cancer antigen 19 − 9 (CA 19 − 9), CA 72 − 4, CA 125 and CA 242 are associated with patient prognosis but are not suitable for early cancer detection (8). Furthermore, circulating molecules such as miRNAs have gained attention; however, they have limited sensitivity and specificity (9, 10).

Rapid technological and analytical advancements have identified cell-free DNA (cfDNA) as a new simple and noninvasive method for early cancer detection with enhanced specificity and sensitivity. The cancer-related features of cfDNA have been exploited in several aspects to differentiate cancer samples from healthy cases: 1. genetic alterations (11–13); 2. microsatellite instability (14); 3. hypermethylation or hypomethylation of certain genes (15, 16) or genome-wide (17–19); 4. chromosomal alterations (20); and 5. unique fragmentation patterns (21, 22). Among them, cfDNA genetic alteration identification is challenging given the low fraction of mutation-bearing ctDNA fragments in early-stage disease or certain tumour types (23, 24). The combination of several features has enhanced detection sensitivity compared to a single feature in kidney cancer (25), hepatocellular cancer, and pancreatic ductal cancer (26). We have also previously developed a multidimensional ensemble model named THorough Epigenetic Marker Integration Solution (THEMIS), which integrates several cfDNA features, such as methylation patterns, chromosomal copy number alterations, and fragmentation profiles, enabling highly sensitive early detection in a pancancer cohort (27). In the subgroup comprising 114 GC patients and 497 healthy controls, the THEMIS model showed an estimated AUC of 0.983 for the training dataset (Fig. 1A) and 0.986 for the test dataset (Fig. 1B). However, the fact that the model was trained on a pan-cancer cohort and the control group does not contain individuals with benign gastric diseases limits its prediction reliability for GC.

This study aimed to develop a highly sensitive GC-specific THEMIS model for the early detection of GC. The study design is illustrated in Fig. 2. We will enroll GC patients in the malignant group, and the control group will include not only healthy individuals but also participants with benign gastric diseases such as gastritis, gastric ulcers, and gastric polyps. Therefore, a new model will be developed to differentiate malignant cancer from nonmalignant gastric status. A nonbisulfite enzymatic whole methylome sequencing (WMS) assay (28) will be applied so that the methylation signals from the cfDNA as well as the molecular fragmentation profile are well maintained. The seq data generated from cfDNA will then be analysed in the abovementioned several dimensions, including methylation pattern, chromosomal copy number alternation, and fragmentation profile. GC-related biomarkers such as PG, G17, and Hp will also be evaluated independently or combined with cfDNA feature model training to enhance the detection sensitivity. The overall clinical performance of the model as well as its performance in each clinical stage will be evaluated.

Study objectives

This study aims to develop and validate a novel blood-based whole methylome sequencing method followed by a multidimensional model to analyse several features of cfDNA for early GC detection. We expect that this noninvasive liquid biopsy assay could help to distinguish individuals with a high probability of GC who will be assigned a positive result and subsequently undergo a confirmed diagnosis by gastroscopy. Meanwhile, individuals with a negative test result indicate a low probability of GC, and they could be recommended for a deferred gastroscope and possibly a repeated test annually.

The primary objective is to validate the overall diagnostic specificity and sensitivity of the model and further in each clinical stage of GC.

The secondary objective is to investigate the specificity and sensitivity of the model in combination with possible biomarkers such as PG, G17, and/or Hp levels for early GC detection.

Timeline

The study is planned for 18 months, starting from November 2022 to April 2024.

Study Population

This study will enroll individuals who receive gastroscopy at Xijing Hospital of Air Force Military Medical University, Xi'an, China. Two groups will be formed based on gastroscopy results: a malignant group and a nonmalignant group. The malignant group included patients diagnosed with high-grade intraepithelial neoplasia or GC (> 50% of patients in stages I and II), while the nonmalignant group contained healthy individuals and patients with gastritis, gastric ulcers, gastric polyps or other benign gastric diseases. Clinical parameters such as personal history, family history of digestive tract cancer, gastroscopic results and gastric cancer staging will be collected for each subject. Blood samples will be collected for WMG analysis, the results of which will be used to establish a GC diagnostic model.

Inclusion criteria

Subjects will be enrolled after understanding and signing the informed consent form, and they must be eligible to participate according to the inclusion/exclusion criteria.

Inclusion criteria must be fulfilled: (1) 18 years and older; (2) complete clinical information; and (3) patients self-agree to join the study and with signed patient consent and good compliance.

The specific inclusion criteria for subjects to be included in the malignant group must be fulfilled: (1) according to the definition of AJCC's 8th Edition Cancer Staging Manual, patients with gastric adenocarcinoma confirmed by histopathology and with pathological stages of stage I-IV, including patients with oesophageal gastric junction adenocarcinoma (EGJ); and (2) had not previously received any local or systematic antitumour treatment.

Exclusion criteria

Subjects will be ineligible if any of the exclusion criteria are met: (1) diagnosed previously with any kind of malignant tumour; (2) have received total or partial gastrectomy; (3) have received bone marrow or organ or stem cell transplantation; (4) have received blood transfusion in the past 6 months; (5) ongoing fever or recipient of anti-inflammation therapy within 14 days prior to study blood draw; (6) female participants during pregnancy or lactation; and (7) incomplete clinical information or unqualified to participate in the study.

Discontinuing Study Interventions And Patient Withdrawal

If the ongoing study is later considered to be infeasible, the principal investigator (PI) shall submit a termination application to the Institutional Review Committee (IRC). The decision for the termination will be given by the IRC. After that, the PI shall provide a clinical trial termination report to the IRC.

Subjects may be withdrawn from the study for the following reasons:

Subjects request to leave the trial and withdraw informed consent.

Subjects refuse to have blood samples collected after informed consent.

Sufficient blood sample collection is difficult for the subjects.

Subjects who are enrolled by mistake and later judged inappropriate for the study.

Sample Collection

Twenty millilitres of peripheral blood will be collected from each subject and stored in a Cell-Free DNA Storage Tube (Cwbiotech). Each subject’s information, such as index, name, sample type and collection time, will be marked clearly. Blood samples shall be delivered to the lab within 72 hours and proceeded with plasma extraction. If in any case, the blood samples cannot be delivered to the lab on time, the plasma shall be extracted on site in the following steps: (1) blood samples are centrifuged at 4,000 × g for 15 min at 4°C and the upper layer containing plasma will be transferred to a new tube. Approximately 4 ml of plasma will be obtained and stored at − 80°C until use or -20℃ for no more than one month before transportation.

Cfdna Extraction

Plasma samples prepared in the previous step will be processed for cfDNA extraction by using the MagMAX Cell-Free DNA Isolation Kit (Thermo Fisher Scientific) per the manufacturer’s instructions. The quantity and quality of extracted cfDNA will be assessed with a Bioanalyzer 2100 (Agilent).

Wms Library Construction

The entire amount of extracted plasma cfDNA (capped at 15 ng if more are extracted) for each sample will be used to generate WMS libraries by NEBNext Enzymatic Methyl-seq Kit (New England Biolabs) according to manufacturer instructions with one modification: 100 ng of carrier RNA (TIANGEN) will be added before denaturation by sodium hydroxide. Libraries will be amplified with 9 cycles of PCR, followed by quantification by a Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific). After that, constructed libraries will be sequenced on a NovaSeq 6000 (Illumina) with a paired-end read length of 100 bp.

Model Establishment

The estimation dataset will be used to establish a machine learning model to predict cancer probability. The plasma cfDNA fragment characteristics, methylation status, etc., will be subjected to data preprocessing, feature filtering, and model selection, and their respective classifier models will be constructed. We previously defined those features as the methylated fragment ratio (MFR), chromosomal aneuploidy of featured fragments (CAFF), fragment size index (FSI), and fragment end motif (FEM).

MFR

Genomic methylation status has been altered extensively since the early cancer development stage. ctDNA released by cancer cells can change the methylation levels of cfDNA in the plasma. The whole genome will be tiled into nonoverlapping 1 Mb windows, the methylation levels of which will be quantified by the fraction of fragments with fully methylated CpGs, resulting in MFR.

CAFF

Cancer cells often have chromosomal instability, and partial or whole chromosomal arms are amplified or missing (29, 30). A previously described plasma aneuploidy (PA) score was calculated for each sample based on the copy number alternation levels of five chromosome arms, which exhibited the most dramatic copy number alterations compared to baseline samples (20).

FSI

The size frequency of ctDNA fragments released from cancer cells differs from cfDNA (33). The whole genome was tiled into nonoverlapping 1 Mb windows, from which the read ratio of short fragments (100–166 bp) to long fragments (169–240 bp) was calculated and defined as the FSI. The FSI of each sample was compared to the healthy population baseline, and the cancer risk for each subject was estimated.

FEM

The preferred FEMs of ctDNA differ from those of cfDNA due to DNA nuclease downregulation in the cfDNA fragmentation process (31). The frequency of a total of 256 4-nucleotide (i.e., 4-mer) fragment 5’ end motifs was analysed (refer) with the following modifications: (1) Fragments shorter than 171 bp were selected for analysis. (2) Only reads mapped to the Crick strand were used for calculation.

An ensemble classifier named Through Epigenetic Marker Integration Solution (THEMIS) based on a generalized linear model (GLM) with elastic-net penalization is developed, which is established by integration of the four abovementioned features: predicted cancer probability scores by MFR, FSI, and FEM along with the PA scores of CAFF. R packages such as CARET under 20-fold cross validation will be used.

Sample Size Estimate And Statistical Analysis

The sample size was estimated using the strategy mentioned in this article (32). Based on the abovementioned pilot study, the ensemble THEMIS model reached a sensitivity of 94% (need to be confirmed with our bioinformatics) under 95% specificity (Fig. 1). We expect that the new model integrating similar features as THEMIS will reach a sensitivity of at least 90%. If we allow the 95% confidence interval width of 0.08 (two-sided test alpha = 0.05), then at least 54 cancer cases are needed. If we would also expect a certain amount of drop-out, such as 10%, no less than 60 cases will be needed. The same number of patients will be enrolled in the nonmalignant control group in this case control study. The plan is to allocate the two groups of subjects by the same 2:1 ratio into training and testing datasets. A total of 360 subjects (180 cancer cases and 180 controls) will be enrolled to ensure at least 60 cases and 60 controls in the testing dataset. Therefore, the total number of subjects in each group shall be no less than 180. The malignant group and the control group will be matched by age and sex to minimize possible confounding factors (Fig. 2).

The area under the curve (AUC) constructed by receiver operator characteristic (ROC) analysis calculated by the pROC package will be used to evaluate individual classifier models as well as the ensembled model’s performance for differentiating cancer/noncancer. Clinical diagnosis results, including but not limited to gastroscopy and/or pathological determinations, are considered the “gold standard”. The cancer risk threshold (cut-off value) will be determined based on the training dataset. After that, the prediction performance of the established model will be evaluated in the testing dataset in several aspects, including sensitivity, specificity, positive prediction value (PPV), and negative prediction value (NPV). These variables as well as 95% confidence intervals will be calculated using the epiR package. Cohen’s Kappa score will be calculated by the vcd R package to demonstrate the concordance of the predicted results versus the pathological diagnostic results. A single blind analysis will be applied, which means that the bioinformatics analysts will be blinded to whether the subjects have gastric cancer or not. The results are considered significant if the p value < 0.05. All statistical analyses will be performed in R (R v.3.6.3).

Patient And Public Involvement Statement

Patients, healthy subjects, and the public will not be involved in our studies for reporting, designing, or implementing. We do not plan to inform the study participants of the results unless they apply for it.

The primary aim of this study was to evaluate the effectiveness of using combined cfDNA features based on whole methylome sequencing analysis for early cancer detection. If our model is incorporated into the current clinical practice, an individual with a positive result would subsequently undergo a gastroscopy and/or biopsy for GC determination, while a negative result would indicate that the individual has a low probability of having GC and is recommended for a deferred gastroscopy and possibly a repeated test annually.

The major strength of the study is that this is the first registered observational study, to our knowledge, designed to evaluate the integrated analysis of methylation patterns, fragmentation profiles, and chromosomal copy number changes in cfDNA for early GC detection. Additionally, cfDNA studies designed for the Chinese GC population are limited. Our study will reveal whether multidimensional analysis of cfDNA will be an effective strategy for differentiating GC patients from nonmalignant individuals in a Chinese population. The findings of this study will be of great value for improving early screening/early diagnosis and ultimately increasing the 5-year survival rate of GC patients.

This study has several potential limitations. The major limitation is that this is a case‒controlled study based on a small cohort. We are also aware that case‒control studies, especially those performed at a single site, may result in selection bias. Individuals enrolled in a single hospital may not be fully representative of a screening population. A large prospective validation in a screening population will be pursued before clinical use. Another limitation would be that it is impossible to include all the possible benign gastric disease types in the control group; therefore, the constructed model might have limited ability to differentiate gastric cancer from other types of benign diseases beyond this study. In addition, although the individuals will be prospectively collected in this study, the analysis will be carried out retrospectively. However, bioinformatics analysts will be blinded to the true pathological outcomes when validating the model in the testing cohort; thus, the analysis bias will be reduced.

Ethics approval and consent to participate

The design and implementation of this study strictly followed the Declaration of Helsinki and Chinese medical research norms and regulations. This protocol was approved by the Medical Ethics Committee of the First Affiliated Hospital of the Air Force Medical University (Xi’an, China; approval No. KY20222222-F-1). This study was also registered at ClinicalTrial.gov (NCT05668910).

All enrolled subjects will sign informed consent forms for blood sample retention, and they will be fully informed that their blood samples would be used for scientific experimental research. The primary principle of the study is to protect the rights and interests of the subjects while ensuring the scientific nature of the study and the authenticity of the data. The subjects shall be voluntary to participate in this study, and their privacy will be fully respected. Throughout the study, all the data will be anonymized and maintained with confidentiality.

Consent for publication

Not applicable.

Availability of data and materials

Unpublished data will be available from the corresponding author on reasonable request.

Acknowledgment

Not applicable.

Authors’ Contributions

YH and XL have designed the study concept and formulated the initial idea. XL is the principal investigator and is responsible for protocol review and approval. JW, WW, and RG were involved in the submission and obtain of ethical approval. NS, XS, YN, and WC were involved in development of the protocol. LX and YL were involved in manuscript drafting. All co-authors have reviewed and approved the final version.

Funding

This study was supported by the National Key R&D Program of China (2021YFC2500400).

Competing interests

NS, XS, YN, YL, LX, and WC are employed by Genecast Biotechnology Co., Ltd. Other authors have declared no conflicts of interest. The study is sponsored by Genecast Biotechnology, which will participate in the detection of the samples and has reviewed the manuscript and approved for publication.

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Competing interest reported. N.S., X.S., Y.N., Y.L., L.X., and W.C. are employed by Genecast Biotechnology Co., Ltd. Other authors have declared no conflicts of interest. The study is sponsored by Genecast Biotechnology, which will participate in the detection of the samples and has reviewed the manuscript and approved for publication.

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Version 1

posted

You are reading this latest preprint version

Development and validation of a blood-based assay for gastric cancer early detection: A multidimensional analysis of cell-free DNA whole methylome sequencing—protocol for an observational, case‒control study

Status:

Version 1

Abstract

Background

Methods

Discussion

Trial registration

Figures

Background

Methods And Design

Study objectives

Timeline

Study Population

Inclusion criteria

Exclusion criteria

Discontinuing Study Interventions And Patient Withdrawal

Sample Collection

Cfdna Extraction

Wms Library Construction

Model Establishment

MFR

CAFF

FSI

FEM

Sample Size Estimate And Statistical Analysis

Patient And Public Involvement Statement

Discussion

Declarations

References

Additional Declarations

Status:

Version 1