Cell-free DNA for low-cost early cancer detection

The UCLA-led Johnson Comprehensive Cancer Center led the study to test a cost-effective way to detect early cancer from cells in blood samples
.

Early detection remains the key to successful treatment of many cancers
.
Increasingly, research is focusing on early detection through cell-free DNA (cfDNA) in the blood circulation, the so-called "liquid biopsy.
"
However, due to the genetic diversity of cancers and the low concentration of tumors in DNA blood fragments, using this method to detect cancers at an early stage is challenging
.

Now, researchers report the successful results of an experimental cancer detection system that appears to have overcome these challenges
in a novel and economical way.
The study, conducted by researchers at the University of California, Los Angeles (UCLA) Jonsson Comprehensive Cancer Center and its collaborating organizations, will be published today (September 29) in the journal Nature Communications
.

Their work highlights a method that saves more than 12 times the cost over traditional cfDNA methyl group sequencing methods, as well as a computational model for extracting information from DNA sequencing to aid in early detection and diagnosis
.

Cell free DNA methylation has proven to be one of
the most promising biomarkers for early cancer detection.
However, cfDNA aberration traits from different cancer types, subtypes, stages, and etiologies are different
.
This leads to significant challenges
in identifying methylated markers suitable for early detection.
This is of particular concern because the sample sizes currently available are small
compared to the diversity of diseases and patient populations (age, sex, ethnicity, and comorbidities).
Analysis of the cfDNA methyl group can solve this challenge because it preserves the genome-wide epigenetic profile
of cancer abnormalities.
Thus, as the training cohort grows, it allows taxonomic models to learn and develop new important features and extend their scope to more cancer types
.
However, traditional methods of analyzing the group's free DNA methyl group of cells are too costly
in clinical applications.

"Our method, cfMethyl-seq, makes cfDNA methyl group sequencing a viable option for clinical use," said
Xianghong "Jasmine" Zhou.
She is the corresponding author of the study and a professor of pathology and laboratory medicine at
UCLA.
"Despite the inherent challenges, our research shows great potential
for accurate early diagnosis of certain cancers with a single blood test.
"

Zhou and her colleagues at UCLA lab focus on precision medicine
.
This includes using patient genomic information to develop more personalized and targeted treatments, as well as large-scale biodata analysis that integrates complex data from different platforms and models into practical methods that can be used clinically
.
In the study, Zhou and collaborators put their new method to the test to see if it could accurately detect four common cancers — colon, liver, lung and stomach — and do so
at an early stage.

The scientists collected blood samples from 408 study participants and applied a methyl-group-based blood test that can identify a wide range of markers for different cancer types and possible causes
.
Of these, 217 were cancer patients and 191 were cancer-free control subjects
.
Samples are collected at UCLA hospitals or purchased from commercial laboratories for cross-source validation
.
The researchers also performed cross-batch validation, age-match validation, and independent validation to prevent bias
in the study.
After collecting and validating the measures, the researchers fed the data into their sophisticated computer model to measure its accuracy in detecting cancer, as well as the specific location of the tumor, known as the "tissue of origin
.
" Their model has an accuracy rate of 80.
7% in detecting all stages of cancer and about 74.
5% accuracy in detecting early-stage cancer (stage I or II) with a specificity of just under 98%.

There is only one normal sample with a misclassification (false positive).

For the accuracy of the source tissue, the model correctly identified tumor locations, with an average accuracy of 89.
1% for all cancer stages and about 85%
for early stage patients.
"The key to early cancer detection is to identify true cancer biomarkers, which require a large cohort of trained samples to cover cancer and population heterogeneity, especially pan-cancer detection
.
" As the training cohort grows, our cfDNA methyl group approach allows for better weights
to include new labels and existing labels.
In fact, our data show that the detection capabilities of our method continue to increase as the training sample size increases," said Zhou, a member of
the UCLA Johnson Comprehensive Cancer Center Gene Regulation Program.
"cfMethyl-seq's cost-effective methyl group sequencing can truly facilitate big data methods
for cancer detection.
"

The team is currently raising funds for large clinical trials to validate the technology, hoping to use it for the benefit of patients
.

Cost-effective Methylome Sequencing of Cell-free DNA for Accurately Detecting and Locating Cancer