Another candidate for inexpensive cancer detection blood tests

A Hong Kong scientist who invented a simple blood test to show pregnant women if their babies have Down syndrome is now testing a similar technology for cancer.

Yuk Ming “Dennis” Lo says screening for signs of cancer from a simple blood draw could cost as little as $1,000. The test works by studying DNA released into a person’s bloodstream by dying tumor cells.

The prenatal tests work by searching for fetal DNA present in a pregnant woman’s blood. Decoding that DNA can determine whether the baby has too many or too few chromosomes, problems that cause birth defects.

Both Lo and scientists at Johns Hopkins recently used a technique nearly identical to the one used in the prenatal tests to demonstrate that they could scan a person’s blood for evidence of genes that are duplicated, missing, or rearranged, something that is a hallmark of cancer cells.

PNAS – Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

Tumor DNA is often present in tiny quantities if the cancer is at an early stage. It may account for just 0.01 percent of the DNA fragments in a blood sample. That means scientists end up decoding 9,999 bits of normal DNA for every stretch of cancer DNA they encounter. The result: building up a rough snapshot of the tumor’s genome using sequencing machines can cost $10,000 or more.

Lo says he’s now developing a different way to measure DNA that could cut the cost of the cancer test by about 90 percent.

The new method looks for changes in methylation—a chemical modification to DNA that controls gene activity. The genes of cancer cells widely lose their methylation marks, a feature that Lo says can be reliably spotted using less sequencing.

Lo is testing his technique in Hong Kong by following 20,000 people at risk for cancer as part of a $4 million study paid for by the Hong Kong government. Many are infected with hepatitis B, a virus that can cause liver cancer and is carried by about 10 percent of the Chinese population.

Lo licensed his patents on prenatal testing to a California company, Sequenom, which launched a pregnancy test in 2011.

Significance of Genome-wide hypomethylation blood analysis

Genome-wide hypomethylation is frequently observed in cancers. In this study, we showed that genome-wide hypomethylation analysis in plasma using shotgun massively parallel bisulfite sequencing is a powerful general approach for the detection of multiple types of cancers. This approach is particularly attractive because high sensitivity and specificity can be achieved using low sequence depth, which is practical diagnostically. This approach can also be used for monitoring patients following treatment. The same sequencing data can be further used for detecting cancer-associated copy number aberrations at no additional costs. One could thus combine plasma hypomethylation and copy number analyses in a synergistic manner for further enhancing detection sensitivity or specificity.

Abstract of Genome-wide hypomethylation blood analysis

We explored the detection of genome-wide hypomethylation in plasma using shotgun massively parallel bisulfite sequencing as a marker for cancer. Tumor-associated copy number aberrations (CNAs) could also be observed from the bisulfite DNA sequencing data. Hypomethylation and CNAs were detected in the plasma DNA of patients with hepatocellular carcinoma, breast cancer, lung cancer, nasopharyngeal cancer, smooth muscle sarcoma, and neuroendocrine tumor. For the detection of nonmetastatic cancer cases, plasma hypomethylation gave a sensitivity and specificity of 74% and 94%, respectively, when a mean of 93 million reads per case were obtained. Reducing the sequencing depth to 10 million reads per case was found to have no adverse effect on the sensitivity and specificity for cancer detection, giving respective figures of 68% and 94%. This characteristic thus indicates that analysis of plasma hypomethylation by this sequencing-based method may be a relatively cost-effective approach for cancer detection. We also demonstrated that plasma hypomethylation had utility for monitoring hepatocellular carcinoma patients following tumor resection and for detecting residual disease. Plasma hypomethylation can be combined with plasma CNA analysis for further enhancement of the detection sensitivity or specificity using different diagnostic algorithms. Using the detection of at least one type of aberration to define an abnormality, a sensitivity of 87% could be achieved with a specificity of 88%. These developments have thus expanded the applications of plasma DNA analysis for cancer detection and monitoring.

PNAS – Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

Significance of 2013 PNAS work

Genome-wide hypomethylation is frequently observed in cancers. In this study, we showed that genome-wide hypomethylation analysis in plasma using shotgun massively parallel bisulfite sequencing is a powerful general approach for the detection of multiple types of cancers. This approach is particularly attractive because high sensitivity and specificity can be achieved using low sequence depth, which is practical diagnostically. This approach can also be used for monitoring patients following treatment. The same sequencing data can be further used for detecting cancer-associated copy number aberrations at no additional costs. One could thus combine plasma hypomethylation and copy number analyses in a synergistic manner for further enhancing detection sensitivity or specificity.

Abstract of 2013 PNAS work

We explored the detection of genome-wide hypomethylation in plasma using shotgun massively parallel bisulfite sequencing as a marker for cancer. Tumor-associated copy number aberrations (CNAs) could also be observed from the bisulfite DNA sequencing data. Hypomethylation and CNAs were detected in the plasma DNA of patients with hepatocellular carcinoma, breast cancer, lung cancer, nasopharyngeal cancer, smooth muscle sarcoma, and neuroendocrine tumor. For the detection of nonmetastatic cancer cases, plasma hypomethylation gave a sensitivity and specificity of 74% and 94%, respectively, when a mean of 93 million reads per case were obtained. Reducing the sequencing depth to 10 million reads per case was found to have no adverse effect on the sensitivity and specificity for cancer detection, giving respective figures of 68% and 94%. This characteristic thus indicates that analysis of plasma hypomethylation by this sequencing-based method may be a relatively cost-effective approach for cancer detection. We also demonstrated that plasma hypomethylation had utility for monitoring hepatocellular carcinoma patients following tumor resection and for detecting residual disease. Plasma hypomethylation can be combined with plasma CNA analysis for further enhancement of the detection sensitivity or specificity using different diagnostic algorithms. Using the detection of at least one type of aberration to define an abnormality, a sensitivity of 87% could be achieved with a specificity of 88%. These developments have thus expanded the applications of plasma DNA analysis for cancer detection and monitoring.

PNAS – Size-based molecular diagnostics using plasma DNA for noninvasive prenatal testing

Significance on DNA prenatal Testing

Noninvasive prenatal testing (NIPT) using fetal DNA in maternal plasma has been rapidly adopted worldwide. Current NIPT for fetal chromosomal disorders are based on the counting of DNA molecules in maternal plasma. Here, we show that plasma DNA-based molecular diagnostics can also be built around DNA fragment size, instead of count. First, we demonstrate that the fetal DNA fraction in maternal plasma can be rapidly measured by size analysis, even simply using microchip-based capillary electrophoresis. Second, we show that plasma DNA size analysis can be used for the detection of multiple types of fetal chromosomal aneuploidies with high accuracy. This strategy has many potential diagnostic applications, e.g., in oncology and transplantation monitoring.

Abstract on DNA prenatal Testing

Noninvasive prenatal testing using fetal DNA in maternal plasma is an actively researched area. The current generation of tests using massively parallel sequencing is based on counting plasma DNA sequences originating from different genomic regions. In this study, we explored a different approach that is based on the use of DNA fragment size as a diagnostic parameter. This approach is dependent on the fact that circulating fetal DNA molecules are generally shorter than the corresponding maternal DNA molecules. First, we performed plasma DNA size analysis using paired-end massively parallel sequencing and microchip-based capillary electrophoresis. We demonstrated that the fetal DNA fraction in maternal plasma could be deduced from the overall size distribution of maternal plasma DNA. The fetal DNA fraction is a critical parameter affecting the accuracy of noninvasive prenatal testing using maternal plasma DNA. Second, we showed that fetal chromosomal aneuploidy could be detected by observing an aberrant proportion of short fragments from an aneuploid chromosome in the paired-end sequencing data. Using this approach, we detected fetal trisomy 21 and trisomy 18 with 100% sensitivity (T21: 36/36; T18: 27/27) and 100% specificity (non-T21: 88/88; non-T18: 97/97). For trisomy 13, the sensitivity and specificity were 95.2% (20/21) and 99% (102/103), respectively. For monosomy X, the sensitivity and specificity were both 100% (10/10 and 8/8). Thus, this study establishes the principle of size-based molecular diagnostics using plasma DNA. This approach has potential applications beyond noninvasive prenatal testing to areas such as oncology and transplantation monitoring.