A recent circulating tumour DNA (ctDNA) paper describes a comparison of ctDNA to CTC's with respect to TP53 mutations in 40 triple negative breast cancer patients. See: Circulating tumour DNA and circulating tumour cells in metastatic triple negative breast cancer patients in the International Journal of Cancer.
The group published a paper earlier in the year (Bidard et al Lancet Oncol 2014) where they counted CTCs before and during treatment in 2000 breast cancers, and reported a high prognostic impact on progression-free and overall survival, irrespective of breast cancer subtype. In this they discussed the biggest problem of CTCs being their very low prevalence, being found in under 50% of metastatic breast cancer patients. As such ctDNA looks like a much more accessible cancer biomarker, and it is one we've been investigating for a number of years here at the CRUK Cambridge Institute, primarily in the research groups of Nitzan Rosenfeld, Carlos Caldas and James Brenton.
In the Int. J. Cancer paper the group used archived tumour tissues and plasma DNA with TP53 sequencing on two NGS platforms, HiSeq and 454; which showed 97% concordance for TP53 mutation type. They chose TP53 because of its high likelihood of mutation in triple negative breast cancers. 26/31 patient samples generated TP53 sequence data and the same mutation was found in 21/26 (81%) patients with an additional mutation found in the plasma of one patient. Mutant allele frequencies were 2 to 70% (median 5%). ctDNA was not detected in 19% of patients, giving a sensitivity of 81% for ctDNA detection of TP53 mutations in triple negative breast cancer patients.
Unlike previous work by Sarah-Jane Dawson in the CRUK Cambridge Institute this group reported that ctDNA levels were not prognostic, and suggested that the mechanisms of ctDNA release may involve biological features that do not dramatically affect patient outcome (more about this at the end of this post). However, while CTC numbers were correlated with prognosis, baseline ctDNA levels were not. They also suggested that ctDNA might be predictive (more useful in identifying mutations that could provide therapeutic targets)rather than prognostic.
Detecting CTCs: The CTCs were detected using the Cellsearch system which defines CTCs as nucleated cells lacking CD45 expression and expressing cytokeratin, from 7.5 ml of blood. (What is CD45 and why does this kit not just find any non-blood cells). However the numbers of CTCs detected are shockingly low and the error rates of measuring CTCs could be quite high. In the study they reported that 30% of patients had no detectable CTCs, 20% had 1-4 CTCs and 45% had more than 5 CTCs. From a small blood-draw, these low numbers are likely to have some technical counting artefact's.
Detecting ctDNA TP53 mutations: The group used Access Array for Illumina, and standard PCR for 454, to amplify all exons and flanking regions of TP53. These PCRs were followed with a second-round of PCR to add either Illumina or 454 adapters making sequencing ready libraries.
Determining absolute ctDNA levels: any analysis of ctDNA means sequencing lots of contaminating normal cfDNA. The paper reported an interesting method to quantify ctDNA in diploid genome equivalents per ml of plasma by multiplying the level of cfcDNA measured by PLOT-PCR (LINE-1 optimised threshold qPCR) by the percentage of mutant TP53 fraction measured by sequencing. I like the figure they present in the paper, but seeing as mutant allele frequencies are often dependant on which mutation you look at their method may well over- or under-estimate absolute ctDNA levels.
|Figure 2 from Madic et al|
How does ctDNA get there: The Int. J. Cancer paper states that "ctDNA release is a passive bi-product of cancer cell death (apoptosis, necrosis. . .)" and that "how ctDNA release relates to tumor biology is currently unknown." It is likely to be critical to adoption of ctDNA as a clinical biomarker that we unravel the mechanisms of it's release: which cells does it come from, are all clones of a tumour contributing to total ctDNA levels at a level that reflects their clonal burden, does this change over time and with treatment, etc. These are some big questions to tackle!