<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-23T13:36:03Z</responseDate><request verb="GetRecord" identifier="oai:www.repository.cam.ac.uk:1810/293567" metadataPrefix="uketd_dc">https://api.repository.cam.ac.uk/server/oai/request</request><GetRecord><record><header><identifier>oai:www.repository.cam.ac.uk:1810/293567</identifier><datestamp>2025-12-20T03:08:59Z</datestamp><setSpec>com_1810_245118</setSpec><setSpec>com_1810_34581</setSpec><setSpec>col_1810_245119</setSpec></header><metadata><uketd_dc:uketddc xmlns:uketd_dc="http://naca.central.cranfield.ac.uk/ethos-oai/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:uketdterms="http://naca.central.cranfield.ac.uk/ethos-oai/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://naca.central.cranfield.ac.uk/ethos-oai/2.0/ http://naca.central.cranfield.ac.uk/ethos-oai/2.0/uketd_dc.xsd">
   <dc:title>Monitoring trace levels of ctDNA using integration of variant reads</dc:title>
   <dc:identifier xsi:type="dcterms:DOI">10.17863/CAM.40703</dc:identifier>
   <dc:creator>Wan, Jonathan Chee Ming</dc:creator>
   <uketdterms:authoridentifier xsi:type="uketdterms:ORCID">0000000300011802</uketdterms:authoridentifier>
   <uketdterms:advisor>Rosenfeld, Nitzan</uketdterms:advisor>
   <dcterms:abstract>In patients with early-stage cancer, ctDNA detection rates can be low due to the presence of
few or no copies of any individual mutation in each sample. Sensitivity may be increased
by collecting larger plasma volumes, but this is not feasible in practice. Although cancers
typically have thousands of mutations in their genome, previous analyses measured only
individual or up to 32 tumour-specific mutations in plasma.

Here, we demonstrate that sensitivity can be greatly enhanced for any given input DNA
mass by analysing a large number of mutations via sequencing. We sequenced in plasma
10^2-10^4 mutated loci per patient, using custom capture panels, whole exome (WES) or
whole genome sequencing (WGS). We developed a method for INtegration of VAriant Reads
 (INVAR) that aggregates reads carrying tumour mutations across multiple mutant loci, and
assigns confidence to error-suppressed reads based on mutation context, fragment length and
tumour representation. This workflow combines a number of concepts in a novel approach in
order to quantify ctDNA with maximal sensitivity.

We applied INVAR to plasma sequencing data from 45 patients with stage II-IV melanoma
and 26 healthy individuals. ctDNA was detected to 1 mutant molecule per million, and tumour volumes of ~1cm^3. We show that this algorithm is applicable across targeted and
untargeted sequencing methods. In patients with stage II-III melanoma who relapsed after
resection, ctDNA was detected within 6 months post-surgery and prior to relapse in 50% of
cases, compared to 16% in a similar cohort analysed with digital PCR. In addition, INVAR
may enhance detection of ctDNA in samples with limited input or sequencing coverage by
aggregating signal across a large number of mutations. Using low-depth WGS (0.6x), ctDNA
was detected to 1 mutant per 10,000 molecules. Given that 60 genome copies of cfDNA may
be obtained from 1 drop of blood (50-75μL), we suggest that INVAR may enable cancer
monitoring from limited samples volumes.

As tumour sequencing becomes more widespread allowing identification of a large
number of mutations per patient, this method has potential to quantify ctDNA with enhanced
sensitivity, and to enable routine cancer monitoring using low-depth sequencing, potentially
from low-volume blood samples that might be self-collected.</dcterms:abstract>
   <uketdterms:institution>University of Cambridge</uketdterms:institution>
   <dcterms:issued>2019-10-01</dcterms:issued>
   <dc:type>Thesis</dc:type>
   <uketdterms:qualificationlevel>Doctoral</uketdterms:qualificationlevel>
   <uketdterms:qualificationname>Doctor of Philosophy (PhD)</uketdterms:qualificationname>
   <dc:language>en</dc:language>
   <uketdterms:sponsor>Cancer Research UK</uketdterms:sponsor>
   <dcterms:isReferencedBy xsi:type="dcterms:URI">https://www.repository.cam.ac.uk/handle/1810/293567</dcterms:isReferencedBy>
   <dc:identifier xsi:type="dcterms:URI">https://www.repository.cam.ac.uk/bitstreams/2e91212f-74e2-46cd-9ded-9c1aaf6293ef/download</dc:identifier>
   <uketdterms:checksum xsi:type="uketdterms:MD5">2d36bdfbd010447fc50722435a232cdf</uketdterms:checksum>
   <dcterms:license>https://www.repository.cam.ac.uk/bitstreams/37624289-ed31-4e1f-b8c6-b731b46f58e4/download</dcterms:license>
   <uketdterms:checksum xsi:type="uketdterms:MD5">87eda9de84448d1f82354d60eee3eb5f</uketdterms:checksum>
   <dc:rights>https://www.rioxx.net/licenses/all-rights-reserved/</dc:rights>
   <dc:subject>liquid biopsy</dc:subject>
   <dc:subject>circulating tumour DNA</dc:subject>
   <dc:subject>ctDNA</dc:subject>
   <dc:subject>cancer genomics</dc:subject>
   <dc:subject>bioinformatics</dc:subject>
   <dc:subject>cancer</dc:subject>
   <dc:subject>melanoma</dc:subject>
   <dc:subject>circulating nucleic acids</dc:subject>
</uketd_dc:uketddc>
</metadata></record></GetRecord></OAI-PMH>