MAESTRO-Pool Enables Highly Parallel and Specific Mutation-Enrichment Sequencing for Minimal Residual Disease Detection in Cohort Studies Article Swipe
Timothy Blewett
,
Justin Rhoades
,
Ruolin Liu
,
Kan Xiong
,
Sainetra Sridhar
,
Andjela Crnjac
,
Ju Cheng
,
Aleigha Lawless
,
Dennie T. Frederick
,
Keith T. Flaherty
,
G. Mike Makrigiorgos
,
Viktor A. Adalsteinsson
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1093/clinchem/hvad203
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1093/clinchem/hvad203
Background Tracing patient-specific tumor mutations in cell-free DNA (cfDNA) for minimal residual disease (MRD) detection is promising but challenging. Assaying more mutations and cfDNA stands to improve MRD detection but requires highly accurate, efficient sequencing methods and proper calibration to prevent false detection with bespoke tests. Methods MAESTRO (Minor Allele Enriched Sequencing Through Recognition Oligonucleotides) uses mutation-specific oligonucleotide probes to enrich cfDNA libraries for tumor mutations and enable their accurate detection with minimal sequencing. A new approach, MAESTRO-Pool, which entails pooling MAESTRO probes for all patients and applying these to all samples from all patients, was used to screen for 22 333 tumor mutations from 9 melanoma patients in 98 plasma samples. This enabled quantification of MRD detection in patient-matched samples and false detection in unmatched samples from other patients. To detect MRD, a new dynamic MRD caller was used that computes a probability for MRD detection based on the number of mutations and cfDNA molecules sequenced, thereby calibrating for variations in each bespoke test. Results MAESTRO-Pool enabled sensitive detection of MRD down to 0.78 parts per million (ppm), reflecting a 10- to 100-fold improvement over existing tests. Of the 8 MRD positive samples with ultra-low tumor fractions <10 ppm, 7 were either in upward-trend preceding recurrence or downward-trend aligning with response. Of 784 patient-unmatched tests, only one was found as MRD positive (tumor fraction = 2.7 ppm), suggesting high specificity. Conclusions MAESTRO-Pool enables massively parallel, tumor-informed MRD testing with concurrent benchmarking of bespoke MRD tests. Meanwhile, our new MRD caller enables more mutations and cfDNA molecules to be tested without compromising specificity. These improve the ability for detecting traces of MRD from blood.
Related Topics
Concepts
Minimal residual disease
Massive parallel sequencing
Bespoke
Mutation
Medicine
DNA sequencing
Computational biology
Oncology
Genetics
Internal medicine
Biology
Gene
Leukemia
Law
Political science
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/clinchem/hvad203
- OA Status
- green
- Cited By
- 10
- References
- 17
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4389509882
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4389509882Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/clinchem/hvad203Digital Object Identifier
- Title
-
MAESTRO-Pool Enables Highly Parallel and Specific Mutation-Enrichment Sequencing for Minimal Residual Disease Detection in Cohort StudiesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-12-09Full publication date if available
- Authors
-
Timothy Blewett, Justin Rhoades, Ruolin Liu, Kan Xiong, Sainetra Sridhar, Andjela Crnjac, Ju Cheng, Aleigha Lawless, Dennie T. Frederick, Keith T. Flaherty, G. Mike Makrigiorgos, Viktor A. AdalsteinssonList of authors in order
- Landing page
-
https://doi.org/10.1093/clinchem/hvad203Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://pmc.ncbi.nlm.nih.gov/articles/PMC10847667/pdf/hvad203.pdfDirect OA link when available
- Concepts
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Minimal residual disease, Massive parallel sequencing, Bespoke, Mutation, Medicine, DNA sequencing, Computational biology, Oncology, Genetics, Internal medicine, Biology, Gene, Leukemia, Law, Political scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
10Total citation count in OpenAlex
- Citations by year (recent)
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2025: 7, 2024: 3Per-year citation counts (last 5 years)
- References (count)
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17Number of works referenced by this work
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-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.blood. | 274 |
| abstract_inverted_index.caller | 138, 251 |
| abstract_inverted_index.detect | 132 |
| abstract_inverted_index.either | 203 |
| abstract_inverted_index.enable | 68 |
| abstract_inverted_index.enrich | 61 |
| abstract_inverted_index.highly | 32 |
| abstract_inverted_index.number | 151 |
| abstract_inverted_index.plasma | 111 |
| abstract_inverted_index.probes | 59, 83 |
| abstract_inverted_index.proper | 38 |
| abstract_inverted_index.screen | 99 |
| abstract_inverted_index.stands | 25 |
| abstract_inverted_index.tested | 260 |
| abstract_inverted_index.tests, | 216 |
| abstract_inverted_index.tests. | 46, 188, 246 |
| abstract_inverted_index.traces | 270 |
| abstract_inverted_index.(cfDNA) | 9 |
| abstract_inverted_index.MAESTRO | 48, 82 |
| abstract_inverted_index.Methods | 47 |
| abstract_inverted_index.Results | 166 |
| abstract_inverted_index.Through | 53 |
| abstract_inverted_index.Tracing | 2 |
| abstract_inverted_index.ability | 267 |
| abstract_inverted_index.bespoke | 45, 164, 244 |
| abstract_inverted_index.disease | 13 |
| abstract_inverted_index.dynamic | 136 |
| abstract_inverted_index.enabled | 114, 168 |
| abstract_inverted_index.enables | 234, 252 |
| abstract_inverted_index.entails | 80 |
| abstract_inverted_index.improve | 27, 265 |
| abstract_inverted_index.methods | 36 |
| abstract_inverted_index.million | 178 |
| abstract_inverted_index.minimal | 11, 73 |
| abstract_inverted_index.pooling | 81 |
| abstract_inverted_index.prevent | 41 |
| abstract_inverted_index.samples | 92, 121, 127, 194 |
| abstract_inverted_index.testing | 239 |
| abstract_inverted_index.thereby | 158 |
| abstract_inverted_index.without | 261 |
| abstract_inverted_index.100-fold | 184 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Assaying | 20 |
| abstract_inverted_index.Enriched | 51 |
| abstract_inverted_index.accurate | 70 |
| abstract_inverted_index.aligning | 210 |
| abstract_inverted_index.applying | 88 |
| abstract_inverted_index.computes | 142 |
| abstract_inverted_index.existing | 187 |
| abstract_inverted_index.fraction | 225 |
| abstract_inverted_index.melanoma | 107 |
| abstract_inverted_index.patients | 86, 108 |
| abstract_inverted_index.positive | 193, 223 |
| abstract_inverted_index.requires | 31 |
| abstract_inverted_index.residual | 12 |
| abstract_inverted_index.samples. | 112 |
| abstract_inverted_index.accurate, | 33 |
| abstract_inverted_index.approach, | 77 |
| abstract_inverted_index.cell-free | 7 |
| abstract_inverted_index.detecting | 269 |
| abstract_inverted_index.detection | 15, 29, 43, 71, 118, 124, 147, 170 |
| abstract_inverted_index.efficient | 34 |
| abstract_inverted_index.fractions | 198 |
| abstract_inverted_index.libraries | 63 |
| abstract_inverted_index.massively | 235 |
| abstract_inverted_index.molecules | 156, 257 |
| abstract_inverted_index.mutations | 5, 22, 66, 104, 153, 254 |
| abstract_inverted_index.parallel, | 236 |
| abstract_inverted_index.patients, | 95 |
| abstract_inverted_index.patients. | 130 |
| abstract_inverted_index.preceding | 206 |
| abstract_inverted_index.promising | 17 |
| abstract_inverted_index.response. | 212 |
| abstract_inverted_index.sensitive | 169 |
| abstract_inverted_index.ultra-low | 196 |
| abstract_inverted_index.unmatched | 126 |
| abstract_inverted_index.&lt;10 | 199 |
| abstract_inverted_index.Background | 1 |
| abstract_inverted_index.Meanwhile, | 247 |
| abstract_inverted_index.Sequencing | 52 |
| abstract_inverted_index.concurrent | 241 |
| abstract_inverted_index.recurrence | 207 |
| abstract_inverted_index.reflecting | 180 |
| abstract_inverted_index.sequenced, | 157 |
| abstract_inverted_index.sequencing | 35 |
| abstract_inverted_index.suggesting | 229 |
| abstract_inverted_index.variations | 161 |
| abstract_inverted_index.Conclusions | 232 |
| abstract_inverted_index.Recognition | 54 |
| abstract_inverted_index.calibrating | 159 |
| abstract_inverted_index.calibration | 39 |
| abstract_inverted_index.improvement | 185 |
| abstract_inverted_index.probability | 144 |
| abstract_inverted_index.sequencing. | 74 |
| abstract_inverted_index.MAESTRO-Pool | 167, 233 |
| abstract_inverted_index.benchmarking | 242 |
| abstract_inverted_index.challenging. | 19 |
| abstract_inverted_index.compromising | 262 |
| abstract_inverted_index.specificity. | 231, 263 |
| abstract_inverted_index.upward-trend | 205 |
| abstract_inverted_index.MAESTRO-Pool, | 78 |
| abstract_inverted_index.downward-trend | 209 |
| abstract_inverted_index.quantification | 115 |
| abstract_inverted_index.tumor-informed | 237 |
| abstract_inverted_index.oligonucleotide | 58 |
| abstract_inverted_index.patient-matched | 120 |
| abstract_inverted_index.patient-specific | 3 |
| abstract_inverted_index.Oligonucleotides) | 55 |
| abstract_inverted_index.mutation-specific | 57 |
| abstract_inverted_index.patient-unmatched | 215 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 12 |
| citation_normalized_percentile.value | 0.91052419 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |