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Abstract PR03: Molecular profiling of advanced solid tumors at Princess Margaret Cancer Centre and patient outcomes with genotype-matched clinical trials

2016· article· en· W2338707509 on OpenAlexaff
Philippe L. Bédard, Amit M. Oza, Blaise Clarke, Ming‐Sound Tsao, Natasha B. Leighl, Eric X. Chen, Albiruni R. Abdul Razak, Hal K. Berman, Stefano Serra, Michael H. A. Roehrl, Nadia Califaretti, Mateya Trinkaus, Tong Zhang, Mahadeo A. Sukhai, Anca Milea, Aaron R. Hansen, Trevor J. Pugh, Tracy Stockley, Suzanne Kamel‐Reid, Lillian L. Siu

Bibliographic record

VenueClinical Cancer Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsMarkham Stouffville HospitalGrand River HospitalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineInternal medicineAmpliconOncologyClinical trialGenotypeMolecular diagnosticsGenotypingMolecular pathologyResponse Evaluation Criteria in Solid TumorsBioinformaticsGeneGeneticsBiologyPolymerase chain reactionPhases of clinical research

Abstract

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Abstract Background: IMPACT and COMPACT are ongoing clinical trials at Princess Margaret (PM) to match advanced solid tumor patients with actionable somatic mutations to clinical trials with investigational therapies [NCT01505400]. We compared the outcome of patients profiled at PM treated on genotype-matched versus genotype-unmatched clinical trials. Methods: Patients with advanced solid tumors treated at PM or collaborating local institutions with available formalin fixed paraffin-embedded (FFPE) tumor tissue were prospectively consented for molecular profiling during standard treatment. Only patients with ECOG performance status ≤1 who were considered therapeutic trial candidates by their treating oncologist were eligible. Following pathology review, tumor DNA from FFPE blocks or unstained slides was extracted and genotyped using a customized Sequenom SNP genotyping panel (23 genes, 279 mutations) or a targeted next generation sequencing (NGS) panel, either the Illumina MiSeq TruSeq Amplicon Cancer Panel (48 genes, 212 amplicons) or the Ion Proton Ampliseq Cancer Hotspot Panel version 2 (50 genes, 207 amplicons) with ≤500x coverage in a Clinical Laboratory Improvement Amendments (CLIA) certified laboratory. An annotated molecular profiling report with somatic variants classified according to clinical actionability was included in the patient's electronic medical record. Oncologists were provided with regular summary tables of their patients' molecular profiling results and mutation-specific clinical trial listings to facilitate genotype-matched trial enrolment. Results: From March 2012 to July 2014, 1893 patients were enrolled with gynaecological (22%), breast (18%), lung (18%) colorectal (17%), pancreatobiliary (8%), upper aerodigestive (6%), genitourinary (5%), and other (5%) cancers. Patients had received a median of 4 prior systemic treatments (range 1-23). Of 253 (13%) screen failures, 10% were for insufficient tissue and 3% for clinical deterioration or other reasons. Patients were more likely to have one or more somatic mutations identified by NGS testing [597/813 (73%); average 1.23 mutations/patient; range 0-9 mutations/patient] compared with SNP genotyping [341/827 (41%); average 0.46 mutations/patient; range 0-2 mutations/patient; p<0.0001]. After a median follow-up of 18 months, a total of 244 patients (13%) were treated on 287 therapeutic clinical trials, including 84 patients (4%) on 92 genotype-matched trials. There was no difference in the proportion of trial enrolment onto genotype-matched therapies between patients profiled on Sequenom compared with targeted NGS [63/176 (36%) vs 29/101 (29%); p=0.23). Patients with pancreatobiliary and upper aerodigestive tract cancers were least likely to be treated on genotype-matched trials. A higher proportion of patients enrolled in genotype-matched trials were treated in phase I studies (80%) compared with genotype-unmatched trials (45%; p<0.001). The overall response rate by RECIST version 1.1 was higher in patients treated on genotype-matched trials (20%) compared with genotype-unmatched trials (11%; p<0.04). Patients treated on genotype-matched trials were more likely to achieve a best response of any shrinkage in the sum of their target lesions (61%) compared with patients treated on genotype-unmatched trials (32%; p<0.001). Conclusions: Few advanced solid tumor patients enrolled in a prospective institutional molecular profiling program were subsequently treated on genotype-matched therapeutic trials. Compared with SNP genotyping, profiling with a broader NGS panel did not increase the likelihood of receiving treatment on a genotype-matched trial. In this non-randomized comparison, genotype-enrichment of early phase clinical trials was associated with an increased objective tumor response rate. Greater efforts should be made to expand opportunities for genotype-trial matching and further studies are needed to evaluate the clinical utility of targeted NGS profiling. This abstract is also presented as Poster 18. Citation Format: Philippe L. Bedard, Amit Oza, Blaise Clarke, Ming-Sound Tsao, Natasha B. Leighl, Eric X. Chen, Albiruni Razak, Hal K. Berman, Stefano Serra, Michael Roehrl, Nadia Califaretti, Mateya Trinkaus, Tong Zhang, Mahadeo A. Sukhai, Anca Milea, Aaron R. Hansen, Trevor J. Pugh, Tracy Stockley, Suzanne Kamel-Reid, Lillian L. Siu. Molecular profiling of advanced solid tumors at Princess Margaret Cancer Centre and patient outcomes with genotype-matched clinical trials. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr PR03.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.120
GPT teacher head0.495
Teacher spread0.376 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations6
Published2016
Admission routes1
Has abstractyes

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