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Abstract PO4-15-01: A multi-center prospective cohort study to evaluate the presence of circulating tumor cells using the Epic Sciences platform among women with metastatic breast cancer

2024· article· en· W4396591390 on OpenAlexaffabout
Katarzyna J. Jerzak, Pamela J. Goodwin, Marguerite Ennis, Christine Brezden‐Masley, Nathaniel Bouganim, Mark Basik, Arushi Jain, Giuseppe Di, Rick Wenstrup, N Hartmann, Megan Slade, Ana Elisa Lohmann

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsLondon Health Sciences CentreJewish General HospitalSunnybrook Health Science CentreMcGill University Health CentreUniversity of TorontoHealth Sciences CentreMount Sinai Hospital
Fundersnot available
KeywordsEPICMedicineCancerEuropean Prospective Investigation into Cancer and NutritionProspective cohort studyCirculating tumor cellOncologyBreast cancerInternal medicineMetastatic breast cancerCenter (category theory)CohortMetastasis

Abstract

fetched live from OpenAlex

Abstract Background: The presence of tumor cells (or their components) in the blood of women with a history of early breast cancer has the potential to herald the development of metastatic recurrence at its earliest stages. Such early detection could potentially lead to novel prevention strategies, but it requires a sensitive assay. Objective: To use the Epic Sciences platform to detect and enumerate CTCs in blood samples from patients with an established diagnosis of metastatic breast cancer (MBC), prior to initiation of 1st line systemic therapy in the metastatic setting. Methods: We conducted a multi-center prospective cohort study to evaluate the presence of CTCs using the Epic Sciences platform among patients with a new diagnosis of MBC. Men or women age 18 to 85 were included, irrespective of breast cancer subtype. Patients with a prior or concurrent malignancy whose natural history or treatment had the potential to interfere with the detection of MBC in a liquid biopsy were excluded. A one-time blood draw was performed before patients received any local or systemic therapy in the metastatic setting. In addition, those with recurrent disease must have been off any systemic adjuvant therapy for ≥3 weeks prior to blood collection. Two 5 mL blood samples were obtained for CTC identification and enumeration. CTC identification was based on immunofluorescence analysis using Epic Sciences platform as previously described (Ueno et al 2017). The presence of CTCs was correlated with clinical and pathological features, which were abstracted from medical records and pathology reports. The association between the presence of CTCs and clinical/pathologic characteristics was tested using Fisher’s exact test for categorical variables and t-test or Wilcoxon rank sum tests for numerical variables. All analyses were performed using the R software package. Results: 100 patients were recruited between February 2021 and January 2023 at five academic oncology centres in Ontario and Quebec, Canada. 95 patients had evaluable blood for analysis and 5 did not due to blood age and/or insufficient blood volume. Six patients were excluded after providing a blood sample because tissue biopsy ultimately revealed a 2nd primary tumor (n=4) or benign tissue (n=2). Hence, 89 patients with a clinical diagnosis of MBC and with evaluable blood for CTC analyses were ultimately included in our cohort. The average age of patients was 61 years. Most patients (n=49, 55%) had a prior history of early breast cancer, 38 (43%) had de-novo metastatic disease and prior breast cancer history was unknown for 2 patients. 50 (66%) of patients had visceral metastatic disease. The most common sites of metastases included bone (62%), lung (30%), liver (29%) and lymph nodes (17%). 63 of 89 patients (71%) had detectable CTCs at baseline, prior to any local or systemic treatment in the metastatic setting. The median number of detectable CTCs per 5mL sample was 2 (IQR 8.5) and the range was 0 – 12,798. Twenty nine of 89 (33%) patients had 5 or more CTCs detected per 5ml blood. The proportion of patients with detectable CTCs was numerically highest (n=39/51, 76%) among patients with hormone receptor (HR)+/HER2-ve breast cancer, followed by HER2+ (n=16/22, 73%) and triple negative (n=8/13, 62%) disease. Associations between CTC detection with prior history of early breast cancer, sites of metastatic disease and disease burden will also be presented. Conclusions: Approximately 3 in 4 women with newly diagnosed metastatic breast cancer have detectable CTCs using the Epic Sciences platform prior to initiation of first line systemic therapy. CTCs may be a promising tool for the monitoring of breast cancer recurrence and will be investigated in an ongoing Canadian prospective observational study that aims to elucidate biomarkers of late breast cancer recurrence. Citation Format: Katarzyna Jerzak, Pamela Goodwin, Marguerite Ennis, Christine Brezden-Masley, Nathaniel Bouganim, Mark Basik, Arushi Jain, Giuseppe Di Caro, Rick Wenstrup, Nadine Hartmann, Megan Slade, Ana Elisa Lohmann. A multi-center prospective cohort study to evaluate the presence of circulating tumor cells using the Epic Sciences platform among women with metastatic breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-15-01.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.134
GPT teacher head0.446
Teacher spread0.312 · 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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Citations0
Published2024
Admission routes2
Has abstractyes

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