Breast Cancer With Release of Tumor Cells in Peripheral Blood Mimicking Acute Myeloid Leukemia
Bibliographic record
Abstract
A 75-year-old woman with a history of lobular breast adenocarcinoma treated with mastectomy and radiotherapy in 2021 and on maintenance hormone therapy, presented with asthenia and tremors. Laboratory tests showed leucocytosis, anemia and low platelet count, with increased serum calcium, lactate dehydrogenase and indirect bilirubin levels. Haptoglobin was decreased and renal function was normal. Peripheral blood smear showed red cell anisocytosis, many schistocytes and immature granulocytes. Furthermore, 15% of white cells displayed large size and atypical morphology. A macroangiopathic hemolytic anemia (MAHA) related to a de novo or recurring cancer was hypothesized, and total body computed tomography (CT) and 18 F-FDG positron emission tomography (PET)/CT were undertaken. Only a slight FDG uptake was demonstrated in the spine, attributable to a reactive bone marrow due to MAHA. Then, to rule out a MAHA related to acute leukemia, a bone marrow aspirate and trephine biopsy were performed, with an extensive cell immunophenotyping. The first myeloid flow cytometry (FC) panel evidenced a large volume population of about 20%, expressing CD117 but negative for CD45 and CD34. All myeloid markers were negative. A more extensive panel was then used, including plasma cell and erythroid markers. Interestingly, the abnormal population resulted positive for CD138 and CD71 with negativity for CD38. A recent study reported that besides CD45 negativity, non-hematological neoplasms frequently express CD56, CD117, or CD138. Therefore, a panel for non-hematological markers including epithelial cell adhesion molecule (EpCAM) was carried out. This population resulted EpCAM positive and also expressed CD9, a breast cancer prognostic marker. Bone marrow smears revealed the presence of the same cells, and the immunohistochemistry analysis of bone marrow biopsy demonstrated the massive infiltration of breast cancer cells, expressing all epithelial markers identified at diagnosis. The FC analysis of the peripheral blood allowed the rapid characterization of a non-hematological neoplastic cell population, circulating at unusually high frequency and mimicking an acute myeloid leukemia. The FC detection of CD45-negative cell populations in peripheral blood, bone marrow or lymph node aspirate should prompt the setup of an immunophenotyping panel including EpCAM, CD9, CD56 and CD117, to allow for a rapid and accurate identification of ectopic malignant epithelial cells. J Hematol. 2024;13(4):168-173 doi: https://doi.org/10.14740/jh1259
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".