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Record W4389247812 · doi:10.1182/blood-2023-181468

Genetic Variations in Multiple Myeloma with Extramedullary Disease

2023· article· en· W4389247812 on OpenAlexaff
Dajung Kim, Seri Jeong, Kevin Song, Jae‐Cheol Jo, Ji‐Hyun Lee, Jee‐Yeong Jeong, Ho Sup Lee

Bibliographic record

VenueBlood · 2023
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsVancouver General HospitalBC Cancer Agency
Fundersnot available
KeywordsMultiple myelomaMedicinePathologyExome sequencingEquidaeInternal medicineBiologyGeneGeneticsMutation

Abstract

fetched live from OpenAlex

Background Extramedullary disease (EM) is aggressive form of MM in which clonal plasma cells exist outside the BM. EM may be found in up to 30% of MM patients and is associated with an adverse prognosis. However, the genetic pathogenesis of EM have not yet been precisely elucidated. Patients and Methods From 2005 to 2020, among patients diagnosed with MM with EM (EMM) confirmed by image study, a total of 12 patients for whom tumor tissue or BM specimens could be obtained were enrolled. Both bone-related EM (EM-B) and soft-tissue-related EM (EM-S) were defined as EM. We performed whole-exome sequencing (WES) and NanoString nCounter assay to investigate the genetic alterations in EMM patients. A total of 9 formalin-fixed paraffin-embeded (FFPE) tumor tissues and 6 BM specimen from 12 EMM patients were sequenced. Paired BM and FFPE were available for analysis in 3 patients. To clarify the genetic difference between MM and EMM, 8 BM samples of 5 MM patients were analyzed as controls. In addition, 4 buccal swabs from one EMM patient were sequenced for germline control. Results The median age was 57 years (range 50-65). Two patients had EM-S involving meninges and Lt. psoas muscle showed adverse prognosis compared to patients with EM-B, with survivals of 1 month and 11 months after diagnosis of EM. One of them had a gain (1q21) chromosomal aberration classified as high risk cytogenetics. WES was performed on 12 EMM cases (BM=6, FFPE=8). In WES, MAP2K3, AHNAK2, CDC27, MUC4, and NBPF1 were the five genes with the most variation in both BM and FFPE (Fig. 1). In particular, CDC27 gene was altered only in FFPE (6 out of 8 samples). We performed RNA analysis by NanoString in 9 EMM patients (BM=6, FFPE=6) and 5 MM patients. Compared with MM, ARG1, IRF4, and CEP55 were up-regulated and CDKN1C, IL15, and CD3E were down-regulated in the BM of EMM. Comparison of BM specimens from MM and plasmacytoma from EMM showed IRF4 up-regulation in EMM. In plasmacytoma, chemokine and chemokine receptor related genes such as CXCL8, S100A9, S100A8, CCR4, CXCR2, and CXCR4 were down-regulated. Up-regulation of IRF4 was also observed in EMM when comparing normal buccal swab and EMM specimens. Conclusions In our study, significant genetic alterations have been identified. Especially, in WES analysis, CDC27 was mutated only in FFPE of EMM patients, and in Nanostring analysis, IRF4 was up-regulated all EMM samples. Further studies are needed to confirm the genetic alterations in more EMM patients.

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)0.000
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.025
GPT teacher head0.279
Teacher spread0.253 · 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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