A molecular compendium of genes expressed in multiple myeloma
Bibliographic record
Abstract
We have created a molecular resource of genes expressed in primary malignant plasma cells using a combination of cDNA library construction, 5' end single-pass sequencing, bioinformatics, and microarray analysis. In total, we identified 9732 nonredundant expressed genes. This dataset is available as the Myeloma Gene Index (www.uhnres.utoronto.ca/akstewart_lab).Predictably, the sequenced profile of myeloma cDNAs mirrored the known function of immunoglobulin-producing, high-respiratory rate, low-cycling, terminally differentiated plasma cells. Nevertheless, approximately 10% of myeloma-expressed sequences matched only entries in the database of Expressed Sequence Tags (dbEST) or the high-throughput genomic sequence (htgs) database. Numerous novel genes of potential biologic significance were identified. We therefore spotted 4300 sequenced cDNAs on glass slides creating a myeloma-enriched microarray. Several of the most highly expressed genes identified by sequencing, such as a novel putative disulfide isomerase (MGC3178), tumor rejection antigen TRA1, heat shock 70-kDa protein 5, and annexin A2, were also differentially expressed between myeloma and B lymphoma cell lines using this myeloma-enriched microarray. Furthermore, a defined subset of 34 up-regulated and 18 down-regulated genes on the array were able to differentiate myeloma from nonmyeloma cell lines. These not only include genes involved in B-cell biology such as syndecan, BCMA, PIM2, MUM1/IRF4, and XBP1, but also novel uncharacterized genes matching sequences only in the public databases. In summary, our expressed gene catalog and myeloma-enriched microarray contains numerous genes of unknown function and may complement other commercially available arrays in defining the molecular portrait of this hematopoietic malignancy. GenBank Accession numbers include BF169967-BF176369, BF185966-BF185969, and BF177280-BF177455.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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 source (direct Gemma or distilled Codex), 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".