Evidence map›Paper›PMID 25368671›Full record

ReviewJournal of Cancer2014

Utilization of translational bioinformatics to identify novel biomarkers of bortezomib resistance in multiple myeloma.

Deanna J Fall, Holly Stessman, Sagar S Patel, Zohar Sachs, Brian G Van Ness, Linda B Baughn, Michael A Linden

Open access · goldAbstract readReview
In one paragraph

Review in Journal of Cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.9field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 21 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Deanna J Fall1. Gillette Children's Specialty Healthcare, St. Paul, MN;
Holly Stessman2. Department of Genomic Sciences, University of Washington, Seattle, WA;
Sagar S Patel3. Department of Medicine, University of Minnesota, Minneapolis, MN;
Zohar Sachs3. Department of Medicine, University of Minnesota, Minneapolis, MN; ; 4. Division of Hematology, Oncology, and Transplantation, University of Minnesota, Minneapolis, MN;
Brian G Van Ness5. Department of Genetics, Cell Biology, University of Minnesota, Minneapolis, MN;
Linda B Baughn5. Department of Genetics, Cell Biology, University of Minnesota, Minneapolis, MN; ; 6. Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN.
Michael A Linden6. Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN.
University of Minnesota · USGillette Children's Specialty Healthcare · USUniversity of Washington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple myeloma (MM) is an incurable malignant neoplasm hallmarked by a clonal expansion of plasma cells, the presence of a monoclonal protein in the serum and/or urine (M-spike), lytic bone lesions, and end organ damage. Clinical outcomes for patients with MM have improved greatly over the last decade as a result of the re-purposing of compounds such as thalidomide derivatives, as well as the development of novel chemotherapeutic agents including first and second generation proteasome inhibitors, bortezomib (Bz) and carfilzomib. Unfortunately, despite these improvements, the majority of patients relapse following treatment. While Bz, one of the most commonly used proteasome inhibitors, has been successfully incorporated into clinical practice, some MM patients have de novo resistance to Bz, and the majority of the remainder subsequently develop drug resistance following treatment. A significant gap in clinical care is the lack of a reliable clinical test that would predict which MM patients have or will subsequently develop Bz resistance. Thus, as Bz resistance remains a significant challenge, research efforts are needed to identify novel biomarkers of early Bz resistance, particularly when an early therapeutic intervention can be initiated. Recent advances in MM research indicate that genomic data can be extracted to identify novel biomarkers that can be utilized to select more effective, personalized treatment protocols for individual patients. Computationally integrating large patient databases with data from whole transcriptome profiling and laboratory-based models can potentially revolutionize our understanding of MM disease mechanisms. This systems-wide approach can provide rational therapeutic targets and novel biomarkers of risk and treatment response. In this review, we discuss the use of high-content datasets (predominantly gene expression profiling) to identify novel biomarkers of treatment response and resistance to Bz in MM.

Indexed as

biomarkersMultiple myeloma

Identifiers

PMID25368671
PMCPMC4216795
OpenAlexW2129156541

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.