Evidence map›Paper›PMID 38244111›Full record

ArticleFunctional & integrative genomics2024

MyeloDB: a multi-omics resource for multiple myeloma.

Ambuj Kumar, Keerthana Vinod Kumar, Kavita Kundal, Avik Sengupta, Simran Sharma, Kunjulakshmi R, Rahul Kumar

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Article in Functional & integrative genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Review
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 2 institutions in 1 country.

Ambuj Kumar *Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India.
Keerthana Vinod Kumar *Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India.
Kavita KundalDepartment of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India.
Avik SenguptaDepartment of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India.
Simran SharmaDepartment of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India.
Kunjulakshmi RDepartment of Biological Sciences, Indian Institute of Science Education and Research, Berhampur, Odisha, 760010, India.
Rahul KumarDepartment of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502284, India. rahulk@bt.iith.ac.in.
Indian Institute of Technology Hyderabad · INIndian Institute of Science Education and Research Berhampur · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple myeloma (MM) is a common type of blood cancer affecting plasma cells originating from the lymphoid B-cell lineage. It accounts for about 10% of all hematological malignancies and can cause significant end-organ damage. The emergence of genomic technologies such as next-generation sequencing and gene expression analysis has opened new possibilities for early detection of multiple myeloma and identification of personalized treatment options. However, there remain significant challenges to overcome in MM research, including integrating multi-omics data, achieving a comprehensive understanding of the disease, and developing targeted therapies and biomarkers. The extensive data generated by these technologies presents another challenge for data analysis and interpretation. To bridge this gap, we have developed a multi-omics open-access database called MyeloDB. It includes gene expression profiling, high-throughput CRISPR-Cas9 screens, drug sensitivity resources profile, and biomarkers. MyeloDB contains 47 expression profiles, 3 methylation profiles comprising a total of 5630 patient samples and 25 biomarkers which were reported in previous studies. In addition to this, MyeloDB can provide significant insight of gene mutations in MM on drug sensitivity. Furthermore, users can download the datasets and conduct their own analyses. Utilizing this database, we have identified five novel genes, i.e., CBFB, MANF, MBNL1, SEPHS2, and UFM1 as potential drug targets for MM. We hope MyeloDB will serve as a comprehensive platform for researchers and foster novel discoveries in MM. MyeloDB Database URL: https://project.iith.ac.in/cgntlab/myelodb/ .

Indexed as

Multiple MyelomaBiomarkersGene Expression ProfilingGenomicsHumansMultiomicsBiomarkersBiomarkersDrug sensitivityGene expressionMultiple myelomaMyeloDBSynthetic lethality

Identifiers

PMID38244111
OpenAlexW4391053264

What OpenQuestion holds

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Registered trials

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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.