Evidence map›Paper›PMID 36811317›Full record

ReviewCancer reports (Hoboken, N.J.)2023

Metabolomics in oncology.

Gurparsad Singh Suri, Gurleen Kaur, Giuseppina M Carbone, Dheeraj Shinde

Full text readReview
In one paragraph

Review in Cancer reports (Hoboken, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
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

28 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Review
  19. Article
  20. Article
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

4 authors.

Gurparsad Singh SuriDepartment of Biological Sciences, California Baptist University, Riverside, California, USA.
Gurleen KaurDepartment of Biological Sciences, California Baptist University, Riverside, California, USA.
Giuseppina M CarboneInstitute of Oncology Research (IOR), Universita' della Svizzera Italiana (USI), Bellinzona, Switzerland.
Dheeraj ShindeInstitute of Oncology Research (IOR), Universita' della Svizzera Italiana (USI), Bellinzona, Switzerland.ORCID 0000-0002-5113-3167

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOncogenic transformation alters intracellular metabolism and contributes to the growth of malignant cells. Metabolomics, or the study of small molecules, can reveal insight about cancer progression that other biomarker studies cannot. Number of metabolites involved in this process have been in spotlight for cancer detection, monitoring, and therapy. RECENT

findingsIn this review, the "Metabolomics" is defined in terms of current technology having both clinical and translational applications. Researchers have shown metabolomics can be used to discern metabolic indicators non-invasively using different analytical methods like positron emission tomography, magnetic resonance spectroscopic imaging etc. Metabolomic profiling is a powerful and technically feasible way to track changes in tumor metabolism and gauge treatment response across time. Recent studies have shown metabolomics can also predict individual metabolic changes in response to cancer treatment, measure medication efficacy, and monitor drug resistance. Its significance in cancer development and treatment is summarized in this review.

conclusionAlthough in infancy, metabolomics can be used to identify treatment options and/or predict responsiveness to cancer treatments. Technical challenges like database management, cost and methodical knowhow still persist. Overcoming these challenges in near further can help in designing new treatment régimes with increased sensitivity and specificity.

Indexed as

MetabolomicsNeoplasmsBiomarkersHumansMagnetic Resonance ImagingMedical OncologyBiomarkersbiomarkercancermetabolic reprogrammingmetabolismmetabolomics

Identifiers

PMID36811317
PMCPMC10026298

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read3
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 Socratic graph.