Evidence map›Paper›PMID 35495618›Full record

ReviewFrontiers in molecular biosciences2022

'Breast Cancer Resistance Likelihood and Personalized Treatment Through Integrated Multiomics'.

Sabba Mehmood, Muhammad Faheem, Hammad Ismail, Syeda Mehpara Farhat, Mahwish Ali, Sidra Younis, Muhammad Nadeem Asghar

Abstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Precision medicine in breast cancer (Review).Molecular and clinical oncology · 2024
    Review
  10. Article
  11. Omics Technologies Improving Breast Cancer Research and Diagnostics.International journal of molecular sciences · 2023
    Review
  12. Review
  13. 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

7 authors.

Sabba MehmoodDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, Pakistan.
Muhammad FaheemDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, Pakistan.
Hammad IsmailDepartment of Biochemistry & Biotechnology University of Gujrat, Gujrat, Pakistan.
Syeda Mehpara FarhatDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, Pakistan.
Mahwish AliDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, Pakistan.
Sidra YounisDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, Pakistan.
Muhammad Nadeem AsgharDepartment of Medical Biology, University of Québec at Trois-Rivieres, Trois-Rivieres, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent times, enormous progress has been made in improving the diagnosis and therapeutic strategies for breast carcinoma, yet it remains the most prevalent cancer and second highest contributor to cancer-related deaths in women. Breast cancer (BC) affects one in eight females globally. In 2018 alone, 1.4 million cases were identified worldwide in postmenopausal women and 645,000 cases in premenopausal females, and this burden is constantly increasing. This shows that still a lot of efforts are required to discover therapeutic remedies for this disease. One of the major clinical complications associated with the treatment of breast carcinoma is the development of therapeutic resistance. Multidrug resistance (MDR) and consequent relapse on therapy are prevalent issues related to breast carcinoma; it is due to our incomplete understanding of the molecular mechanisms of breast carcinoma disease. Therefore, elucidating the molecular mechanisms involved in drug resistance is critical. For management of breast carcinoma, the treatment decision not only depends on the assessment of prognosis factors but also on the evaluation of pathological and clinical factors. Integrated data assessments of these multiple factors of breast carcinoma through multiomics can provide significant insight and hope for making therapeutic decisions. This omics approach is particularly helpful since it identifies the biomarkers of disease progression and treatment progress by collective characterization and quantification of pools of biological molecules within and among the cancerous cells. The scrupulous understanding of cancer and its treatment at the molecular level led to the concept of a personalized approach, which is one of the most significant advancements in modern oncology. Likewise, there are certain genetic and non-genetic tests available for BC which can help in personalized therapy. Genetically inherited risks can be screened for personal predisposition to BC, and genetic changes or variations (mutations) can also be identified to decide on the best treatment. Ultimately, further understanding of BC at the molecular level (multiomics) will define more precise choices in personalized medicine. In this review, we have summarized therapeutic resistance associated with BC and the techniques used for its management.

Indexed as

breast cancerdrug resistancegenomicsmetabolomicsproteomicsradiomicstranscriptomics

Identifiers

PMID35495618
PMCPMC9048735

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.