Evidence map›Paper›PMID 35283582›Full record

ArticleBioinformation2021

Combinational therapeutics to combat cancer.

Ahmed Al Otaibi, Subuhi Sherwani, Eida Mohammed Alshammari, Salma Ahmed Al-Zahrani, Wahid Ali Khan, Abdulmohsen Khalaf Dhahi Alsukaibi, Sourabh Dwivedi, Shahper Nazeer Khan, Mohd Wajid Ali Khan

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In one paragraph

Article in Bioinformation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Ahmed Al OtaibiDepartment of Chemistry, College of Sciences, University of Hail, Hail-2440, Saudi Arabia.
Subuhi SherwaniDepartment of Biology, College of Sciences, University of Hail, Hail-2440, Saudi Arabia.
Eida Mohammed AlshammariDepartment of Chemistry, College of Sciences, University of Hail, Hail-2440, Saudi Arabia.
Salma Ahmed Al-ZahraniDepartment of Chemistry, College of Sciences, University of Hail, Hail-2440, Saudi Arabia.
Wahid Ali KhanDepartment of Clinical Biochemistry,College of Medicine, King Khalid University, Abha-62529, Saudi Arabia.
Abdulmohsen Khalaf Dhahi AlsukaibiDepartment of Chemistry, College of Sciences, University of Hail, Hail-2440, Saudi Arabia.
Sourabh DwivediDepartment of Applied Physics, Aligarh Muslim University, Aligarh-202002, U.P., India.
Shahper Nazeer KhanInterdisciplinary Nanotechnology Centre, Aligarh Muslim University, Aligarh-202002, U.P, India.
Mohd Wajid Ali KhanMolecular Diagnostic and Personalised Therapeutics Unit, University of Hail, Hail-2440, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mono-therapeutics is rarely effective as a treatment option, which limits the survival of patients in advanced grade aggressive cancers. Combinational therapeutics (multiple drugs for multiple targets) to combat cancer is gaining momentum in recent years. Hence, it is of interest to document known data for combinational therapeutics in cancer treatment. An amalgamation of therapeutic agents enhances the efficacy and potency of the therapy. Combinational therapy can potentially target multiple pathways that are necessary for the cancer cells to proliferate, and/or target molecules, which may help cancer to become more aggressive and metastasize. In this review, we discuss combinational therapeutics, which include human γδ T cells in combinations with biologically active anti-cancer molecules, which synergistically may produce promising combinational therapeutics.

Indexed as

biologically active moleculescancercombinational therapeuticssynergisticT cells

Identifiers

PMID35283582
PMCPMC8882074

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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.