Evidence map›Paper›PMID 35037094›Full record

ReviewClinical and experimental medicine2023

The NEK family of serine/threonine kinases as a biomarker for cancer.

Nagesh Kishan Panchal, Sabina Evan Prince

Abstract readReview
PubMed Publisher
In one paragraph

Review in Clinical and experimental medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
6.2field-weighted citation impact, top 2% 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

43 citing papers in PubMed, 55 citations in OpenAlex.

  1. Molecules (Basel, Switzerland) · 2026
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  14. DivergentLife science alliance · 2025
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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

2 authors at 1 institution in 1 country.

Nagesh Kishan PanchalDepartment of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, 632 014, India.
Sabina Evan PrinceDepartment of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, 632 014, India. eps674@gmail.com.ORCID http://orcid.org/0000-0003-2073-5971
Vellore Institute of Technology University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is defined by unrestrained cell proliferation due to impaired protein activity. Cell cycle-related proteins are likely to play a role in human cancers, including proliferation, invasion, and therapeutic resistance. The serine/threonine NEK kinases are the part of Never In Mitosis A Kinases (NIMA) family, which are less explored kinase family involved in the cell cycle, checkpoint regulation, and cilia biology. They comprise of eleven members, namely NEK1, NEK2, NEK3, NEK4, NEK5, NEK6, NEK7, NEK8, NEK9, NEK10, and NEK11, located in different cellular regions. Recent research has shown the role of NEK family in various cancers by perversely expressing. Therefore, this review aimed to provide a systematic account of our understanding of NEK kinases; structural details; and its role in the cell cycle regulation. Furthermore, we have comprehensively reviewed the NEK kinases in terms of their expression and regulation in different cancers. Lastly, we have emphasized on some of the potential NEK inhibitors reported so far.

Indexed as

NeoplasmsProtein Serine-Threonine KinasesBiomarkersCell Cycle ProteinsHumansNIMA-Related KinasesSerineThreonineBiomarkersCell Cycle ProteinsNEK2 protein, humanNEK3 protein, humanNEK5 protein, humanNEK6 protein, humanNEK9 protein, humanNIMA-Related KinasesProtein Serine-Threonine KinasesSerineThreonineBreast cancerCell cycleLung cancerNEK kinasesOvarian cancerPancreatic cancer

Identifiers

PMID35037094
OpenAlexW4205828811

What OpenQuestion holds

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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.