Evidence map›Paper›PMID 36558926›Full record

ReviewPharmaceuticals (Basel, Switzerland)2022

Targeting the DNA Damage Response Machinery for Lung Cancer Treatment.

Katharigatta N Venugopala

Abstract readReview
In one paragraph

Review in Pharmaceuticals (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. ATR expression as a prognostic biomarker inJournal of thoracic disease · 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

1 author.

Katharigatta N VenugopalaDepartment of Pharmaceutical Sciences, College of Clinical Pharmacy, King Faisal University, Al-Ahsa 31982, Saudi Arabia.ORCID 0000-0003-0680-1549

Funding

National Research Foundation 129173This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Al-Ahsa, Saudi Arabia GRANT772
6 · The paper itself

Abstract

Lung cancer is considered the most commonly diagnosed cancer and one of the leading causes of death globally. Despite the responses from small-cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) patients to conventional chemo- and radiotherapies, the current outcomes are not satisfactory. Recently, novel advances in DNA sequencing technologies have started to take off which have provided promising tools for studying different tumors for systematic mutation discovery. To date, a limited number of DDR inhibition trials have been conducted for the treatment of SCLC and NSCLC patients. However, strategies to test different DDR inhibitor combinations or to target multiple pathways are yet to be explored. With the various biomarkers that have either been recently discovered or are the subject of ongoing investigations, it is hoped that future trials would be designed to allow for studying targeted treatments in a biomarker-enriched population, which is defensible for the improvement of prognosis for SCLC and NSCLC patients. This review article sheds light on the different DNA repair pathways and some of the inhibitors targeting the proteins involved in the DNA damage response (DDR) machinery, such as ataxia telangiectasia and Rad3-related protein (ATR), DNA-dependent protein kinase (DNA-PK), and poly-ADP-ribose polymerase (PARP). In addition, the current status of DDR inhibitors in clinical settings and future perspectives are discussed.

Indexed as

ATMiBERDDRDNA-PKihomologous recombination (HR)NERNHEJPARPi

Identifiers

PMID36558926
PMCPMC9781725

What Socratic holds

Textmetadata
LicenceCC BY
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.