Evidence map›Paper›PMID 29057232›Full record

ReviewAnnals of translational medicine2017

Expanded molecular interrogation for potential actionable targets in non-squamous non-small cell lung cancer.

Kah Weng Lau, Claudia Seng, Tony K H Lim, Daniel S W Tan

Abstract readReview
In one paragraph

Review in Annals of translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Emerging uses of biomarkers in lung cancer management.Annals of translational medicine · 2017
    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.

Kah Weng LauDepartment of Anatomical Pathology, Singapore General Hospital, Singapore.
Claudia SengDivision of Medical Oncology, National Cancer Centre Singapore, Singapore.
Tony K H LimDepartment of Anatomical Pathology, Singapore General Hospital, Singapore.
Daniel S W TanDivision of Medical Oncology, National Cancer Centre Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advent of targeted therapies has established new standards of care for defined molecular subsets of non-small cell lung cancer (NSCLC). Not only has this led to significant changes in the routine clinical management of lung cancer e.g., multiplexed genomic testing, but it has provided important principles and benchmarks for determining "actionability". At present, the clinical paradigms are most evolved for EGFR mutations and ALK rearrangements, where multiple randomized phase III trials have determined optimal treatment strategies in both treatment naïve and resistant settings. However, this may not always be feasible with low prevalence alterations e.g., ROS1 and BRAF mutations. Another emerging observation is that not all targets are equally "actionable", necessitating a rigorous preclinical, clinical and translational framework to prosecute new targets and drug candidates. In this review, we will cover the role of targeted therapies for NSCLC harbouring BRAF, MET, HER2 and RET alterations, all of which have shown promise in non-squamous non-small cell lung cancer (ns-NSCLC). We further review some early epigenetic targets in NSCLC, an area of emerging interest. With increased molecular segmentation of lung cancer, we discuss the upcoming challenges in drug development and implementation of precision oncology approaches, especially in light of the complex and rapidly evolving therapeutic landscape.

Indexed as

actionable alterationsepigeneticMolecular profilingnovel targets

Identifiers

PMID29057232
PMCPMC5635263

What OpenQuestion holds

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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.