Evidence map›Paper›PMID 39337530›Full record

ReviewInternational journal of molecular sciences2024

Emerging Targets in Non-Small Cell Lung Cancer.

Louisa Liu, Joshua Soler, Karen L Reckamp, Kamya Sankar

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

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

  1. Pooled it
  2. Review
  3. METTL14-Mediated lncRNA MSTRG.292666.16 mInternational journal of molecular sciences · 2026
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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

4 authors.

Louisa LiuSamuel-Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
Joshua SolerRiverside School of Medicine, University of California, Riverside, CA 92521, USA.ORCID 0000-0003-3751-2440
Karen L ReckampSamuel-Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.ORCID 0000-0002-9213-0325
Kamya SankarSamuel-Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is responsible for a high burden of disease globally. Over the last two decades, the discovery of targetable oncogenic genomic alterations has revolutionized the treatment landscape for early-stage and advanced non-small cell lung cancer (NSCLC). New molecular drivers continue to emerge as promising therapeutic targets, including KRAS non-G12C, RAF/MEK, HER3, Nectin-4, folate receptor alpha, ITGB6, and PRMT5. In this review, we summarize the emerging molecular targets with a potential clinical impact in advanced NSCLC, elaborating on their clinical characteristics and specific mechanisms and molecular pathways for which targeted treatments are currently available. Additionally, we present an aggregate of ongoing clinical trials investigating the available treatment options targeting such alterations, in addition to their current recruitment status and preliminary efficacy data. These advancements may guide further research endeavors and inform future treatment strategies to improve the management of and transform outcomes for patients with advanced NSCLC.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsMolecular Targeted TherapyAntineoplastic AgentsHumansAntineoplastic Agentsnon-small cell lung cancernovel combinatorial approachesoncogene drivertargeted therapies

Identifiers

PMID39337530
PMCPMC11432526

What OpenQuestion holds

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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 OpenQuestion graph.