Evidence map›Paper›PMID 39125693›Full record

ArticleInternational journal of molecular sciences2024

Utilizing Plasma-Based Next-Generation Sequencing to Expedite the Diagnostic Process in Suspected Lung Cancer: A Case Report.

Chia-Min Hung, Chen-Te Wu, Suyog Jain, Chiao-En Wu

Abstract readCase Reports
In one paragraph

Article 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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.

Chia-Min HungCollege of Medicine, Chang Gung University, Taoyuan 333, Taiwan.
Chen-Te WuCollege of Medicine, Chang Gung University, Taoyuan 333, Taiwan.
Suyog JainDepartment of Medical Affairs, Guardant Health AMEA, Singapore 138543, Singapore.ORCID 0000-0002-2223-9181
Chiao-En WuCollege of Medicine, Chang Gung University, Taoyuan 333, Taiwan.ORCID 0000-0002-1081-8805

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is the leading cause of cancer mortality worldwide. Fortunately, the advent of precision medicine, which includes targeted therapy and immunotherapy, offers hope. However, identifying specific mutations is imperative before initiating precise medications. Traditional methods, such as real-time PCR examination of individual mutations, are time-consuming. Contemporary techniques, such as tissue- and plasma-based next-generation sequencing (NGS), allow comprehensive genome analysis concurrently. Notably, plasma-based NGS has a shorter turnaround time (TAT) and thus a shorter time-to-treatment (TTT). In this case report, we demonstrate the benefits of plasma-based NGS before pathological diagnosis in a patient with image-suspected non-small cell lung cancer (NSCLC). An 82-year-old Taiwanese woman presented with lower back pain persisting for one month and left-sided weakness for two weeks. Whole-body computed tomography (CT) revealed lesions suspicious for brain and bone metastases, along with a mass consistent with a primary tumor in the left upper lobe, indicative of advanced NSCLC with T4N3M1c staging. The patient underwent a bronchoscopic biopsy on Day 0, and the preliminary report that came out on Day 1 was suggestive of metastatic NSCLC. Blood was also collected for plasma-based NGS on Day 0. The patient was Coronavirus disease 2019-positive and was treated with molnupiravir on Day 6. On Day 7, pathology confirmed pulmonary adenocarcinoma, and the results of plasma-based NGS included EGFR L858R mutation. The patient was started on targeted therapy (afatinib) on Day 9. Unfortunately, the patient died of hypoxic respiratory failure on Day 26, a complication of underlying viral infection. Plasma-based NGS offers a rapid and efficient means of mutation detection in NSCLC, streamlining treatment initiation and potentially improving the negative emotions of patients. Its utility, particularly in regions with a high prevalence of specific mutations, such as EGFR alterations in East Asian populations, highlights its relevance in guiding personalized therapy decisions.

Indexed as

Carcinoma, Non-Small-Cell LungHigh-Throughput Nucleotide SequencingLung NeoplasmsAged, 80 and overFemaleHumansMutationGuardant360non-small cell lung cancerplasma-based NGS

Identifiers

PMID39125693
PMCPMC11312071

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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.