Lung microbial and host genomic signatures as predictors of prognosis in early-stage adenocarcinoma.


Journal

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
ISSN: 1538-7755
Titre abrégé: Cancer Epidemiol Biomarkers Prev
Pays: United States
ID NLM: 9200608

Informations de publication

Date de publication:
03 Sep 2024
Historique:
accepted: 28 08 2024
received: 06 05 2024
revised: 15 07 2024
medline: 3 9 2024
pubmed: 3 9 2024
entrez: 3 9 2024
Statut: aheadofprint

Résumé

Risk of early-stage lung adenocarcinoma (LUAD) recurrence after surgical resection is significant, and post-recurrence median survival is approximately two years. Currently there are no commercially available biomarkers that predict recurrence. Here, we investigated whether microbial and host genomic signatures in the lung can predict recurrence. In 91 early-stage (Stage IA/IB) LUAD-patients with extensive follow-up, we used 16s rRNA gene sequencing and host RNA-sequencing to map the microbial and host transcriptomic landscape in tumor and adjacent unaffected lung samples. 23 out of 91 subjects had tumor recurrence over 5-year period. In tumor samples, LUAD recurrence was associated with enrichment with Dialister, Prevotella, while in unaffected lung, recurrence was associated with enrichment with Sphyngomonas and Alloiococcus. The strengths of the associations between microbial and host genomic signatures with LUAD recurrence were greater in adjacent unaffected lung samples than in the primary tumor. Among microbial-host features in the unaffected lung samples associated with recurrence, enrichment with Stenotrophomonas geniculata and Chryseobacterium were positively correlated with upregulation of IL-2, IL-3, IL-17, EGFR, HIF-1 signaling pathways among the host transcriptome. In tumor samples, enrichment with Veillonellaceae Dialister, Ruminococcacea, Haemophilus Influenza, and Neisseria were positively correlated with upregulation of IL-1, IL-6, IL17, IFN, and Tryptophan metabolism pathways. Overall, modeling suggested that a combined microbial/transcriptome approach using unaffected lung samples had the best biomarker performance (AUC=0.83). This study suggests that LUAD recurrence is associated with distinct pathophysiological mechanisms of microbial-host interactions in the unaffected lung rather than those present in the resected tumor.

Sections du résumé

BACKGROUND BACKGROUND
Risk of early-stage lung adenocarcinoma (LUAD) recurrence after surgical resection is significant, and post-recurrence median survival is approximately two years. Currently there are no commercially available biomarkers that predict recurrence. Here, we investigated whether microbial and host genomic signatures in the lung can predict recurrence.
METHODS METHODS
In 91 early-stage (Stage IA/IB) LUAD-patients with extensive follow-up, we used 16s rRNA gene sequencing and host RNA-sequencing to map the microbial and host transcriptomic landscape in tumor and adjacent unaffected lung samples.
RESULTS RESULTS
23 out of 91 subjects had tumor recurrence over 5-year period. In tumor samples, LUAD recurrence was associated with enrichment with Dialister, Prevotella, while in unaffected lung, recurrence was associated with enrichment with Sphyngomonas and Alloiococcus. The strengths of the associations between microbial and host genomic signatures with LUAD recurrence were greater in adjacent unaffected lung samples than in the primary tumor. Among microbial-host features in the unaffected lung samples associated with recurrence, enrichment with Stenotrophomonas geniculata and Chryseobacterium were positively correlated with upregulation of IL-2, IL-3, IL-17, EGFR, HIF-1 signaling pathways among the host transcriptome. In tumor samples, enrichment with Veillonellaceae Dialister, Ruminococcacea, Haemophilus Influenza, and Neisseria were positively correlated with upregulation of IL-1, IL-6, IL17, IFN, and Tryptophan metabolism pathways.
CONCLUSIONS CONCLUSIONS
Overall, modeling suggested that a combined microbial/transcriptome approach using unaffected lung samples had the best biomarker performance (AUC=0.83).
IMPACT CONCLUSIONS
This study suggests that LUAD recurrence is associated with distinct pathophysiological mechanisms of microbial-host interactions in the unaffected lung rather than those present in the resected tumor.

Identifiants

pubmed: 39225784
pii: 747757
doi: 10.1158/1055-9965.EPI-24-0661
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Jun-Chieh J Tsay (JJ)

New York University, New York, New York, United States.

Fares Darawshy (F)

New York University, New York, New York, United States.

Chan Wang (C)

New York University, New York, NY, United States.

Benjamin Kwok (B)

New York University, New York, New York, United States.

Kendrew K Wong (KK)

New York University, New York, New York, United States.

Benjamin G Wu (BG)

New York University, New York, New York, United States.

Imran Sulaiman (I)

New York University, New York, New York, United States.

Hua Zhou (H)

New York University, New York, United States.

Bradley Isaacs (B)

New York University, New York, New York, United States.

Matthias C Kugler (MC)

New York University Langone Medical Center, New York, NY, United States.

Elizabeth Sanchez (E)

New York University, New York, New York, United States.

Alexander Bain (A)

New York University, New York, New York, United States.

Yonghua Li (Y)

New York University Langone Medical Center, New York, NY, United States.

Rosemary Schluger (R)

New York University, New York, New York, United States.

Alena Lukovnikova (A)

New York University, New York, New York, United States.

Destiny Collazo (D)

New York University, New York, New York, United States.

Yaa Kyeremateng (Y)

New York University Langone Medical Center, New York, NY, United States.

Ray Pillai (R)

New York University, New York, New York, United States.

Miao Chang (M)

New York University Langone Medical Center, New York, NY, United States.

Qingsheng Li (Q)

New York University, New York, NY, United States.

Rami S Vanguri (RS)

New York University, New York, NY, United States.

Anton S Becker (AS)

New York University Grossman School of Medicine, New York, NY, United States.

William H Moore (WH)

New York University, New York, New York, United States.

George Thurston (G)

New York University, New York, New York, United States.

Terry Gordon (T)

NYU School of Medicine, New York, New York, United States.

Andre L Moreira (AL)

New York University, New York, New York, United States.

Chandra M Goparaju (CM)

NYU Langone Medical Center, New York, NY, United States.

Daniel H Sterman (DH)

New York University, New York City, NY, United States.

Aristotelis Tsirigos (A)

NYU Langone Medical Center, New York, NY, United States.

Huilin Li (H)

New York University, New York, New York, United States.

Leopoldo N Segal (LN)

NYU Langone Medical Center, New York, New York, United States.

Harvey I Pass (HI)

NYU Langone Medical Center, New York, New York, United States.

Classifications MeSH