J Korean Med Sci.  2024 Jan;39(2):e16. 10.3346/jkms.2024.39.e16.

JAK2 Loss Arising From Tumor-SpreadThrough-Air-Spaces (STAS) Promotes Tumor Progression by Suppressing CD8+ T Cells in Lung Adenocarcinoma: A Machine Learning Approach

• Choi S
• Kim HS
• Min KW
• Noh YK
• Lee JY
• Moon JY
• Jung US
• Kwon MJ
• Kim DH
• Son BK
• Pyo JS
• Ro SK

• KMID: 2550798
• DOI: http://doi.org/10.3346/jkms.2024.39.e16

Abstract

Background
Tumor spread through air spaces (STAS) is a recently discovered risk factor for lung adenocarcinoma (LUAD). The aim of this study was to investigate specific genetic alterations and anticancer immune responses related to STAS. By using a machine learning algorithm and drug screening in lung cancer cell lines, we analyzed the effect of Janus kinase 2 (JAK2) on the survival of patients with LUAD and possible drug candidates.
Methods
This study included 566 patients with LUAD corresponding to clinicopathological and genetic data. For analyses of LUAD, we applied gene set enrichment analysis (GSEA), in silico cytometry, pathway network analysis, in vitro drug screening, and gradient boosting machine (GBM) analysis.
Results
The patients with STAS had a shorter survival time than those without STAS (P < 0.001). We detected gene set-related downregulation of JAK2 associated with STAS using GSEA. Low JAK2 expression was related to poor prognosis and a low CD8+ T-cell fraction. In GBM, JAK2 showed improved survival prediction performance when it was added to other parameters (T stage, N stage, lymphovascular invasion, pleural invasion, tumor size). In drug screening, mirin, CCT007093, dihydroretenone, and ABT737 suppressed the growth of lung cancer cell lines with low JAK2 expression.
Conclusion
In LUAD, low JAK2 expression linked to the presence of STAS might serve as an unfavorable prognostic factor. A relationship between JAK2 and CD8+ T cells suggests that STAS is indirectly related to the anticancer immune response. These results may contribute to the design of future experimental research and drug development programs for LUAD with STAS.

Keyword

JAK2; Lung Adenocarcinoma; Tumor Spread Through Air Spaces (STAS); CD8+ T Cells; Machine Learning

Figure

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  Fig. 1 Schematic diagram depicting the plan of the study.

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  Fig. 2 Representative microphotographs revealing tumor spread through air spaces: (A, B) scattered tumor clusters (black arrow) within the air space (original magnification ×100) (C, D) multiple solid clusters (black arrow) (original magnification ×200) (E, F) single cluster (black arrow) (original magnification ×200).

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  Fig. 3 Survival analyses, gene set enrichment analysis and JAK2 expression. (A, B) Tumor STAS was associated with a low survival rate in patients with lung adenocarcinoma. (C) Gene set enrichment analysis of JAK2 regulation. (D) Bar plots: JAK2 expression was lower in lung adenocarcinoma (DSS, P < 0.001; OS, P < 0.001). (E, F) Low JAK2 expression was related to short survival time in patients with lung adenocarcinoma (DSS, P < 0.050; OS, P = 0.012).STAS = spread through air spaces, JAK2 = Janus kinase 2, DSS = disease-specific survival, OS = overall survival.

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  Fig. 4 We applied supervised machine learning models for prognostic prediction using a GBM. The covariates included confounding factors: (A) Model 1; JAK2, T stage, N stage, tumor size, lymphovascular invasion, pleural invasion, solid predominant histological subtype and micropapillary predominant histological subtype versus (B) Model 2; T stage, N stage, tumor size, lymphovascular invasion, pleural invasion, solid predominant histological subtype and micropapillary predominant histological subtype. And their relative importance based on survival. Receiver operating characteristic curves for the GBM models were generated based on a multivariate Bernoulli model.JAK2 = Janus kinase 2, T = tumor (American joint committee on cancer [AJCC] staging system, 8th edition), N = lymph nodes (AJCC staging system, 8th edition), GBM = gradient boosting machine.

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  Fig. 5 Bar plots of JAK2 expression according to immune cells. Bar plot of (A) CD8+ T cells, (B) naïve B cells, and (C) macrophages. M1, (D) activated memory CD4+ T cells, (E) CD 274 expression, (F) TIDE signature score, (G) IFN-γ expression between samples with low (orange) and high (green) JAK2 expression (P = 0.014, = 0.010, P < 0.001, P < 0.001, P < 0.001, P < 0.001 and P < 0.001, respectively), (H) JAK2 expression between no-responder (red) and responder (blue) patients (P = 0.859) (error bars: standard errors of the mean). (I) Grouping of networks based on functionally enriched Gene Ontology (GO) terms and pathways: JAK2 was directly or indirectly linked to SLC2A4 vesicle translocation, insulin secretion, immune response and IL-6 signaling pathway.JAK2 = Janus kinase 2, PD-1 = programmed death 1, TIDE = Tumor Immune Dysfunction and Exclusion, IFN-γ = interferon-gamma, IL-6 = interleukin-6.

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  Fig. 6 Genomics of Drug Sensitivity in Cancer (GDSC) database analysis. Spearman’s correlations showing the natural log of the half-maximal inhibitory concentration (LN IC50) values of (A, left) Mirin (r = 0.275, P = 0.005), (B, left) CCT007093 (r = 0.195, P = 0.047), (C, left) dihydrorotenone (r = 0.250, P = 0.023) and (D, left) ABT737 (r = 0.222, P = 0.042) [green, high JAK2 expression; orange, low JAK2 expression]. Bar plot showing the LN IC50 values of (A, right) mirin, (B, right) CCT007093, (C, right) dihydrorotenone and (D, right) ABT737 between non-small cell lung cancer cell lines with high (green) and low (orange) JAK2 expression.JAK2 = Janus kinase 2.

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