Abstract
The invasive capacity of lung adenocarcinoma (LUAD) is an important factor influencing patients’ metastatic status and survival outcomes. However, there is still a lack of suitable biomarkers to evaluate tumor invasiveness. LUAD molecular subtypes were identified by unsupervised consistent clustering of LUAD. The differences in prognosis, tumor microenvironment (TME), and mutation were assessed among different subtypes. After that, the invasion-related gene score (IRGS) was constructed by genetic differential analysis, WGCNA analysis, and LASSO analysis, then we evaluated the relationship between IRGS and invasive characteristics, TME, and prognosis. The predictive ability of the IRGS was verified by in vitro experiments. Next, the “oncoPredict” R package and CMap were used to assess the potential value of IRGS in drug therapy. The results showed that LUAD was clustered into two molecular subtypes. And the C1 subtype exhibited a worse prognosis, higher stemness enrichment activity, less immune infiltration, and higher mutation frequency. Subsequently, IRGS developed based on molecular subtypes demonstrated a strong association with malignant characteristics such as invasive features, higher stemness scores, less immune infiltration, and worse survival. In vitro experiments showed that the higher IRGS LUAD cell had a stronger invasive capacity than the lower IRGS LUAD cell. Predictive analysis based on the “oncoPredict” R package showed that the high IRGS group was more sensitive to docetaxel, erlotinib, paclitaxel, and gefitinib. Among them, in vitro experiments verified the greater killing effect of paclitaxel on high IRGS cell lines. In addition, CMap showed that purvalanol-a, angiogenesis-inhibitor, and masitinib have potential therapeutic effects in the high IRGS group. In summary we identified and analyzed the molecular subtypes associated with the invasiveness of LUAD and developed IRGS that can efficiently predict the prognosis and invasive ability of the tumor. IRGS may be able to facilitate the precision treatment of LUAD to some extent.
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Introduction
Lung cancer is the leading cause of cancer-related deaths worldwide, and its incidence rate is ranked second in the world1. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer which accounts for about 40% of all lung cancers2,3,4. Despite the great advances in cancer treatment in the fields of surgery, chemotherapy, radiotherapy, and targeted therapy in recent years have led to improved survival rates for LUAD5. However, there are still many LUAD patients who cannot achieve the desired outcome with conventional therapies due to the heterogeneity, metastasis, and drug resistance, and the heterogeneity within the tumor also leads to different benefit levels for each LUAD6,7,8,9. Therefore, it is necessary to develop a biomarker that can effectively differentiate different subtypes of LUAD for precise clinical treatment of patients to improve the prognosis of lung adenocarcinoma.
The invasive ability and metastatic ability of tumors are closely interrelated, and they directly affect patient prognosis as major hallmarks of cancer10. Accumulating evidence shows that molecular characteristics are generally altered between tumors with different invasiveness or between the primary and metastatic sites of tumors11,23. Similarly, in a study by Santisteban et al.61, it was found that CD8 T cells can induce EMT transformation to promote cancer progression. (in which EMT, as one of the tumor markers, is closely related to the invasive ability of the tumor). In addition, it has also been reported that the remodeling of inflammatory tumor microenvironment in lung adenocarcinoma is closely associated with the altered EMT status62. Comparatively, in the C3 subtype, which has the least distribution of IRGS, the TME attributes are dominated by Th17 and Th1, and low to moderate tumor cell proliferation, where Th17 is thought to suppress tumor63. From these results, we can see that immune infiltration, including T cells, can induce changes in the invasive capacity of tumors, and that the changes in tumor invasive capacity induced by differences in the type of T-cell infiltration as well as the different degree of infiltration. Overall, multiple factors within TME can contribute to a patient’s transformation to an invasive malignant phenotype.
To further expand the potential clinical value of IRGS. We analyzed the drug sensitivity of each patient, and LUAD patients with high IRGS showed sensitivity to drugs such as Docetaxel, Erlotinib, Paclitaxel, and Gefitinib. Subsequent in vitro experiments validated the greater killing effect of paclitaxel on high IRGS cell lines. This means that this IRGS may be able to provide some extent of guidance in the selection of clinical treatment options. CMap analysis screened for drugs including purvalanol-a, angiogenesis-inhibitor, and masitinib as therapeutic candidates for invasive LUAD. These drugs may have an important role in suppressing the invasive phenotype and preventing metastasis in LUAD. Among them, the CMap database perturbation scores showed that purvalanol-a was the most perturbative drug on the expression of highly aggressive LUAD molecules. purvalanol-a acts as a CDK inhibitor, which effectively inhibits cell progression from the G2 phase to mitosis. In a previous study, Chen et al. reported that purvalanol-a could enhance the cytotoxic effect of purvalanol on non-small cell carcinoma by inhibiting tumor protein 18 (Oncoprotein 18)64. In gastric cancer, Iizuka et al. found that purvalanol-a could promote apoptosis in X-ray irradiated gastric cancer cells by activating the active fragment of caspase 365. And in colon cancer, purvalanol-a can promote apoptosis of colon cancer cells by upregulating the protein expression of Bax and Puma66. Overall, these studies consistently suggest that purvalanol-a could be a potential therapeutic agent for patients with highly invasive phenotypes, which provides further evidence for purvalanol-a-related clinical drug development.
However, there are still limitations to this study. Firstly, although our invasion-related gene score has been validated in several datasets as well as in vitro experiments in predicting the invasive ability and prognosis of patients. But further in vivo experiments are still needed for validation. Second, Further exploration of the potential link between TME and tumor invasive capacity is still needed to shed more light on the potential factors that contribute to the heterogeneity of tumor invasive capacity. Thirdly, the effects of potential drugs screened based on IRGS for invasive LUAD still need further vivo experimental validation. Furthermore, more clinical samples are still needed to corroborate the efficiency of IRGS in predicting the invasive ability of LUAD patients.
Conclusions
In summary, this study identified novel invasive molecular subtypes of LUAD based on the expression patterns of metastasis-related pathways and established the invasion-related gene score (IRGS), which is effective in predicting the prognosis and invasiveness of LUAD. It can provide some reference for the selection of clinical decisions.
Data availability
The datasets analyzed during the current study are available on the UCSC website (https://xenabrowser.net/datapages/); MSigDB website (http://www.gseamsigdb.org/gsea/msigdb/index.jsp); CCLE database (https://sites.broadinstitute.org/ccle/) and Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/), including GSE72094 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE72094), GSE31210 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31210), GSE50081 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50081), GSE42127 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42127), GSE166722 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE166722), GSE27717 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE27717), GSE202859 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE202859) and GSE136935 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE136935) datasets.
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Acknowledgements
The authors are grateful to the patients and staff who participated in GEO and TCGA.
Funding
This study was sponsored by the National Natural Science Foundation of China (81971483); the Collaborative Innovation Project of Colleges and Universities of Anhui Province (GXXT-2020-058); Anhui Province Engineering Laboratory of Occupational Health and Safety (AYZJSGCLK202201001, AYZJSGCLK202201002, AYZJSGCLK 202202001); Key Laboratory of Industrial Dust Deep Reduction and Occupational Health and Safety of Anhui Higher Education Institutes (AYZJSGXLK202202002); the Innovation and Entrepreneurship Project of Anhui University of Science and Technology (2021CX2125, 2021CX2126, 2021CX2124) and Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology (2022y jrc14).
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H.D., B.Y. and W.J.: designing research ideas and supervising the study. Z.J., L.Y., H.T., G.J., X.Y., and X.J.: development of methodology, analysis, and writing of the manuscript. L.Y. and H.T. contributed equally to this work.
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Han, T., Liu, Y., Zhou, J. et al. Development of an invasion score based on metastasis-related pathway activity profiles for identifying invasive molecular subtypes of lung adenocarcinoma. Sci Rep 14, 1692 (2024). https://doi.org/10.1038/s41598-024-51681-9
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DOI: https://doi.org/10.1038/s41598-024-51681-9
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