In this study, RNA-sequencing and 18F-FDG PET/CT images of non-small cell lung cancer patients were used to search for gene groups expression related to non-small cell lung cancer metastasis and imaging features related to the expression of gene groups. The gene group involved in metastasis has an EMT function known to be induce metastasis. It was observed that one of the imaging features, GLCM_contrast, was expressed in relation to the expression of EMT function. This is a clue that can predict the metastasis of non-small cell lung cancer through the analysis of imaging features.
Recently, a combination of two analysis methods, NGS and PET CT imaging, has been studied to overcome the limitations of each. The prediction and diagnosis of lung cancer metastasis is related to serious problems for patients because lung cancer shows no symptoms or pain until the late stages and has spread to other organs, with a high probability of being at a late stage when diagnosed18. Development of a composite diagnosis method for genes and images has the advantage of being noninvasive19 and fast compared to existing diagnostic methods, and is also capable of diagnosing overall cancer. In terms of genetic analysis, two methods were used to reduce the number of genes used for analysis. The first was to select genes with significant differences between the two groups using a t-test20 and the second was to use the hub gene assay to select genes with the desired functions. A t-test was performed for more efficient analysis to remove genes with low P-values using mathematical calculations20. Genes were divided into modules according to the gene expression pattern through WGCNA analysis, and each module was assigned a significant value according to its contribution to the module. One module selected had the highest gene significance. A total of 7 genes were identified as EMT-related genes from the selected module (GS > 0.8 and AUC > 0.6). The hypergeometric distribution method21 was used to identify which EMT-related genes are associated with image features extracted from the genetics. The relevance of image features and genes was calculated by P-value and was listed from low values. P-values greater than 0.05 were excluded. Gene expressed levels were compared in patients with and without metastasis of each gene to identify differences in both conditions. A total of seven genes were identified as having a high relationship with one radiomics: GLCM_contrast. The seven identified genes, NME1.NME2, LST1, KAT7, BMX, CLIC1, TAP2 and PSMB9 are known to be involved in EMT. Bone marrow X-linked kinase (BMX) has been reported to be involved in EMT, such as cell growth, transformation, migration, survival, apoptosis, and tumorigenicity22–25. Nucleoside diphosphate kinase A (NME1) and nucleoside diphosphate kinase B (NME2) form the complex unit NM23 (NME1.NME2) and have the nucleoside diphosphate kinase activity, which catalyzes the phosphorylation of nucleoside diphosphates to the corresponding nucleoside triphosphates. NME1.NME2 is the first metastasis suppressor in lung cancer. A decrease in NME1.NME2 increases cancer metastasis26. The function or mechanism of leukocyte-specific transcript 1 protein (LST1) has not been well studied, but high expression of LST1 in metastasized lung cancer has been reported27. Chloride intracellular channel 1 (CLIC1) has the ability of the antiangiogenic peptide CLT1 on proliferating endothelial cells 28. CLIC1 is mainly overexpressed in the tumor vasculature, and overexpression has been observed in breast, lung, and liver cancer patients29,30. CLIC1 has been shown to promote regular invasion and proliferation of tumor and endothelial cells, but the underlying mechanism is unclear31. Transporter associated with antigen processing 1 (TPA1) regulates WISP2, which can affect TGF-b signaling. TGB-b signaling is one of the most important roles of EMT in breast cancer32. Proteasome subunit beta type-9 (PSMB9) is co-expressed with RARRES3 and is a well-known metastasis suppressor in breast cancer cells33.
EMT is an evolutionarily conserved process in which cells undergo the conversion from epithelial cells to mesenchymal cells. EMT was found in a study on the development of embryo stem cells. EMT is a major activity during embryo stem cell development, gastrulation, neural nests, and development of the heart and other tissues and organs34. Recent studies have shown that EMT is also implicated in cancer progression and metastasis. Studies on breast cancer metastasis suggest that EMT is also involved in the acquisition of characteristics of cancer stem-like cells (CSCs)35. CSCs are cancer cells that have the characteristics of embryonic stem cells of self-renewal, regeneration, and differentiation to diverse types of cancer cells. CSCs are thought to be crucial for the initiation and maintenance of tumors as well as their metastasis36. Many studies using NGS for NSCLC have been performed because of the ability to determine the molecular characteristics of the cancer state for diagnosis or treatment37. NGS is a technology that can analyze gene expression levels at a fast and large scale compared to conventional gene analysis methods. However, a limitation is biopsies are need for sampling, which is not available all cancer cases because of cancer location38. Another limitation is representativeness39. Cancer tissues have a high heterogeneity; biopsy samples cannot represent all cancer regions. To overcome this limitation, image features had to be introduced into the analysis.
PET/CT images have become a popular research topic for the diagnosis of NSCLC in recent days. Features extracted from the images were used for analysis. Each feature is represented by a call status such as cell shape, cell surface texture, and cell density. These features were digitized for cancer analysis using a mathematical method40. Many studies have been published on the possibility of tumor classification by analysis of PET/CT texture features with 18F-FDG PET/CT. The development of 18FDG PET/CT imaging technology and techniques for analyzing digitized features from images have information on cell activity 41. A limitation of the PET/CT imaging method is the lack of information from image analysis. Imaging factors of cells or tissues can only provide information on cell morphology and the texture of the cell surface. Some cancers with a unique phenotype can be diagnosed, but accurate diagnosis is not possible for most cancers using a phenotype because it cannot represent the genotype42.
GLCM_contrast is a feature from image feature analysis. It is considered a texture feature from the LIFEx image analysis tool. In general, features such as SUVmax, SUVpeak, TLG, and ENTROPY were used for radiogenomics analysis for cancer prediction or cancer metastasis prediction43. However, in this study, the correlation (P-value) of SUVmax, SUVpeak, TLG, and ENTROPY was lower than that of GLCM_contrast. This result shows that new factors such as GLCM_contrast can be used to develop a model for predicting metastasis of NSCLC using radiogenomics. One of the limitations of our study that although we provide the evidence that EMT related gene has relation to GLCM_contrast in NSCLC but do not provide mechanistic studies. While this was not the goal of this study, future investigations could be directed toward to uncover the mechanisms of operation of genes that play an important role in NSCLC metastasis, and to elucidate the correlation of expression of imaging features. Large scale of follow-up studies with molecular mechanism of metastasis in NSCLC could strengthen the study and further confirm and extend our findings. In addition, it was possible to search for radiomics related to EMT genes in this study and it will be possible to search for imaging biomarkers for diagnosis and prognosis by analyzing genetic functions related to other cancers or diseases.