Lung cancer is the first leading cause of cancer-related deaths in 2020, of which LUAD accounts for almost 40% [2]. Apart from environmental factors like occupational carcinogens, exposure to tobacco smoke, pre-existing non-malignant lung disease, and radon, molecular abnormalities play a critical role in the development of lung cancer. In this regard, many signaling axes have been accused so far in the pathogenesis of this cancer; however, it appears that the mortality of lung cancer is caused by overlaps among these oncogenic pathways. According to the results of KEGG, we found that 91 DE-IRGs are mainly associated with several oncogenic pathways, such as PI3K-Akt, MAPK, RAS, and EGFR. Notably, the new wave of studies has uncovered the role played by the PI3K/Akt pathway not only in lung cancer cell survival but also at the crossroads of different cancer-related pathways. [25]. The oncogenic role of MAPK, RAS, and EGFR deregulation has been also highlighted in the development of NSCLC [26]; interestingly, it has been indicated that upregulation of CBLC __as one of the 9-IRG in our model__ leads to enhanced stability of EGFR and sustained activation of its downstream signaling [27]. Given these, in recent years, PI3K, MAPK, and EGFR have been found to be viable therapeutic targets for novel treatments of cancer; however, lung cancer progression relies not only on the molecular features of tumor cells but also on their interaction with the tumor microenvironment, specifically with the immune cells [28]. In this vein, T-cell activation-induced inhibitory checkpoint molecules, such as CTLA4, PD1, PDL1, and PDL2 are the most relevant target for immunotherapy nowadays [29], and certain ICIs are approved for the treatment of a wide range of malignancies including NSCLC [30].
Despite advances in ICI therapy, only a subset of patients achieves durable clinical benefits, and their survival rate is still unsatisfactory [4]. Accordingly, there is an urgent need to present specific biomarkers that can be used to assess risk and predict the prognosis of LUAD patients and facilitate the development of beneficial therapies. In the current study, we constructed a prognostic immune-related signature by using 9-IRGs, which their details are summarized in Table 6. Four genes (BIRC5, CBLC, S100P, and LGR4) were associated with high risk, whereas five genes (SHC3, ANOS1, PGC, VIPR1, and IGKV4.1) were protective factors in LUAD patients. An increasing body of evidence supports the role of BIRC5, CBLC, VIPR1, and LGR4 in proliferation [31–34], as well as S100P and PGC in cancer metastasis [35, 36]. Interestingly, LGR4 alteration was associated with immunomodulation by promoting macrophage M2 polarization by Rspo/Lgr4/Erk/Stat3 signaling and restricting the anti-tumor activity of CD8+ T cells [37]. Notably, the infiltrating of immune cells into the TME contributes to different biological functions in malignant tumors, and the cross-talk between cancer cells and immune cells can determine the fate of tumor [38, 39].
For further investigation, we applied multiple algorithms to examine the immune infiltration status between the low-and high-risk groups. The results showed that LUAD patients' risk scores were negatively correlated with immune cells infiltrating the tumor; it appears that according to the low frequency of DC, MQ, and different types of T cells in high-risk patients, antigen presentation, T cell activation, and finally, killing of cancer cells are hampered in these patients. Notably, it has been documented that CD8+ T cell infiltration in the TME is associated with improved cancer patient responses to ICIs; Wong et al. demonstrated that melanoma patients who received anti-PD-1 therapy experienced prolonged survival when they had a high CD8+ T cell count [40]. Figure 12 provides a better overview of the TIME and underlying mechanisms of our 9-IRGs.
Apart from immune cells infiltration, it is reported that TMB could be a possible predictive factor for ICI therapy. A recent meta-analysis containing 11 studies demonstrated that NSCLC patients with high TMB could benefit more from immunotherapy than patients with low TMB [41]; however, several other studies showed that high TMB failed to predict ICI response across all cancer types [42–44]. There is also a controversy about the cutoff value of the TMB [45]. Consistent with a previous study, we found that the TMB was markedly lower in the low-risk group [46], indicating that high TMB does not necessarily lead to a better response to ICI therapy. This may be explained by assuming that IPS is a complex model including several factors; therefore, it is possible that other variables, like upregulated immune checkpoint expression, may contribute to the better ICI response in the low-risk group.
Since it has been proved that IPS has a predictive value in patients receiving PD-1 and CTLA-4 inhibitors for melanoma [24], we investigated IPS among our risk groups. According to the results, low-risk patients had significantly higher IPS values, meaning that the immunogenicity of the tumor immune contexture was also elevated in this group. To reconfirm the checkpoint inhibitor-based immunotherapy efficacy in LUAD samples with different risk scores, we also investigated the expression of immune checkpoint genes. The findings revealed that the low-risk group had high levels of their expression, indirectly implying the preexisted T cell activation for this group, suggesting that they had a better chance of receiving ICI treatment. Taken together, we developed an IRG-based prognostic model in LUAD patients, which is predictive of patients' survival and ICI immunotherapy outcomes and reflects the tumor immune microenvironment status based on RNA sequencing data. We believe that this signature might be helpful in managing LUAD patients in clinical practice; however, its validation in clinical settings is required.
Table 6
The detail of 9-IRGs are included in the model.
Symbol | Protein | Alternation | Description | Alteration in other cancers |
BIRC5 | Survivin | Up-regulated | • Inhibitor of apoptosis protein5 • Through its roles in mitosis, apoptosis suppression, autophagy, metabolism, angiogenesis, and migration, survivin can have multiple functions in promoting tumor cell survival and metastasis | Almost all cancers, such as pancreatic, breast, ovarian, brain, and colon cancer |
CBLC | CBL proto-oncogene c | Up-regulated | • Enhanced stability of EGFR and sustained activation of its downstream signaling • Leads to uncontrolled cell proliferation, tumorigenesis, and cancer progression | Pancreas, breast, and colorectal carcinomas cells cancer |
S100P | S100 calcium binding protein P | Up-regulated | • Through combining Ca2 + ions, receptor for advanced glycation end products, cytoskeletal protein ezrin, calcyclin-binding protein/Siah-1-interacting protein and cathepsin D, S100P plays a part in inducing tumor growth, metastasis and invasion. | Cervical, colon, breast, melanoma, ovarian, and oral cancer |
IGKV4.1 | Immunoglobulin kappa variable 4 − 1 | Up-regulated | • IGKV41 gene encodes a B cell receptor | Breast, renal, head and neck cancers |
LGR4 | Leucine-rich repeat-containing G-protein–coupled receptor 4 | Up-regulated | • Lgr4 and its ligands R-spondin have been shown to promote the growth and metastasis of tumor cells. • Promotes macrophage M2 polarization through Rspo/Lgr4/Erk/Stat3 signaling. | Multiple myeloma, thyroid carcinoma, ovarian, prostate, colon, and breast cancer |
PGC | Pepsinogen C | Down-regulated | • PGC in the acidic organelles hydrolyses pro-surfactant protein B (pro-SPB), which is secreted by alveolar type 2 epithelial cells. So, it plays a major role in lung maturation. | Gastric, breast, prostate, ovarian, endometrial, pancreatic, kidney, bladder, squamous cell carcinoma and melanoma cancers |
SHC3 | SHC adaptor protein 3 | Down-regulated | • Signaling adapter that couples activated growth factor receptors to signaling pathway in neurons | |
ANOS1 | Anosmin-1 | Down-regulated | • Anosmin-1 is an extracellular matrix protein with adhesion and chemoattractant characteristics | Colon, ovary, hepatocellular carcinoma, breast cancer |
VIPR1 | Vasoactive Intestinal Peptide receptor | Down-regulated | • A receptor for vasoactive intestinal peptide (VIP), a small neuropeptide. • VIPR1 inhibits the growth, migration, and invasion of several cancers. | Hepatocellular carcinoma |