Tumor-derived KLK8 predicts inferior survival and promotes an immune-suppressive tumor microenvironment in lung squamous cell carcinoma.

Lung squamous cell carcinoma (LUSC) is the second most common lung cancer worldwide, leading to millions of deaths annually. Although immunotherapy has expanded the therapeutic choices for LUSC and achieved considerable efficacy in a subset of patients, many patients could not benefit, and resistance was pervasive. Therefore, it is significant to investigate the mechanisms leading to patients' poor response to immunotherapies and explore novel therapeutic targets. Using multiple public LUSC datasets, we found that Kallikrein-8 (KLK8) expression was higher in tumor samples and was correlated with inferior survival. Using a LUSC cohort (n = 190) from our center, we validated the bioinformatic findings about KLK8 and identified high KLK8 expression as an independent risk factor for LUSC. Function enrichment showed that several immune signaling pathways were upregulated in the KLK8 low-expression group and downregulated in the KLK8 high-expression group. For patients with low KLK8 expression, they were with a more active TME, which was both observed in the TCGA database and immune marker immunohistochemistry, and they had extensive positive relations with immune cells with tumor-eliminating functions. This study identified KLK8 as a risk factor in LUSC and illustrated the associations between KLK8 and cancer immunity, suggesting the potentiality of KLK8 as a novel immune target in LUSC.

Integrated pathological analysis to develop a Gal-9 based immune survival stratification to predict the outcome of lung large cell neuroendocrine carcinoma and its usefulness in immunotherapy.

This study aimed to integrate the cell spatial organization to develop a Gal-9-based immune survival stratification in the lung large cell neuroendocrine carcinoma (LCNEC) and investigate its potentials to immunotherapy. The expression of Gal-9 and other twelve immune markers were evaluated in 122 cases of surgical LCNEC samples from our center using immunohistochemistry. The Gal-9-based immune survival stratification risk score was constructed and its predictive performance was evaluated. Then, we thoroughly explored the effects of Gal-9 and immune risk score on LCNEC immune pathways, immune micro-environment and immunotherapy sensitivity in different cohort and platform, and made a validation in pathology images using Histology-based Digital-Staining (HDS). In 122 LCNEC samples, 43 cases were positive Gal-9 expression on tumor cells (Gal-9 TC). Increased Gal-9 TC predicted worse overall survival. Gal-9's interaction with other immune markers added to the immune suppression and immune tolerance in LCNEC. Immune protein marker-based risk score consisting of Gal-9, CD3, CD4, PD-L1, and PD-1 was developed and validated to robustly discriminate survival high-risk or low-risk in LCNEC patients. The high-risk group characterized by immune-desert tumor had less various T cells. The low-risk group featuring immune-inflamed tumor was more likely to respond to anti-PD1 immunotherapy. HDS in 122 LCNEC samples' 108,369 cells validated that the high-risk group had more tumor cells, less stromal cells, less lymphocytes, higher tumor cell nucleic solidity and lower stromal cells nucleic solidity. An integrated pathological analysis confirms the Gal-9 based immune survival stratification is distinctively related to micro-environment status involved in immune suppression and immune tolerance and could act as a combinatorial biomarker to predict the outcome of LCNEC. These findings may help effectively stratify LCNEC patients sensitive to immunotherapy.

The combination of novel immune checkpoints HHLA2 and ICOSLG: A new system to predict survival and immune features in esophageal squamous cell carcinoma.

Studies on immune checkpoint inhibitors targeting B7-CD28 family pathways in esophageal squamous cell carcinoma (ESCC) have shown promising results. However, a comprehensive understanding of B7-CD28 family members in ESCC is still limited. This study aimed to construct a novel B7-CD28 family-based prognosis system to predict survival in patients with ESCC. We collected 179 cases from our previously published microarray data and 86 cases with qPCR data. Specifically, 119 microarray data (GSE53624) were used as a training set, whereas the remaining 60 microarray data (GSE53622), all 179 microarray data (GSE53625) and an independent cohort with 86 qPCR data were used for validation. The underlying mechanism and immune landscape of the system were also explored using bioinformatics and immunofluorescence. We examined 13 well-defined B7-CD28 family members and identified 2 genes (ICSOLG and HHLA2) with the greatest prognostic value. A system based on the combination HHLA2 and ICOSLG (B7-CD28 signature) was constructed to distinguish patients as high- or low-risk of an unfavorable outcome, which was further confirmed as an independent prognostic factor. As expected, the signature was well validated in the entire cohort and in the independent cohort, as well as in different clinical subgroups. The signature was found to be closely related to immune-specific biological processes and pathways. Additionally, high-risk group samples demonstrated high infiltration of Tregs and fibroblasts and distinctive immune checkpoint panels. Collectively, we built the first, practical B7-CD28 signature for ESCC that could independently identify high-risk patients. Such information may help inform immunotherapy-based treatment decisions for patients with ESCC.

LAMC1 upregulation via TGFß induces inflammatory cancer-associated fibroblasts in esophageal squamous cell carcinoma via NF-κB-CXCL1-STAT3.

Cancer-associated fibroblasts (CAF) are a heterogeneous cell population within the tumor microenvironment,and play an important role in tumor development. By regulating the heterogeneity of CAF, transforming growth factor ß (TGFß) influences tumor development. Here, we explored oncogenes regulated by TGFß1 that are also involved in signaling pathways and interactions within the tumor microenvironment. We analyzed sequencing data of The Cancer Genome Atlas (TCGA) and our own previously established RNA microarray data (GSE53625), as well as esophageal squamous cell carcinoma (ESCC) cell lines with or without TGFß1 stimulation. We then focused on laminin subunit gamma 1 (LAMC1), which was overexpressed in ESCC cells, affecting patient prognosis, which could be upregulated by TGFß1 through the synergistic activation of SMAD family member 4 (SMAD4) and SP1. LAMC1 directly promoted the proliferation and migration of tumor cells, mainly via Akt-NFκB-MMP9/14 signaling. Additionally, LAMC1 promoted CXCL1 secretion, which stimulated the formation of inflammatory CAF (iCAF) through CXCR2-pSTAT3. Inflammatory CAF promoted tumor progression. In summary, we identified the dual mechanism by which the upregulation of LAMC1 by TGFß in tumor cells not only promotes ESCC proliferation and migration, but also indirectly induces carcinogenesis by stimulating CXCL1 secretion to promote the formation of iCAF. This finding suggests that LAMC1 could be a potential therapeutic target and prognostic marker for ESCC.

PLAU directs conversion of fibroblasts to inflammatory cancer-associated fibroblasts, promoting esophageal squamous cell carcinoma progression via uPAR/Akt/NF-κB/IL8 pathway.

Cancer-associated fibroblasts (CAFs) plays an important role in the tumor microenvironment. The heterogeneity of CAFs affects the effect of CAFs on promoting or inhibiting tumors, which can be regulated by other cells in the tumor microenvironment through paracrine methods. The urokinase-type plasminogen activator (PLAU) system mediates cell proliferation, migration, adhesion, and other functions through the proteolytic system, intracellular signal transduction, and chemokine activation. PLAU promotes tumor progression in many tumors. We explored the function of PLAU in ESCC and the influence of PLAU secreted by tumor cells on the heterogeneity of CAFs. We found that PLAU is highly expressed in ESCC, which is related to poor prognosis and can be used as a prognostic marker for ESCC. Through loss-of function and gain-of function experiments, we found that PLAU promoted ESCC proliferation and clone formation via MAPK pathway, and promotes migration by upregulating Slug and MMP9, which can be reversed by the MEK 1/2 inhibitor U0126. At the same time, through sequencing, cytokine detection, and RT-qPCR verification, we found that tumor cells secreted PLAU promoted the conversion of fibroblasts to inflammatory CAFs, which upregulated expression and secretion of IL8 via the uPAR/Akt/NF-κB pathway. The IL8 secreted by CAFs in turn promotes the high expression of PLAU in tumor cells and further promoted the progression of ESCC. In summary, PLAU was not only a prognostic marker of ESCC, which promoted tumor cell proliferation and migration, but also promoted the formation of inflammatory CAFs by the PLAU secreted by tumor cells.

The average copy number variation (CNVA) of chromosome fragments is a potential surrogate for tumor mutational burden in predicting responses to immunotherapy in non-small-cell lung cancer.

OBJECTIVES: The tumor mutational burden (TMB) is closely related to immunotherapy outcome. However, the cost of TMB detection is extremely high, which limits its use in clinical practice. A new indicator of genomic instability, the average copy number variation (CNVA), calculates the changes of 0.5-Mb chromosomal fragments and requires extremely low sequencing depth. METHODS: In this study, 50 samples (23 of which were from patients who received immunotherapy) were subjected to low-depth (10X) chromosome sequencing on the MGI platform. CNVA was calculated by the formula avg (abs (copy number-2)). In addition, CNVA and TMB were compared with regard to their ability to predict immune infiltration in 509 patients from TCGA. RESULTS: The high-CNVA group had higher expression levels of PD-L1, CD39 and CD19 and a higher degree of infiltration of CD8+ T cells and CD3 + T cells. Among the 23 patients treated with immunotherapy, the average CNVA value of the stable disease/partial response group was higher than that of the progressive disease group (P < 0.05). Whole-genome sequencing data of 509 patients from TCGA and RT-PCR results of 22 frozen specimens showed that CNVA is more effective than TMB in indicating infiltration of CD8+ T cells and expression of PD-L1, and CNVA also showed a specific positive correlation with TMB (r = 0.2728, P < 0.0001). CONCLUSIONS: Copy number variation can be a good indicator of immune infiltration and immunotherapy efficacy, and with its low cost, it is expected to become a substitute for TMB.

The membrane-bound and soluble form of melanotransferrin function independently in the diagnosis and targeted therapy of lung cancer.

Melanotransferrin (MFI2) is a newly identified tumor-associated protein, which consists of two forms of proteins, membrane-bound (mMFI2) and secretory (sMFI2). However, little is known about the expression pattern and their relevance in lung cancer. Here, we found that both two forms of MFI2 are highly expressed in lung cancer. The expression of MFI2 in lung cancer was detected by using the public database and qRT-PCR. Overexpression and knockdown cell lines and recombinant sMFI2 protein were used to study the function of mMFI2 and sMFI2. RNA-seq, protein chip, ChIP assay, Immunoprecipitation, ELISA, and immunofluorescence were used to study the molecular biological mechanism of mMFI2 and sMFI2. We found that mMFI2 promoted the expression of EMT's common marker N-cadherin by downregulating the transcription factor KLI4, which in turn promoted tumor metastasis; sMFI2 could promote the metastasis of autologous tumor cells in an autocrine manner but the mechanism is different from that of mMFI2. In addition, sMFI2 was proved could inhibit the migration of vascular endothelial cells and subsequently enhance angiogenic responses in a paracrine manner. We propose that the expressions and functions of the two forms of MFI2 in lung cancer are relatively independent. Specifically, mMFI2 was a potential lung cancer therapeutic target, while sMFI2 was highly enriched in advanced lung cancer, and could be used as a tumor staging index.

ERO1L promotes IL6/sIL6R signaling and regulates MUC16 expression to promote CA125 secretion and the metastasis of lung cancer cells.

The abnormal secretion of CA125, a classic tumor marker, is usually related to a poor prognosis in various tumors. Thus, this study aimed to explore the potential mechanisms that promote CA125 secretion in lung cancer. By querying the database, the gene endoplasmic reticulum oxidoreductase 1L (ERO1L) was identified and chosen as the research subject. The antibody chips were used to screen the lung cancer cell supernatant and found that the most obvious secreted protein was CA125. ERO1L was found to promote the secretion of IL6R by affecting the formation of disulfide bonds. IL6R bound to IL6 and triggered the activation of the NF-κB signaling pathway. Then, NF-κB bound to the promoter of MUC16, resulting in overexpression of MUC16. The extracellular segment of MUC16 was cleaved to form CA125, while the C terminus of MUC16 promoted the EMT phenotype and the release of IL6, forming a positive feedback pathway. In conclusion, ERO1L might affect the secretion of CA125 through the IL6 signaling pathway and form a positive feedback loop to further promote the development of lung cancer. This might expand the application scope of CA125 in lung cancer.

A three-lncRNA signature of pretreatment biopsies predicts pathological response and outcome in esophageal squamous cell carcinoma with neoadjuvant chemoradiotherapy.

BACKGROUND: Current strategies are insufficient to predict pathologically complete response (pCR) for esophageal squamous cell carcinomas (ESCCs) before treatment. Here, we aim to develop a novel long noncoding RNA (lncRNA) signature for pCR and outcome prediction of ESCCs through a multicenter analysis for a Chinese population. METHODS: Differentially expressed lncRNAs (DELs) between pCRs and less than pCR (

An individualized immune signature of pretreatment biopsies predicts pathological complete response to neoadjuvant chemoradiotherapy and outcomes in patients with esophageal squamous cell carcinoma.

No clinically available biomarkers can predict pathological complete response (pCR) for esophageal squamous cell carcinomas (ESCCs) with neoadjuvant chemoradiotherapy (nCRT). Considering that antitumor immunity status is an important determinant for nCRT, we performed an integrative analysis of immune-related gene profiles from pretreatment biopsies and constructed the first individualized immune signature for pCR and outcome prediction of ESCCs through a multicenter analysis. During the discovery phase, 14 differentially expressed immune-related genes (DEIGs) with greater than a twofold change between pCRs and less than pCRs (

Comprehensive molecular analyses of a TNF family-based signature with regard to prognosis, immune features, and biomarkers for immunotherapy in lung adenocarcinoma.

BACKGROUND: Tumour Necrosis Factor (TNF) family members play important roles in mounting anti-tumour immune responses, and clinical trials targeting these molecules are ongoing. However, the expression patterns and clinical significance of TNF members in lung adenocarcinoma (LUAD) remain unrevealed. This study aimed to explore the gene expression profiles of TNF family members in LUAD and constructed a TNF family-based prognosis signature. METHODS: In total, 1300 LUAD cases from seven different cohorts were collected. Samples from The Cancer Genome Atlas (TCGA) were used as the training set, and the RNA data from five Gene Expression Omnibus (GEO) datasets and qPCR data from 102 samples were used for validation. The immune profiles and potential immunotherapy response prediction value of the signature were also explored. FINDINGS: After univariate Cox proportional hazards regression and stepwise multivariable Cox analysis, a TNF family-based signature was constructed in the TCGA dataset that significantly stratified cases into high- and low-risk groups in terms of OS. This signature remained an independent prognostic factor in multivariate analyses. Moreover, the clinical significance of the signature was well validated in different clinical subgroups and independent validation cohorts. Further analysis revealed that signature high-risk patients were characterized by distinctive immune cell proportions and immune-suppressive states. Additionally, signature scores were positively related to multiple immunotherapy biomarkers. INTERPRETATION: This was the first TNF family-based model for predicting outcomes and immune landscapes for patients with LUAD. The capability of this signature for predicting immunotherapy response needs further validation.

Immune signature of tumor-infiltrating immune cells predicts the prognosis and therapeutic effects in squamous cell carcinoma.

Tumor-infiltrating immune cells (TICs) are involved in tumor progression and determine the prognosis. We investigated how TICs affect the prognosis and therapeutic effects of squamous cell carcinoma (SCC), which share common histological features and certain risk factors. The SCC data from The Cancer Genome Atlas (TCGA) and Gene expression Omnibus (GEO) databases were downloaded to evaluate the composition of TICs with the CIBERSORT algorithm. LASSO and Cox multivariate regression analyses were used to build a prognostic risk model. Chemotherapeutic and immunotherapeutic responses were compared between patients with SCC. A Gene set variation analysis (GSVA) was also performed to elucidate the mechanism. Naïve B cells and resting mast cells were selected to construct the prognostic model. According to these two immune cell subtypes, patients with SCC were divided into low- and high-risk groups. The low-risk group with high proportions of naïve B cells and resting mast cells had a better overall survival rate than the high-risk group and might benefit from immunotherapy and chemotherapy due to differences in the immune microenvironment. Activation of the Wnt signaling pathway was observed in the high-risk group. Based on the findings from the present study, the immune signature provides prognostic determinants of SCC and may be a biomarker to guide chemotherapy and immunotherapy. Wnt inhibitors may be attractive candidates for combination treatment in high-risk patients with SCC.

Combined detection of aneuploid circulating tumor-derived endothelial cells and circulating tumor cells may improve diagnosis of early stage non-small-cell lung cancer.

BACKGROUND: Many tumor-derived endothelial cells (TECs) are shed into the blood and turn into circulating TECs (CTECs). Rare circulating non-hematologic aneuploid cells contain CTCs and CTECs, which are biologically and functionally different from each other. CD31 is one of the most representative endothelial cell (EC) markers, yet CD31 alone is not sufficient to detect malignant CTECs due to the existence of abundant normal ECs in circulation. Aneuploidy of chromosome 8 (CEP8) is an important criterion for the identification of malignant cells. Combined in situ phenotypic and karyotypic characterization, which includes an examination of both protein expression and aneuploid chromosomes, has demonstrated its unique advantage for both effective distinguishing and comprehensive detection of CTCs and CTECs. METHODS: A total of 98 subjects were recruited in the current study, including healthy donors and patients with benign disease and early-stage non-small-cell lung cancer (NSCLC). SE-iFISH was performed to quantitatively analyze diverse subtypes of aneuploid CD31+ CTECs and CD31- CTCs classified upon the ploidy of chromosome 8 and tumor marker expression in the specimens collected from the recruited subjects. RESULTS: CD31- CTCs primarily consist of triploid CTCs with a small cell size (≤5 µm) and large hyperploid CTCs (≥ pentaploid), whereas CD31+ CTECs are mainly comprised of large hyperploid cells. Enumeration of the total numbers of both CTCs and CTECs might help identify malignant nodules with a high sensitivity, whereas quantification of tetraploid CTCs and CTECs specifically exhibited a high specificity for the identification of malignant nodules. CONCLUSIONS: Combined detection of the specific subtypes of aneuploid CD31+ CTECs and CD31- CTCs may help to effectively identify malignant nodules with a higher sensitivity and specificity in early stage NSCLC patients.

Systematic profiling of immune signatures identifies prognostic predictors in lung adenocarcinoma.

PURPOSE: Lung adenocarcinoma (LUAD) is the predominant subtype of lung cancer, with increasing evidence showing clinical benefits of immunotherapy. However, a lack of integrated profiles of complex LUAD immune microenvironments hampers the application of immunotherapy, resulting in limited eligible patient populations as well as drug resistance problems. Here, we aimed to systematically profile the immune signatures of LUADs and to assess the role of the immune microenvironment in patient outcome. METHODS: We systematically profiled the immune signatures of LUADs deposited in the TCGA and GEO databases using a total of 730 immune-related genes. Differential expression analysis was used to identify dysregulated genes. Univariate Cox analysis followed by robust likelihood-based survival analysis and multivariate Cox analysis were applied to construct an immune-related prognostic model. RESULTS: We found that differentially expressed immune genes were mainly enriched in immune cell proliferation, migration, activation and the NF-κB and TNF signaling pathways. The 10-immune gene predictive model that we constructed could differentiate LUAD patients with different overall survival times in several datasets, with areas under the curve (AUCs) of 0.67, 0.69, 0.72 and 0.74. LUAD patients with high- or low-risk scores exhibited distinct immune cell compositions, which may explain the prognostic significance of our model. CONCLUSIONS: Our results add to the current knowledge of immune processes in LUADs and underscore the critical role of the immune microenvironment in LUAD patient outcome.

Clinical significance and inflammatory landscapes of a novel recurrence-associated immune signature in early-stage lung adenocarcinoma.

The prevalence of early-stage lung adenocarcinoma (LUAD) has increased alongside increased implementation of lung cancer screenings. Robust discrimination criteria are urgently needed to identify those patients who might benefit from additional systemic therapy. Here, to develop a reliable, individualized immune gene-set-based signature to predict recurrence in early-stage LUAD, a novel recurrence-associated immune signature was identified using a least absolute shrinkage and selection operator model, and a stepwise Cox proportional hazards regression model with a training set comprised of 338 early-stage LUAD samples form TCGA, which was subsequently validated in 226 cases from GSE31210 and an independent set of 68 frozen tumor samples with qRT-PCR data. This new classification system remained strongly predictive of prognoses across clinical subgroups and mutation status. Further analysis revealed that samples from high-risk cases were characterized by active interferon signal transduction, distinctive immune cell proportions and immune checkpoint profiles. Moreover, the signature was identified as an independent prognostic factor. In conclusion, the signature is highly predictive of recurrence in patients with early-stage LUAD, which may serve as a powerful prognostic tool to further optimize immunotherapies for cancer.

Tumor microenvironment characterization identifies two lung adenocarcinoma subtypes with specific immune and metabolic state.

The tumor microenvironment (TME) is a vital component of tumor tissue. Increasing evidence suggests their significance in predicting outcomes and guiding therapies. However, no studies have reported a systematic analysis of the clinicopathologic significance of TME in lung adenocarcinoma (LUAD). Here, we inferred tumor stromal cells in 1184 LUAD patients using computational algorithms based on bulk tumor expression data, and evaluated the clinicopathologic significance of stromal cells. We found LUAD patients showed heterogeneous abundance in stromal cells. Infiltration of stromal cells was influenced by clinicopathologic features, such as age, gender, smoking, and TNM stage. By clustering stromal cells, we identified 2 clinically and molecularly distinct LUAD subtypes with immune active and immune repressed features. The immune active subtype is characterized by repressed metabolism and repressed proliferation of tumor cells, while the immune repressed subtype is characterized by active metabolism and active proliferation of tumor cells. Differentially expressed gene analysis of the two LUAD subtypes identified an immune activation signature. To diagnose TME subtypes practically, we constructed a TME score using principal component analysis based on the immune activation signature. The TME score predicted TME subtypes effectively in 3 independent datasets with areas under the receiver operating characteristic curves of 0.960, 0.812, and 0.819, respectively. In conclusion, we proposed 2 clinically and molecularly distinct LUAD subtypes based on tumor microenvironment that could be valuable in predicting clinical outcome and guiding immunotherapy.

Utility of isocitrate dehydrogenase 1 as a serum protein biomarker for the early detection of non-small-cell lung cancer: A multicenter in vitro diagnostic clinical trial.

We aimed to verify the expression status and diagnostic significance of isocitrate dehydrogenase 1 (IDH1) in non-small-cell lung cancer (NSCLC), especially during early stages. Serum IDH1 levels were measured by ELISA. A total of 1223 participants (660 patients with NSCLC, 276 healthy controls [HCs], 95 patients with benign pulmonary conditions [BPCs], 135 patients with other cancers [OCs], and 57 samples with interfering factors) were divided into a training cohort and a validation cohort according to 3 testing centers. The IDH1 concentrations in the NSCLC group were obviously higher than those in the control groups (P < .001). Area under the receiver operating characteristic curves (AUCs) for discriminating NSCLC patients from controls (HC, BPC, and OC) were 0.870 and 0.745 (sensitivity, 63.3% and 55.0%; specificity, 86.8% and 86.3%) in the training cohort and validation cohort, respectively. The AUCs for discriminating stage 0-IA lung cancer patients from HCs were 0.907 and 0.788 (sensitivity, 58.6% and 59.1%; specificity, 92.9% and 89.3%) in 2 cohorts, respectively. Isocitrate dehydrogenase 1 showed specificity for NSCLC and had no diagnostic value for other common cancers. Furthermore, IDH1 was significantly reduced in postoperative serum. Isocitrate dehydrogenase 1 shows clinical utility as a serum protein biomarker for the early diagnosis of NSCLC.

Identification of a costimulatory molecule-based signature for predicting prognosis risk and immunotherapy response in patients with lung adenocarcinoma.

Background: Costimulatory molecules play significant roles in mounting anti-tumor immune responses, and antibodies targeting these molecules are recognized as promising adjunctive cancer immunotherapies. Here, we aim to conduct a first full-scale exploration of costimulatory molecules from the B7-CD28 and TNF families in patients with lung adenocarcinoma (LUAD) and generated a costimulatory molecule-based signature (CMS) to predict survival and response to immunotherapy. Methods: We enrolled 1549 LUAD cases across 10 different cohorts and included 502 samples from TCGA for discovery. The validation set included 970 cases from eight different Gene Expression Omnibus (GEO) datasets and 77 frozen tumor tissues with qPCR data. The underlying mechanisms and predictive immunotherapy capabilities of the CMS were also explored. Results: A five gene-based CMS (CD40LG, TNFRSF6B, TNFSF13, TNFRSF13C, and TNFRSF19) was initially constructed using the bioinformatics method from TCGA that classifies cases as high- vs. low-risk groups per OS. Multivariable Cox regression analysis confirmed that the CMS was an independent prognostic factor. As expected, CMS exhibited prognostic significance in the stratified cohorts and different validation cohorts. Additionally, the prognostic meta-analysis revealed that CMS was superior to the previous signature. Samples in high- and low-risk groups exhibited significantly different tumor-infiltrating leukocytes and inflammatory activities. Importantly, we found that the CMS scores were closely related to multiple immunotherapy biomarkers. Conclusion: We conducted the first and most comprehensive costimulatory molecule landscape analysis of patients with LUAD and built a clinically feasible CMS for prognosis and immunotherapy response prediction, which will be helpful for further optimize immunotherapies for cancer.