A novel immune checkpoints-based signature to predict prognosis and response to immunotherapy in lung adenocarcinoma

Exploring the role of TIGIT in patients with Small Cell Lung Cancer as a novel predictor of prognosis and immunotherapy response

BACKGROUND

T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domains (TIGIT) is a novel immune checkpoint playing a crucial role in immunosuppression and immune evasion. This study aims to elucidate the expression patterns, characteristics, and possible mechanisms of TIGIT in small cell lung cancer (SCLC).

METHODS

TIGIT expression was analyzed across various cancers and normal tissues using The Cancer Genome Atlas (TCGA). Transcriptomic data from SCLC patients, sourced from the Gene Expression Omnibus (GEO) and literature, were analyzed to assess TIGIT-related characteristics. Immunohistochemistry (IHC) was used to verify TIGIT expression in post-surgical and advanced SCLC samples, focusing on expression characteristics, prognostic value, and treatment response.

RESULTS

TIGIT was significantly overexpressed in various tumors, including SCLC (p < 0.05). Higher expression was associated with better overall survival (OS) (p < 0.05). Notably, a significant positive correlation was observed between TIGIT expression and immune-related metagenes, such as HCK, interferon, and LCK (p < 0.05). Immune infiltration analysis revealed a strong positive correlation between TIGIT expression and immune score in multiple cohorts. Additionally, TIGIT expression correlated positively with immune cells, including CD8 T cells, cytotoxic lymphocytes, and B cells (p < 0.05), and multiple immune checkpoints like BTLA, ICOS, and LAG3 (p < 0.05), while it had a significant negative correlation with the TIDE score (p < 0.05). In the validation section, patients with high TIGIT expression showed significantly prolonged disease-free survival (DFS) and OS (p < 0.05), and demonstrated a better response to adjuvant chemotherapy (ACT) and immunotherapy.

CONCLUSION

TIGIT serves as a biomarker in SCLC, with its high expression indicating favorable prognosis and treatment response. These effects may be due to TIGIT's unique immune landscape and its association with other immune checkpoints.

CRABP2 (Cellular Retinoic Acid Binding Protein 2D): A novel biomarker for the diagnosis and prognosis involved in immune infiltration of lung adenocarcinoma

Objective: Overexpressed CRABP2 (Cellula Retinoi Aci Bindin Protei 2D) can promote progression of various tumors. However, there are few comprehensive analysis studies on CRABP2 in lung adenocarcinoma (LUAD). Methods: Several large public databases and online analysis tools such as TCGA, GEO, GEPIA2, UALCAN, Kaplan Meier plotter, LinkedOmics, TIMER, CCLE and Metascape were used for big data mining analysis. RNA interference technology, CCK8 assay, flow cytometry and apoptosis detection, and western blot were used for in vitro experiments. Results: The study revealed that the expression level of CRABP2 in plasma were higher (mean level 31.6587 ±13.8541 ng/mL vs. 13.9328 ± 5.5805 ng/mL, p<0.0001) in patients with early stage (stage IA) LUAD compared to the control group based on analysis of 640 LUAD patients and 640 matched healthy control plasma samples from Lishui Central Hospital. Receiver Operating Characteristic curve showed that CRABP2 had certain accuracy in predicting early LUAD, with a sensitivity of 70.98%, a specificity of 94.53%, a cut-off value of 0.6551 ng/mL, and an Area Under the Curve of 0.839 (95%CI: 0.817 - 0.859, p<0.0001). Compared with normal lung tissue, CRABP2 was significantly overexpressed in LUAD (p<0.05). High CRABP2 expression in LUAD predicts poor prognosis both in Overall Survival (95%CI: 1.04-1.46, HR:1.23, p=0.018) and FP (First Progression, 95%CI: 1.10-1.65, HR = 1.35, p=0.0032) in LUAD patients. CRABP2 can promote the progression of LUAD by promoting the G2/M phase transition, inhibiting the apoptosis and participating in the regulation of immune microenvironment. The high expression of CRABP2 will inhibit the recruitment of immune effector cells and promote the proportion of immuno-suppressive cells, thus promoting the progression of LUAD. The low expression of CRABP2 may enhance the expression of CD274(PD-L1), HAVCR2 and PDCD1LG2(PD-L2) in LUAD. While, the high expression of CRABP2 may enhance the expression of CTLA4, LAG3, PDCD1(PD-1), TIGIT and IGSF8 in LUAD. Conclusions: CRABP2 may be a valuable biomarker for diagnosis, treatment and prognosis of LUAD. Patients with high expression of CRABP2 in LUAD may have suboptimal efficacy when treated with inhibitors targeting CD274, HAVCR2, and PDCD1LG2, whereas they may experience better efficacy with inhibitors targeting CTLA4, LAG3, PDCD1, TIGIT, and IGSF8. Most of cancer patients with high CRABP2 expression may benefit from immune checkpoint inhibitor therapy. Our study results have laid a positive foundation for LUAD diagnosis and therapy.

A fatty acid metabolism-related genes model for predicting the prognosis and immunotherapy effect of lung adenocarcinoma

ObjectiveLung adenocarcinoma (LUAD) is a common and highly heterogeneous malignancy cancer with increasing morbidity and mortality. Dysregulation of fatty acid metabolism (FAM) has been identified as a key regulator of LUAD progression. Our purpose was to establish a risk model of FAM-related genes to provide a reference for the prognosis prediction of LUAD.MethodsFirstly, we screened FAM-related differentially expressed genes (DEGs) based on the Cancer Genome Atlas (TCGA) database, and identified the prognostic signatures by Cox-regression analysis. The least absolute shrinkage and selection operator algorithm (LASSO) was used to obtain the formula for risk model. And the analysis of Gene Expression Omnibus (GEO) dataset used to verify. Nomogram was produced for individualized prediction in clinical treatment. Immune cell function and drug sensitivity analysis used to screen potential therapeutic drugs.ResultsPatients in low-risk had better overall survival (OS). High-risk patients exhibit higher TMB and lower TIDE scores, and they are more likely to benefit from immunotherapy. The analysis of GEO verified that risk model has a high prediction accuracy.ConclusionThe risk model based on 17 FAM-related DEGs is of great value in predicting the prognosis of LUAD, and these prognostic signatures may be potential therapeutic targets for LUAD.

Development of a novel centrosome-related risk signature to predict prognosis and treatment response in lung adenocarcinoma

BACKGROUND

Abnormalities of centrosomes, the major microtubular organizing centers of animal cells and regulators of cell cycle progression, usually accelerate tumor progression, but their prognostic value in lung adenocarcinoma (LUAD) remains insufficiently explored.

METHODS

We collected centrosome genes from the literature and identified LUAD-specific centrosome-related genes (CRGs) using the single-sample gene set enrichment analysis (ssGSEA) algorithm and weighted gene co-expression network analysis (WGCNA). Univariate Cox was performed to screen prognostic CRGs. Consistent clustering was performed to classify LUAD patients into two subgroups, and centrosome-related risk score signatures were constructed by Lasso and multivariate Cox regression to predict overall survival (OS). We further explored the correlation between CRS and patient prognosis, clinical manifestations, mutation status, tumor microenvironment, and response to different treatments.

RESULTS

We constructed centrosome-associated prognostic features and verified that CRS could effectively predict 1-, 3-, and 5-year survival in LUAD patients. In addition, patients in the high-risk group exhibited elevated tumor mutational loads and reduced levels of immune infiltration, particularly of T and B cells. Patients in the high-risk group were resistant to immunotherapy and sensitive to 5-fluoropyrimidine and gefitinib. The key gene spermine synthase (SRM) is highly expressed at the mRNA and protein levels in LUAD.

DISCUSSION

Our work develops a novel centrosome-related prognostic signature that accurately predicts OS in LUAD and can assist in clinical diagnosis and treatment.

Fatty acid metabolism prognostic signature predicts tumor immune microenvironment and immunotherapy, and identifies tumorigenic role of MOGAT2 in lung adenocarcinoma

Background

Aberrant fatty acid metabolism (FAM) plays a critical role in the tumorigenesis of human malignancies. However, studies on its impact in lung adenocarcinoma (LUAD) are limited.

Methods

We developed a prognostic signature comprising 10 FAM-related genes (GPR115, SOAT2, CDH17, MOGAT2, COL11A1, TCN1, LGR5, SLC34A2, RHOV, and DKK1) using data from LUAD patients in The Cancer Genome Atlas (TCGA). This signature was validated using six independent LUAD datasets from the Gene Expression Omnibus (GEO). Patients were classified into high- and low-risk groups, and overall survival (OS) was compared by Kaplan-Meier analysis. The signature's independence as a prognostic indicator was assessed after adjusting for clinicopathological features. Receiver operating characteristic (ROC) analysis validated the signature. Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology.

Results

Low-risk group patients exhibited decreased OS. The signature was an independent prognostic indicator and demonstrated strong risk-stratification utility for disease relapse/progression. ROC analysis confirmed the signature's validity across validation sets. TIME analysis revealed higher infiltration of CD8+ T cells, natural killers, and B cells, and lower tumor purity, stemness index, and tumor mutation burden (TMB) in low-risk patients. These patients also showed elevated T cell receptor richness and diversity, along with reduced immune cell senescence. High-risk patients exhibited enrichment in pathways related to resistance to immune checkpoint blockades, such as DNA repair, hypoxia, epithelial-mesenchymal transition, and the G2M checkpoint. LUAD patients receiving anti-PD-1 treatment had lower risk scores among responders compared to non-responders. MOGAT2 was expressed at higher levels in low-risk LUAD patients. Functional assays revealed that MOGAT2 knockdown in H1299 cells promoted proliferation and migration, induced G2 cell cycle arrest, and decreased apoptosis.

Conclusions

This FAM-related gene signature provides a valuable tool for prognostic stratification and monitoring of TIME and immunotherapy responses in LUAD. MOGAT2 is identified as a potential anti-tumor regulator, offering new insights into its role in LUAD pathogenesis.

Integrating multi-omics and machine learning survival frameworks to build a prognostic model based on immune function and cell death patterns in a lung adenocarcinoma cohort

Introduction

The programmed cell death (PCD) plays a key role in the development and progression of lung adenocarcinoma. In addition, immune-related genes also play a crucial role in cancer progression and patient prognosis. However, further studies are needed to investigate the prognostic significance of the interaction between immune-related genes and cell death in LUAD.

Methods

In this study, 10 clustering algorithms were applied to perform molecular typing based on cell death-related genes, immune-related genes, methylation data and somatic mutation data. And a powerful computational framework was used to investigate the relationship between immune genes and cell death patterns in LUAD patients. A total of 10 commonly used machine learning algorithms were collected and subsequently combined into 101 unique combinations, and we constructed an immune-associated programmed cell death model (PIGRS) using the machine learning model that exhibited the best performance. Finally, based on a series of in vitro experiments used to explore the role of PSME3 in LUAD.

Results

We used 10 clustering algorithms and multi-omics data to categorize TCGA-LUAD patients into three subtypes. patients with the CS3 subtype had the best prognosis, whereas patients with the CS1 and CS2 subtypes had a poorer prognosis. PIGRS, a combination of 15 high-impact genes, showed strong prognostic performance for LUAD patients. PIGRS has a very strong prognostic efficacy compared to our collection. In conclusion, we found that PSME3 has been little studied in lung adenocarcinoma and may be a novel prognostic factor in lung adenocarcinoma.

Discussion

Three LUAD subtypes with different molecular features and clinical significance were successfully identified by bioinformatic analysis, and PIGRS was constructed using a powerful machine learning framework. and investigated PSME3, which may affect apoptosis in lung adenocarcinoma cells through the PI3K/AKT/Bcl-2 signaling pathway.

Shaping the immune-suppressive microenvironment on tumor-associated myeloid cells through tumor-derived exosomes

Tumor-associated myeloid cells (TAMCs) play a crucial role in orchestrating the dynamics of the tumor immune microenvironment. This heterogeneous population encompasses myeloid-derived suppressor cells, tumor-associated macrophages and dendritic cells, all of which contribute to the establishment of an immunosuppressive milieu that fosters tumor progression. Tumor-derived exosomes (TEXs), small extracellular vesicles secreted by tumor cells, have emerged as central mediators in intercellular communication within the tumor microenvironment. In this comprehensive review, we explore the intricate mechanisms through which TEXs modulate immune-suppressive effects on TAMCs and their profound implications in cancer progression. We delve into the multifaceted ways in which TEXs influence TAMC functions, subsequently affecting tumor immune evasion. Furthermore, we elucidate various therapeutic strategies aimed at targeting TEX-mediated immune suppression, with the ultimate goal of bolstering antitumor immunity.

Identification of CD160-TM as a tumor target on triple negative breast cancers: possible therapeutic applications

BACKGROUND

Despite major therapeutic advances, triple-negative breast cancer (TNBC) still presents a worth prognosis than hormone receptors-positive breast cancers. One major issue relies in the molecular and mutational heterogeneity of TNBC subtypes that is reinforced by the absence of reliable tumor-antigen that could serve as a specific target to further promote efficient tumor cell recognition and depletion. CD160 is a receptor mainly expressed by NK lymphocytes and presenting two isoforms, namely the GPI-anchored form (CD160-GPI) and the transmembrane isoform (CD160-TM). While CD160-GPI is constitutively expressed on resting cells and involved in the generation of NK cells' cytotoxic activity, CD160-TM is neo-synthesized upon activation and promotes the amplification of NK cells' killing ability.

METHODS

CD160 expression was assessed by immunohistochemistry (IHC) and flow cytometry on TNBC patient biopsies or cell lines, respectively. Antibody (Ab)-mediated tumor depletion was tested in vitro by performing antibody-dependent cell cytotoxicity (ADCC) and phagocytosis (ADCP) assays, and in vivo on a TNBC mouse model.

RESULTS

Preliminary data obtained by IHC on TNBC patients' tumor biopsies revealed an unconventional expression of CD160 by TNBC tumor cells. By using a specific but conformation-dependent anti-CD160-TM Ab, we established that CD160-TM, but not CD160-GPI, was expressed by TNBC tumor cells. A conformation-independent anti-CD160-TM mAb (22B12; muIgG2a isotype) was generated and selected according to pre-defined specificity and functional criterions. In vitro functional assays demonstrated that ADCC and ADCP could be induced in the presence of 22B12, resulting in TNBC cell line apoptosis. The ability of 22B12 to exert an in vivo anti-tumor activity was also demonstrated on a TNBC murine model.

CONCLUSIONS

Our data identify CD160-TM as a tumor marker for TNBC and provide a rational for the use of anti-CD160-TM antibodies as therapeutic tools in this tumor context.

Identification and validation of a 4-extracellular matrix gene signature associated with prognosis and immune infiltration in lung adenocarcinoma

Background

The extracellular matrix (ECM) plays a crucial role in the development and tumor microenvironment of lung adenocarcinoma (LUAD). This study aimed to establish a risk score of ECM-related genes in LUAD and explore the association between the risk score and patient survival as well as immune cell infiltration, somatic mutations, and therapy response.

Methods

Gene expression data from The Cancer Genome Atlas (TGCA) and eight Gene Expression Omnibus (GEO) databases were used to analyze and identify differentially expressed genes (DEGs). Prognostic ECM-related genes were identified and utilized to formulate a prognostic signature. A nomogram was constructed using TCGA dataset and validated in two GEO datasets. Differences between high- and low-risk patients were analyzed for function enrichment, immune cell infiltration, somatic mutations, and therapy response. Finally, Quantitative real-time PCR (qRT-PCR) was used to detect the mRNA expression of DEGs in LUAD.

Results

A risk score based on four ECM-related genes, ANOS1, CD36, COL11A1, and HMMR, was identified as an independent prognostic factor for overall survival (OS) compared to other clinical variables. Subsequently, a nomogram incorporating the risk score and TNM staging was developed using the TCGA dataset. Internal and external validation of the nomogram, conducted through calibration plots, C-index, time-dependent receiver operating characteristics (ROC), integrated discrimination improvement (IDI), and decision curve analyses (DCA), demonstrated the excellent discriminatory ability and clinical practicability of this nomogram. The risk score correlated with the distribution of function enrichment, immune cell infiltration, and immune checkpoint expression. More somatic mutations occurred in the high-risk group. The risk score also demonstrated a favorable ability to predict immunotherapy response and drug sensitivity.

Conclusion

A novel signature based on four ECM-related genes is developed to help predict LUAD prognosis. This signature correlates with tumor immune microenvironment and can predict the response to different therapies in LUAD patients.

The prognostic and biological importance of chromatin regulation-related genes for lung cancer is examined using bioinformatics and experimentally confirmed

BACKGROUND

The pathogenesis and clinical diagnosis of lung adenocarcinoma (LUAD), a malignant illness with substantial morbidity and mortality, are still being investigated. Genes involved in chromatin regulation are crucial in the biological function of LUAD.

METHODS

The prognostic prediction model for LUAD was developed using multivariables and least absolute shrinkage and selection operator (LASSO) regression. It consisted of 10 chromatin regulators. The LUAD has been divided into two groups, high- and low-risk, using a predictive model. The model was shown to be accurate in predicting survival by the nomogram, receiver operating characteristic (ROC) curves, and principal component analysis (PCA). An analysis of differences in immune-cell infiltration, immunologicalfunction, and clinical traits between low- and high-risk populations was conducted. Protein-protein interaction (PPI) networks and Gene Ontology (GO) pathways of differentially expressed genes (DEGs) in the high versus low risk group were also examined to investigate the association between genes and biological pathways. The biological roles of chromatin regulators (CRs) in LUAD were finally estimated using colony formation and cell movement. The important genes' mRNA expression has been measured using real-time polymerase chain reaction (RT-PCR).

RESULTS AND CONCLUSION

Risk score and stage based on the model could be seen as separate prognostic indicators for patients with LUAD. The main signaling pathway difference across various risk groups was in cell cycle. The immunoinfiltration profile of the tumor microenvironment (TME) and individuals with different risk levels were correlated, suggesting that the interaction of immune cells with the tumor led to the creation of a favorable immunosuppressive microenvironment. These discoveries aid in the creation of individualized therapies for LUAD patients.

The clinical significance and mechanism of microRNA-22-3p targeting TP53 in lung adenocarcinoma

BACKGROUND

At present, studies on MircoRNA-22-3p (miR-22-3p) in lung adenocarcinoma use a single method, lack multi-center validation and multi-method validation, and there is no big data concept to predict and validate target genes.

OBJECTIVE

To investigate the expression, potential targets and clinicopathological significance of miR-22-3p in lung adenocarcinoma (LUAD) tissues.

METHODS

LUAD formalin-fixed paraffin-embedded (FFPE) tumors and adjacent normal lung tissues were collected for real-time quantitative polymerase chain reaction (RT-qPCR). Collect miR-22-3p in LUAD and non-cancer lung tissue from high-throughput datasets, standardized mean difference (SMD) and area under the curve (AUC) of the comprehensive receiver operating curve (summary receiver operating characteristic cure, sROC curve) were calculated. Cell function experiments on A549 cells transfected with LV-hsa-miR-22-3p. Target genes were predicted by the miRwalk2.0 website and the resulting target genes were subjected to Gene Ontology (GO) pathway enrichment analysis and constructed to protein-protein interaction network. Finally, the protein expression level of the key gene TP53 was validated by searching The Human Protein Atlas (THPA) database to incorporate TP53 immunohistochemical results in LUAD.

RESULTS

RT-qPCR result from 41 pairs of LUAD and adjacent lung tissues showed that miR-22-3p was downregulated in LUAD (AUC = 0.6597, p= 0.0128). Globally, a total of 838 LUADs and 494 non-cancerous lung tissues were included, and were finally combined into 14 platforms. Compared with noncancerous tissue, miR-22-3p expression level was significantly reduced in LUAD tissue (SMD =-0.32, AUC = 0.72l); cell function experiments showed that miR-22-3p has inhibitory effects on cell proliferation, migration and invasion, and has promotion effect on apoptosis. Moreover, target genes prediction, GO pathway enrichment analysis and PPI network exhibited TP53 as a key gene of target gene of miR-22-3p; at last, a total of 114 high-throughput datasets were included, including 3897 LUADs and 2993 non-cancerous lung tissues, and were finally combined into 37 platforms. Compared with noncancerous tissue, TP53 expression level was significantly increased in LUAD (SMD = 0.39, p< 0.01) and it was verified by the protein expression data from THPA.

CONCLUSION

Overexpression of miR-22-3p may inhibit LUAD cell proliferation, migration and invasion through TP53, and promote cell apoptosis.