Immune landscape and a promising immune prognostic model associated with TP53 in early-stage lung adenocarcinoma

Multiple Omics Analysis of the Role of RBM10 Gene Instability in Immune Regulation and Drug Sensitivity in Patients with Lung Adenocarcinoma (LUAD)

OBJECTIVE

The RNA-binding protein RBM10 can regulate apoptosis during the proliferation and migration of pancreatic cancer, endometrial cancer, and osteosarcoma cells; however, the molecular mechanism underlying lung adenocarcinoma is rarely reported. Recent studies have detected multiple truncated and missense mutations in RBM10 in lung adenocarcinoma, but the role of RBM10 in lung adenocarcinoma is unclear. This study mainly explored the immune regulation mechanism of RBM10 in the development of lung adenocarcinoma and its influence on sensitivity to targeted therapy drugs.

METHODS

The transcriptome data of CGAP were used to analyze the RNA-seq data of lung adenocarcinoma patients from different subgroups by using the CIBERSORT algorithm to infer the relative proportion of various immune infiltrating cells, and Spearman correlation analysis was performed to determine the gene expression and immune cell content. In addition, this study utilized drug trial data from the GDSC database. The IC50 estimates for each specific targeted therapy were obtained by using a regression method, and the regression and prediction accuracy were tested via ten cross-validations with the GDSC training set. An immunohistochemical test was performed on the samples of 20 patients with lung adenocarcinoma in the subcomponent analysis of immune cells, and the protein expression of RBM10 in lung adenocarcinoma tissues was verified by cellular immunofluorescence assays. Nucleic acids were extracted at low temperatures, and qRT-PCR was used to verify the expression levels of the mRNA of RBM10 in lung adenocarcinoma tissues and normal tissues (p < 0.05).

RESULTS

After screening and inclusion using a machine language, the results showed that RBM10 was significantly highly expressed in the lung adenocarcinoma tissues. The related signaling pathways were mainly concentrated in ncRNA processing, rRNA metabolic processes, ribosome biogenesis, and the regulation of translation. The qRT-PCR for 20 lung adenocarcinoma tissues showed that the expression of RBM10 in these tissues was significantly different from that in normal tissues (p = 0.0255). Immunohistochemistry analysis and cell immunofluorescence staining also confirmed that RBM10 was involved in the immune regulation of lung adenocarcinoma tissues, and the number of immune cell aggregations was significantly higher than that of the control group. RBM10 regulates B cell memory-CIBERSORT (p = 0.042) and B cell memory-CIBERSOTRT-abs (p = 0.027), cancer-associated fibroblast-EPIC (p = 0.001), cancer-associated fibroblast- MCPCounter (p = 0.0037), etc. The risk score was significantly associated with the sensitivity of patients to lapatinib (p = 0.049), nilotinib (p = 0.015), pazopanib (p = 0.001), and sorafenib (p = 0.048).

CONCLUSIONS

RBM10 can inhibit the proliferation and invasion of lung adenocarcinoma cells through negative regulation and promote the apoptosis of lung adenocarcinoma cells through immunomodulatory mechanisms. The expression level of RBM10 affects the efficacy of targeted drug therapy and the survival prognosis of lung adenocarcinoma patients, which has a certain guiding significance for the clinical treatment of these patients.

Mapping Immune-Tumor Bidirectional Dialogue Using Ultrasensitive Nanosensors for Accurate Diagnosis of Lung Cancer

Lung cancer is one of the most common cancers with high mortality worldwide despite the development of molecularly targeted therapies and immunotherapies. A significant challenge in managing lung cancer is the accurate diagnosis of cancerous lesions owing to the lack of sensitive and specific biomarkers. The current procedure necessitates an invasive tissue biopsy for diagnosis and molecular subtyping, which presents patients with risk, morbidity, anxiety, and high false-positive rates. The high-risk diagnostic approach has highlighted the need to search for a reliable, low-risk noninvasive diagnostic approach to capture lung cancer heterogeneity precisely. The immune interaction profile of lung cancer is driven by immune cells' distinctive, precise interactions with the tumor microenvironment. Here, we hypothesize that immune cells, particularly T cells, can be used for accurate lung cancer diagnosis by exploiting the distinctive immune-tumor interaction by detecting the immune-diagnostic signature. We have developed an ultrasensitive T-sense nanosensor to probe these specific diagnostic signatures using the physical synthesis process of multiphoton ionization. Our research employed predictive in vitro models of lung cancers, cancer-associated T cells (PCAT, MCAT) and CSC-associated T cells (PCSCAT, MCSCAT), from primary and metastatic lung cancer patients to reveal the immune-diagnostic signature and uncover the molecular, functional, and phenotypic separation between patient-derived T cells (PDT) and healthy samples. We demonstrated this by adopting a machine learning model trained with SERS data obtained using cocultured T cells with preclinical models (CAT, CSCAT) of primary (H69AR) and metastatic lung cancer (H1915). Interrogating these distinct signatures with PDT captured the complexity and diversity of the tumor-associated T cell signature across the patient population, exposing the clinical feasibility of immune diagnosis in an independent cohort of patient samples. Thus, our predictive approach using T cells from the patient peripheral blood showed a highly accurate diagnosis with a specificity and sensitivity of 94.1% and 100%, respectively, for primary lung cancer and 97.9% and 94.4% for metastatic lung cancer. Our results prove that the immune-diagnostic signature developed in this study could be used as a clinical technology for cancer diagnosis and determine the course of clinical management with T cells.

Integrative analysis of TP53 mutations in lung adenocarcinoma for immunotherapies and prognosis

BACKGROUND

The TP53 tumor suppressor gene is one of the most mutated genes in lung adenocarcinoma (LUAD) and plays a vital role in regulating the occurrence and progression of cancer. We aimed to elucidate the association between TP53 mutations, response to immunotherapies and the prognosis of LUAD.

METHODS

Genomic, transcriptomic, and clinical data of LUAD were downloaded from The Cancer Genome Atlas (TCGA) dataset. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, gene set enrichment analysis (GSEA). Gene set variation analysis (GSVA) were performed to determine the differences in biological pathways. A merged protein-protein interaction (PPI) network was constructed and analyzed. MSIpred was used to analyze the correlation between the expression of the TP53 gene, tumor mutation burden (TMB) and tumor microsatellite instability (MSI). CIBERSORT was used to calculate the abundance of immune cells. Univariate and multivariate Cox regression analyses were used to determine the prognostic value of TP53 mutations in LUAD.

RESULTS

TP53 was the most frequently mutated in LUAD, with a mutational frequency of 48%. GO and KEGG enrichment analysis, GSEA, and GSVA results showed a significant upregulation of several signaling pathways, including PI3K-AKT mTOR (P < 0.05), Notch (P < 0.05), E2F target (NES = 1.8, P < 0.05), and G2M checkpoint (NES = 1.7, P < 0.05). Moreover, we found a significant correlation between T cells, plasma cells, and TP53 mutations (R² < 0.01, P = 0.040). Univariate and multivariate Cox regression analyses revealed that the survival prognosis of LUAD patients was related to TP53 mutations (Hazard Ratio (HR) = 0.72 [95% CI, 0.53 to 0.98], P < 0.05), cancer status (P < 0.05), and treatment outcomes (P < 0.05). Lastly, the Cox regression models showed that TP53 exhibited good power in predicting three- and five-year survival rates.

CONCLUSIONS

TP53 may be an independent predictor of response to immunotherapy in LUAD, and patients with TP53 mutations have higher immunogenicity and immune cell infiltration.

Molecular fingerprints of nuclear genome and mitochondrial genome for early diagnosis of lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer with high morbidity and mortality rates. Due to the heterogeneity of LUAD, its characteristics remain poorly understood. Exploring the clinical and molecular characteristics of LUAD is challenging but vital for early diagnosis.

METHODS

This observational and validation study enrolled 80 patients and 13 healthy controls. Nuclear and mtDNA-captured sequencings were performed.

RESULTS

This study identified a spectrum of nuclear and mitochondrial genome mutations in early-stage lung adenocarcinoma and explored their association with diagnosis. The correlation coefficient for somatic mutations in cfDNA and patient-matched tumor tissues was high in nuclear and mitochondrial genomes. The mutation number of highly mutated genes was evaluated, and the Least Absolute Shrinkage and Selection Operator (LASSO) established a diagnostic model. Receiver operating characteristic (ROC) curve analysis explored the diagnostic ability of the two panels. All models were verified in the testing cohort, and the mtDNA panel demonstrated excellent performance. This study identified somatic mutations in the nuclear and mitochondrial genomes, and detecting mutations in cfDNA displayed good diagnostic performance for early-stage LUAD. Moreover, detecting somatic mutations in the mitochondria may be a better tool for diagnosing early-stage LUAD.

CONCLUSIONS

This study identified specific and sensitive diagnostic biomarkers for early-stage LUAD by focusing on nuclear and mitochondrial genome mutations. This also further developed an early-stage LUAD-specific mutation gene panel for clinical utility. This study established a foundation for further investigation of LUAD molecular pathogenesis.

A new immune signature for survival prediction and immune checkpoint molecules in non-small cell lung cancer

Background

Immune checkpoint blockade (ICB) therapy has brought remarkable clinical benefits to patients with advanced non-small cell lung carcinoma (NSCLC). However, the prognosis remains largely variable.

Methods

The profiles of immune-related genes for patients with NSCLC were extracted from TCGA database, ImmPort dataset, and IMGT/GENE-DB database. Coexpression modules were constructed using WGCNA and 4 modules were identified. The hub genes of the module with the highest correlations with tumor samples were identified. Then integrative bioinformatics analyses were performed to unveil the hub genes participating in tumor progression and cancer-associated immunology of NSCLC. Cox regression and Lasso regression analyses were conducted to screen prognostic signature and to develop a risk model.

Results

Functional analysis showed that immune-related hub genes were involved in the migration, activation, response, and cytokine-cytokine receptor interaction of immune cells. Most of the hub genes had a high frequency of gene amplifications. MASP1 and SEMA5A presented the highest mutation rate. The ratio of M2 macrophages and naïve B cells revealed a strong negative association while the ratio of CD8 T cells and activated CD4 memory T cells showed a strong positive association. Resting mast cells predicted superior overall survival. Interactions including protein-protein, lncRNA and transcription factor interactions were analyzed and 9 genes were selected by LASSO regression analysis to construct and verify a prognostic signature. Unsupervised hub genes clustering resulted in 2 distinct NSCLC subgroups. The TIDE score and the drug sensitivity of gemcitabine, cisplatin, docetaxel, erlotinib and paclitaxel were significantly different between the 2 immune-related hub gene subgroups.

Conclusions

These findings suggested that our immune-related genes can provide clinical guidance for the diagnosis and prognosis of different immunophenotypes and facilitate the management of immunotherapy in NSCLC.

A novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncRNAs: A Review

Lung adenocarcinoma (LUAD) is a highly heterogeneous disease with complex pathogenesis, high mortality, and poor prognosis. Cuproptosis is a new type of programmed cell death triggered by copper accumulation that may play an important role in cancer. LncRNAs are becoming valuable prognostic factors in cancer patients. The effect of cuproptosis-related lncRNAs (CRlncRNAs) on LUAD has not been clarified. Based on the Cancer Genome Atlas database, CRlncRNAs were screened by co-expression analysis of cuproptosis- related genes and lncRNAs. Using CRlncRNAs, Cox and LASSO regression analyses constructed a risk prognostic model. The predictive efficacy of the model was assessed and validated using survival analysis, receiver operating characteristic curve, univariate and multifactor Cox regression analysis, and principal component analysis. A nomogram was constructed and calibration curves were applied to enhance the predictive efficacy of the model. Tumor Mutational Burden analysis and chemotherapeutic drug sensitivity prediction were performed to assess the clinical feasibility of the risk model. The novel prognostic signature consisted of 5 potentially high-risk CRlncRNAs, MAP3K20-AS1, CRIM1-DT, AC006213.3, AC008035.1, and NR2F2-AS1, and 5 potentially protective CRlncRNAs, AC090948.1, AL356481.1, AC011477.2, AL031600.2, and AC026355.2, which had accurate and robust predictive power for LUAD patients. Collectively, the novel prognostic signature constructed based on CRlncRNAs can effectively assess and predict the prognosis of patients and provide a new perspective for the diagnosis and treatment of LUAD.

Aberrant Expression and Prognostic Potential of IL-37 in Human Lung Adenocarcinoma

Interleukin-37 (IL-37) is a relatively new IL-1 family cytokine that, due to its immunoregulatory properties, has lately gained increasing attention in basic and translational biomedical research. Emerging evidence supports the implication of this protein in any human disorder in which immune homeostasis is compromised, including cancer. The aim of this study was to explore the prognostic and/or diagnostic potential of IL-37 and its receptor SIGIRR (single immunoglobulin IL-1-related receptor) in human tumors. We utilized a series of bioinformatics tools and -omics datasets to unravel possible associations of IL-37 and SIGIRR expression levels and genetic aberrations with tumor development, histopathological parameters, distribution of tumor-infiltrating immune cells, and survival rates of patients. Our data revealed that amongst the 17 human malignancies investigated, IL-37 exhibits higher expression levels in tumors of lung adenocarcinoma (LUAD). Moreover, the expression profiles of IL-37 and SIGIRR are associated with LUAD development and tumor stage, whereas their high mRNA levels are favorable prognostic factors for the overall survival of patients. What is more, IL-37 correlates positively with a LUAD-associated transcriptomic signature, and its nucleotide changes and expression levels are linked with distinct infiltration patterns of certain cell subsets known to control LUAD anti-tumor immune responses. Our data indicate the potential value of IL-37 and its receptor SIGIRR to serve as biomarkers and/or immune-checkpoint therapeutic targets for LUAD patients. Further, the data highlight the urgent need for further exploration of this cytokine and the underlying pathogenetic mechanisms to fully elucidate its implication in LUAD development and progression.

Polygenic Risk Scores Associated with Tumor Immune Infiltration in Common Cancers

It is largely unknown whether genetic susceptibility contributes to tumor immune infiltration in common cancers. We systematically investigated the association between polygenic risk scores (PRSs) and tumor immune infiltration in common cancers. First, we constructed a PRS for common cancers using the risk variants identified in previous genome-wide association studies. Then, we analyzed 139 immune traits predicted by previous studies by examining gene expression data in tumor tissues from The Cancer Genome Atlas (TCGA). We applied regression analyses to evaluate the associations between PRS and immune traits for each cancer overall and stratified by stage, including 2160 pathologically confirmed cases of breast, colorectal, lung, ovarian, pancreatic, and prostate cancers in the White population. At a nominal (p < 0.05) significance level, we identified 31 significant associations between PRS and immune traits. In the analyses stratified by stage for breast, colorectal, lung adenocarcinoma, and lung squamous cell carcinoma, we identified 65 significant associations, including 56 associations that were undetected by the overall analysis. This study provides evidence for genetic risk factors affecting immune infiltration and provides novel insights into the role of genetic susceptibility in immune responses, underlying cancer development, prognosis, and the potential role of an early diagnostic or therapeutic targeting strategy.

Molecular subtypes based on cuproptosis-related genes and immune profiles in lung adenocarcinoma

Background: Recent studies have identified several molecular subtypes of lung adenocarcinoma (LUAD) that have different prognoses to help predict the efficacy of immunotherapy. However, the prognostic prediction is less than satisfactory. Alterations in intracellular copper levels may affect the tumor immune microenvironment and are linked to cancer progression. Previous studies have identified some genes related to cuproptosis. The characteristics of the cuproptosis molecular subtypes have not been thoroughly studied in LUAD.

Methods: The transcriptomic data and clinical information of 632 LUAD patients were used to investigate the LUAD molecular subtypes that are associated with the cuproptosis-related genes (CRGs), the tumor immune microenvironment, and stemness. The cuproptosis score was constructed using univariate Cox regression and the minor absolute shrinkage and selection operator (LASSO) to quantify the prognostic characteristics.

Results: Three different molecular subtypes related to cuproptosis, with different prognoses, were identified in LUAD. Cluster A had the highest cuproptosis score and the worst prognosis. Patients in the high cuproptosis score group had a higher somatic mutation frequency and stemness scores. Patients in the low cuproptosis score group had more immune infiltration and better prognosis.

Conclusion: Molecular subtypes of LUAD based on CRGs reflect the differences in LUAD patients. The cuproptosis score can be used as a promising biomarker, which is of great significance to distinguish the relationship between cuproptosis and the immune microenvironment. The cuproptosis signature based on the cuproptosis score and clinical characteristics of individual patients will be useful for guiding immunotherapy in LUAD.

Cellular and Molecular Profiling of Tumor Microenvironment and Early-Stage Lung Cancer

Lung cancers are broadly divided into two categories: non-small-cell lung carcinoma (NSCLC), which accounts for 80–85% of all cancer cases, and small-cell lung carcinoma (SCLC), which covers the remaining 10–15%. Recent advances in cancer biology and genomics research have allowed an in-depth characterization of lung cancers that have revealed new therapy targets (EGFR, ALK, ROS, and KRAS mutations) and have the potential of revealing even more biomarkers for diagnostic, prognostic, and targeted therapies. A new source of biomarkers is represented by non-coding RNAs, especially microRNAs (miRNAs). MiRNAs are short non-coding RNA sequences that have essential regulatory roles in multiple cancers. Therefore, we aim to investigate the tumor microenvironment (TME) and miRNA tumor profile in a subset of 51 early-stage lung cancer samples (T1 and T2) to better understand early tumor and TME organization and molecular dysregulation. We analyzed the immunohistochemistry expression of CD4 and CD8 as markers of the main TME immune populations, E-cadherin to evaluate early-stage epithelial-to-mesenchymal transition (EMT), and p53, the main altered tumor suppressor gene in lung cancer. Starting from these 4 markers, we identified and validated 4 miRNAs that target TP53 and regulate EMT that can be further investigated as potential early-stage lung cancer biomarkers.

BTG2 Serves as a Potential Prognostic Marker and Correlates with Immune Infiltration in Lung Adenocarcinoma

Background

B-cell translocation gene 2 (BTG2) has been revealed to be involved in the occurrence and development of multiple cancers. However, the role of BTG2 in lung adenocarcinoma (LUAD) is still ambiguous. Thus, this study aims to investigate the prognostic value of BTG2 and its correlation with immune infiltration in LUAD.

Methods

The expression of BTG2 in LUAD was analyzed using the TIMER and UALCAN databases. The correlations between BTG2 expression and clinicopathological factors were investigated using the UALCAN databases. The Kaplan–Meier plotter, GEPIA, and TCGA databases were employed to assess the prognostic value of BTG2. The STRING database and Cytoscape software were used to construct an interaction network and mine co-expression genes. The TISIDB database was examined for a correlation between BTG2 and driver genes in LUAD. Enrichment analysis of co-expressed genes and BTG2 was performed using the LinkedOmics database. Finally, the correlations between BTG2 and immune infiltrates were investigated using the TIMER, GEO, and TISIDB database.

Results

BTG2 was significantly downregulated in LUAD. The decreased expression of BTG2 in LUAD was significantly correlated with higher cancer stages and shorter duration of overall survival. The expressions of BTG2-related co-expression genes were associated with the prognosis in LUAD. The expression of BTG2 was closely associated with the mutations of TP53 and ROS1. Enrichment analysis revealed that BTG2 was significantly correlated with immune‐associated signaling pathways and function. In addition, the expression of BTG2 was found to be closely related to immune infiltration, multiple gene markers of immune cells, chemokines, and chemokine receptors.

Conclusion

Our findings have effectively demonstrated that BTG2 expression was downregulated in LUAD, indicating poor prognosis. Closely relating to immune cell infiltration, BTG2 may be a promising immune-related biomarker and molecular target for patients with LUAD.

Differences in genetics and microenvironment of lung adenocarcinoma patients with or without TP53 mutation

Background

Differences in genetics and microenvironment of LUAD patients with or without TP53 mutation were analyzed to illustrate the role of TP53 mutation within the carcinogenesis of LUAD, which will provide new concepts for the treatment of LUAD.

Methods

In this study, we used genetics and clinical info from the TCGA database, including somatic mutations data, RNA-seq, miRNA-seq, and clinical data. More than one bioinformatics tools were used to analyze the unique genomic pattern of TP53-related LUAD.

Results

According to TP53 gene mutation status, we divided the LUAD patients into two groups, including 265 in the mutant group (MU) and 295 in the wild-type group (WT). 787 significant somatic mutations were detected between the groups, including mutations in titin (TTN), type 2 ryanodine receptor (RYR2) and CUB and Sushi multiple domains 3(CSMD3), which were up-regulated in the MU. However, no significant survival difference was observed. At the RNA level, we obtained 923 significantly differentially expressed genes; in the MU, α-defensin 5(DEFA5), pregnancy-specific glycoprotein 5(PSG5) and neuropeptide Y(NPY) were the most up-regulated genes, glucose-6-phosphatase (G6PC), alpha-fetoprotein (AFP) and carry gametocidal (GC) were the most down-regulated genes. GSVA analysis revealed 30 significant pathways. Compared with the WT, the expression of 12 pathways in the mutant group was up-regulated, most of which pointed to cell division. There were significant differences in tumor immune infiltrating cells, such as Macrophages M1, T cells CD4 memory activated, Mast cells resting, and Dendritic cells resting. In terms of immune genes, a total of 35 immune-related genes were screened, of which VGF (VGF nerve growth factor inducible) and PGC (peroxisome proliferator-activated receptor gamma coactivator) were the most significant up-regulated and down-regulated genes, respectively. Research on the expression pattern of immunomodulators found that 9 immune checkpoint molecules and 6 immune costimulatory molecules were considerably wholly different between the two groups.

Conclusions

Taking the mutant group as a reference, LUAD patients in the mutant group had significant differences in somatic mutations, mRNA-seq, miRNA-seq, immune infiltration, and immunomodulators, indicating that TP53 mutation plays a crucial role in the occurrence and development of LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01671-8.

A Personalized Genomics Approach of the Prostate Cancer

Decades of research identified genomic similarities among prostate cancer patients and proposed general solutions for diagnostic and treatments. However, each human is a dynamic unique with never repeatable transcriptomic topology and no gene therapy is good for everybody. Therefore, we propose the Genomic Fabric Paradigm (GFP) as a personalized alternative to the biomarkers approach. Here, GFP is applied to three (one primary—“A”, and two secondary—“B” & “C”) cancer nodules and the surrounding normal tissue (“N”) from a surgically removed prostate tumor. GFP proved for the first time that, in addition to the expression levels, cancer alters also the cellular control of the gene expression fluctuations and remodels their networking. Substantial differences among the profiled regions were found in the pathways of P53-signaling, apoptosis, prostate cancer, block of differentiation, evading apoptosis, immortality, insensitivity to anti-growth signals, proliferation, resistance to chemotherapy, and sustained angiogenesis. ENTPD2, AP5M1 BAIAP2L1, and TOR1A were identified as the master regulators of the “A”, “B”, “C”, and “N” regions, and potential consequences of ENTPD2 manipulation were analyzed. The study shows that GFP can fully characterize the transcriptomic complexity of a heterogeneous prostate tumor and identify the most influential genes in each cancer nodule.

The TP53-Related Signature Predicts Immune Cell Infiltration, Therapeutic Response, and Prognosis in Patients With Esophageal Carcinoma

TP53 mutation (TP53^MUT) is one of the most common gene mutations and frequently occurs in many cancers, especially esophageal carcinoma (ESCA), and it correlates with clinical prognostic outcomes. Nevertheless, the mechanisms by which TP53^MUT regulates the correlation between ESCA and prognosis have not been sufficiently studied. Here, in the current research, we constructed a TP53^MUT-related signature to predict the prognosis of patients with esophageal cancer and successfully verified this model in patients in the TP53 mutant group, esophageal squamous cell carcinoma group, and adenocarcinoma group. The risk scores proved to be better independent prognostic factors than clinical features, and prognostic features were combined with other clinical features to establish a convincing nomogram to predict overall survival from 1 to 3 years. In addition, we further predicted the tumor immune cell infiltration, chemical drugs, and immunotherapy responses between the high-risk group and low risk group. Finally, the gene expression of the seven-gene signature (AP002478.1, BHLHA15, FFAR2, IGFBP1, KCTD8, PHYHD1, and SLC26A9) can provide personalized prognosis prediction and insights into new treatments.