A systematic dissection of the epigenomic heterogeneity of lung adenocarcinoma reveals two different subclasses with distinct prognosis and core regulatory networks

Pulmonary Cytopathology: Current and Future Impact on Patient Care

Small biopsies of lung are routinely obtained by many methods, including several that result in cytologic specimens. Because lung cancer is often diagnosed at a stage for which primary resection is not an option, it is critical that all diagnostic, predictive, and prognostic information be derived from such small biopsy specimens. As the number of available diagnostic and predictive markers expands, cytopathologists must familiarize themselves with current requirements for specimen acquisition, handling, results reporting, and molecular and other ancillary testing, all of which are reviewed here.

Cell of origin alters myeloid-mediated immunosuppression in lung adenocarcinoma

Solid carcinomas are often highly heterogenous cancers, arising from multiple epithelial cells of origin. Yet, how the cell of origin influences the response of the tumor microenvironment is poorly understood. Lung adenocarcinoma (LUAD) arises in the distal alveolar epithelium which is populated primarily by alveolar epithelial type I (AT1) and type II (AT2) cells. It has been previously reported that Gramd2 + AT1 cells can give rise to a histologically-defined LUAD that is distinct in pathology and transcriptomic identity from that arising from Sftpc + AT2 cells1,2. To determine how cells of origin influence the tumor immune microenvironment (TIME) landscape, we comprehensively characterized transcriptomic, molecular, and cellular states within the TIME of Gramd2 + AT1 and Sftpc + AT2-derived LUAD using KRASG12D oncogenic driver mouse models. Myeloid cells within the Gramd2 + AT1-derived LUAD TIME were increased, specifically, immunoreactive monocytes and tumor associated macrophages (TAMs). In contrast, the Sftpc + AT2 LUAD TIME was enriched for Arginase-1+ myeloid derived suppressor cells (MDSC) and TAMs expressing profiles suggestive of immunosuppressive function. Validation of immune infiltration was performed using flow cytometry, and intercellular interaction analysis between the cells of origin and major myeloid cell populations indicated that cell-type specific markers SFTPD in AT2 cells and CAV1 in AT1 cells mediated unique interactions with myeloid cells of the differential immunosuppressive states within each cell of origin mouse model. Taken together, Gramd2 + AT1-derived LUAD presents with an anti-tumor, immunoreactive TIME, while the TIME of Sftpc + AT2-derived LUAD has hallmarks of immunosuppression. This study suggests that LUAD cell of origin influences the composition and suppression status of the TIME landscape and may hold critical implications for patient response to immunotherapy.

An exosomes-related lncRNA prognostic model correlates with the immune microenvironment and therapy response in lung adenocarcinoma

Recent research highlights the significance of exosomes and long noncoding RNAs (lncRNAs) in cancer progression and drug resistance, but their role in lung adenocarcinoma (LUAD) is not fully understood. We analyzed 121 exosome-related (ER) mRNAs from the ExoBCD database, along with mRNA and lncRNA expression profiles of TCGA-LUAD using "DESeq2", "survival," "ConsensusClusterPlus," "GSVA," "estimate," "glmnet," "clusterProfiler," "rms," and "pRRophetic" R packages. This comprehensive approach included univariate cox regression, unsupervised consensus clustering, GSEA, functional enrichment analysis, and prognostic model construction. Our study identified 134 differentially expressed ER-lncRNAs, with 19 linked to LUAD prognosis. These ER-lncRNAs delineated two patient subtypes, one with poorer outcomes. Additionally, 286 differentially expressed genes were related to these ER-lncRNAs, 261 of which also correlated with LUAD prognosis. We constructed an ER-lncRNA-related prognostic model and calculated an ER-lncRNA-related risk score (ERS), revealing that a higher ERS correlates with poor overall survival in both the Meta cohort and two validation cohorts. The ERS potentially serves as an independent prognostic factor, and the prognostic model demonstrates superior predictive power. Notably, significant differences in the immune landscape were observed between the high- and low-ERS groups. Drug sensitivity analysis indicated varying responses to common chemotherapy drugs based on ERS stratification, with the high-ERS group showing greater sensitivity, except to rapamycin and erlotinib. Experimental validation confirmed that thymidine kinase 1 enhances lung cancer invasion, metastasis, and cell cycle progression. Our study pioneers an ER-lncRNA-related prognostic model for LUAD, proposing that ERS-based risk stratification could inform personalized treatment strategies to improve patient outcomes.

Pathogenic role of super-enhancers as potential therapeutic targets in lung cancer

Lung cancer is still one of the deadliest malignancies today, and most patients with advanced lung cancer pass away from disease progression that is uncontrollable by medications. Super-enhancers (SEs) are large clusters of enhancers in the genome's non-coding sequences that actively trigger transcription. Although SEs have just been identified over the past 10 years, their intricate structure and crucial role in determining cell identity and promoting tumorigenesis and progression are increasingly coming to light. Here, we review the structural composition of SEs, the auto-regulatory circuits, the control mechanisms of downstream genes and pathways, and the characterization of subgroups classified according to SEs in lung cancer. Additionally, we discuss the therapeutic targets, several small-molecule inhibitors, and available treatment options for SEs in lung cancer. Combination therapies have demonstrated considerable advantages in preclinical models, and we anticipate that these drugs will soon enter clinical studies and benefit patients.

Non-invasively Discriminating the Pathological Subtypes of Non-small Cell Lung Cancer with Pretreatment 18F-FDG PET/CT Using Deep Learning

RATIONALE AND OBJECTIVES

To develop an end-to-end deep learning (DL) model for non-invasively predicting non-small cell lung cancer (NSCLC) pathological subtypes based on 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) images, and to explore the potential value of DL technology.

MATERIALS AND METHODS

Preoperative 18F-FDG PET/CT images of 189 patients with NSCLC were retrospectively collected. The whole cohort was randomly divided into a training cohort, a validation cohort, and an internal/extended test cohort at the ratio of 6:2:2 after preprocessing the images. In the training and validation cohorts, seven DL models-Shufflenet, VGG16, Googlenet, Inception v3, Resnet50, Densenet201, and Mobilenet v2-were trained and optimized. The generalization ability and clinical utility of the optimal model were evaluated in the internal and extended test cohorts. Moreover, Spearman's correlation analysis was used to evaluate the correlation between DL features and traditional radiological features such as tumor size and maximum standardized uptake values (SUVmax).

RESULTS

Some DL features were significantly correlated with SUVmax and tumor size (P < 0.05). The Mobilenet v2 model achieved the best performance during the model development and validation phases. In the internal test group (area under the receiver operating characteristic curve [AUC]: 0.744, area under the precision-recall curve [AP]: 0.759) and extended test group (AUC: 0.767, AP: 0.768), the Mobilenet v2 model showed good generalization ability and reproducibility. Meanwhile, the decision curve analysis revealed that patients can benefit from the decisions made based on the Mobilenet v2 model.

CONCLUSION

DL models offer great potential for classifying NSCLC pathological subtypes. Specifically, the Mobilenet v2 model performs well at end-to-end non-invasive pathological subtype stratification of NSCLC.

Molecular signature to predict quality of life and survival with glioblastoma using Multiview omics model

Glioblastoma multiforme (GBM) patients show a variety of signs and symptoms that affect their quality of life (QOL) and self-dependence. Since most existing studies have examined prognostic factors based only on clinical factors, there is a need to consider the value of integrating multi-omics data including gene expression and proteomics with clinical data in identifying significant biomarkers for GBM prognosis. Our research aimed to isolate significant features that differentiate between short-term (≤ 6 months) and long-term (≥ 2 years) GBM survival, and between high Karnofsky performance scores (KPS ≥ 80) and low (KPS ≤ 60), using the iterative random forest (iRF) algorithm. Using the Cancer Genomic Atlas (TCGA) database, we identified 35 molecular features composed of 19 genes and 16 proteins. Our findings propose molecular signatures for predicting GBM prognosis and will improve clinical decisions, GBM management, and drug development.

Advances in diagnosis and prediction for aggression of pure solid T1 lung cancer

A growing number of early-stage lung cancers presenting as malignant pulmonary nodules have been diagnosed because of the increased adoption of low-dose spiral computed tomography. But pure solid T1 lung cancer with ≤3 cm in the greatest dimension is not always at an early stage, despite its small size. This type of cancer can be highly aggressive and is associated with pathological involvement, metastasis, postoperative relapse, and even death. However, it is easily misdiagnosed or delay diagnosed in clinics and thus poses a serious threat to human health. The percentage of nodal or extrathoracic metastases has been reported to be >20% in T1 lung cancer. As such, understanding and identifying the aggressive characteristics of pure solid T1 lung cancer is crucial for prevention, diagnosis, and therapeutic strategies, and beneficial to improving the prognosis. With the widespread of lung cancer screening, these highly invasive pure solid T1 lung cancer will become the main advanced lung cancer in future. However, there is limited information regarding precision medicine on how to identify these "early-stage" aggressive lung cancers. To provide clinicians with new insights into early recognition and intervention of the highly invasive pure solid T1 lung cancer, this review summarizes its clinical characteristics, imaging, pathology, gene alterations, immune microenvironment, multi-omics, and current techniques for diagnosis and prediction.

Circ_0001715 accelerated lung adenocarcinoma process by the miR-1322/CANT1 axis

Lung adenocarcinoma (LUAD) is a type of lung cancer, which belongs to non-small cell lung cancer and has seriously endangered the physical and mental health of people. The study of circRNAs (circRNAs) has been increasingly hot in recent years, in which circRNAs also play an important regulatory role in cancer. The aim of this study was to investigate the biological molecular mechanisms of circ_0001715 in the progression of LUAD. The expression of circ_0001715, miR-1322 and calcium-activated nucleotidase 1 (CANT1) in LUAD tissues and cell lines was assessed by quantitative reverse transcription PCR (RT-qPCR) and western bot assay. Clone formation assay, 5-Ethynyl-2'-Deoxyuridine (EDU) assay and wound healing assay were used to verify the proliferation ability of cells. Dual-luciferase reporter assay and RNA pull-down assay were performed to characterize the interactions between the three factors. Finally, a mouse tumor model was constructed to assess the tumorigenicity of circ_0001715. RT-qPCR assay results showed that circ_0001715 expression was significantly increased in LUAD tissues and cell lines. Finally, knockdown of circ_0001715 could inhibit tumor growth in vivo. Circ_0001715 regulated the progression of LUAD through the miR-1322/CANT1 axis. The results of this study provided ideas for understanding the molecular mechanisms of circ_0001715 in LUAD.

INHA acts as a novel and potential biomarker in lung adenocarcinoma and shapes the immune-suppressive tumor microenvironment

BACKGROUND

INHA expression has been correlated with the development, growth, and progression of multiple cancer types. However, the biological role of INHA has not been investigated in patients with lung adenocarcinoma (LUAD). Here, we performed a comprehensive bioinformatics analysis of the LUAD dataset to determine the mechanisms underlying the regulation of tumorigenesis by INHA.

MATERIALS AND METHODS

INHA expression and clinical information of patients with LUAD were obtained from The Cancer Genome Atlas (TCGA) database. Protein levels in LUAD cell lines and human lung epithelial cells were examined by western blotting. Next, the prognostic value of INHA in LUAD was assessed using Cox regression analysis, while the potential biological functions and the impact on the immune microenvironment of INHA were investigated using gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA). Finally, the effect of INHA on LUAD cell proliferation and invasion was determined in vitro and in vivo.

RESULTS

We found significantly high mRNA and protein expression levels of INHA in LUAD tissues and cell lines. Additionally, a higher expression of INHA was linked to a shorter overall survival (OS) and a worse pathological stage, while INHA expression was associated with immune cell infiltration and immune-related markers in the LUAD tumor microenvironment. LUAD with high INHA expression tends to be a cold tumor. Furthermore, GO and KEGG enrichment analysis indicated that INHA-related genes were enriched in the cell adhesion and immune signaling pathways of LUAD. INHA promoted LUAD cell proliferation and invasion, in vitro and in vivo, by inducing the EGFR pathway.

CONCLUSION

Our findings revealed that INHA is overexpressed in LUAD and is linked to a poor prognosis. Our study demonstrates the potential of INHA as an immunotherapeutic and predictive biomarker in LUAD.

Super-enhancer landscape rewiring in cancer: The epigenetic control at distal sites

Super-enhancers evolve as elements at the top of the hierarchical control of gene expression. They are important end-gatherers of signaling pathways that control stemness, differentiation or adaptive responses. Many epigenetic regulations focus on these regions, and not surprisingly, during the process of tumorigenesis, various alterations can account for their dysfunction. Super-enhancers are emerging as key drivers of the aberrant gene expression landscape that sustain the aggressiveness of cancer cells. In this review, we will describe and discuss about the structure of super-enhancers, their epigenetic regulation, and the major changes affecting their functionality in cancer.

A pan-cancer analysis reveals role of clusterin (CLU) in carcinogenesis and prognosis of human tumors

Clusterin (CLU) is a chaperone-like protein that has been demonstrated to have a direct relationship with cancer occurrence, progression, or metastasis. Clusterin was downregulated in tumor tissues using three datasets of tongue squamous carcinoma from the Gene Expression Omnibus. We further retrieved datasets from The Cancer Genome Atlas and Gene Expression Omnibus to thoroughly investigate the carcinogenic consequences of Clusterin. Our findings revealed that decreased Clusterin expression in malignancies was associated with a worse overall survival prognosis in individuals with multiple tumors; Clusterin gene deep deletions were found in almost all malignancies and were connected to most cancer patient's prognosis, Clusterin DNA methylation level was dependent on tumor type, Clusterin expression was also linked to the invasion of cancer-associated CD8+ T-cells and fibroblasts in numerous cancer forms. Moreover, pathway enrichment analysis revealed that Clusterin primarily regulates biological processes such as cholesterol metabolism, phospholipid binding, and protein-lipid complex formation. Overall, our pan-cancer research suggests that Clusterin expression levels are linked to tumor carcinogenesis and prognosis, which contributes to understanding the probable mechanism of Clusterin in tumorigenesis as well as its clinical prognostic significance.

Non-genetic stratification reveals epigenetic heterogeneity and identifies vulnerabilities of glycolysis addiction in lung adenocarcinoma subtype

Lung adenocarcinoma (LUAD) exhibits high heterogeneity and is well known for its high genetic variation. Recently, the understanding of non-genetic variation provides a new perspective to study the heterogeneity of LUAD. Little is known about whether super-enhancers (SEs) may be primarily responsible for the inter-tumor heterogeneity of LUAD. We used super-enhancer RNA (seRNA) levels of a large-scale clinical well-annotated LUAD cohort to stratify patients into three clusters with different prognosis and other malignant characteristics. Mechanistically, estrogen-related receptor alpha (ERRα) in cluster 3-like cell lines acts as a cofactor of BRD4 to assist SE-promoter loops to activate glycolysis-related target gene expression, thereby promoting glycolysis and malignant progression, which confers a therapeutic vulnerability to glycolytic inhibitors. Our study identified three groups of patients according to seRNA levels, among which patients in cluster 3 have the worst prognosis and vulnerability of glycolysis dependency. We also proposed a 3-TF index model to stratify patients with glycolysis-addicted tumors according to tumor SE stratification.

Single-cell RNA sequencing reveals the cellular and molecular changes that contribute to the progression of lung adenocarcinoma

Pure ground glass nodules (GGNs) and solid nodules (SNs) represent early and relatively late stages of lung adenocarcinoma (LUAD) in radiology, respectively. The cellular and molecular characteristics of pure GGNs and SNs have not been comprehensively elucidated. Additionally, the mechanism driving the progression of lung adenocarcinoma from pure GGN to SN in radiology is also elusive. In this study, by analyzing the single-cell transcriptomic profiles of 76,762 cells from four pure GGNs, four SNs, and four normal tissues, we found that anti-tumor immunity mediated by NK and CD8+T cells gradually weakened with the progression of LUAD and humoral immunity mediated by plasma B cells was more active in SNs. Additionally, the proliferation ability of some special epithelial cell increased during the progression process from pure GGN to SN. Furthermore, stromal cells and M2 macrophages could assist the progression of LUAD. Through comprehensive analyses, we revealed dynamic changes in cellular components and intercellular interactions during the progression of LUAD. These findings could facilitate our understanding of LUAD and discovery of novel therapeutic targets.

Characterization of Necroptosis-Related Molecular Subtypes and Therapeutic Response in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most common malignant tumors with high morbidity and mortality and is usually associated with therapeutic resistance and poor prognosis because of individual biological heterogeneity. There is an unmet need to screen for reliable parameters, especially immunotherapy-related biomarkers to predict the patient’s outcomes. Necroptosis is a special caspase-independent form of necrotic cell death associated with the pathogenesis, progression, and prognosis of multiple tumors but the potential connection between necroptosis-related genes (NRGs) and LUAD still remains unclear. In this study, we expounded mutational and transcriptional alterations of 67 NRGs in 522 LUAD samples and proposed a consensus-clustering subtype of these patients into two cohorts with distinct immunological and clinical prognosis characteristics. Cluster B patients were associated with a better prognosis and characterized by relatively lower expression of NRGs, higher immune scores in the tumor microenvironment (TME), more mild clinical stages, and downregulated expression of immunotherapy checkpoints. Subsequently, the NRG score was further established to predict the overall survival (OS) of LUAD patients using univariate Cox, LASSO, and multivariate Cox regression analyses. The immunological characteristics and potential predictive capability of NRG scores were further validated by 583 LUAD patients in external datasets. In addition to better survival and immune-activated conditions, low-NRG-score cohorts exhibited a significant positive correlation with the mRNA stem index (mRNAsi) and tumor mutation burden (TMB) levels. Combined with classical clinical characteristics and NRG scores, we successfully defined a novel necroptosis-related nomogram to accurately predict the 1/3/5-year survival rate of individual LUAD patients, and the potential predictive capability was further estimated and validated in multiple test datasets with high AUC values. Integrated transcriptomic analysis helps us seek vital NRGs and supplements a novel clinical application of NRG scores in predicting the overall survival and therapeutic benefits for LUAD patients.

Functional characterization and clinical significance of super-enhancers in lung adenocarcinoma

Super-enhancers (SEs) are important transcriptional regulators in tumorigenesis; however, the functional characterization and clinical significance of SEs in lung adenocarcinoma (LUAD) remain unclear. By using H3K27ac ChIP-seq data of two LUAD cell lines and eight lung tissues, we detected 1045 cancer-specific and 5032 normal-specific SEs. Compared to normal-specific SEs, cancer-specific SEs have different regulatory mechanisms where associated target genes were enriched in critical tumor-related pathways and tended to be regulated by transcription factors of Fos Proto-Oncogene, AP-1 Transcription Factor Subunit and Jun Proto-Oncogene, AP-1 Transcription Factor Subunit families. By using expression data of 513 LUAD and 57 adjacent samples from The Cancer Genome Atlas and 80 tumor-normal paired LUAD samples from the Nanjing Lung Cancer Cohort study, we performed differential expression analysis of target genes for SEs and defined 243 crucial SEs. Unsupervised clustering of crucial SEs revealed two subtypes with different levels of genomic aberrations (i.e., mutation and copy number alteration) and clinical outcomes (progression-free interval: p = 0.030; disease-free interval: p = 0.047). In addition, patients with adverse clinical outcomes were more sensitive to three small molecule inhibitors (bortezomib, doxorubicin, and etoposide), and their targets (PSMB5 and TOP2A) also have elevated expression levels among these patients. Taken together, our findings provided a comprehensive characterization of SEs in LUAD and emphasized their clinical significance in LUAD therapy.

HyperChIP: identification of hypervariable signals across ChIP-seq or ATAC-seq samples

Identifying genomic regions with hypervariable ChIP-seq or ATAC-seq signals across given samples is essential for large-scale epigenetic studies. In particular, the hypervariable regions across tumors from different patients indicate their heterogeneity and can contribute to revealing potential cancer subtypes and the associated epigenetic markers. We present HyperChIP as the first complete statistical tool for the task. HyperChIP uses scaled variances that account for the mean-variance dependence to rank genomic regions, and it increases the statistical power by diminishing the influence of true hypervariable regions on model fitting. A pan-cancer case study illustrates the practical utility of HyperChIP.

Observation on the clinical efficacy and side effects of EGFR-TKI ± chemotherapy in the treatment of EGFR mutation-positive advanced lung adenocarcinoma

Objective

To assess the clinical efficacy and side effects of EGFR-TKI with or without chemotherapy in the treatment of EGFR mutation-positive advanced lung adenocarcinoma.

Methods

A total of 103 IIIB or IV EGFR mutation-positive lung adenocarcinoma patients admitted to the oncology department of Fujian Provincial Hospital from January 2017 to October 2020 were selected. According to genetic mutation status, patients were divided into the following groups: 19del alone, 19del combined with TP53 or other co-mutations, L858R mutation alone, and L858R mutation combined with TP53 or other co-mutations. Targeted drugs or targeted drugs combined with chemotherapy were respectively administered in the four groups. In patients with simple 19 deletion, only targeted drugs with no combined therapy were applied, resulting in seven total groups. The difference between short-term treatment and long-term treatment effects and the occurrence of adverse reactions was calculated and compared.

Results

There was no statistical significance of difference in the incidence of adverse reactions in seven groups ( p > 0.05). The short-term disease control rate of the combination group was higher than the targeted drug group with the difference yielding statistical significance ( p < 0.001). The short-term objective response rate of the combination group was higher than the targeted drug group, also yielding statistical significance ( p < 0.001). By October 2020, the median progression-free survival (PFS) was 16 months in the EGFR-TKI-targeted combined with chemotherapy group and 10 months in the single-drug EGFR-TKI group, and the PFS time was longer in the combination group than in the single targeted drug group, the difference being statistically significant ( p = 0.001).

Conclusions

In the treatment of advanced lung adenocarcinoma patients with EGFR-gene sensitive mutations, compared with single EGFR-TKI-targeted therapy, EGFR-TKI-targeted drug combined chemotherapy can control the disease progression more effectively, and does not increase adverse reactions.

tsRNA-5001a promotes proliferation of lung adenocarcinoma cells and is associated with postoperative recurrence in lung adenocarcinoma patients

Background

The biological role and clinical significance of transfer RNA-derived small RNAs (tsRNAs) remain largely unclear. The purpose of this study was to investigate the biological function, molecular mechanism, and clinical significance of tsRNA-5001a in lung adenocarcinoma.

Methods

The function of tsRNA-5001a on the growth of tumor cells was accessed by cell function experiments. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression of tsRNA-5001a in paired samples of lung adenocarcinoma. Cell localization of tsRNA-5001a was performed by nuclear-cytoplasmic separation assay. Transcriptome sequencing was used to screen the molecules involved in the regulatory network of tsRNA-5001a. Independent samples t-test was used to compare the two groups. Prism software (Prism 7.0) was used to analyze the statistical results. P<0.05 was considered statistically significant.

Results

tsRNA-5001a was significantly upregulated in lung adenocarcinoma tissues. Upregulation of tsRNA-5001a was found to increase the risk of postoperative recurrences in patients with lung adenocarcinoma and was associated with poor prognosis. Function assay showed that overexpression tsRNA-5001a could significantly promote cell proliferation. In contrast, knockdown of tsRNA-5001a significantly inhibited the proliferation of lung adenocarcinoma cells. In addition, nucleoplasmic isolation assay indicated that tsRNA-5001a was located mainly in the cytoplasm. According to the results of RNA sequencing and The Cancer Genome Atlas database (TCGA database) analysis, growth arrest and DNA damage 45G (GADD45G) was screened and may be the target gene of tsRNA-5001a.

Conclusions

tsRNA-5001a promotes the proliferation of lung adenocarcinoma cells and increases the risk of postoperative recurrences in lung adenocarcinoma patients.