Molecular biomarkers for lung adenocarcinoma

UBASH3B-mediated MRPL12 Y60 dephosphorylation inhibits LUAD development by driving mitochondrial metabolism reprogramming

BACKGROUND

Metabolic reprogramming plays a pivotal role in tumorigenesis and development of lung adenocarcinoma (LUAD). However, the precise mechanisms and potential targets for metabolic reprogramming in LUAD remain elusive. Our prior investigations revealed that the mitochondrial ribosomal protein MRPL12, identified as a novel mitochondrial transcriptional regulatory gene, exerts a critical influence on mitochondrial metabolism. Despite this, the role and regulatory mechanisms underlying MRPL12's transcriptional activity in cancers remain unexplored.

METHODS

Human LUAD tissues, Tp53fl/fl;KrasG12D-driven LUAD mouse models, LUAD patient-derived organoids (PDO), and LUAD cell lines were used to explored the expression and function of MRPL12. The posttranslational modification of MRPL12 was analyzed by mass spectrometry, and the oncogenic role of key phosphorylation sites of MRPL12 in LUAD development was verified in vivo and in vitro.

RESULTS

MRPL12 was upregulated in human LUAD tissues, Tp53fl/fl;KrasG12D-driven LUAD tissues in mice, LUAD PDO, and LUAD cell lines, correlating with poor patient survival. Overexpression of MRPL12 significantly promoted LUAD tumorigenesis, metastasis, and PDO formation, while MRPL12 knockdown elicited the opposite phenotype. Additionally, MRPL12 deletion in a Tp53fl/fl;KrasG12D-driven mouse LUAD model conferred a notable survival advantage, delaying tumor onset and reducing malignant progression. Mechanistically, we discovered that MRPL12 promotes tumor progression by upregulating mitochondrial oxidative phosphorylation. Furthermore, we identified UBASH3B as a specific binder of MRPL12, dephosphorylating tyrosine 60 in MRPL12 (MRPL12 Y60) and inhibiting its oncogenic functions. The decrease in MRPL12 Y60 phosphorylation impeded the binding of MRPL12 to POLRMT, downregulating mitochondrial metabolism in LUAD cells. In-depth in vivo, in vitro, and organoid models validated the inhibitory effect of MRPL12 Y60 mutation on LUAD.

CONCLUSION

This study establishes MRPL12 as a novel oncogene in LUAD, contributing to LUAD pathogenesis by orchestrating mitochondrial metabolism reprogramming towards oxidative phosphorylation (OXPHOS). Furthermore, it confirms Y60 as a specific phosphorylation modification site regulating MRPL12's oncogenic functions, offering insights for the development of LUAD-specific targeted drugs and clinical interventions.

Personalized treatment using predictive biomarkers in solid organ malignancies: A review

In recent years, the influence of specific biomarkers in the diagnosis and prognosis of solid organ malignancies has been increasingly prominent. The relevance of the use of predictive biomarkers, which predict cancer response to specific forms of treatment provided, is playing a more significant role than ever before, as it affects diagnosis and initiation of treatment, monitoring for efficacy and side effects of treatment, and adjustment in treatment regimen in the long term. In the current review, we explored the use of predictive biomarkers in the treatment of solid organ malignancies, including common cancers such as colorectal cancer, breast cancer, lung cancer, prostate cancer, and cancers associated with high mortalities, such as pancreatic cancer, liver cancer, kidney cancer and cancers of the central nervous system. We additionally analyzed the goals and types of personalized treatment using predictive biomarkers, and the management of various types of solid organ malignancies using predictive biomarkers and their relative efficacies so far in the clinical settings.

Analysis of cancer-associated fibroblasts related genes identifies COL11A1 associated with lung adenocarcinoma prognosis

BACKGROUND

The treatment of lung adenocarcinoma is difficult due to the limited therapeutic options. Cancer-associated fibroblasts play an important role in the development of cancers. This study aimed to identify a promising molecular target associated with cancer-associated fibroblasts for the treatment of lung adenocarcinoma.

METHODS

The Cancer Genome Atlas lung adenocarcinoma dataset was used to screen hub genes associated with cancer-associated fibroblasts via the EPIC algorithm and Weighted Gene Co-expression Network Analysis. Multiple databases were used together with our data to verify the differential expression and survival of COL11A1. Functional enrichment analysis and the single-cell TISCH database were used to elucidate the mechanisms underlying COL11A1 expression. The correlation between COL11A1 and immune checkpoint genes in human cancers was also evaluated.

RESULTS

Using the EPIC algorithm and Weighted Gene Co-expression Network Analysis, 13 hub genes associated with cancer-associated fibroblasts in lung adenocarcinoma were screened. Using the GEPIA database, Kaplan-Meier Plotter database, GSE72094, GSE75037, GSE32863, and our immunohistochemistry experiment data, we confirmed that COL11A1 overexpresses in lung adenocarcinoma and that high expression of COL11A1 is associated with a poor prognosis. COL11A1 has a genetic alteration frequency of 22% in patients with lung adenocarcinoma. COL11A1 is involved in the extracellular matrix activities of lung adenocarcinoma. Using the TISCH database, we found that COL11A1 is mainly expressed by cancer-associated fibroblasts in the tumor microenvironment rather than by lung adenocarcinoma cells. Finally, we found that COL11A1 is positively correlated with HAVCR2(TIM3), CD274 (PD-L1), CTLA4, and LAG3 in lung adenocarcinoma.

CONCLUSION

COL11A1 may be expressed and secreted by cancer-associated fibroblasts, and a high expression of COL11A1 may result in T cell exhaustion in the tumor microenvironment of lung adenocarcinoma. COL11A1 may serve as an attractive biomarker to provide new insights into cancer therapeutics.

TIMM17A overexpression in lung adenocarcinoma and its association with prognosis

Lung adenocarcinoma (LUAD), a leading cause of cancer-related mortality worldwide, demands a deeper understanding of its molecular mechanisms and the identification of reliable biomarkers for better diagnosis and targeted therapy. Leveraging data from the Cancer Genome Atlas (TCGA), the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and the Human Protein Atlas (HPA), we investigated the mRNA and protein expression profiles of TIMM17A and assessed its prognostic significance through Kaplan-Meier survival curves and Cox regression analysis. Through Gene Set Enrichment Analysis, we explored the regulatory mechanisms of TIMM17A in LUAD progression and demonstrated its role in modulating the proliferative capacity of A549 cells, a type of LUAD cell, via in vitro experiments. Our results indicate that TIMM17A is significantly upregulated in LUAD tissues, correlating with clinical staging, lymph node metastasis, overall survival, and progression-free survival, thereby establishing it as a critical independent prognostic factor. The construction of a nomogram model further enhances our ability to predict patient outcomes. Knockdown of TIMM17A inhibited the growth of LUAD cells. The potential of TIMM17A as a biomarker and therapeutic target for LUAD presents a promising pathway for improving patient diagnosis and treatment strategies.

Mitochondrial ribosomal protein S24 is associated with immunosuppressive microenvironment and cold tumor in lung adenocarcinoma

Objective

MRPS24 (Mitochondrial Ribosomal Protein S24) belongs to the mitochondrial ribosomal protein family, which participates in the protein synthesis of the mitochondrion. However, the relationship of MRPS24 with lung adenocarcinoma (LUAD) remained unknown. We aimed to identify its immunological and functional mechanisms in LUAD.

Methods

The analysis of MRPS24 expression, clinical features, diagnosis, prognosis, function analysis, genetic alteration, copy number variations, methylation, and tumor microenvironment was investigated by the TCGA, UCSC Xena, GEO, HPA, GEPIA, cBioPortal, MethSurv, TIMER, TIMER2.0, and TISIDB databases.

Results

MRPS24 was found to be more abundant in LUAD tumor tissue than in normal tissue. High levels of MRPS24 expression were found to be an independent prognostic factor by multivariate analysis. Functional analysis revealed that MRPS24 expression was associated with the immune, cell cycle and methylation. MRPS24 methylation level was inversely linked with its expression (p < 0.001). Patients with low MRPS24 methylation had a worse prognosis than those with high methylation (p < 0.05). In addition, the result revealed that the MRPS24 expression was inversely linked to the immune cell infiltration in LUAD. Finally, the validations of the expression level, prognosis, and immune cell infiltration of MRPS24 were in accordance with our previous results.

Conclusions

This study systematically explored that MRPS24 expression was significantly correlated with prognosis, tumorigenesis, genetic alteration, copy number variations, methylation, and immune cell infiltration in LUAD. MRPS24 might be a potential immune-related biomarker in the development and treatment of LUAD, thereby acting as a promising predictor of immunotherapy response in LUAD.

DLGAP5 promotes lung adenocarcinoma growth via upregulating PLK1 and serves as a therapeutic target

BACKGROUND

Human discs large-associated protein 5 (DLGAP5) is reported to play a pivotal role in regulating the cell cycle and implicate in tumorigenesis and progression of various cancers. Our current research endeavored to explore the prognostic value, immune implication, biological function and targeting strategy of DLGAP5 in LUAD through approaches including bioinformatics, network pharmacology analysis and experimental study.

METHODS

Multiple databases, including TCGA, GEO, CPTAC and Human Protein Atlas, were utilized to explore the expression and clinical significance of DLGAP5 in LUAD. The genetic alterations of DLGAP5 were assessed through cBioPortal and COSMIC databases. The relationship between DLGAP5 expression and genetic abnormalities of driver genes in LUAD was analyzed through TIMER2.0 database. CancerSEA database was utilized to explore the function of DLGAP5 in 14 different states in LUAD at single-cell resolution. GDSC database was utilized to analyze the impact of DLGAP5 on IC50 of frequently-used anti-LUAD drugs. CIBERSORT method and TIMER2.0 database was utilized to explore the relationship between DLGAP5 and tumor immune infiltration. Network pharmacology was applied to screen potential DLGAP5 inhibitor. In vitro and in vivo experiments were utilized to evaluate biological function and downstream targets of DLGAP5, and the effect of screened DLGAP5 inhibitor on LUAD growth.

RESULTS

High DLGAP5 expression was commonly observed in LUAD and associated with mutation of major driver genes, poor prognosis, high IC50 values of frequently-used anti-LUAD drugs, increasing immune infiltration and elevated immune checkpoint blockade-related genes in LUAD. PLK1 was revealed as a potential DLGAP5 downstream target in LUAD. DLGAP5 overexpression or knockdown significantly promoted or inhibited LUAD cell proliferation and PLK1 expression. PLK1 overexpression well rescued DLGAP5 knockdown-induced cell proliferation inhibition, or vice versa. Furthermore, by virtual screening of an investigational drug library from the DrugBank database, AT9283 was screened and identified as a novel DLGAP5 inhibitor. AT9283 effectively suppressed growth of LUAD cells both in vitro and in vivo. DLGAP5 overexpression significantly reversed AT9283-induced proliferation inhibition. Moreover, AT9283 significantly suppressed DLGAP5 and PLK1 expression, while DLGAP5 overexpression significantly reversed AT9283-induced PLK1 suppression.

CONCLUSION

Our research has demonstrated that DLGAP5 is upregulated in LUAD and exhibits a strong correlation with unfavorable prognosis. Furthermore, DLGAP5 assumes a significant function in the regulation of tumor immunity and treatment outcome of immune checkpoint inhibitors. Of note, we found that DLGAP5 promotes cell proliferation of LUAD via upregulating PLK1. Targeting DLGAP5 by AT9283, our newly identified DLGAP5 inhibitor, suppresses LUAD growth. DLGAP5 may become a promising prognostic biomarker and therapeutic target for patients with LUAD.

Construction of a New Immune-Related Competing Endogenous RNA Network with Prognostic Value in Lung Adenocarcinoma

Tumor microenvironment has significant influence on the gene expression of tumor tissues and on the clinical outcomes in lung adenocarcinoma. Infiltrating immune and stromal cells not only perturb the tumor signal in molecular studies, but also play crucial roles in cancer biology. The competing endogenous RNAs (ceRNAs) are useful to explain the post-transcriptional layer regulated by gene translation and play an important role in the occurrence and progression of lung adenocarcinoma. Therefore, identifying novel molecular markers by constructing ceRNA associated with immune infiltration is of great significance to guide the treatment of lung adenocarcinoma in the future. According to the immune and stromal scores of lung adenocarcinoma samples in The Cancer Genome Atlas (TCGA) database calculated by the ESTIMATE algorithm, we identified differentially expressed lncRNAs, miRNAs and mRNAs associated with immune infiltration, including 60 dysregulated lncRNAs, 38 dysregulated mRNAs, and 29 dysregulated miRNAs. Based on the PPI network and Cox regression analysis, 5 mRNAs including CNR2, P2RY12, ZNF831, RSPO1, and F2 were identified to be related to immune infiltration and prognosis in lung adenocarcinoma, and their differential expression, prognosis and correlation with immune cells were verified. Next, through target binding prediction, pearson correlation analysis and expression analysis, a novel immune-related ceRNA network containing 6 lncRNAs, 4 miRNAs, and 3 mRNAs was finally constructed. The present study constructed a novel immune-associated lncRNA-miRNA-mRNA ceRNA network, which deepens our understanding on the molecular network mechanism of lung adenocarcinoma and provides potential prognostic markers and novel therapeutic targets for the patients with lung adenocarcinoma.

Multidimensional progressive single-cell sequencing reveals cell microenvironment composition and cancer heterogeneity in lung cancer

Despite substantial advances in cancer biology and treatment, the clinical outcomes of patients with lung cancer remain unsatisfactory. The tumor microenvironment (TME) is a potential target. Using single-cell RNA sequencing, we could distinguish eight distinct cell types in the lung cancer microenvironment, demonstrating substantial intratumoral heterogeneity in 19 different lung cancer tumor samples. Through the re-dimensional grouping of cancer-associated fibroblasts (CAFs), myeloid cells, epithelial cells, natural killer (NK) cells, and T cells, the difference in the TME of lung cancer was revealed. We discovered SFTPB, SFN, and KRT8 as possible predictive biomarkers for lung cancer by assessing the gene expression patterns in epithelial cells. Examining cell-to-cell communications showed a robust association between the quantity of matrix CAFs, epithelial cells, and macrophages in the thrombospondin signaling pathway. Additionally, we found that the amyloid precursor protein signaling pathway primarily originated from the matrix, and inflammatory cancer-associated endothelial and fibroblast cells showed a co-expression relationship with myeloid cells and B cells. Through cell-to-cell correlation analysis, we found positive regulation between NK cells, regulatory T cells, GZMB-CD8 T cells, and GZMK-CD8 T cells, which could play a role in developing immune TMEs. These findings support studies on cancer heterogeneity and add to our understanding of lung cancer's cellular microenvironment.

Activation of KrasG12D in Subset of Alveolar Type II Cells Enhances Cellular Plasticity in Lung Adenocarcinoma

We have previously identified alveolar type II cell as the cell-of-origin of KrasG12D-induced lung adenocarcinoma using cell lineage-specific inducible Cre mouse models. Using gain-of-function and loss-of-function genetic models, we discovered that active Notch signaling and low Sox2 levels dictate the ability of type II cells to proliferate and progress into lung adenocarcinoma upon KrasG12D activation. Here, we examine the phenotype of type II cells after Kras activation and find evidence for proliferation of cells that coexpress type I and type II markers. Three-dimensional organoid culture and transplantation studies determine that these dual-positive cells are highly plastic and tumor initiating in vivo. RNA sequencing analysis reveals that these dual-positive cells are enriched in Ras/MAPK, EGFR, and Notch pathways. Furthermore, the proliferation of these cells requires active Notch signaling and is inhibited by genetic/chemical Sox2 upregulation. Our findings could provide new therapeutic strategies to target KRAS-activated lung adenocarcinomas.

SIGNIFICANCE

Identification of progenitor like tumor-initiating cells in KRAS-mutant lung adenocarcinoma may allow development of novel targeted therapeutics.

Classification of SLC family-related genes involved in ferroptosis predicts lung cancer prognosis and immunotherapy response

Lung adenocarcinoma, the most frequent type of lung cancer, is the leading cause of cancer-related deaths worldwide. Ferroptosis, controlled cell death that involves a high degree of iron-dependent lipid peroxidation, has been linked to tumor therapy sensitivity, patient prognosis, and cancer development. The solute carrier superfamily has over 400 members and comprises the largest class of transporters in the human genome. Solute carrier proteins can facilitate the movement of different substrates across biological membranes, which is crucial for physiological activities, including ferroptosis. Here, we developed a new model to further explore the role of the solute carrier family in ferroptosis in the lung adenocarcinoma immunological milieu. We used consensus clustering to classify patients with lung cancer into two subgroups (cluster1 and cluster2). Patients in the cluster1 subtype had a better prognosis and higher immune cell infiltration ratios than those in the cluster2 subtype. Furthermore, to evaluate the prognosis, the immune cell infiltration ratio, and the medication sensitivity of patients with lung adenocarcinoma, we developed gene scores related to the solute carrier family. In conclusion, we successfully developed a model incorporating the solute carrier family and ferroptosis to predict survival and the impact of immunotherapy on patients with lung cancer.

Screening and validation of plasma cell-derived, purinergic, and calcium signalling-related genetic signature to predict prognosis and PD-L1/PD-1 blockade responses in lung adenocarcinoma

BACKGROUND

This study aims at  screening and validation of prospective genetic signature for lung adenocarcinoma (LUAD) prognosis and treatment.

METHODS

The immune-related genes (IRGs) were obtained from The Cancer Genome Atlas (TCGA) dataset where a total of 535 LUAD and 59 control samples were included. A risk model was then developed for the risk stratification of LUAD patients.  The immune cell infiltration, clinical outcomes, and the therapeutic efficacy of programmed cell death protein 1 (PD-1) and its ligand (PD-L1) blockade were compared between high and low-risk groups. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to explore the biological processes and signalling pathways associated with the IRGs. Finally, IRGs mRNA levels were assayed by reverse transcription quantitative real-time PCR (RT-qPCR) in LUAD and relevant cell lines.

RESULTS

Two IRGs, P2RX1 (purinergic receptor P2X 1) and PCP4 (Purkinje cell protein 4), were screened from a module that possesses the highest correlation with plasma cells. RT-qPCR verified the expression of the two IRGs in plasmacytoma cell RPMI 8226 but not in LUAD cells. A higher risk score is associated with a lower infiltration of immune cells. Kaplan-Meier and nomogram analysis showed that the high-risk group has a lower survival rate than the low-risk cohort. Furthermore, the high-risk group had a worse response rate to PD-L1/PD-1 blockade. GSVA and GSEA-GO results indicated that a lower risk score is linked to signalling pathways and biological functions promoting immune response and inflammation. In contrast, a higher risk score is associated with signalling cascades promoting tumour growth.

CONCLUSION

The immune-related prognostic model based on P2RX1 and PCP4 is conducive to predicting the therapeutic response of PD-L1/PD-1 blockade and clinical outcomes of LUAD.

Prognosis of recurrence after complete resection in early-stage lung adenocarcinoma based on molecular alterations: a systematic review and meta-analysis

Molecular biomarkers have the potential to predict the recurrence risk of early-stage lung adenocarcinoma (LUAD) after complete resection, but the study results are controversial. We aimed to clarify the association of molecular alterations with disease-free survival (DFS) and recurrence-free survival (RFS) in early-stage LUAD with R0 resection. Comprehensive searches were conducted in PubMed/MEDLINE, Web of Science, and Cochrane Library for this systematic review and meta-analysis with date restrictions from 2012 to 2022. In the 18 included studies, data from a total of 7417 participants in 11 studies and 4167 participants in 9 studies were collected for the EGFR and KRAS meta-analyses, respectively. Two studies were assessed as having a moderate risk of bias, and the others were all assessed as having a high individual risk of bias. The molecular alterations in KRAS rather than EGFR, were associated with a high risk of recurrence for early-stage LUAD patients suffering from R0 resection, especially for those in pStage I, the pooled hazard ratios (HRs) of KRAS were 2.71 (95% CI, 1.81-4.06; I2 = 22%; P < 0.00001) and 1.95 (95% CI, 1.25-3.20; I2 = 57%; P = 0.003) with small interstudy heterogeneity in univariate and multivariate analyses, respectively. This finding suggests that molecular alterations in KRAS that could be detected by polymerase chain reaction techniques would provide new insight into stratifying risk and personalizing patient postoperative follow-up.

High Yield of Pleural Cell-Free DNA for Diagnosis of Oncogenic Mutations in Lung Adenocarcinoma

BACKGROUND

Pleural cytology is currently used to assess targetable mutations in patients with advanced lung adenocarcinoma. However, it is fraught with low diagnostic yield.

RESEARCH QUESTION

Can pleural cell-free DNA (cfDNA) be used to assess targetable mutations in lung adenocarcinoma patients with malignant pleural effusions (MPE)?

STUDY DESIGN AND METHODS

Patients with lung adenocarcinoma MPE were recruited prospectively between January 2017 and September 2021. Oncogenic mutations were assessed by treating providers using pleural fluid cytology or lung cancer biopsies. Pleural and plasma cfDNA were used to assess the mutations using next-generation sequencing (NGS).

RESULTS

Fifty-four pleural fluid samples were collected from 42 patients. The diagnostic yield to detect oncogenic mutations for pleural cfDNA, pleural cytology, biopsy, and plasma cfDNA was 49/54 (90.7%), 16/33 (48.5%), 22/25 (88%), and 24/32 (75%), respectively, P < .001. The agreement of mutations in positive samples between pleural cfDNA and pleural cytology was 100%, whereas the agreement of pleural cfDNA with biopsies was 89.4%. The median concentration (interquartile range) of pleural cfDNA was higher than plasma: 28,444 (4,957-67,051) vs 2,966.5 (2,167-5,025) copies of amplifiable DNA per mL, P < .01. Median of 5 mL (interquartile range, 4.5-5) of pleural fluid supernatant was adequate for cfDNA testing.

INTERPRETATION

The diagnostic yield of pleural cfDNA NGS for oncogenic mutations in lung adenocarcinoma patients is comparable to tumor biopsies and higher than pleural cytology and plasma cfDNA. The pleural cfDNA can be longitudinally collected, can be readily incorporated in clinical workflow, and may decrease the need for additional biopsies.

The E2F1/MELTF axis fosters the progression of lung adenocarcinoma by regulating the Notch signaling pathway

BACKGROUND

Lung adenocarcinoma (LUAD) represents the predominant subtype of lung cancer. MELTF, an oncogene, exhibits high expression in various cancer tissues. Nevertheless, the precise role of MELTF in the progression of LUAD remains enigmatic. This work was devised to investigate the effect of MELTF on LUAD progression and its underlying mechanism.

METHODS

mRNA expression data of LUAD were from The Cancer Genome Atlas database, and the enrichment pathway of MELTF was analyzed. The upstream transcription factors of MELTF were predicted, and the correlation between MELTF and E2F1 as well as the expression of the two in LUAD tissues were dissected by bioinformatics. The expression of MELTF and E2F1 in LUAD tissues and cells was assayed by qRT-PCR. Effects of MELTF/E2F1 on proliferation, migration, and invasion of LUAD cells were tested by CCK-8, colony formation, and Transwell assays. The binding relationship between E2F1 and MELTF was estimated by dual-luciferase reporter gene assay and ChIP assay. Western blot was utilized to assay the expression of Notch signaling pathway-related proteins in different treatment groups.

RESULTS

Bioinformatics analysis and qRT-PCR results exhibited high expression of E2F1 and MELTF in LUAD tissues and cells, respectively. Dual-luciferase reporter gene assay and ChIP assay ascertained the binding of E2F1 to MELTF. MELTF was ascertained to enrich the Notch signaling pathway by bioinformatics means. In cell experiments, MELTF was shown to foster the malignant progression of LUAD cells and promoted the expression of NOTCH1 and HES1 proteins, but RO4929097 offset the effect of MELTF on cells. Rescue assay confirmed that E2F1 activated MELTF to promote LUAD progression via the Notch signaling pathway.

CONCLUSION

Together, our outcomes demonstrated that E2F1 fostered LUAD progression by activating MELTF via the Notch signaling activity. Hence, MELTF emerged as a feasible target for treating LUAD.

Dissecting the alternation landscape of mitochondrial metabolism-related genes in lung adenocarcinoma and their latent mechanisms

Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer with high incidence and unsatisfactory prognosis. The majority of LUAD patients eventually succumb to local and/or distinct metastatic recurrence. Genomic research of LUAD has broadened our understanding of this disease's biology and improved target therapies. However, the alternation landscape and characteristics of mitochondrial metabolism-related genes (MMRGs) in LUAD progression remain poorly understood. We performed a comprehensive analysis to identify the function and mechanism of MMRGs in LUAD based on the TCGA and GEO databases, which might offer therapeutic values for clinical researchers. Then, we figured out three hub prognosis-associated MMRGs (also termed as PMMRGs: ACOT11, ALDH2, and TXNRD1) that were engaged in the evolution of LUAD. To investigate the correlation between clinicopathological characteristics and MMRGs, we divided LUAD samples into two clusters (C1 and C2) based on key MMRGs. In addition, important pathways and the immune infiltration landscape affected by LUAD clusters were also delineated. Further, we nominated potential regulatory mechanisms underlying the MMRGs in LUAD development and progression. In conclusion, our integrative analysis enables a more comprehensive understanding of the mutation landscape of MMRGs in LUAD and provides an opportunity for more precise treatment.

The role of molecular subtypes and immune infiltration characteristics based on disulfidptosis-associated genes in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common type of lung cancer which accounts for about 40% of all lung cancers. Early detection, risk stratification and treatment are important for improving outcomes for LUAD. Recent studies have found that abnormal accumulation of cystine and other disulfide occurs in the cell under glucose starvation, which induces disulfide stress and increases the content of disulfide bond in actin cytoskeleton, resulting in cell death, which is defined as disulfidptosis. Because the study of disulfidptosis is in its infancy, its role in disease progression is still unclear. In this study, we detected the expression and mutation of disulfidptosis genes in LUAD using a public database. Clustering analysis based on disulfidptosis gene was performed and differential genes of disulfidptosis subtype were analyzed. 7 differential genes of disulfidptosis subtype were used to construct a prognostic risk model, and the causes of prognostic differences were investigated by immune-infiltration analysis, immune checkpoint analysis, and drug sensitivity analysis. qPCR was used to verify the expression of 7 key genes in lung cancer cell line (A549) and normal bronchial epithelial cell line (BEAS-2B). Since G6PD had the highest risk factor of lung cancer, we further verified the protein expression of G6PD in lung cancer cells by western blot, and confirmed through colony formation experiment that interference with G6PD was able to significantly inhibit the proliferation ability of lung cancer cells. Our results provide evidence for the role of disulfidptosis in LUAD and provide new ideas for individualized precision therapy of LUAD.

Core genes in lung adenocarcinoma identified by integrated bioinformatic analysis

This study aims to identify potential core genes of lung adenocarcinoma (LUAD). Three datasets (GSE32863, GSE43458, and GSE116959) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between LUAD and normal tissues were filtrated by GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed via Metascape database. The protein-protein interaction (PPI) network was constructed and core genes were identified using STRING and Cytoscape. Core genes expressions and their relevant clinical characteristics were performed via Oncomine and UALCAN databases respectively. The correlation between core genes and immune infiltrates was investigated by TIMER database. Kaplan-Meier plotter was performed for survival analysis. The signal pathway network of core genes was mapped by KEGG Mapper analysis tool. In this study, ten core genes were significantly related to overall survival (OS) of LUAD patients, which can provide clues for prognosis of LUAD.

Construction and validation of a cuproptosis-related lncRNA signature for the prediction of the prognosis of LUAD and LUSC

Lung cancer is one of the most prevalent malignant tumors worldwide, with lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) accounting for the majority of cases. Cuproptosis, tumor immune microenvironment (TIME) and long non-coding RNA (lncRNA) have been demonstrated to be associated with tumorigenesis. The objective of the present study was to develop a novel cuproptosis-related lncRNA signature to assess the association between cuproptosis and TIME in patients with LUAD or LUSC and to predict prognosis. Based on the outputs of the least absolute shrinkage and selection operator regression model, a cuproptosis-related lncRNA signature was developed. Kaplan-Meier survival curves were generated to confirm the predictive ability of the signature. Univariate and multivariate analysis was also performed to determine the association between overall survival and this signature and other clinical characteristics, and a nomogram was created. Additionally, the relationship between the signature, TIME, tumor mutation burden and m6A methylation was established. The results of the present study revealed that 8 cuproptosis-related lncRNAs were associated with the prognosis of patients with LUAD and LUSC. This novel cuproptosis-related lncRNA signature is associated with TIME and m6A methylation in LUAD and LUSC and can predict prognosis with accuracy.

Prognostic roles of a novel basement membranes-related gene signature in lung adenocarcinoma

Background: The basement membranes (BMs) are involved in tumor progression, while few comprehensive analyses to date are performed on the role of BM-related gene signatures in lung adenocarcinoma (LUAD). Thus, we aimed to develop a novel prognostic model in LUAD based on BMs-related gene profiling. Methods: The LUAD BMs-related gene profiling and corresponding clinicopathological data were obtained from the basement membrane BASE, The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) databases. The Cox regression and least absolute shrinkage and selection operator (LASSO) methods were used to construct a BMs-based risk signature. The concordance index (C-index), receiver operating characteristic (ROC), and calibration curves were generated to evaluate the nomogram. The GSE72094 dataset was used to validate prediction of the signature. The differences in functional enrichment, immune infiltration, and drug sensitivity analyses were compared based on risk score. Results: In TCGA training cohort, 10 BMs-related genes were found, (e.g., ACAN, ADAMTS15, ADAMTS8, BCAN, etc). The signal signature based on these 10 genes was categorized into high- and low-risk groups regarding survival differences (p < 0.001). Multivariable analysis showed that the signature of combined 10 BMs-related genes was an independent prognostic predictor. Such a prognostic value of BMs-based signature in validation cohort of the GSE72094 were further verified. The GEO verification, C-index, and ROC curve showed that the nomogram had accurate prediction performance. The functional analysis suggested that BMs were mainly enriched in extracellular matrix-receptor (ECM-receptor) interaction. Moreover, the BMs-based model was correlated with immune checkpoint. Conclusion: This study identified BMs-based risk signature genes and demonstrated their ability to predict prognosis and guide personalized treatment of patients with LUAD.

Establishing a metastasis-related diagnosis and prognosis model for lung adenocarcinoma through CRISPR library and TCGA database

PURPOSE

Existing biomarkers for diagnosing and predicting metastasis of lung adenocarcinoma (LUAD) may not meet the demands of clinical practice. Risk prediction models with multiple markers may provide better prognostic factors for accurate diagnosis and prediction of metastatic LUAD.

METHODS

An animal model of LUAD metastasis was constructed using CRISPR technology, and genes related to LUAD metastasis were screened by mRNA sequencing of normal and metastatic tissues. The immune characteristics of different subtypes were analyzed, and differentially expressed genes were subjected to survival and Cox regression analyses to identify the specific genes involved in metastasis for constructing a prediction model. The biological function of RFLNA was verified by analyzing CCK-8, migration, invasion, and apoptosis in LUAD cell lines.

RESULTS

We identified 108 differentially expressed genes related to metastasis and classified LUAD samples into two subtypes according to gene expression. Subsequently, a prediction model composed of eight metastasis-related genes (RHOBTB2, KIAA1524, CENPW, DEPDC1, RFLNA, COL7A1, MMP12, and HOXB9) was constructed. The areas under the curves of the logistic regression and neural network were 0.946 and 0.856, respectively. The model effectively classified patients into low- and high-risk groups. The low-risk group had a better prognosis in both the training and test cohorts, indicating that the prediction model had good diagnostic and predictive power. Upregulation of RFLNA successfully promoted cell proliferation, migration, invasion, and attenuated apoptosis, suggesting that RFLNA plays a role in promoting LUAD development and metastasis.

CONCLUSION

The model has important diagnostic and prognostic value for metastatic LUAD and may be useful in clinical applications.

Molecular characterization based on tumor microenvironment-related signatures for guiding immunotherapy and therapeutic resistance in lung adenocarcinoma

Background: Although the role of tumor microenvironment in lung adenocarcinoma (LUAD) has been explored in a number of studies, the value of TME-related signatures in immunotherapy has not been comprehensively characterized. Materials and Methods: Consensus clustering was conducted to characterize TME-based molecular subtypes using transcription data of LUAD samples. The biological pathways and immune microenvironment were assessed by CIBERSORT, ESTIMATE, and gene set enrichment analysis. A TME-related risk model was established through the algorithms of least absolute shrinkage and selection operator (Lasso) and stepwise Akaike information criterion (stepAIC). Results: Four TME-based molecular subtypes including C1, C2, C3, and C4 were identified, and they showed distinct overall survival, genomic characteristics, DNA methylation pattern, immune microenvironment, and biological pathways. C1 had the worst prognosis and high tumor proliferation rate. C3 and C4 had higher enrichment of anti-tumor signatures compared to C1 and C2. C4 had evidently low enrichment of epithelial-mesenchymal transition (EMT) signature and tumor proliferation rate. C3 was predicted to be more sensitive to immunotherapy compared with other subtypes. C1 is more sensitive to chemotherapy drugs, including Docetaxel, Vinorelbine and Cisplatin, while C3 is more sensitive to Paclitaxel. A five-gene risk model was constructed, which showed a favorable performance in three independent datasets. Low-risk group showed a longer overall survival, more infiltrated immune cells, and higher response to immunotherapy than high-risk group. Conclusion: This study comprehensively characterized the molecular features of LUAD patients based on TME-related signatures, demonstrating the potential of TME-based signatures in exploring the mechanisms of LUAD development. The TME-related risk model was of clinical value to predict LUAD prognosis and guide immunotherapy.

Suitability of transbronchial needle aspiration for genotyping peripheral pulmonary tumors

Background

Transbronchial needle aspiration (TBNA) is a sampling tool that has demonstrated a higher accuracy in the diagnosis of peripheral pulmonary lesions (PPL) compared to other techniques. However, there are no studies investigating the value of TBNA in defining the genotype of peripheral lung cancer.

Objective

To evaluate the accuracy of TBNA in defining the molecular characteristics of peripheral lung cancer.

Methods

Consecutive patients who underwent TBNA for the diagnosis of a PPL at the Pulmonary Unit of the Azienda Ospedali Riuniti of Ancona (Italy) between January 2020 and September 2022 were included in the study. TBNA was performed under fluoroscopic guidance and the additional support of an ultrasound miniprobe, with an ultrathin bronchoscope with a flexible 21G needle. Samples were smeared on glass slides for cytological evaluation and flushed in 10% neutral-buffered formalin for cell-blocks.

Results

154 patients were enrolled:55 were diagnosed with adenocarcinoma and 21 with squamous cell carcinoma. TBNA correctly diagnosed 43/55 (78.2%) patients with adenocarcinoma and 17/21 (81.0%) patients with squamous cell carcinoma, with a sensitivity of 77.5%. Complete genotyping for guiding targeted therapies was obtained in 52 patients (86.6%).

Conclusions

TBNA is a valid tool for the diagnosis of PPL, allowing a correct diagnosis and a complete genotyping of the tumors in a considerable proportion of patients.

CircCCDC66: Emerging roles and potential clinical values in malignant tumors

Circular RNAs (circRNAs) are endogenous non-coding RNAs (ncRNAs) with a closed-loop structure. In recent years, circRNAs have become the focus of much research into RNA. CircCCDC66 has been identified as a novel oncogenic circRNA and is up-regulated in a variety of malignant tumors including thyroid cancer, non-small cell carcinoma, gastric cancer, colorectal cancer, renal cancer, cervical cancer, glioma, and osteosarcoma. It mediates cancer progression by regulating epigenetic modifications, variable splicing, transcription, and protein translation. The oncogenicity of circCCDC66 suppresses or promotes the expression of related genes mainly through direct or indirect pathways. This finding suggests that circCCDC66 is a biomarker for cancer diagnosis, prognosis assessment and treatment. However, there is no review on the relationship between circCCDC66 and cancers. Thus, the expression, biological functions, and regulatory mechanisms of circCCDC66 in malignant tumor and non-tumor diseases are summarized. The clinical value and prognostic significance of circCCDC66 are also evaluated, which can provide insights helpful to those exploring new strategies for the early diagnosis and targeted treatment of malignancies.

RASGRP2 is a potential immune-related biomarker and regulates mitochondrial-dependent apoptosis in lung adenocarcinoma

Background

Ras guanine nucleotide-releasing protein 2 (RASGRP2), one of the guanine nucleotide exchange factors (GEFs), has attracted much attention in recent years. However, the correlation between RASGRP2 and immune infiltration and malignant features in lung adenocarcinoma (LUAD) has rarely been mentioned.

Methods

The Limma package and the LASSO regression model were performed to screen for differentially expressed genes. Data from the TCGA and 5 GEO databases were used to explore the expression level of RASGRP2 in LUAD patients. A weighted co-expression network and LinkFinder module were established to find the related genes of RASGRP2. The ESTIMATE algorithm was used to analyze the correlation between RASGRP2 and immune infiltration in LUAD. Tumor-infiltrating immune cells were sorted and sequenced at the single-cell level to analyze differences in RASGRP2. Real-time PCR and immunohistochemistry were performed in the real-world cohort to verify the expression of RASGRP2 and its correlation with immune-related genes. Clone formation and EdU assays were used to verify the proliferation ability. The proportion of apoptotic cells was analyzed by flow cytometry. Observation of mitochondrial membrane potential (MMP) changes by fluorescence microscopy.

Results

Our results suggested that decreased RASGRP2 was associated with worse clinical parameters and prognosis in LUAD patients. And we constructed a FLI1-HSA-miR-1976-RASGRP2 transcriptional network to support the role of RASGRP2. Enrichment analysis revealed that RASGRP2 was involved in lymphocyte activation and leukocyte adhesion. RASGRP2 was found to be positively correlated with the infiltration of most immune cells, immunoregulators, and chemokines in a subsequent study. Meanwhile, the real-world cohort confirmed that the expression levels of PDCD1, CTLA4, CD40LG, CCL14, CXCR5, and CCR7 were higher in the high-RASGRP2 expression group. Cytological experiments proved that RASGRP2 inhibited cell proliferation in LUAD by regulating mitochondrial-dependent apoptosis.

Conclusion

RASGRP2 was a potential immune-related biomarker of LUAD. In addition, RASGRP2 was involved in the malignant progression of LUAD through the regulation of mitochondrial-dependent apoptosis.

Integrated bioinformatics analysis of microarray data from the GEO database to identify the candidate genes linked to poor prognosis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most common cancers with high morbidity and mortality and remains a crucial factor endangering human health.

OBJECTIVE

This study aimed to elucidate the potential treatment target and prognostic biomarker in patients with LUAD through a comprehensive bioinformatics analysis.

METHODS

The three public microarray datasets of GSE118370, GSE116959, and GSE43767 were obtained from the GEO data resource. The DEGs were explored between LUAD and non-malignant samples using GEO2R online tool in GEO data resource. GO along with KEGG analysis of DEGs were examined using WebGestalt tool. The STRING web resource was employed to develop the PPI network of DEGs, whereas Cytoscape software was employed to perform module analysis. Finally, the mRNA, protein expression along with survival analysis of hub genes were explored via GEPIA, HPA along with Kaplan-Meier plotter web resource, respectively.

RESULTS

Only 82 upregulated and 105 downregulated DEGs were found among the three datasets. Further, GO analysis illustrated that 187 DEGs were primary enriched in extracellular structure organization, tube development along with cell adhesion. The KEGG enrichments showed that these DEGs were primary linked to leukocyte transendothelial migration, vascular smooth muscle contraction along with ECM-receptor interaction. Among the 187 DEGs, the 10 hub genes (P4HB, SPP1, CP, GOLM1, COL1A1, MMP9, COL10A1, APOA1, COL4A6, and TIMP1) were identified. The mRNA along with protein levels of hub genes in LUAD tissues were further verified by Oncomine, UCSC Xena, GEPIA and HPA databases. Additionally, overall survival curves illustrated that LUAD patients with the higher levels of P4HB, SPP1, COL1A1, and MMP9 were dramatically linked to shorter overall survival.

CONCLUSIONS

The current study identified DEGs candidate genes (P4HB, SPP1, COL1A1, and MMP9) and pathways in LUAD using bioinformatics analysis, which could enhance our understanding of pathogenesis along with underlying molecular events in LUAD, and these hub genes and pathways may help provide candidate treatment targets for LUAD.

Identification of prognostic values of the transcription factor-CpG-gene triplets in lung adenocarcinoma: A narrative review

OBJECTIVE

Abnormal DNA methylation can regulate carcinogenesis in lung adenocarcinoma (LUAD), while transcription factors (TFs) mediate methylation in a site-specific manner to affect downstream transcriptional regulation and tumor progression. Therefore, this study aimed to explore the TF-methylation-gene regulatory relationships that influence LUAD prognosis.

METHODS

Differential analyses of methylation sites and genes were generated by integrating transcriptome and methylome profiles from public databases. Through target gene identification, motif enrichment in the promoter region, and TF prediction, TF-methylation and methylation-gene relation pairs were obtained. Then, the prognostic TF-methylation-gene network was constructed using univariate Cox regression analysis. Prognostic models were constructed based on the key regulatory axes. Finally, Kaplan-Meier curves were created to evaluate the model efficacy and the relationship between candidate genes and prognosis.

RESULTS

A total of 1878 differential expressed genes and 1233 differential methylation sites were screened between LUAD and normal samples. Then 10 TFs were predicted to bind 144 enriched motifs. After integrating TF-methylation and methylation-gene relations, a prognostic TF-methylation-gene network containing 4 TFs, 111 methylation sites, and 177 genes was constructed. In this network, ERG-cg27071152-MTURN and FOXM1-cg19212949-PTPR regulatory axes were selected to construct the prognostic models, which showed robust abilities in predicting 1-, 3-, and 5-year survival probabilities. Finally, ERG and MTURN were downregulated in LUAD samples, whereas FOXM1 and PTPR were upregulated. Their expression levels were related to LUAD prognosis.

CONCLUSION

ERG-cg27071152-MTURN and FOXM1-cg19212949-PTPR regulatory axes were proposed as potential biomarkers for predicting the prognosis of LUAD.

Prediction of the Presence of Targetable Molecular Alteration(s) with Clinico-Metabolic 18 F-FDG PET Radiomics in Non-Asian Lung Adenocarcinoma Patients

This study aimed to investigate if combining clinical characteristics with pre-therapeutic 18 F-fluorodeoxyglucose (18 F-FDG) positron emission tomography (PET) radiomics could predict the presence of molecular alteration(s) in key molecular targets in lung adenocarcinoma. This non-interventional monocentric study included patients with newly diagnosed lung adenocarcinoma referred for baseline PET who had tumour molecular analyses. The data were randomly split into training and test datasets. LASSO regression with 100-fold cross-validation was performed, including sex, age, smoking history, AJCC cancer stage and 31 PET variables. In total, 109 patients were analysed, and it was found that 63 (57.8%) patients had at least one molecular alteration. Using the training dataset (n = 87), the model included 10 variables, namely age, sex, smoking history, AJCC stage, excessKustosis_HISTO, sphericity_SHAPE, variance_GLCM, correlation_GLCM, LZE_GLZLM, and GLNU_GLZLM. The ROC analysis for molecular alteration prediction using this model found an AUC equal to 0.866 (p < 0.0001). A cut-off value set to 0.48 led to a sensitivity of 90.6% and a positive likelihood ratio (LR+) value equal to 2.4. After application of this cut-off value in the unseen test dataset of patients (n = 22), the test presented a sensitivity equal to 90.0% and an LR+ value of 1.35. A clinico-metabolic 18 F-FDG PET phenotype allows the detection of key molecular target alterations with high sensitivity and negative predictive value. Hence, it opens the way to the selection of patients for molecular analysis.

Brain metastases: A Society for Neuro-Oncology (SNO) consensus review on current management and future directions

Brain metastases occur commonly in patients with advanced solid malignancies. Yet, less is known about brain metastases than cancer-related entities of similar incidence. Advances in oncologic care have heightened the importance of intracranial management. Here, in this consensus review supported by the Society for Neuro-Oncology (SNO), we review the landscape of brain metastases with particular attention to management approaches and ongoing efforts with potential to shape future paradigms of care. Each coauthor carried an area of expertise within the field of brain metastases and initially composed, edited, or reviewed their specific subsection of interest. After each subsection was accordingly written, multiple drafts of the manuscript were circulated to the entire list of authors for group discussion and feedback. The hope is that the these consensus guidelines will accelerate progress in the understanding and management of patients with brain metastases, and highlight key areas in need of further exploration that will lead to dedicated trials and other research investigations designed to advance the field.

The development and validation of a m6A-lncRNAs based prognostic model for overall survival in lung squamous cell carcinoma

BACKGROUND

No biomarkers have been identified for the prognosis of lung squamous cell carcinoma (LUSC). Risk models based on m6A-lncRNAs help to predict survival in some cancers. However, very few studies have reported m6A-lncRNA risk models in LUSC. We aimed to construct a prognostic model based on m6A-lncRNAs in LUSC.

METHODS

The clinical and RNA-sequencing information of 504 LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Prognostic m6A-lncRNAs were identified by a Pearson correlation analysis and univariate Cox regression analysis. The ConsensusClusterPlus algorithm was used to cluster the prognostic m6A-lncRNAs. The overall survival (OS) and clinicopathological characteristics of the 2 clusters were compared. A gene set enrichment analysis (GSEA) analysis was performed to analyze the genes enriched in the 2 clusters. A least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to construct the risk-score model. Two hundred and forty eight patients were randomly chosen from TCGA-LUSC cohort for the training set. The receiver operating characteristic (ROC) curve analysis was used to assess the predictive ability of the model. The clinical characteristics and OS in the high- and low-risk groups were compared. The independent prognostic value of the model was tested by Cox regression analyses.

RESULTS

Thirteen m6A-lncRNAs were identified as prognostic lncRNAs and classified into cluster A and cluster B. The OS of patients in cluster A was better than that of patients in cluster B (P<0.001). Patients in cluster B had higher expressions of immune checkpoints. Immune score, stromal score, and ESTIMATE score were higher in cluster B (P<0.001). Seven of the 13 lncRNAs were used to construct the risk-score model. Patients in the high-risk group had a worse OS. ROC curves showed a under the curve (AUC) of 0.639 in the training set and 0.624 in the validation set. A high risk was associated with cluster B, a high immune score, and stage III-IV disease. Patients in the high-risk group had increased expressions of immune checkpoints. The Cox regression analyses showed that the risk-score model had independent prognostic value for OS. The risk-score model retained its prognostic value in different subgroups.

CONCLUSIONS

The m6A-lncRNA risk-score model is an independent prognostic factor for OS in LUSC patients. However, the risk-score model need to be further tested clinically.

EGFR Mutations and PD-L1 Expression in Early-Stage Non-Small Cell Lung Cancer: A Real-World Data From a Single Center in Brazil

BACKGROUND

Targeted and immunotherapies are currently moving toward early-stage settings for patients with non-small cell lung cancer (NSCLC). Predictive biomarkers data are scarce in this scenario. We aimed to describe the frequency of EGFR mutations and PD-L1 expression levels in early-stage non-squamous patients with NSCLC from a large, single Brazilian oncology center.

METHODS

We retrospectively evaluated patients with NSCLC diagnosed at an early-stage (IB to IIIA-AJCC seventh edition) at Barretos Cancer Hospital (n = 302). EGFR mutational status was assessed in FFPE tumor tissues using distinct methodologies (NGS, Cobas, or Sanger sequencing). PD-L1 expression was evaluated by immunohistochemistry (clone 22C3) and reported as Tumor Proportion Score (TPS), categorized as <1%, 1-49%, and ≥50%. We evaluated the association between EGFR mutational status and PD-L1 expression with sociodemographic and clinicopathological parameters by Fisher's test, qui-square test, and logistic regression. Survival analysis was assessed by the Kaplan-Meier method and Cox regression model.

RESULTS

EGFR mutations were detected in 17.3% (n = 48) of cases and were associated with female sex, never smokers, and longer overall and event-free survival. PD-L1 positivity was observed in 36.7% (n = 69) of cases [TPS 1-49% n = 44(23.4%); TPS ≥50% n = 25(13.3%)]. PD-L1 positivity was associated with smoking, weight loss, and higher disease stages (IIB/IIIA).

CONCLUSION

The frequencies of EGFR mutations and PD-L1 positivity were described for early-stage non-squamous patients with NSCLC. These results will be essential for guiding treatment strategies with the recent approvals of osimertinib and immunotherapy in the adjuvant setting.

Comprehensive landscape of the ST3GAL family reveals the significance of ST3GAL6-AS1/ST3GAL6 axis on EGFR signaling in lung adenocarcinoma cell invasion

Sialylation aberration has been implicated in lung cancer development by altering signaling pathways. Hence, it is urgent to identify key sialyltransferases in the development of lung adenocarcinoma (LUAD), which is a common malignant subtype of non-small cell lung cancer. Herein, by systematically investigating the expression levels of ST3GAL family members in several public databases, we consistently found the frequent downregulation of ST3GAL6 in LUAD samples. Its downregulation is significantly negatively associated with stage, and significantly reduced in proximal-proliferative molecular subtype and predicts poor clinical outcomes. By protein–protein interaction network analysis and validation, we found that ST3GAL6 deficiency promotes LUAD cell invasiveness with the activated EGFR/MAPK signaling, accompanied by the elevated expression levels of matrix metalloproteinases 2 and 9, which can be partially reversed by EGFR inhibitor, gefitinib. Additionally, the ST3GAL6 level was positively regulated by ST3GAL6-AS1, an antisense long non-coding RNA to its host gene. The downregulation of ST3GAL6-AS1 also heralds a worse prognosis in LUAD patients and promotes LUAD cell invasiveness, recapitulating the function of its host gene, ST3GAL6. Altogether, ST3GAL6-AS1-regulated ST3GAL6 is a frequently downregulated sialyltransferase in LUAD patients and negatively regulates EGFR signaling, which can serve as a promising independent prognostic marker in LUAD patients.

Identification of lactate metabolism-related subtypes and development of a lactate-related prognostic indicator of lung adenocarcinoma

Background: Increasing evidence supports that lactate plays an important role in tumor proliferation, invasion and within the tumor microenvironment (TME). This is particularly relevant in lung adenocarcinoma (LUAD). Therefore, there is a current need to investigate lactate metabolism in LUAD patients and how lactate metabolism is affected by different therapies.

Methods: Data from LUAD patients were collected from The Cancer Genome Atlas (TCGA) and patients were divided into two subtypes according to 12 lactate metabolism-related genes to explore the effect of lactate metabolism in LUAD. We established a lactate-related prognostic indicator (LRPI) based on different gene expression profiles. Subsequently, we investigated associations between this LRPI and patient survival, molecular characteristics and response to therapy. Some analyses were conducted using the Genomics of Drug Sensitivity in Cancer (GDSC) database.

Results: The two LUAD subtypes exhibited different levels of lactate metabolism, in which patients that displayed high lactate metabolism also had a worse prognosis and a poorer immune environment. Indeed, LRPI was shown to accurately predict the prognosis of LUAD patients. Patients with a high LRPI showed a poor prognosis coupled with high sensitivity to chemotherapy using GDSC data. Meanwhile, these patients exhibited a high responsiveness to immunotherapy in TMB (Tumor mutation burden) and TIDE (Tumor Immune Dysfunction and Exclusion) analyses.

Conclusion: We validated the effect of lactate metabolism on the prognosis of LUAD patients and established a promising biomarker. LRPI can predict LUAD patient survival, molecular characteristics and response to therapy, which can aid the individualized treatment of LUAD patients.

Characterization and validation of a ferroptosis-related LncRNA signature as a novel prognostic model for lung adenocarcinoma in tumor microenvironment

Ferroptosis is a more relatively recently identified type of programmed cell death, which is associated with tumor progression. However, the mechanism underlying the effect of ferroptosis-related long non-coding RNAs (lncRNAs) in lung adenocarcinoma (LUAD) remains elusive. Therefore, the current study aimed to investigate the role of ferroptosis-related lncRNAs in LUAD and to develop a prognostic model. The clinicopathological characteristics of patients and the gene sequencing data were obtained from The Cancer Genome Atlas, while the ferroptosis-associated mRNAs were downloaded from the FerrDb database. A ferroptosis-related lncRNA signature was established with Least Absolute Shrinkage and Selection Operator Cox regression analysis. Furthermore, the risk scores of ferroptosis-related lncRNAs were calculated and LUAD patients were then assigned to high- and low-risk groups based on the median risk score. The prognostic model was established by K-M plotters and nomograms. Gene set enrichment analysis (GSEA) was performed to evaluate the association between immune responses and ferroptosis-related lncRNAs. A total of 10 ferroptosis-related lncRNAs were identified as independent predictors of LUAD outcome, namely RP11-386M24.3, LINC00592, FENDRR, AC104699.1, AC091132.1, LANCL1-AS1, LINC-PINT, IFNG-AS1, LINC00968 and AC006129.2. The area under the curve verified that the established signatures could determine LUAD prognosis. The nomogram model was used to assess the predictive accuracy of the established signatures. Additionally, GSEA revealed that the 10 ferroptosis-related lncRNAs could be involved in immune responses in LUAD. Overall, the results of the current study may provide novel insights into the development of novel therapies or diagnostic strategies for LUAD.

Immune Subtypes in LUAD Identify Novel Tumor Microenvironment Profiles With Prognostic and Therapeutic Implications

The six transcriptomic immune subtypes (ISs) (C1 - C6) were reported to have complex and different interplay between TME and cancer cells in TCGA (The Cancer Genome Atlas) pan-cancer cohort. Our study specifically explored how the consequence of interplay determines the prognosis and the response to therapy in LUAD cohorts. Clinical and molecular information of LUAD patients were from TCGA and Gene Expression Omnibus (GEO). The immune cell populations and gene/pathway enrichment analysis were performed to explore the molecular differences among the C3 IS and other ISs in the LUAD population. The proportion of C3 inflammatory IS was identified as the most common IS in both TCGA (N = 457) and GEO (N = 901) cohorts. The C3 IS was also found to be the most accurate prognostic subtype, which was associated with significantly longer OS (p <0.001) and DFS (p <0.001). The C3 IS presented higher levels of CD8 T, M1 macrophage, and myeloid dendritic cells, while lower levels of M2 macrophages and cancer-associated fibroblast cells. Moreover, the C3 subtype was enriched in the antigen process and presenting, interferon-gamma response, T cell receptor signaling, and natural killer cell-mediated cytotoxicity pathways than C1/C2. In contrast, the C1/C2 presented greater activation of pathways related to the cell cycles, DNA repair, and p53 signaling pathways. The immune-related C3 IS had a great ability to stratify the prognosis of LUAD, providing clues for further pathogenic research. This classification might help direct precision medicine screenings of LUAD patients, thus possibly improving their prognoses.

Comprehensive analysis of KCTD family genes associated with hypoxic microenvironment and immune infiltration in lung adenocarcinoma

To obtain novel insights into the tumor biology and therapeutic targets of LUAD, we performed a comprehensive analysis of the KCTD family genes. The expression patterns and clinical significance of the KCTD family were identified through multiple bioinformatics mining. Moreover, the molecular functions and potential mechanisms of differentially expressed KCTDs were evaluated using TIMER 2.0, cBioPortal, GeneMANIA, LinkedOmics and GSEA. The results indicated that the mRNA and protein expression levels of KCTD9, KCTD10, KCTD12, KCTD15 and KCTD16 were significantly decreased in LUAD, while those of KCTD5 were significantly increased. High KCTD5 expression was significantly associated with advanced tumor stage, lymph node metastasis, TP53 mutation and poor prognosis. In addition, KCTD5 was positively correlated with CD8 + T cell, neutrophil, macrophage and dendritic cell infiltration. Additionally, KCTDs demonstrate promising prospects in the diagnosis of LUAD. Importantly, high KCTD5 expression was enriched in signaling pathways associated with the malignant progression of tumors, including the inflammatory response, the IL6/JAK/STAT3 signaling pathway, EMT and hypoxia. Further association analysis showed that KCTD5 was positively correlated with hypoxia-related genes such as HIF1. Overall, KCTDs can be used as molecular targets for the treatment of LUAD, as well as effective molecular biomarkers for diagnosis and prognosis prediction.

Early Steps of Resistance to Targeted Therapies in Non-Small-Cell Lung Cancer

Simple Summary

Patients with lung cancer benefit from more effective treatments, such as targeted therapies, and the overall survival has increased in the past decade. However, the efficacy of targeted therapies is limited due to the emergence of resistance. Growing evidence suggests that resistances may arise from a small population of drug-tolerant persister (DTP) cells. Understanding the mechanisms underlying DTP survival is therefore crucial to develop therapeutic strategies to prevent the development of resistance. Herein, we propose an overview of the current scientific knowledge about the characterisation of DTP, and summarise the new therapeutic strategies that are tested to target these cells.

Abstract

Lung cancer is the leading cause of cancer-related deaths among men and women worldwide. Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are effective therapies for advanced non-small-cell lung cancer (NSCLC) patients harbouring EGFR-activating mutations, but are not curative due to the inevitable emergence of resistances. Recent in vitro studies suggest that resistance to EGFR-TKI may arise from a small population of drug-tolerant persister cells (DTP) through non-genetic reprogramming, by entering a reversible slow-to-non-proliferative state, before developing genetically derived resistances. Deciphering the molecular mechanisms governing the dynamics of the drug-tolerant state is therefore a priority to provide sustainable therapeutic solutions for patients. An increasing number of molecular mechanisms underlying DTP survival are being described, such as chromatin and epigenetic remodelling, the reactivation of anti-apoptotic/survival pathways, metabolic reprogramming, and interactions with their micro-environment. Here, we review and discuss the existing proposed mechanisms involved in the DTP state. We describe their biological features, molecular mechanisms of tolerance, and the therapeutic strategies that are tested to target the DTP.

Economic Analysis of Tissue-First, Plasma-First, and Complementary NGS Approaches for Treatment-Naïve Metastatic Lung Adenocarcinoma

Background

To compare the testing costs and testing turnaround times of tissue-first, plasma-first, and complementary next-generation sequencing (NGS) approaches in patients with treatment-naïve metastatic lung adenocarcinoma.

Materials and Methods

We developed a decision tree model to compare three different approaches. Patients were entered into the model upon cancer diagnosis and those with both insufficient tissue specimens and negative liquid-based NGS were subjected to tissue re-biopsy. Actionable gene alterations with the U.S. Food and Drug Administration (FDA)-approved therapies included epidermal growth factor receptor (EGFR) mutation, anaplastic lymphoma kinase (ALK) gene rearrangement, ROS proto-oncogene 1 (ROS1) rearrangement, B-Raf proto-oncogene (BRAF) V600E mutation, rearranged during transfection (RET) gene rearrangement, mesenchymal-epithelial transition factor (MET) mutation, neurotrophic tyrosine receptor kinase (NTRK) gene rearrangement, K-Ras proto-oncogene (KRAS) G12C mutation, and human epidermal growth factor receptor 2 (HER2) mutation. Model outcomes were testing costs, testing turnaround times, and monetary losses taking both cost and time into consideration. We presented base-case results using probabilistic analysis. Stacked one-way and three-way sensitivity analyses were also performed.

Results

In terms of testing costs, tissue-first approach incurred US$2,354($1,963-$2,779) and was the most cost-efficient strategy. Complementary approach testing turnaround time (days) of 12.7 (10.8 to 14.9) was found as the least time-consuming strategy. Tissue-first, complementary, and plasma-first approaches resulted in monetary losses in USD of $4,745 ($4,010-$5,480), $6,778 ($5,923-$7,600), and $7,006 ($6,047-$7,964) respectively, and identified the same percentage of patients with appropriate FDA-approved therapies. Costs for liquid-based NGS, EGFR mutation rates, and quantity of tissue specimens were the major determinants in minimizing monetary loss. Plasma-first approach would be the preferable strategy if its testing price was reduced in USD to $818, $1,343, and $1,869 for populations with EGFR mutation rates of 30%, 45%, and 60% respectively.

Conclusion

The tissue-first approach is currently the best strategy in minimizing monetary loss. The complementary approach is an alternative for populations with a low EGFR mutation rate. The plasma-first approach becomes increasingly preferable as EGFR mutation rates gradually increase.

Circulating microRNAs as molecular biomarkers for lung adenocarcinoma

BACKGROUND: The potential of microRNAs (miRNAs) as molecular tumor biomarkers for early diagnosis and prognosis in lung cancer is still unclear. OBJECTIVE: To analyze expression of miRNAs in A549 lung adenocarcinoma (LUAD) cells and in primary, non-malignant bronchial epithelial (BE) cells from healthy donors. To analyze the most prominently deregulated miRNAs in plasma samples of LUAD patients and healthy donors. MATERIALS AND METHODS: The expression of 752 miRNAs in LUAD and BE cells was assessed by RT-qPCR with mean-centering restricted normalization. The relative plasma levels of 18 miRNAs in LUAD patients and healthy donors were analyzed using RT-qPCR and normalized to miR-191-5p and miR-16-3p. Putative interactions between miRNAs and their target genes were investigated in silico. RESULTS: Out of 752 miRNAs, 37 miRNAs were significantly deregulated in A549 cells compared to BE cells. MiR-15b-3p, miR-148a-3p, miR-193b-3p, and miR-195-5p were significantly deregulated in plasma samples of LUAD patients compared to donors. The target genes of those four miRNAs are involved in essential mechanisms in cancer development and progression. CONCLUSIONS: There are substantial differences between cancer and control miRNA expression in vitro and in plasma samples of LUAD patients compared to healthy donors. Four deregulated miRNAs are promising as a diagnostic biomarker for adenocarcinoma of the lung.

Economic Analysis of Exclusionary EGFR Test Versus Up-Front NGS for Lung Adenocarcinoma in High EGFR Mutation Prevalence Areas

BACKGROUND

This study sought to determine whether exclusionary EGFR mutation testing followed by next-generation sequencing (NGS) is a cost-efficient and timely strategy in areas with high prevalence rates of EGFR mutation.

METHODS

We developed a decision tree model to compare exclusionary EGFR testing followed by NGS and up-front NGS. Patients entered the model upon diagnosis of metastatic lung adenocarcinoma. Gene alterations with FDA-approved targeted therapies included EGFR, ALK, ROS1, BRAF, RET, MET, NTRK, and KRAS. Model outcomes were testing-related costs; time-to-test results; monetary loss, taking both costs and time into consideration; and percentage of patients who could be treated by FDA-approved therapies. Stacked 1-way and 3-way sensitivity analyses were performed.

RESULTS

Exclusionary EGFR testing incurred testing-related costs of US $1,387 per patient, a savings of US $1,091 compared with the costs of up-front NGS. The time-to-test results for exclusionary EGFR testing and up-front NGS were 13.0 and 13.6 days, respectively. Exclusionary EGFR testing resulted in a savings of US $1,116 in terms of net monetary loss, without a reduction of patients identified with FDA-approved therapies. The EGFR mutation rate and NGS cost had the greatest impact on minimizing monetary loss. Given that the tissue-based NGS turnaround time was shortened to 7 days, up-front NGS testing would become the best strategy if its price could be reduced to US $568 in Taiwan.

CONCLUSIONS

In areas with high prevalence rates of EGFR mutation, exclusionary EGFR testing followed by NGS, rather than up-front NGS, is currently a cost-efficient strategy for metastatic lung adenocarcinoma.

PEAC: An Ultrasensitive and Cost-Effective MRD Detection System in Non-small Cell Lung Cancer Using Plasma Specimen

Circulating tumor DNA (ctDNA), a tumor-derived fraction of cell-free DNA (cfDNA), has emerged as a promising marker in targeted therapy, immunotherapy, and minimal residual disease (MRD) monitoring in postsurgical patients. However, ctDNA level in early-stage cancers and postsurgical patients is very low, which posed many technical challenges to improve the detection rate and sensitivity, especially in the clinical practice of MRD detection. These challenges usually include insufficient DNA input amount, limit of detection (LOD), and high experimental costs. To resolve these challenges, we developed an ultrasensitive ctDNA MRD detection system in this study, namely PErsonalized Analysis of Cancer (PEAC), to simultaneously detect up to 37 mutations, which account for 70–80% non-small cell lung cancer (NSCLC) driver mutations from low plasma sample volume and enables LOD of 0.01% at a single-site level. We demonstrated the high performance achieved by PEAC on both cfDNA reference standards and clinical plasma samples from three NSCLC patient cohorts. For cfDNA reference standards, PEAC achieved a specificity of 99% and a sensitivity of 87% for the mutations at 0.01% allele fraction. In the second cohort, PEAC showed 100% concordance rate between ddPCR and Next-generation sequencing (NGS) among 29 samples. In the third cohort, 22 of 59 patients received EGFR TKI treatment. Among them, three in four patients identified low level actionable gene mutations only by PEAC had partial responses after targeted therapy, demonstrating high ctDNA detection ability of PEAC. Overall, the developed PEAC system can detect the majority of NSCLC driver mutations using 8–10 ml plasma samples, and has the advantages of high detection sensitivity and lower costs compared with the existing technologies such as ddPCR and NGS. These advantages make the PEAC system quite appropriate for ctDNA and MRD detection in early-stage NSCLC and postsurgical recurrence monitoring.

CircMMD_007 promotes oncogenic effects in the progression of lung adenocarcinoma through microRNA-197-3p/protein tyrosine phosphatase non-receptor type 9 axis

Circular RNAs play important roles in cancer biology. In this research, we explored the underlying function and mechanism of cirMMD_007 in lung adenocarcinoma (LC). Clinical lung adenocarcinoma samples were obtained from surgery. Bioinformatic databases were used to predict miRNAs that can potentially target circRNAs and miRNA target genes. hsa_circMMD_007, miR-197-3p, and PTPN9 mRNA expressions were investigated by qRT-PCR. Protein expressions were examined using Western blot. The proliferation abilities were assessed by Cell Counting Kit-8 assays. Wound healing cell migration assay was applied to evaluate cell migration ability. Luciferase reporter assay and rescue experiments were then performed to elucidate the underlying mechanism. We found that the expression of circMMD_007 was abnormally increased in LC. The expression of circMMD_007 was higher in advanced stages. Knockout of circMMD_007 hindered the tumorigenesis of LC in vivo and in vitro. circMMD_007 could negatively regulate the expression of miR-197-3p. PTPN9 behaved to be a molecular target of miR-197-3p. In summary, this research demonstrated that circular RNA circMMD_007 could promote the oncogenic effects in the progression of LC through miR-197-3p/PTPN9 axis.

Computational Analyses of YY1 and Its Target RKIP Reveal Their Diagnostic and Prognostic Roles in Lung Cancer

Simple Summary

Lung cancer (LC) is the tumor with the highest global mortality rate. Novel personalized therapies are currently being tested (e.g., targeted inhibitors, the immune-checkpoint inhibitors), but they cannot yet prevent the very frequent relapse and generalized metastases observed in a large population of LC patients. Currently, there is an urgent need for novel reliable biomarkers for the prognosis and diagnosis of LC. Through the systematic analysis of multiple deposited expression datasets, this report aims to explore the role of the Yin-Yang 1 (YY1) transcription factor and its target the Raf Kinase Inhibitory Protein (RKIP) in LC. The computational analysis suggested the predictive diagnostic and prognostic roles for both YY1 and RKIP stimulating further studies for proving their implication as novel biomarkers, as well as therapeutically druggable targets in LC.

Abstract

Lung cancer (LC) represents a global threat, being the tumor with the highest mortality rate. Despite the introduction of novel therapies (e.g., targeted inhibitors, immune-checkpoint inhibitors), relapses are still very frequent. Accordingly, there is an urgent need for reliable predictive biomarkers and therapeutically druggable targets. Yin-Yang 1 (YY1) is a transcription factor that may work either as an oncogene or a tumor suppressor, depending on the genotype and the phenotype of the tumor. The Raf Kinase Inhibitory Protein (RKIP), is a tumor suppressor and immune enhancer often found downregulated in the majority of the examined cancers. In the present report, the role of both YY1 and RKIP in LC is thoroughly explored through the analysis of several deposited RNA and protein expression datasets. The computational analyses revealed that YY1 negatively regulates RKIP expression in LC, as corroborated by the deposited YY1-ChIP-Seq experiments and validated by their robust negative correlation. Additionally, YY1 expression is significantly higher in LC samples compared to normal matching ones, whereas RKIP expression is lower in LC and high in normal matching tissues. These observed differences, unlike many current biomarkers, bear a diagnostic significance, as proven by the ROC analyses. Finally, the survival data support the notion that both YY1 and RKIP might represent strong prognostic biomarkers. Overall, the reported findings indicate that YY1 and RKIP expression levels may play a role in LC as potential biomarkers and therapeutic targets. However, further studies will be necessary to validate the in silico results.

Identification of a Four-Gene Signature Associated with the Prognosis Prediction of Lung Adenocarcinoma Based on Integrated Bioinformatics Analysis

Lung adenocarcinoma (LUAD) is often diagnosed at an advanced stage, so it is necessary to identify potential biomarkers for the early diagnosis and prognosis of LUAD. In our study, a gene co-expression network was constructed using weighted gene co-expression network analysis (WGCNA) in order to obtain the key modules and genes correlated with LUAD prognosis. Four hub genes (HLF, CHRDL1, SELENBP1, and TMEM163) were screened out using least absolute shrinkage and selection operator (LASSO)–Cox regression analysis; then, a prognostic model was established for predicting overall survival (OS) based on these four hub genes..Furthermore, the prognostic values of this four-gene signature were verified in four validation sets (GSE26939, GSE31210, GSE72094, and TCGA-LUAD) as well as in the GEPIA database. To assess the prognostic values of hub genes, receiver operating characteristic (ROC) curves were constructed and a nomogram was created. We found that a higher expression of four hub genes was associated with a lower risk of patient death. In a training set, it was demonstrated that this four-gene signature was a better prognostic factor than clinical factors such as age and stage of disease. Moreover, our results revealed that these four genes were suppressor factors of LUAD and that their high expression was associated with a lower risk of death. In summary, we demonstrated that this four-gene signature could be a potential prognostic factor for LUAD patients. These findings provide a theoretical basis for exploring potential biomarkers for LUAD prognosis prediction in the future.

Identification and Validation of a Novel Six-lncRNA-Based Prognostic Model for Lung Adenocarcinoma

Objective

This study was conducted in order to establish a long non-coding RNA (lncRNA)-based model for predicting overall survival (OS) in patients with lung adenocarcinoma (LUAD).

Methods

Original RNA-seq data of LUAD samples were extracted from The Cancer Genome Atlas (TCGA) database. Univariate Cox survival analysis was performed to select lncRNAs associated with OS. The least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox analysis were performed for building an OS-associated lncRNA prognostic model. Moreover, receiver operating characteristic (ROC) curves were generated to assess predictive values of the hub lncRNAs. Consequently, qRT-PCR was conducted to validate its prognostic value. The potential roles of these lncRNAs in immunotherapy and anti-angiogenic therapy were also investigated.

Results

The lncRNA-associated risk score of OS (LARSO) was established based on the LASSO coefficient of six individual lncRNAs, including CTD-2124B20.2, CTD-2168K21.1, DEPDC1-AS1, RP1-290I10.3, RP11-454K7.3, and RP11-95M5.1. Kaplan–Meier analysis revealed that LUAD patients with higher LARSO values had a shorter OS. Furthermore, a new risk score (NRS), including LARSO, stage, and N stage, could better predict the prognosis of LUAD patients compared with LARSO alone. Evaluation of the prognostic model in our cohort demonstrated that patients with higher scores had a worse prognosis. In addition, correlation analysis between these six lncRNAs and immune checkpoints or anti-angiogenic targets suggested that LUAD patients with high LARSO might not be sensitive to immunotherapy or anti-angiogenic therapy.

Conclusions

This robust six-lncRNA prognostic signature may be used as a novel and powerful prognostic biomarker for lung adenocarcinoma.

Identification of a Six-Gene SLC Family Signature With Prognostic Value in Patients With Lung Adenocarcinoma

Given the importance of solute carrier (SLC) proteins in maintaining cellular metabolic homeostasis and that their dysregulation contributes to cancer progression, here we constructed a robust SLC family signature for lung adenocarcinoma (LUAD) patient stratification. Transcriptomic profiles and relevant clinical information of LUAD patients were downloaded from the TCGA and GEO databases. SLC family genes differentially expressed between LUAD tissues and adjacent normal tissues were identified using limma in R. Of these, prognosis-related SLC family genes were further screened out and used to construct a novel SLC family-based signature in the training cohort. The accuracy of the prognostic signature was assessed in the testing cohort, the entire cohort, and the external GSE72094 cohort. Correlations between the prognostic signature and the tumor immune microenvironment and immune cell infiltrates were further explored. We found that seventy percent of SLC family genes (279/397) were differentially expressed between LUAC tissues and adjacent normal. Twenty-six genes with p-values < 0.05 in univariate Cox regression analysis and Kaplan-Meier survival analysis were regarded as prognosis-related SLC family genes, six of which were used to construct a prognostic signature for patient classification into high- and low-risk groups. Kaplan-Meier survival analysis in all internal and external cohorts revealed a better overall survival for patients in the low-risk group than those in the high-risk group. Univariate and multivariate Cox regression analyses indicated that the derived risk score was an independent prognostic factor for LUAD patients. Moreover, a nomogram based on the six-gene signature and clinicopathological factors was developed for clinical application. High-risk patients had lower stromal, immune, and ESTIMATE scores and higher tumor purities than those in the low-risk group. The proportions of infiltrating naive CD4 T cells, activated memory CD4 T cells, M0 macrophages, resting dendritic cells, resting mast cells, activated mast cells, and eosinophils were significantly different between the high- and low-risk prognostic groups. In all, the six-gene SLC family signature is of satisfactory accuracy and generalizability for predicting overall survival in patients with LUAD. Furthermore, this prognostics signature is related to tumor immune status and distinct immune cell infiltrates in the tumor microenvironment.

A promising prognostic signature for lung adenocarcinoma (LUAD) patients basing on 6 hypoxia-related genes

BACKGROUND

Hypoxia signaling plays a critical role in the development of lung adenocarcinoma (LUAD). We herein aimed to explore the prognostic value of hypoxia-related genes and construct the hypoxia-related prognostic signature for LUAD patients.

METHODS

A total of 26 hypoxia-related genes were collected. Five hundred thirteen and 246 LUAD samples were obtained from the Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. Univariate Cox regression and LASSO Cox regression analyses were conducted to screen the hypoxia-related genes associated with the prognosis of LUAD patients, which would be used for constructing prognosis predictive model for LUAD patients. Multivariate Cox regression analysis was done to determine the independent prognostic factors. The Nomogram model was constructed to predict the prognosis of LUAD patients.

RESULTS

Based on 26 hypoxia-related genes, LUAD samples could be divided into 4 clusters with different prognoses. Among which, 6 genes were included to construct the Risk Score and the LUAD patients with higher Risk Score had worse prognosis. Besides, the Nomogram based on all the independent risk factors could relatively reliably predict the survival probability. And 9 types of immune cells' infiltration was significantly differential between high and low risk LUAD patients.

CONCLUSION

The Risk Score model based on the 6 crucial hypoxia-related genes could relatively reliably predict the prognosis of LUAD patients.

p.G12C KRAS mutation prevalence in non-small cell lung cancer: Contribution from interregional variability and population substructures among Hispanics

•

The identification of the KRAS G12C mutation in non-small cell lung cancer is relevant with new molecules being introduced for treatment.

•

The variation of mutation prevalence among different regions indicate that certain populations are more prone to develop KRAS G12C mutations among lung cancer than others.

•

Using genomic markers traditionally employed for the identification of individuals we managed to construct a model that was predictive for KRAS G12C mutational incidence, further indicating that appearance of KRAS G12C follows population substructures.

Background

The KRAS exon 2 p. G12C mutation in patients with lung adenocarcinoma has been increasing in relevance due to the development and effectiveness of new treatment medications. Studies around different populations indicate that regional variability between ethnic groups and ancestries could play an essential role in developing this molecular alteration within lung cancer.

Methods

In a prospective and retrospective cohort study on samples from lung adenocarcinoma from 1000 patients from different administrative regions in Colombia were tested for the KRAS p.G12C mutation. An analysis of STR populations markers was conducted to identify substructure contributions to mutation prevalence.

Results

Included were 979 patients with a national mean frequency for the KRAS exon 2 p.G12C mutation of 7.97% (95%CI 6.27–9.66%). Variation between regions was also identified with Antioquia reaching a positivity value of 12.7% (95%CI 9.1–16.3%) in contrast to other regions such as Bogota DC (Capital region) with 5.4% (2.7–8.2%) and Bolivar with 2.4% (95%CI 0–7.2%) (p-value = 0.00262). Furthermore, Short tandem repeat population substructures were found for eight markers that strongly yielded association with KRAS exon 2 p.G12C frequency reaching an adjusted R2 of 0.945 and a p-value of < 0.0001.

Conclusions

Widespread identification of KRAS exon 2 p.G12C mutations, especially in cases where NGS is not easily achieved is feasible at a population based level that can characterize regional and national patterns of mutation status. Furthermore, this type of mutation prevalence follows a population substructure pattern that can be easily determined by population and ancestral markers such as STR.

A narrative review of mechanisms of ferroptosis in cancer: new challenges and opportunities

Objective

This article reviews the specific mechanism of ferroptosis in cancer and introduces in detail the opportunities and challenges of ferroptosis-based cancer therapy, aiming to provide a new research direction for tumor therapy.

Background

Ferroptosis is a newly discovered programmed non-apoptotic form of cell death. Involving changes in metabolic processes and the accumulation of peroxidation caused by factors such as drugs or genes which destruct the cell membrane structure, this kind of cell death has been linked with the pathological process of diseases such as tumors, neurological diseases, ischemia-reperfusion injury, kidney injury, and hemopathy. This kind of cell death can play a vital role in inhibiting tumorigenesis by eliminating the adaptive characteristics of malignant cells and removing cells that are unable to obtain key nutritional factors or are infected and damaged by environmental changes. The present focus of research on the regulation of ferroptosis-related diseases involves the use of small molecule compounds.

Methods

We described the mechanism of ferroptosis and its related small molecules compounds, which involved in the regulatory mechanism, and analyzed the role and regulatory mechanism of ferroptosis in different tumors.

Conclusions

This article reviewed the mechanism of ferroptosis and its role and mechanism in different tumors, and showed it can inhibit the occurrence and development of different tumors and may reduce the adverse effects of current treatment methods.