Genome-wide identification of transcription factors that are critical to non-small cell lung cancer

Integration of single-cell sequencing and mendelian randomization reveals novel causal pathways between monocytes and hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) represents one of the most prevalent malignant neoplasms worldwide, characterized by poor prognosis and low 5-year survival rates. Despite extensive research, its pathogenesis remains largely unclear. Within the tumor microenvironment (TME), monocytes play a dual role: they participate in tumor cell recognition and elimination while regulating immune responses through cytokine secretion. This study aims to investigate the association between differentially expressed genes in monocytes and HCC development.

METHODS

This investigation employed single-cell transcriptomic analysis of human hepatic innate lymphoid cells (ILCs) to identify monocyte subpopulations and their cellular markers. Subsequently, two-sample Mendelian randomization (MR) analysis was conducted to examine the causal relationships between these cells, their associated genes, and HCC development.

RESULTS

Through comprehensive analysis of the monocyte cluster, we identified 2338 differentially expressed genes (DEGs). MR analysis revealed 13 genes significantly associated with HCC risk: CONCLUSION: This study represents the first integration of single-cell sequencing technology with MR analysis to investigate the relationship between monocytes and HCC. Through this innovative methodological approach, we have revealed potential associations between monocyte gene expression and HCC development, providing new directions for further research on HCC prevention and treatment, as well as identifying potential therapeutic targets.

The NR3C2-SIRT1 signaling axis promotes autophagy and inhibits epithelial mesenchymal transition in colorectal cancer

Colorectal cancer (CRC) is one of the most aggressive and lethal cancers with a complex pathogenesis, there is an urgent need to find new drug therapeutic targets. This study highlights the important role of the NR3C2-SIRT1 signaling axis in the metastasis mechanism of CRC. Our findings revealed that the expression of NR3C2 in CRC tissues was lower than that in adjacent non-cancerous tissues, and was negatively correlated with N stage by bioanalysis, IHC, western blot and qRT-PCR. NR3C2 overexpression / knockdown can significantly inhibit / promote the migration and invasion of CRC cells, at the same time inhibit / promote EMT. Mechanically, the regulatory molecule SIRT1 was identified by RNA-seq, bioinformatics analysis, western blot and ChIP. SIRT1 was also involved in the metastasis process of CRC, and NR3C2 was found to regulate the expression of LC3B and SQSTM1/p62 in a SIRT1-dependent manner. Therefore, NR3C2 forms a signaling axis with SIRT1, which can directly promote autophagy and inhibit EMT process in vivo and in vitro. Collectively, our findings suggest that NR3C2 - SIRT1 signal axis promote autophagy and inhibit EMT, ultimately inhibits lung metastasis of CRC.

Aloin blocks the malignant behavior of lung squamous cell carcinoma cells and M2 macrophage polarization by modulating the NR3C2/MT1M axis

OBJECTIVE

Aloin, the main active component in Aloe vera (L.) Burm. f., has shown promising anti-tumor effects. This study investigated the impact of aloin in lung squamous cell carcinoma (LUSC) and explored its functional mechanism.

METHODS

We analyzed the viability, migration, invasion, proliferation, and apoptosis of two LUSC cell lines after treatment with aloin. Target molecules of aloin and downstream target transcripts of nuclear receptor subfamily 3 group C member 2 (NR3C2) were predicted by bioinformatics. The biological functions of NR3C2 and metallothionein 1 M (MT1M) in the malignant properties of LUSC cells were determined. A co-culture system of LUSC cells with monocyte-derived macrophages was constructed. Mouse xenograft tumor models were generated to analyze the functions of aloin and NR3C2 in the tumorigenic activity of LUSC cells and macrophage polarization in vivo.

RESULTS

Aloin suppressed malignant properties of LUSC cells in vitro. However, these effects were negated by the silencing of NR3C2. NR3C2 was found to activate MT1M transcription by binding to its promoter. Additional upregulation of MT1M suppressed the malignant behavior of LUSC cells augmented by NR3C2 silencing. Analysis of the M1 and M2 markers/cytokines in the macrophages or the culture supernatant revealed that aloin treatment or MT1M overexpression in LUSC cells enhanced M1 polarization while suppressing M2 polarization of macrophages, whereas NR3C2 silencing led to reverse trends. Consistent findings were reproduced in vivo.

CONCLUSION

This study demonstrated that aloin activates the NR3C2/MT1M axis to suppress the malignant behavior of LUSC cells and M2 macrophage polarization. Please cite this article as: Chen YN, Lu JY, Gao CF, Fang ZR, Zhou Y. Aloin blocks the malignant behavior of lung squamous cell carcinoma cells and M2 macrophage polarization by modulating the NR3C2/MT1M axis. J Integr Med. 2025; 23(2): 195-208.

Chromatin Remodulator CHD4: A Potential Target for Cancer Interception

Cancer initiation and progression are associated with numerous somatic mutations, genomic rearrangements, and structure variants. The transformation of a normal cell into a cancer cell involves spatio-temporal changes in the regulation of different gene networks. The accessibility of these genes within the cell nucleus is manipulated via nucleosome remodeling ATPases, comprising one of the important mechanisms. Here, we reviewed studies of an ATP-dependent chromatin remodulator, chromodomain helicase DNA-binding 4 (CHD4), in cancer. Multiple domains of CHD4 are known to take part in nucleosome mobilization and histone binding. By binding with other proteins, CHD4 plays a vital role in transcriptional reprogramming and functions as a key component of Nucleosome Remodeling and Deacetylase, or NuRD, complexes. Here, we revisit data that demonstrate the role of CHD4 in cancer progression, tumor cell proliferation, DNA damage responses, and immune modulation. Conclusively, CHD4-mediated chromatin accessibility is essential for transcriptional reprogramming, which in turn is associated with tumor cell proliferation and cancer development.

The differential expression of AFF3 in cervical cancer and its correlation with clinicopathological features and prognosis

BACKGROUND

Cervical cancer (CC) is the second most common malignancy in women, and identifying biomarkers of CC is crucial for prognosis prediction. Here, we investigated the expression of AF4/FMR2 Family Member 3 (AFF3) in CC and its association with clinicopathological features and prognosis.

METHODS

Tumour and adjacent tissues, along with clinicopathological features and follow-up information, were collected from 78 patients. AFF3 expression was assessed using quantitative real-time polymerase chain reaction and Western blotting. The correlation between AFF3 expression and CC symptoms was using chi-square test. The 5-year overall survival (OS) was analysed using the Kaplan-Meier method. The Univariate analysis of prognostic risk factors was conducted using the COX proportional hazards model, followed by multivariate COX regression analysis including variables with p < 0.01.

RESULTS

AFF3 expression was downregulated in CC, and its levels were correlated with lymph node metastasis (LNM) and International Federation of Gynaecology and Obstetrics (FIGO) stage. Patients with low AFF3 expression had a lower 5-year OS rate (52.78%, 19/36). Postoperative survival was reduced in patients with histological grade 3 (G3), myometrial invasion (depth ≥ 1/2), lymphovascular space invasion, LNM, and advanced FIGO stage. Low expression of AFF3 (HR: 2.848, 95% CI: 1.144-7.090) and histological grade G3 (HR: 4.393, 95% CI: 1.663-11.607) were identified as independent prognostic risk factors in CC patients.

CONCLUSION

Low expression of AFF3 and histological G3 are independent predictors of poor prognosis in CC patients, suggesting that AFF3 could serve as a potential biomarker for prognostic assessment in CC.

Unravelling the function of prdm16 in human tumours: A comparative analysis of haematologic and solid tumours

Extensive research has shown that PR domain 16 (PRDM16) plays a critical role in adipose tissue metabolism, including processes such as browning and thermogenesis of adipocytes, beigeing of adipocytes, and adipogenic differentiation of myoblasts. These functions have been associated with diseases such as obesity and diabetes. Additionally, PRDM16 has been correlated with various other conditions, including migraines, heterochromatin abnormalities, metabolic syndrome, cardiomyopathy, sarcopenia, nonsyndromic cleft lip, and essential hypertension, among others. However, there is currently no systematic or comprehensive conclusion regarding the mechanism of PRDM16 in human tumours, including haematologic and solid tumours. The aim of this review is to provide an overview of the research progress on PRDM16 in haematologic and solid tumours by incorporating recent literature findings. Furthermore, we explore the prospects of PRDM16 in the precise diagnosis and treatment of human haematologic and solid tumours.

Identification of NR3C2 as a functional diagnostic and prognostic biomarker and potential therapeutic target in non-small cell lung cancer

Background

Non-small cell lung cancer (NSCLC), including the lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) subtypes, is a malignant tumor type with a poor 5-year survival rate. The identification of new powerful diagnostic biomarkers, prognostic biomarkers, and potential therapeutic targets in NSCLC is urgently required.

Methods

The UCSC Xena, UALCAN, and GEO databases were used to screen and analyze differentially expressed genes, regulatory modes, and genetic/epigenetic alterations in NSCLC. The UCSC Xena database, GEO database, tissue microarray, and immunohistochemistry staining analyses were used to evaluate the diagnostic and prognostic values. Gain-of-function assays were performed to examine the roles. The ESTIMATE, TIMER, Linked Omics, STRING, and DAVID algorithms were used to analyze potential molecular mechanisms.

Results

NR3C2 was identified as a potentially important molecule in NSCLC. NR3C2 is expressed at low levels in NSCLC, LUAD, and LUSC tissues, which is significantly related to the clinical indexes of these patients. Receiver operating characteristic curve analysis suggests that the altered NR3C2 expression patterns have diagnostic value in NSCLC, LUAD, and especially LUSC patients. Decreased NR3C2 expression levels can help predict poor prognosis in NSCLC and LUAD patients but not in LUSC patients. These results have been confirmed both with database analysis and real-world clinical samples on a tissue microarray. Copy number variation contributes to low NR3C2 expression levels in NSCLC and LUAD, while promoter DNA methylation is involved in its downregulation in LUSC. Two NR3C2 promoter methylation sites have high sensitivity and specificity for LUSC diagnosis with clinical application potential. NR3C2 may be a key participant in NSCLC development and progression and is closely associated with the tumor microenvironment and immune cell infiltration. NR3C2 co-expressed genes are involved in many cancer-related signaling pathways, further supporting a potentially significant role of NR3C2 in NSCLC.

Conclusions

NR3C2 is a novel potential diagnostic and prognostic biomarker and therapeutic target in NSCLC.

IRX5's influence on macrophage polarization and outcome in papillary thyroid cancer

Background

With a rise in recent years, thyroid cancer (TC) is the most prevalent hormonal cancer worldwide. It is essential to investigate the inherent variability at the molecular level and the immune environment within tumors of various thyroid cancer subtypes in order to identify potential targets for therapy and provide precise treatment for patients with thyroid adenocarcinoma.

Methods

First, we analyzed the expression of IRX5 in pan-cancer and papillary thyroid carcinoma by bioinformatics methods and collected paired samples from our center for validation. Subsequently, we analyzed the significance of IRX5 on the prognosis and diagnosis of PTC. Next, we explored the possible mechanisms by which IRX5 affects the prognosis of thyroid cancer patients by GO/KEGG enrichment analysis, and further investigated the effect of IRX5 on immune infiltration of thyroid cancer. Ultimately, by conducting experiments on cells and animals, we were able to show how IRX5 impacts the aggressive characteristics of thyroid cancer cells and its influence on macrophages within the immune system of thyroid cancer.

Results

In 11 malignant tumors, including PTC, IRX5 is overexpressed and associated with a poor prognosis. IRX5 may affect the prognosis of PTC through embryonic organ development, ossification, mesenchyme development, etc. Increased IRX5 expression decreases the presence of cytotoxic and Th17 cells in papillary thyroid cancer. IRX5 was highly expressed in different PTC cell lines, such as K-1 and TPC-1. Silencing IRX5 effectively halted the growth and movement of PTC cells while also decreasing M2 polarization and enhancing M1 polarization in tumor-associated macrophages.

Conclusion

IRX5 could impact the outlook of individuals with PTC by stimulating the shift of macrophages to M2 in the immune surroundings of thyroid cancer growths, suggesting a potential new focus for treating thyroid cancer, particularly through immunotherapy.

Identification of molecular subtypes and a prognostic signature based on m6A/m5C/m1A-related genes in lung adenocarcinoma

Lung cancer, specifically the histological subtype lung adenocarcinoma (LUAD), has the highest global occurrence and fatality rate. Extensive research has indicated that RNA alterations encompassing m6A, m5C, and m1A contribute actively to tumorigenesis, drug resistance, and immunotherapy responses in LUAD. Nevertheless, the absence of a dependable predictive model based on m6A/m5C/m1A-associated genes hinders accurately predicting the prognosis of patients diagnosed with LUAD. In this study, we collected patient data from The Cancer Genome Atlas (TCGA) and identified genes related to m6A/m5C/m1A modifications using the GeneCards database. The "ConsensusClusterPlus" R package was used to produce molecular subtypes by utilizing genes relevant to m6A/m5C/m1A identified through differential expression and univariate Cox analyses. An independent prognostic factor was identified by constructing a prognostic signature comprising six genes (SNHG12, PABPC1, IGF2BP1, FOXM1, CBFA2T3, and CASC8). Poor overall survival and elevated expression of human leukocyte antigens and immune checkpoints were correlated with higher risk scores. We examined the associations between the sets of genes regulated by m6A/m5C/m1A and the risk model, as well as the immune cell infiltration, using algorithms such as ESTIMATE, CIBERSORT, TIMER, ssGSEA, and exclusion (TIDE). Moreover, we compared tumor stemness indices (TSIs) by considering the molecular subtypes related to m6A/m5C/m1A and risk signatures. Analyses were performed based on the risk signature, including stratification, somatic mutation analysis, nomogram construction, chemotherapeutic response prediction, and small-molecule drug prediction. In summary, we developed a prognostic signature consisting of six genes that have the potential for prognostication in patients with LUAD and the design of personalized treatments that could provide new versions of personalized management for these patients.

Engrailed 2 serves as a master regulator of the super-enhancer in the TNC gene locus in non-small cell lung cancer

Engrailed 2 (EN2) is a homeodomain-containing protein that is dysregulated in many types of cancer. However, the role of EN2 in non-small cell lung cancer (NSCLC) and the mechanism underlying its biological function are largely unclear. Here, we showed that EN2 played an oncogenic function in NSCLC and greatly enhanced the malignant phenotype of NSCLC cells. Meanwhile, EN2 was able to boost the expression of a well-studied oncogenic Tenascin-C (TNC) gene, which in turn activated the AKT signaling pathway. Interestingly, we found that EN2 directly bound to the super-enhancer (SE) region in the TNC locus. The histone marker H3K27ac was also enriched in the region, indicating the activation of the SE. Treatment of the cells with JQ1, an inhibitor of SE activity, abrogated the effect of EN2 on the expression of TNC and phosphorylation of AKT-Ser473. Collectively, our work unveils a novel mode of EN2 function, in which EN2 governs the SE in the TNC locus, consequently activating the oncogenic TNC-AKT axis in NSCLC.

BARX1 repressed FOXF1 expression and activated Wnt/β-catenin signaling pathway to drive lung adenocarcinoma

BACKGROUND

Underlying molecular mechanisms of BARX homeobox 1 (BARX1) in lung adenocarcinoma (LUAD) remain elusive.

METHODS

Abnormally expressed genes in LUAD tissues were analyzed by RNA-sequencing. CCK-8, colony formation, transwell, and wound healing assays examined proliferation, colony formation, invasion, and migration of LUAD cells, respectively. Electrophoretic mobility shift assay and chromatin immunoprecipitation assay examined the interaction between BARX1 and Forkhead Box F1 (FOXF1). Xenograft mouse model of LUAD was constructed to monitor the growth and metastasis of tumor.

RESULTS

BARX1 was upregulated, FOXF1 was downregulated in LUAD tissues and cells. There was a negative correlation between BARX1 and FOXF1 expression. BARX1 deficiency limited malignant phenotypes of LUAD cells, including proliferation, invasion, migration and EMT. In vivo, BARX1 knockdown suppressed tumor growth and metastasis in A549-drove xenograft mouse model. BARX1 interacted with FOXF1 promoter and repressed FOXF1 expression. Upregulation of BARX1 promoted the expression of Wnt5a, β-catenin, and phosphorylated-glycogen synthase kinase-3 beta (p-GSK3β), whereas inhibited FOXF1, p-β-catenin, and GSK3β in LUAD cells. BARX1 knockdown caused an opposite result. Rescue assays uncovered that FOXF1 reversed the impact of BARX1 on malignant phenotypes and Wnt/β-catenin of LUAD cells.

CONCLUSION

BARX1 repressed FOXF1 expression and activated Wnt/β-catenin signaling pathway to drive lung adenocarcinoma.

Dynamics and recognition of homeodomain containing protein-DNA complex of IRX4

Iroquois Homeobox 4 (IRX4) belongs to a family of homeobox TFs having roles in embryogenesis, cell specification, and organ development. Recently, large scale genome-wide association studies and epigenetic studies have highlighted the role of IRX4 and its associated variants in prostate cancer. No studies have investigated and characterized the structural aspect of the IRX4 homeodomain and its potential to bind to DNA. The current study uses sequence analysis, homology modeling, and molecular dynamics simulations to explore IRX4 homeodomain-DNA recognition mechanisms and the role of somatic mutations affecting these interactions. Using publicly available databases, gene expression of IRX4 was found in different tissues, including prostate, heart, skin, vagina, and the protein expression was found in cancer cell lines (HCT166, HEK293), B cells, ascitic fluid, and brain. Sequence conservation of the homeodomain shed light on the importance of N- and C-terminal residues involved in DNA binding. The specificity of IRX4 homodimer bound to consensus human DNA sequence was confirmed by molecular dynamics simulations, representing the role of conserved amino acids including R145, A194, N195, S190, R198, and R199 in binding to DNA. Additional N-terminal residues like T144 and G143 were also found to have specific interactions highlighting the importance of N-terminus of the homeodomain in DNA recognition. Additionally, the effects of somatic mutations, including the conserved Arginine (R145, R198, and R199) residues on DNA binding elucidated the importance of these residues in stabilizing the protein-DNA complex. Secondary structure and hydrogen bonding analysis showed the roles of specific residues (R145, T191, A194, N195, R198, and R199) in maintaining the homogeneity of the structure and its interaction with DNA. The differences in relative binding free energies of all the mutants shed light on the structural modularity of this protein and the dynamics behind protein-DNA interaction. We also have predicted that the C-terminal sequence of the IRX4 homeodomain could act as a potential cell-penetrating peptide, emphasizing the role these small peptides could play in targeting homeobox TFs.

ZFP36 loss-mediated BARX1 stabilization promotes malignant phenotypes by transactivating master oncogenes in NSCLC

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, with high morbidity and mortality worldwide. Although the dysregulation of BARX1 expression has been shown to be associated with malignant cancers, including NSCLC, the underlying mechanism remains elusive. In this study, we identified BARX1 as a common differentially expressed gene in lung squamous cell carcinoma and adenocarcinoma. Importantly, we uncovered a novel mechanism behind the regulation of BARX1, in which ZFP36 interacted with 3'UTR of BARX1 mRNA to mediate its destabilization. Loss of ZFP36 led to the upregulation of BARX1, which further promoted the proliferation, migration and invasion of NSCLC cells. In addition, the knockdown of BARX1 inhibited tumorigenicity in mouse xenograft. We demonstrated that BARX1 promoted the malignant phenotypes by transactivating a set of master oncogenes involved in the cell cycle, DNA synthesis and metastasis. Overall, our study provides insights into the mechanism of BARX1 actions in NSCLC and aids a better understanding of NSCLC pathogenesis.

A transformable nanoplatform with multiple therapeutic and immunostimulatory properties for treatment of advanced cancers

Cancer is a complex pathological phenomenon that needs to be treated from different aspects. Herein, we developed a size/charge dually transformable nanoplatform (PDR NP) with multiple therapeutic and immunostimulatory properties to effectively treat advanced cancers. The PDR NPs exhibit three different therapeutic modalities (chemotherapy, phototherapy and immunotherapy) that can be used to effectively treat primary and distant tumors, and reduce recurrent tumors; the immunotherapy is simultaneously activated by three major pathways, including toll-like receptor, stimulator of interferon genes and immunogenic cell death, effectively suppresses the tumor development in combination with an immune checkpoint inhibitor. In addition, PDR NPs show size and charge responsive transformability in the tumor microenvironment, which overcomes various biological barriers and efficiently delivers the payloads into tumor cells. Taking these unique characteristics together, PDR NPs effectively ablate primary tumors, activate strong anti-tumor immunity to suppress distant tumors and reduce tumor recurrence in bladder tumor-bearing mice. Our versatile nanoplatform shows great potential for multimodal treatments against metastatic cancers.

IRX5 promotes DNA damage repair and activation of hair follicle stem cells

The molecular mechanisms allowing hair follicles to periodically activate their stem cells (HFSCs) are incompletely characterized. Here, we identify the transcription factor IRX5 as a promoter of HFSC activation. Irx5-/- mice have delayed anagen onset, with increased DNA damage and diminished HFSC proliferation. Open chromatin regions form near cell cycle progression and DNA damage repair genes in Irx5-/- HFSCs. DNA damage repair factor BRCA1 is an IRX5 downstream target. Inhibition of FGF kinase signaling partially rescues the anagen delay in Irx5-/- mice, suggesting that the Irx5-/- HFSC quiescent phenotype is partly due to failure to suppress Fgf18 expression. Interfollicular epidermal stem cells also show decreased proliferation and increased DNA damage in Irx5-/-mice. Consistent with a role for IRX5 as a promoter of DNA damage repair, we find that IRX genes are upregulated in many cancer types and that there is a correlation between IRX5 and BRCA1 expression in breast cancer.

PRDM16, Negatively Regulated by miR-372-3p, Suppresses Cell Proliferation and Invasion in Prostate Cancer

Prostate cancer (PCa) is one of the most prevalent malignant tumors. The alternation of microRNA (miRNA) expression is associated with prostate cancer progression, whereas its way to influence progression of prostate cancer remains elusive. The expression levels of PRDM16 mRNA and miR-372-3p in PCa cell lines were analyzed using qRT-PCR. The protein expression of PRDM16 in PCa cell lines was also analyzed using western blot. CCK-8, wound healing, and Transwell assays were applied to examine cell proliferation, migration, and invasion in prostate cancer cells, respectively. Dual-luciferase reporter assay was utilized to validate the interaction between miR-372-3p and PRDM16. In the present study, markedly decreased PRDM16 mRNA and protein expression levels were observed in prostate cancer cells. PRDM16 overexpression hampered cellular proliferation, migration, and invasion, while silencing PRDM16 had the opposite effect. Moreover, miR-372-3p could target the regulation expression of PRDM16. Rescue experiments demonstrated that upregulating miR-372-3p conspicuously restored the inhibitory effect of increased PRDM16 on cell proliferation, migration, and invasion in PCa. Overall, our study clarifies the biological role of miR-372-3p/PRDM16 axis in prostate cancer progression, which may be effective biomarkers for clinical treatment of prostate cancer.

BARX1 promotes osteosarcoma cell proliferation and invasion by regulating HSPA6 expression

Osteosarcoma (OS) is a bone tumour affecting adolescents. Dysregulation of Barx homeobox 1 (BARX1) expression is involved in various cancers, but its function and mechanism in the process of OS are undefined. This study revealed that BARX1 expression is higher in OS tissue than in adjacent normal tissue. Downregulation of BARX1 in OS cells significantly suppressed their proliferation and migration, whereas enforced expression of exogenous BARX1 exerted the opposite effects on OS cells. Subsequently, heat shock 70-kDa protein 6 (HSPA6) expression was clearly increased after BARX1 overexpression in OS cells, as confirmed by RNA sequencing. The dual-luciferase reporter assay confirmed that HSPA6 expression is directly regulated by BARX1. The in vitro assay indicated that silencing HSPA6 expression attenuated OS proliferation and migration induced by BARX1. A dual immunofluorescence labelling assay provided further evidence that BARX1 was overexpressed and associated with HSPA6 overexpression in OS tumour tissue. In conclusion, BARX1 promotes OS cell proliferation and migration by inducing the expression of HSPA6, which plays an oncogenic role in OS. BARX1 and HSPA6 can potentially act as novel therapeutic targets for OS.

Differentiation-related genes in tumor-associated macrophages as potential prognostic biomarkers in non-small cell lung cancer

Background

The purpose of this study was to evaluate the role of differentiation-related genes (DRGs) in tumor-associated macrophages (TAMs) in non-small cell lung cancer (NSCLC).

Methods

Single cell RNA-seq (scRNA-seq) data from GEO and bulk RNA-seq data from TCGA were analyzed to identify DRGs using trajectory method. Functional gene analysis was carried out by GO/KEGG enrichment analysis. The mRNA and protein expression in human tissue were analyzed by HPA and GEPIA databases. To investigate the prognostic value of these genes, three risk score (RS) models in different pathological types of NSCLC were generated and predicted NSCLC prognosis in datasets from TCGA, UCSC and GEO databases.

Results

1,738 DRGs were identified through trajectory analysis. GO/KEGG analysis showed that these genes were predominantly related to myeloid leukocyte activation and leukocyte migration. 13 DRGs (C1QB, CCL4, CD14, CD84, FGL2, MS4A6A, NLRP3, PLEK, RNASE6, SAMSN1, SPN, TMEM176B, ZEB2) related to prognosis were obtained through univariate Cox analysis and Lasso regression. C1QB, CD84, FGL2, MS4A6A, NLRP3, PLEK, SAMSN1, SPN, and ZEB2 were downregulated in NSCLC compared to non-cancer tissue. The mRNA of 13 genes were significantly expressed in pulmonary macrophages with strong cell specificity. Meanwhile, immunohistochemical staining showed that C1QB, CCL4, SPN, CD14, NLRP3, SAMSN1, MS4A6A, TMEM176B were expressed in different degrees in lung cancer tissues. ZEB2 (HR=1.4, P&lt;0.05) and CD14 (HR=1.6, P&lt;0.05) expression were associated with a worse prognosis in lung squamous cell carcinoma; ZEB2 (HR=0.64, P&lt;0.05), CD84 (HR=0.65, P&lt;0.05), PLEK (HR=0.71, P&lt;0.05) and FGL2 (HR=0.61, P&lt;0.05) expression were associated with a better prognosis in lung adenocarcinoma. Three RS models based on 13 DRGs both showed that the high RS was significantly associated with poor prognosis in different pathological types of NSCLC.

Conclusions

This study highlights the prognostic value of DRGs in TAMs in NSCLC patients, providing novel insights for the development of therapeutic and prognostic targets based on TAM functional differences.

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

Background

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

Methods

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

Results

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

Conclusions

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

Synergies of Radiomics and Transcriptomics in Lung Cancer Diagnosis: A Pilot Study

Radiotranscriptomics is an emerging field that aims to investigate the relationships between the radiomic features extracted from medical images and gene expression profiles that contribute in the diagnosis, treatment planning, and prognosis of cancer. This study proposes a methodological framework for the investigation of these associations with application on non-small-cell lung cancer (NSCLC). Six publicly available NSCLC datasets with transcriptomics data were used to derive and validate a transcriptomic signature for its ability to differentiate between cancer and non-malignant lung tissue. A publicly available dataset of 24 NSCLC-diagnosed patients, with both transcriptomic and imaging data, was used for the joint radiotranscriptomic analysis. For each patient, 749 Computed Tomography (CT) radiomic features were extracted and the corresponding transcriptomics data were provided through DNA microarrays. The radiomic features were clustered using the iterative K-means algorithm resulting in 77 homogeneous clusters, represented by meta-radiomic features. The most significant differentially expressed genes (DEGs) were selected by performing Significance Analysis of Microarrays (SAM) and 2-fold change. The interactions among the CT imaging features and the selected DEGs were investigated using SAM and a Spearman rank correlation test with a False Discovery Rate (FDR) of 5%, leading to the extraction of 73 DEGs significantly correlated with radiomic features. These genes were used to produce predictive models of the meta-radiomics features, defined as p-metaomics features, by performing Lasso regression. Of the 77 meta-radiomic features, 51 can be modeled in terms of the transcriptomic signature. These significant radiotranscriptomics relationships form a reliable basis to biologically justify the radiomics features extracted from anatomic imaging modalities. Thus, the biological value of these radiomic features was justified via enrichment analysis on their transcriptomics-based regression models, revealing closely associated biological processes and pathways. Overall, the proposed methodological framework provides joint radiotranscriptomics markers and models to support the connection and complementarities between the transcriptome and the phenotype in cancer, as demonstrated in the case of NSCLC.

The epigenetic factor CHD4 contributes to metastasis by regulating the EZH2/β-catenin axis and acts as a therapeutic target in ovarian cancer

BACKGROUND

The overall survival rate of patients with advanced ovarian cancer (OC) has remained static for several decades. Advanced ovarian cancer is known for its poor prognosis due to extensive metastasis. Epigenetic alterations contribute to tumour progression and therefore are of interest for potential therapeutic strategies.

METHODS

Following our previous study, we identified that CHD4, a chromatin remodelling factor, plays a strong role in ovarian cancer cell metastasis. We investigated the clinical significance of CHD4 through TCGA and GEO database analyses and explored the effect of CHD4 expression modulation and romidepsin treatment on the biological behaviour of ovarian cancer through CCK-8 and transwell assays. Bioluminescence imaging of tumours in xenografted mice was applied to determine the therapeutic effect of romidepsin. GSEA and western blotting were used to screen the regulatory mechanism of CHD4.

RESULTS

In ovarian cancer patient specimens, high CHD4 expression was associated with a poor prognosis. Loss of function of CHD4 in ovarian cancer cells induced suppression of migration and invasion. Mechanistically, CHD4 knockdown suppressed the expression of EZH2 and the nuclear accumulation of β-catenin. CHD4 also suppressed the metastasis of ovarian cancer cells and prevented disease progression in a mouse model. To inhibit the functions of CHD4 that are mediated by histone deacetylase, we evaluated the effect of the HDAC1/2 selective inhibitor romidepsin. Our findings indicated that treatment with romidepsin suppressed the progression of metastases in vitro and in vivo.

CONCLUSIONS

Collectively, our results uncovered an oncogenic function of CHD4 in ovarian cancer and provide a rationale for clinical trials of romidepsin in ovarian cancer patients.

Identifying key transcription factors and immune infiltration in non-small-cell lung cancer using weighted correlation network and Cox regression analyses

Introduction

Lung cancer is one of the most common cancers and a significant cause of cancer-related deaths. Non-small cell lung cancer (NSCLC) accounts for about 85% of all lung cancer cases. Therefore, it is crucial to identify effective diagnostic and therapeutic methods. In addition, transcription factors are essential for eukaryotic cells to regulate their gene expression, and aberrant expression transcription factors are an important step in the process of oncogenesis in NSCLC.

Methods

Differentially expressed transcription factors between NSCLC and normal tissues by analyzing mRNA profiling from The Cancer Genome Atlas (TCGA) database program were identified. Weighted correlation network analysis (WGCNA) and line plot of least absolute shrinkage and selection operator (LASSO) were performed to find prognosis-related transcription factors. The cellular functions of transcription factors were performed by 5-ethynyl-2'-deoxyuridine (EdU) assay, wound healing assay, cell invasion assay in lung cancer cells.

Results

We identified 725 differentially expressed transcription factors between NSCLC and normal tissues. Three highly related modules for survival were discovered, and transcription factors highly associated with survival were obtained by using WGCNA. Then line plot of LASSO was applied to screen transcription factors related to prognosis and build a prognostic model. Consequently, SETDB2, SNAI3, SCML4, and ZNF540 were identified as prognosis-related transcription factors and validated in multiple databases. The low expression of these hub genes in NSCLC was associated with poor prognosis. The deletions of both SETDB2 and SNAI3 were found to promote proliferation, invasion, and stemness in lung cancer cells. Furthermore, there were significant differences in the proportions of 22 immune cells between the high- and low-score groups.

Discussion

Therefore, our study identified the transcription factors involved in regulating NSCLC, and we constructed a panel for the prediction of prognosis and immune infiltration to inform the clinical application of transcription factor analysis in the prevention and treatment of NSCLC.

In vivo genome-wide CRISPR screening identifies ZNF24 as a negative NF-κB modulator in lung cancer

Systemic identification of tumor suppressor genes (TSGs) and elucidation of their signaling provide a new angle for understanding of tumorigenesis, which is important for developing successful treatment for lung cancer patients. In our current work, we conducted an in vivo screen for lung cancer TSGs through CRISPR/Cas9 mediated knockout of genes at genome-wide scale. We found that ZNF24 was a potent and clinically relevant TSG of lung cancer. Ectopic expression of ZNF24 arrested lung cancer cells in S phase. Mechanistically, ZNF24 bound to promoter region of P65 to negatively regulate its transcription and thereby the signaling activity of NF-κB pathway. This signaling cascade is clinically relevant. Importantly, we found that combinational inhibition of KRAS, NF-κB, and PD-1 effectively shrank autochthonous Kras^G12D/ZNF24^-/- lung cancers in transgenic mouse model. Our current work thus revealed an important role played by loss of function of ZNF24 in lung tumorigenesis and shed new light in precision medicine for a portion of lung cancer patients.

A Systems Biology and LASSO-Based Approach to Decipher the Transcriptome-Interactome Signature for Predicting Non-Small Cell Lung Cancer

The lack of precise molecular signatures limits the early diagnosis of non-small cell lung cancer (NSCLC). The present study used gene expression data and interaction networks to develop a highly accurate model with the least absolute shrinkage and selection operator (LASSO) for predicting NSCLC. The differentially expressed genes (DEGs) were identified in NSCLC compared with normal tissues using TCGA and GTEx data. A biological network was constructed using DEGs, and the top 20 upregulated and 20 downregulated hub genes were identified. These hub genes were used to identify signature genes with penalized logistic regression using the LASSO to predict NSCLC. Our model’s development involved the following steps: (i) the dataset was divided into 80% for training (TR) and 20% for testing (TD1); (ii) a LASSO logistic regression analysis was performed on the TR with 10-fold cross-validation and identified a combination of 17 genes as NSCLC predictors, which were used further for development of the LASSO model. The model’s performance was assessed on the TD1 dataset and achieved an accuracy and an area under the curve of the receiver operating characteristics (AUC-ROC) of 0.986 and 0.998, respectively. Furthermore, the performance of the LASSO model was evaluated using three independent NSCLC test datasets (GSE18842, GSE27262, GSE19804) and achieved high accuracy, with an AUC-ROC of >0.99, >0.99, and 0.95, respectively. Based on this study, a web application called NSCLCpred was developed to predict NSCLC.

Engrailed homeobox 1 transcriptional regulation of COL22A1 inhibits nasopharyngeal carcinoma cell senescence through the G1/S phase arrest

EN1 is well known as a transcription factor in other tumours, but its role in NPC is unclear. In this study, we first used bioinformatics to analyse GEO data to obtain the differentially expressed gene EN1, and subsequently verified that EN1 was highly expressed in nasopharyngeal carcinoma cells by tissue microarrays as well as cell lines. Further, we down‐regulated the expression of EN1 in cells for RNA sequencing. The analysis of sequencing results using KEGG and GO revealed significant changes in cell proliferation and cycle function after downregulation of EN1. Meanwhile, we found that cells underwent senescence after inhibition of EN1 under electron microscopy and the SA‐β‐gal assays. Based on the sequencing results, we verified that EN1 can promote the proliferation and cycle of NPC cells in cell function experiments and animal experiments. To investigate how EN1 affects cell senescence, we found that EN1 transcriptional regulation of COL22A1 regulated cell proliferation and cycle via CDK4/6‐cyclin D1‐Rb signalling pathway by dual luciferase reporter, Immunoblotting and rescue experiment. Accordingly, we uncovered that EN1 could serve as a target for the regulation of senescence in NPC.

PRDM16, negatively regulated by miR-372-3p, suppresses cell proliferation and invasion in prostate cancer

Prostate cancer (PCa) is one of the most prevalent malignant tumours. The alternation of microRNAs (miRNAs) expression is associated with prostate cancer progression, whereas its way to influence progression of prostate cancer remains elusive. The expression levels of PRDM16 mRNA and miR-372-3p in PCa cell lines were analysed using qRT-PCR. The protein expression of PRDM16 in PCa cell lines was also analysed using Western blot. CCK-8, wound healing and Transwell assays were applied to examine cell proliferation, migration, and invasion in prostate cancer cells, respectively. Dual-luciferase reporter assay was utilised to validate the interaction between miR-372-3p and PRDM16. In the present study, markedly decreased PRDM16 mRNA and protein expression levels were observed in prostate cancer cells. PRDM16 overexpression hampered cellular proliferation, migration, and invasion, while silencing PRDM16 had the opposite effect. Moreover, miR-372-3p could target the regulation expression of PRDM16. Rescue experiments demonstrated that upregulating miR-372-3p conspicuously restored the inhibitory effect of increased PRDM16 on cell proliferation, migration, and invasion in PCa. Overall, our study clarifies the biological role of miR-372-3p/PRDM16 axis in prostate cancer progression, which may be effective biomarkers for clinical treatment of prostate cancer.

SEMA3C Supports Pancreatic Cancer Progression by Regulating the Autophagy Process and Tumor Immune Microenvironment

To date, driver genes for pancreatic cancer treatment are difficult to pursue therapeutically. Targeting mutated KRAS, the most renowned driver gene in pancreatic cancer, is an active area of study. We discovered a gene named SEMA3C was highly expressed in pancreatic cancer cell lines and patients with a G12D mutation in KRAS. High expression of SEMA3C in patients was significantly associated with the decreased survival of pancreatic cancer patients based on the TCGA database. In pancreatic cancer cells, SEMA3C knockdown or inhibition exhibited growth/colony inhibition and cell cycle arrest. In addition, SEMA3C inhibition sensitized KRAS or MEK1/2 inhibition in pancreatic cancer cells. Overexpression of SEMA3C resulted in the induction of autophagy, whereas depletion of SEMA3C compromised induction of autophagy. SEMA3C modified the PD-L1 expression in tumor and immune cells and is correlated with the M2-like macrophage marker ARG1/CD163 expression, which could reshape the tumor microenvironment. Inhibition of SEMA3C decreased tumor formation in the xenograft model in vivo. Taken together, our data suggest that SEMA3C plays a substantial role in promoting cancer cell survival by regulating the autophagy process and impacting the tumor environment immune response. SEMA3C can be used as a novel target or marker with therapeutic or diagnostic potential in pancreatic cancer especially in tumors harboring the specific KRAS G12D mutation.

Nuclear receptor subfamily 3 group c member 2 (NR3C2) is downregulated due to hypermethylation and plays a tumor-suppressive role in colon cancer

Nuclear receptor subfamily 3 group c member 2 (NR3C2) has been reported to function as a tumor suppressor in several tumors. However, the clinical significance and potential action mechanisms of NR3C2 in colon cancer (COAD) remain unclear. NR3C2 expression and its correlation with clinicopathological features in COAD were analyzed based on the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Receiver operating characteristic (ROC) curves and Human Protein Atlas (HPA) database were used to evaluate the diagnostic and prognostic values of NR3C2 in COAD. Immune infiltration and DNA methylation analyses were performed by Gene Set Cancer Analysis (GSCA) database. NR3C2-correlated genes were identified by UALCAN database and subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analyses. Cell apoptosis and proliferation were evaluated using TUNEL and CCK-8 assays, respectively. NR3C2 was downregulated in COAD based on TCGA and GEO databases, which may be due to promoter hypermethylation. NR3C2 expression was correlated with prognosis and immune infiltration of COAD. High NR3C2 expression displayed good diagnostic value in COAD. KEGG pathway analysis presented that NR3C2-correlated genes were mainly clustered in choline metabolism in cancer and apoptosis. In vitro experiments confirmed that NR3C2 overexpression induced apoptosis and suppressed proliferation in COAD cells. In conclusion, our study revealed the potential prognostic and diagnostic values of NR3C2 and provided insights into understanding the tumor-suppressive role of NR3C2 in COAD progression.

Identification of condition-specific regulatory mechanisms in normal and cancerous human lung tissue

Background

Lung cancer is the leading cause of cancer death in both men and women. The most common lung cancer subtype is non-small cell lung carcinoma (NSCLC) comprising about 85% of all cases. NSCLC can be further divided into three subtypes: adenocarcinoma (LUAD), squamous cell carcinoma (LUSC), and large cell lung carcinoma. Specific genetic mutations and epigenetic aberrations play an important role in the developmental transition to a specific tumor subtype. The elucidation of normal lung versus lung tumor gene expression patterns and regulatory targets yields biomarker systems that discriminate lung phenotypes (i.e., biomarkers) and provide a foundation for the discovery of normal and aberrant gene regulatory mechanisms.

Results

We built condition-specific gene co-expression networks (csGCNs) for normal lung, LUAD, and LUSC conditions. Then, we integrated normal lung tissue-specific gene regulatory networks (tsGRNs) to elucidate control-target biomarker systems for normal and cancerous lung tissue. We characterized co-expressed gene edges, possibly under common regulatory control, for relevance in lung cancer.

Conclusions

Our approach demonstrates the ability to elucidate csGCN:tsGRN merged biomarker systems based on gene expression correlation and regulation. The biomarker systems we describe can be used to classify and further describe lung specimens. Our approach is generalizable and can be used to discover and interpret complex gene expression patterns for any condition or species.

Supplementary Information

The online version contains available at 10.1186/s12864-022-08591-9.

AFF3 is a novel prognostic biomarker and a potential target for immunotherapy in gastric cancer

Background

Gastric cancer (GC) is one of the most common cancers worldwide with a poor prognosis. The tumor microenvironment (TME) serves a pivotal role in affecting the prognosis and efficacy of immunotherapy. Given the poor prognosis of GC patients and the limitation of immunotherapy, we urged to identify new prognostic and immunotherapeutic biomarkers.

Methods

The transcriptome data were downloaded from the TCGA, GEO, and GEPIA databases, and performed differential analysis of AFF3 in tumor samples and normal samples. The UALCAN, Kaplan–Meier plotter and GEPIA databases were employed to assess the correlation of AFF3 with clinicopathological characteristics and prognosis. The potential mechanism of AFF3 was explored by the GO and KEGG enrichment. The potential role of AFF3 on tumor‐infiltrating immune cells (TIICs) was explored by TIMER2.0 and TISIDB. TIMER2.0 and SangerBox3.0 databases were, respectively, used to determine the correlation of AFF3 with immune checkpoint (ICs), tumor mutational burden (TMB), and microsatellite instability (MSI) in GC.

Results

We found significant downregulation of AFF3 in GC tissues as compared with normal tissues. However, GC patients having a higher expression of AFF3 were found to have worse clinicopathological characteristics and prognosis. Moreover, the GO enrichment analysis illustrated that AFF3 might regulate the immune cells in the TME. In addition, the AFF3 was positively correlated with TIICs, ICs, TMB, and MSI.

Conclusion

Here, we conclude that AFF3 may be a promising potential marker for the diagnosis and prognosis of GC patients, and may influence response to ICIs by affecting TIICs and ICs expression in the TME.

Identification of Tumor Antigens and Immune Subtypes in Lung Adenocarcinoma for mRNA Vaccine Development

Cancer vaccines are emerging as a viable strategy for cancer treatment. In the current study, we screened for genes associated with the prognosis of patients with lung adenocarcinoma and positively correlated with antigen-presenting cell infiltration and identified KLRG1 and CBFA2T3 as potential tumor antigens for mRNA vaccines in lung adenocarcinoma (LUAD). Further analyses of immune subtypes revealed that patients with early-stage LUAD, high immune cell infiltration, high immune checkpoint expression, and low tumor mutation burden might benefit from mRNA vaccination. Moreover, we identified four biomarkers that can be used to assess mRNA vaccination suitability. We also identified potentially sensitive anti-cancer drugs for populations not suitable for vaccination by means of anti-cancer drug susceptibility prediction. Overall, we provided a new perspective for mRNA vaccine treatment strategies for LUAD and emphasized the importance of precise and personalized treatments.

Multi-omic characterization of genome-wide abnormal DNA methylation reveals diagnostic and prognostic markers for esophageal squamous-cell carcinoma

This study investigates aberrant DNA methylations as potential diagnosis and prognosis markers for esophageal squamous-cell carcinoma (ESCC), which if diagnosed at advanced stages has <30% five-year survival rate. Comparing genome-wide methylation sites of 91 ESCC and matched adjacent normal tissues, we identified 35,577 differentially methylated CpG sites (DMCs) and characterized their distribution patterns. Integrating whole-genome DNA and RNA-sequencing data of the same samples, we found multiple dysregulated transcription factors and ESCC-specific genomic correlates of identified DMCs. Using featured DMCs, we developed a 12-marker diagnostic panel with high accuracy in our dataset and the TCGA ESCC dataset, and a 4-marker prognostic panel distinguishing high-risk patients. In-vitro experiments validated the functions of 4 marker host genes. Together these results provide additional evidence for the important roles of aberrant DNA methylations in ESCC development and progression. Our DMC-based diagnostic and prognostic panels have potential values for clinical care of ESCC, laying foundations for developing targeted methylation assays for future non-invasive cancer detection methods.

Genomics and Prognosis Analysis of N6-Methyladenosine Regulators in Lung Adenocarcinoma

Objective: N⁶-methyladenosine (m⁶A) modification is involved in modulating various biological processes in human cancers. But the implication of m⁶A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical implication of m⁶A regulators in LUAD.

Methods: Consensus clustering analysis of 502 LUAD samples in the TCGA dataset was presented based on the expression profiles of 20 m⁶A regulators using ConsensusClusterPlus package. Overall survival (OS), activation of signaling pathways and tumor immunity (immune/stromal score, tumor purity, expression of HLA and immune checkpoints, and immune cell infiltration) were compared between m⁶A modification patterns. The m⁶A-related genes between patterns were identified and prognostic m⁶A-related genes were imported into LASSO-cox regression analysis. The m⁶A risk score was developed and its prognostic implication was evaluated and externally verified in the GSE30219 and GSE72094 dataset. Furthermore, a nomogram that contained independent prognostic indicators was established, followed by external verification.

Results: Two m⁶A modification patterns were clustered across LUAD based on the expression similarity of the m⁶A regulators via consensus clustering analysis, with distinct OS, activation of signaling pathways and tumor immunity. Totally, 213 m⁶A-related genes that were identified by comparing two patterns were significantly related to LUAD prognosis. By LASSO method, we constructed the m⁶A risk score that was a reliable and independent prognostic factor for LUAD. Patients with low m⁶A risk score displayed a prominent survival advantage. After incorporating independent clinical features, we developed the prognostic nomogram that exhibited high predictive accuracy and the best clinical net benefit for OS.

Conclusion: Collectively, our study may provide a clinically useful tool for precise prognostic management and optimization of immunotherapeutic strategies for LUAD patients.

SALL Proteins; Common and Antagonistic Roles in Cancer

Simple Summary

Transcription factors play essential roles in regulating gene expression, impacting the cell phenotype and function, and in the response of cells to environmental conditions. Alterations in transcription factors, including gene amplification or deletion, point mutations, and expression changes, are implicated in carcinogenesis, cancer progression, metastases, and resistance to cancer treatments. Not surprisingly, transcription factor activity is altered in numerous cancers, representing a unique class of cancer drug targets. This review updates and integrates information on the SALL family of transcription factors, highlighting the synergistic and/or antagonistic functions they perform in various cancer types.

Abstract

SALL proteins are a family of four conserved C2H2 zinc finger transcription factors that play critical roles in organogenesis during embryonic development. They regulate cell proliferation, survival, migration, and stemness; consequently, they are involved in various human genetic disorders and cancer. SALL4 is a well-recognized oncogene; however, SALL1–3 play dual roles depending on the cancer context and stage of the disease. Current reviews of SALLs have focused only on SALL2 or SALL4, lacking an integrated view of the SALL family members in cancer. Here, we update the recent advances of the SALL members in tumor development, cancer progression, and therapy, highlighting the synergistic and/or antagonistic functions they perform in similar cancer contexts. We identified common regulatory mechanisms, targets, and signaling pathways in breast, brain, liver, colon, blood, and HPV-related cancers. In addition, we discuss the potential of the SALL family members as cancer biomarkers and in the cancer cells’ response to therapies. Understanding SALL proteins’ function and relationship will open new cancer biology, clinical research, and therapy perspectives.

Establishment of a prognostic model of ten transcription factors in gastric cancer

Transcription factors (TFs) play an important role in tumors. We integrated and analyzed 13 GPL570 platform gastric cancer (GC) microarrays, identified 10 independent prognostic TFs, and constructed a GC prognostic model. Using GSE26942 as the verification set, the Kaplan-Meier curve showed that the signature distinguish the survival rate of GC patients (P < 0.01), and the AUC values are 0.746 and 0.630, respectively. Compared with the clinicopathological characteristics, the signature is an independent prognostic factor (P < 0.05). A nomogram was established based on the model, and the five-year calibration curve verified that the prediction of the nomogram was almost consistent with the actual survival rate, C-index of 0.747 indicated a moderate prognostic ability. The analysis of target genes of 10 TFs showed that they are closely related to the progression of GC. External database and rt-PCR showed that the RNA and protein expression of TFs are consistent with our analysis.

Comprehensive Analysis of a Nine-Gene Signature Related to Tumor Microenvironment in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common malignancy, leading to more than 1 million related deaths each year. Due to low long-term survival rates, the exploration of molecular mechanisms underlying LUAD progression and novel prognostic predictors is urgently needed to improve LUAD treatment. In our study, cancer-specific differentially expressed genes (DEGs) were identified using the robust rank aggregation (RRA) method between tumor and normal tissues from six Gene Expression Omnibus databases (GSE43458, GSE62949, GSE68465, GSE115002, GSE116959, and GSE118370), followed by a selection of prognostic modules using weighted gene co-expression network analysis. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were applied to identify nine hub genes (CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6) that constructed a prognostic risk model. The RNA expressions of nine hub genes were validated in tumor and normal tissues by RNA-sequencing and single-cell RNA-sequencing, while immunohistochemistry staining from the Human Protein Atlas database showed consistent results in the protein levels. The risk model revealed that high-risk patients were associated with poor prognoses, including advanced stages and low survival rates. Furthermore, a multivariate Cox regression analysis suggested that the prognostic risk model could be an independent prognostic factor for LUAD patients. A nomogram that incorporated the signature and clinical features was additionally built for prognostic prediction. Moreover, the levels of hub genes were related to immune cell infiltration in LUAD microenvironments. A CMap analysis identified 13 small molecule drugs as potential agents based on the risk model for LUAD treatment. Thus, we identified a prognostic risk model including CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6 as novel biomarkers and validated their prognostic and predicted values for LUAD.

Systematic profiling of invasion-related gene signature predicts prognostic features of lung adenocarcinoma

Due to the high heterogeneity of lung adenocarcinoma (LUAD), molecular subtype based on gene expression profiles is of great significance for diagnosis and prognosis prediction in patients with LUAD. Invasion-related genes were obtained from the CancerSEA database, and LUAD expression profiles were downloaded from The Cancer Genome Atlas. The ConsensusClusterPlus was used to obtain molecular subtypes based on invasion-related genes. The limma software package was used to identify differentially expressed genes (DEGs). A multi-gene risk model was constructed by Lasso-Cox analysis. A nomogram was also constructed based on risk scores and meaningful clinical features. 3 subtypes (C1, C2 and C3) based on the expression of 97 invasion-related genes were obtained. C3 had the worst prognosis. A total of 669 DEGs were identified among the subtypes. Pathway enrichment analysis results showed that the DEGs were mainly enriched in the cell cycle, DNA replication, the p53 signalling pathway and other tumour-related pathways. A 5-gene signature (KRT6A, MELTF, IRX5, MS4A1 and CRTAC1) was identified by using Lasso-Cox analysis. The training, validation and external independent cohorts proved that the model was robust and had better prediction ability than other lung cancer models. The gene expression results showed that the expression levels of MS4A1 and KRT6A in tumour tissues were higher than in normal tissues, while CRTAC1 expression in tumour tissues was lower than in normal tissues. The 5-gene signature prognostic stratification system based on invasion-related genes could be used to assess prognostic risk in patients with LUAD.

Authentication of differential gene expression in oral squamous cell carcinoma using machine learning applications

BACKGROUND

Recently, the possibility of tumour classification based on genetic data has been investigated. However, genetic datasets are difficult to handle because of their massive size and complexity of manipulation. In the present study, we examined the diagnostic performance of machine learning applications using imaging-based classifications of oral squamous cell carcinoma (OSCC) gene sets.

METHODS

RNA sequencing data from SCC tissues from various sites, including oral, non-oral head and neck, oesophageal, and cervical regions, were downloaded from The Cancer Genome Atlas (TCGA). The feature genes were extracted through a convolutional neural network (CNN) and machine learning, and the performance of each analysis was compared.

RESULTS

The ability of the machine learning analysis to classify OSCC tumours was excellent. However, the tool exhibited poorer performance in discriminating histopathologically dissimilar cancers derived from the same type of tissue than in differentiating cancers of the same histopathologic type with different tissue origins, revealing that the differential gene expression pattern is a more important factor than the histopathologic features for differentiating cancer types.

CONCLUSION

The CNN-based diagnostic model and the visualisation methods using RNA sequencing data were useful for correctly categorising OSCC. The analysis showed differentially expressed genes in multiwise comparisons of various types of SCCs, such as KCNA10, FOSL2, and PRDM16, and extracted leader genes from pairwise comparisons were FGF20, DLC1, and ZNF705D.

ECMarker: interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages

MOTIVATION

Gene expression and regulation, a key molecular mechanism driving human disease development, remains elusive, especially at early stages. Integrating the increasing amount of population-level genomic data and understanding gene regulatory mechanisms in disease development are still challenging. Machine learning has emerged to solve this, but many machine learning methods were typically limited to building an accurate prediction model as a 'black box', barely providing biological and clinical interpretability from the box.

RESULTS

To address these challenges, we developed an interpretable and scalable machine learning model, ECMarker, to predict gene expression biomarkers for disease phenotypes and simultaneously reveal underlying regulatory mechanisms. Particularly, ECMarker is built on the integration of semi- and discriminative-restricted Boltzmann machines, a neural network model for classification allowing lateral connections at the input gene layer. This interpretable model is scalable without needing any prior feature selection and enables directly modeling and prioritizing genes and revealing potential gene networks (from lateral connections) for the phenotypes. With application to the gene expression data of non-small-cell lung cancer patients, we found that ECMarker not only achieved a relatively high accuracy for predicting cancer stages but also identified the biomarker genes and gene networks implying the regulatory mechanisms in the lung cancer development. In addition, ECMarker demonstrates clinical interpretability as its prioritized biomarker genes can predict survival rates of early lung cancer patients (P-value < 0.005). Finally, we identified a number of drugs currently in clinical use for late stages or other cancers with effects on these early lung cancer biomarkers, suggesting potential novel candidates on early cancer medicine.

AVAILABILITYAND IMPLEMENTATION

ECMarker is open source as a general-purpose tool at https://github.com/daifengwanglab/ECMarker.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification and Characterization of Alternatively Spliced Transcript Isoforms of IRX4 in Prostate Cancer

Alternative splicing (AS) is tightly regulated to maintain genomic stability in humans. However, tumor growth, metastasis and therapy resistance benefit from aberrant RNA splicing. Iroquois-class homeodomain protein 4 (IRX4) is a TALE homeobox transcription factor which has been implicated in prostate cancer (PCa) as a tumor suppressor through genome-wide association studies (GWAS) and functional follow-up studies. In the current study, we characterized 12 IRX4 transcripts in PCa cell lines, including seven novel transcripts by RT-PCR and sequencing. They demonstrate unique expression profiles between androgen-responsive and nonresponsive cell lines. These transcripts were significantly overexpressed in PCa cell lines and the cancer genome atlas program (TCGA) PCa clinical specimens, suggesting their probable involvement in PCa progression. Moreover, a PCa risk-associated SNP rs12653946 genotype GG was corelated with lower IRX4 transcript levels. Using mass spectrometry analysis, we identified two IRX4 protein isoforms (54.4 kDa, 57 kDa) comprising all the functional domains and two novel isoforms (40 kDa, 8.7 kDa) lacking functional domains. These IRX4 isoforms might induce distinct functional programming that could contribute to PCa hallmarks, thus providing novel insights into diagnostic, prognostic and therapeutic significance in PCa management.

BarH-like homeobox 1 induces the progression of cell malignant phenotype in endometrial carcinoma through the regulation of ERK/MEK signaling pathway

The aim of this article was to assess whether and how BARX1 affects the progression of malignant phenotype of endometrial carcinoma (EC) cells. BARX1 levels and its prognostic value were evaluated using the EC-related RNA sequence dataset from The Cancer Genome Atlas (TCGA) database. Functional experiments were performed to evaluate the biological roles of BARX1 in EC HEC-1-A and KLE cells by silencing BARX1. BARX1 was upregulated in EC tissues according to the public database and in EC cells. High expression of BARX1 led to a poor prognosis and significantly related to clinical stage, pathological grade, death, histological subtypes, and menopause status in patients with EC. Silencing BARX1 notably suppressed the aggressive phenotypes of EC cells, as evidenced by inhibiting cells viability, growth, invasion and migration. Furthermore, depletion of BARX1 decreased the phosphorylation (p) levels of ERK and MEK, also reinforced the suppressive effects of ERK/MEK pathway blocker PD98059 on the p-ERK and p-MEK levels. Together, our results demonstrated that BARX1 functions as a carcinogen by regulating the cell viability, invasion, and migration at least partly through the ERK/MEK pathway.

miR-301b and NR3C2 co-regulate cells malignant properties and have the potential to be independent prognostic factors in breast cancer

This study intends to address the function of miR-301b/nuclear receptor subfamily 3 group C member 2 (NR3C2) in breast cancer. The Cancer Genome Atlas database was processed to investigate the expression of miR-301b/NR3C2 in breast cancer samples, as well as the relationship between their expression and the prognosis of the patients. Cox regression analysis was performed to determine whether miR-301b/NR3C2 was an independent predictor of the patient's prognosis. Associations between miR-301b and NR3C2 were analyzed by prediction website, dual-luciferase assay, and Pearson correlation coefficient. Quantitative polymerase chain reaction and Western blot analyses were implemented to detect gene expression. The relevant biological characteristics of MCF7 and BCAP-37 cells were tested by cell counting kit-8, colony formation, and transwell assays. Lower expression of NR3C2, which was closely related to the bad prognosis of breast cancer patients, was presented in breast cancer samples and can be used as an independent predictor. miR-301b, as an upstream regulator of NR3C2, was highly expressed in breast cancer samples and can be used as an independent predictor as well. Notably, a higher level of miR-301b and lower level of NR3C2 were related to the reduced overall survival in patients with breast cancer. The proliferative and migratory behaviors of cells were elevated or blocked after overexpression of miR-301b or NR3C2, respectively. However, the above situation was attenuated after together upregulation of miR-301b and NR3C2. The present data afforded evidence that miR-301b may be a tumor-promoting miRNA in breast cancer, and that miR-301b/NR3C2 axis mediated tumor development from cell proliferation and migration.

Emerging Roles of PRDM Factors in Stem Cells and Neuronal System: Cofactor Dependent Regulation of PRDM3/16 and FOG1/2 (Novel PRDM Factors)

PRDI-BF1 (positive regulatory domain I-binding factor 1) and RIZ1 (retinoblastoma protein-interacting zinc finger gene 1) (PR) homologous domain containing (PRDM) transcription factors are expressed in neuronal and stem cell systems, and they exert multiple functions in a spatiotemporal manner. Therefore, it is believed that PRDM factors cooperate with a number of protein partners to regulate a critical set of genes required for maintenance of stem cell self-renewal and differentiation through genetic and epigenetic mechanisms. In this review, we summarize recent findings about the expression of PRDM factors and function in stem cell and neuronal systems with a focus on cofactor-dependent regulation of PRDM3/16 and FOG1/2. We put special attention on summarizing the effects of the PRDM proteins interaction with chromatin modulators (NuRD complex and CtBPs) on the stem cell characteristic and neuronal differentiation. Although PRDM factors are known to possess intrinsic enzyme activity, our literature analysis suggests that cofactor-dependent regulation of PRDM3/16 and FOG1/2 is also one of the important mechanisms to orchestrate bidirectional target gene regulation. Therefore, determining stem cell and neuronal-specific cofactors will help better understanding of PRDM3/16 and FOG1/2-controlled stem cell maintenance and neuronal differentiation. Finally, we discuss the clinical aspect of these PRDM factors in different diseases including cancer. Overall, this review will help further sharpen our knowledge of the function of the PRDM3/16 and FOG1/2 with hopes to open new research fields related to these factors in stem cell biology and neuroscience.

miR-224, miR-147b and miR-31 associated with lymph node metastasis and prognosis for lung adenocarcinoma by regulating PRPF4B, WDR82 or NR3C2

Background

The present study is to screen lymph node metastasis-related microRNAs (miRNAs) in lung adenocarcinoma (LUAD) and uncover their underlying mechanisms.

Methods

The miRNA microarray dataset was collected from the Gene Expression Omnibus database under accession number GSE64859. The differentially expressed miRNAs (DEMs) were identified using a t-test. Target genes of DEMs were predicted through the miRWalk2.0 database. The function of these target genes was annotated with the clusterProfiler and the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools. Protein-protein interaction network was established using the STRING database to extract hub target genes. The expressions and associations with survival and lymph node metastasis of miRNAs and target genes were validated by analysis of The Cancer Genome Atlas (TCGA) dataset.

Results

Eight DEMs were identified between lymph node metastasis and non-metastasis samples of GSE64859 dataset. miRNA-target gene pairs were predicted between six DEMs and 251 target genes (i.e. hsa-miR-224-PRPF4B, hsa-miR-147b-WDR82 and hsa-miR-31-NR3C2). The clusterProfiler analysis showed WDR82 was involved in the mRNA surveillance pathway, while the GO enrichment analysis using the DAVID database indicated PRPF4B participated in the protein phosphorylation and NR3C2 was related with the transcription, DNA-templated. WDR82 and PRPF4B may be hub genes because they could interact with others. Two DEMs (miR-31-5p and miR-31-3p) and 45 target genes (including PRPF4B and NR3C2) were significantly associated with overall survival. The expressions of miR-224 and miR-147b were validated to be upregulated, while WDR82, PRPF4B and NR3C2 were downregulated in lymph node metastasis samples of TCGA datasets compared with non-metastasis samples. Also, there were significantly negative expression correlations between miR-147b and WDR82, between miR-224 and PRPF4B, as well as between miR-31 and NR3C2 in LUAD samples.

Conclusions

The present study identified several crucial miRNA-mRNA interaction pairs, which may provide novel explanations for the lymph node metastasis and poor prognosis for LUAD patients.

Aberrant super-enhancer landscape reveals core transcriptional regulatory circuitry in lung adenocarcinoma

Lung adenocarcinoma (LUAD) relies on dysregulated gene expression to sustain its infinite growth and progression. Emerging evidence indicates that aberrant transcriptional program results from core transcriptional regulatory circuitry (CRC) which is driven by super-enhancers (SEs). In this study, by integrating profiles of H3K27Ac chromatin immunoprecipitation sequencing (ChIP-seq) from normal adult lung and LUAD cell lines, we revealed that widespread alterations of the super-enhancer were presence during lung carcinogenesis. With SE-based modeling of regulatory circuits and assessments of transcription factor (TF) dependencies, we reconstructed an interconnected transcriptional regulation network formed by three master TFs, including ELF3, EHF, and TGIF1, all of which promoted each other’s expression that confirmed by ChIP-qPCR and western blot. Loss-of function assay revealed that each of them is essential for LUAD cells survival, invasion and metastasis. Meanwhile, the rescue assay also illustrated the transacting transcriptional regulatory circuitry. In addition, the mRNA levels of ELF3, EHF, and TGIF1 were differentially expressed in LUAD tumors and peritumoral tissue. IHC of serial sections revealed that high expressions of CRC (ELF3/EHF/TGIF1-High) were closely associated with high proliferative activity in tumor tissue and poor prognosis on patients with LUAD. Finally, we used small molecular inhibitors to perturb the transcriptional circuitry, also exhibited a prominent anti-cancer effect in vitro. Our findings reveal the mechanism of the transcriptional dysregulation and addiction of LUAD.

Novel immune subtypes of lung adenocarcinoma identified through bioinformatic analysis

The magnitude of the immune response is closely associated with clinical outcome in patients with cancer. However, finding potential therapeutic targets for lung cancer in the immune system remains challenging. Here, we constructed a vital immune‐prognosis genes (VIPGs) based cluster of lung adenocarcinoma (LUAD) from IMMPORT databases and The Cancer Genome Atlas. A transcription factor regulatory network for the VIPGs was also established. The tumor microenvironment of LUAD was analyzed using the ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) algorithm and single‐sample Gene Set Enrichment Analysis. The immune checkpoints and genomic alterations were explored in the different immune clusters. We identified 15 VIPGs for patients with LUAD and clustered the patients into low‐immunity and high‐immunity subtypes. The immune score, stromal score and ESTIMATE score were significantly higher in the high‐immunity subtype, whereas tumor purity was higher in the low‐immunity subtype. In addition, the immune checkpoints cytotoxic T lymphocyte associate protein‐4(CTLA4), programmed cell death protein‐1 and programmed death‐ligand were elevated in the low‐immunity subtype. The genomic results also showed that the tumor mutation burden was higher in the high‐immunity subtype. Finally, Gene Set Enrichment Analysis showed that several immune‐related gene sets, including interleukin‐2/STAT5 signaling, inflammatory response, interleukin‐6/Janus kinase(JAK)/signal transducer and activator of transcription 3 (STAT3) signaling, interferon‐gamma response and allograft rejection, were elevated in the high‐immunity subtype. Finally, high‐immunity patients exhibited greater overall and disease‐specific survival outcome compared with low‐immunity patients (log rank P = 0.013 and P = 0.0097). Altogether, here we have identified 15 immune‐prognosis genes and a potential immune subtype for patients with LUAD, which may provide new insights into the prognosis and treatment of LUAD.

1,25-dihydroxyvitamin D3 signaling-induced decreases in IRX4 inhibits NANOG-mediated cancer stem-like properties and gefitinib resistance in NSCLC cells

Recent studies have demonstrated that acquisition of cancer stem-like properties plays an essential role in promoting epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) resistance in non-small cell lung cancer (NSCLC); however, how to regulate cancer stem-like properties and EGFR-TKI resistance is largely unclear. In this study, we discovered that increased iroquois-class homeodomain protein 4 (IRX4) was related to gefitinib resistance in NSCLC cells. Knockdown of IRX4 inhibited cell proliferation, sphere formation, and the expression of CD133, ALDH1A1, NANOG, Sox2 and Notch1, and the transcriptional activity of NANOG promoter. IRX4 overexpression increased the protein level of NANOG and CD133 in PC-9 cells. Combination of knocking-down IRX4 with gefitinib increased cell apoptosis and decreased cell viability and the expression of p-EGFR and NANOG in PC-9/GR cells. IRX4 knockdown in a PC-9/GR xenograft tumor model inhibited tumor progression and the expression of NANOG and CD133 more effectively than single treatment alone. Knockdown of NANOG inhibited the expression of CD133 and restored gefitinib cytotoxicity, and NANOG overexpression-induced cancer stem-like properties and gefitinib resistance could be obviously reversed by knocking-down IRX4. Further, we found that 1,25-dihydroxyvitamin D3 (1,25(OH)₂D₃) reduced obviously the expression of IRX4 and NANOG by inhibiting the activation of TGF-β1/Smad3 signaling pathway; moreover, combination of 1,25(OH)₂D₃ and gefitinib decreased cell viability and proliferation or tumor progression and the expression of IRX4 and NANOG compared with single treatment alone both in PC-9/GR cells and in a PC-9/GR xenograft tumor model. These results reveal that inhibition of IRX4-mediated cancer stem-like properties by regulating 1,25(OH)₂D₃ signaling may increase gefitinib cytotoxicity. Combination therapy of gefitinib and 1,25(OH)₂D₃ by targeting IRX4 and NANOG, could provide a promising strategy to improve gefitinib cytotoxicity.

Potential five-mRNA signature model for the prediction of prognosis in patients with papillary thyroid carcinoma

Although the mortality rate of papillary thyroid carcinoma (PTC) is relatively low, the recurrence rates of PTC remain high. The high recurrence rates are related to the difficulties in treatment. Gene expression profiles has provided novel insights into potential therapeutic targets and molecular biomarkers of PTC. The aim of the present study was to identify mRNA signatures which may categorize PTCs into high-and low-risk subgroups and aid with the predictions for prognoses. The mRNA expression profiles of PTC and normal thyroid tissue samples were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs were identified using the ‘EdgeR’ software package. Gene signatures associated with the overall survival of PTC were selected, and enrichment analysis was performed to explore the biological pathways and functions of the prognostic mRNAs using the Database for Visualization, Annotation and Integration Discovery. A signature model was established to investigate a specific and robust risk stratification for PTC. A total of 1,085 differentially expressed mRNAs were identified between the PTC and normal thyroid tissue samples. Among them, 361 mRNAs were associated with overall survival (P<0.05). A 5-mRNA prognostic signature for PTC (ADRA1B, RIPPLY3, PCOLCE, TEKT1 and SALL3) was identified to classify the patients into high-and low-risk subgroups. These prognostic mRNAs were enriched in Gene Ontology terms such as ‘calcium ion binding’, ‘enzyme inhibitor activity’, ‘carbohydrate binding’, ‘transcriptional activator activity’, ‘RNA polymerase II core promoter proximal region sequence-specific binding’ and ‘glutathione transferase activity’, and Kyoto Encyclopedia of Genes and Genomes signaling pathways such as ‘pertussis’, ‘ascorbate and aldarate metabolism’, ‘systemic lupus erythematosus’, ‘drug metabolism-cytochrome P450 and ‘complement and coagulation cascades’. The 5-mRNA signature model may be useful during consultations with patients with PTC to improve the prediction of their prognosis. In addition, the prognostic signature identified in the present study may reveal novel therapeutic targets for patients with PTC.

Independent Validation of Early-Stage Non-Small Cell Lung Cancer Prognostic Scores Incorporating Epigenetic and Transcriptional Biomarkers With Gene-Gene Interactions and Main Effects

BACKGROUND

DNA methylation and gene expression are promising biomarkers of various cancers, including non-small cell lung cancer (NSCLC). Besides the main effects of biomarkers, the progression of complex diseases is also influenced by gene-gene (G×G) interactions.

RESEARCH QUESTION

Would screening the functional capacity of biomarkers on the basis of main effects or interactions, using multiomics data, improve the accuracy of cancer prognosis?

STUDY DESIGN AND METHODS

Biomarker screening and model validation were used to construct and validate a prognostic prediction model. NSCLC prognosis-associated biomarkers were identified on the basis of either their main effects or interactions with two types of omics data. A prognostic score incorporating epigenetic and transcriptional biomarkers, as well as clinical information, was independently validated.

RESULTS

Twenty-six pairs of biomarkers with G×G interactions and two biomarkers with main effects were significantly associated with NSCLC survival. Compared with a model using clinical information only, the accuracy of the epigenetic and transcriptional biomarker-based prognostic model, measured by area under the receiver operating characteristic curve (AUC), increased by 35.38% (95% CI, 27.09%-42.17%; P = 5.10 × 10-17) and 34.85% (95% CI, 26.33%-41.87%; P = 2.52 × 10-18) for 3- and 5-year survival, respectively, which exhibited a superior predictive ability for NSCLC survival (AUC3 year, 0.88 [95% CI, 0.83-0.93]; and AUC5 year, 0.89 [95% CI, 0.83-0.93]) in an independent Cancer Genome Atlas population. G×G interactions contributed a 65.2% and 91.3% increase in prediction accuracy for 3- and 5-year survival, respectively.

INTERPRETATION

The integration of epigenetic and transcriptional biomarkers with main effects and G×G interactions significantly improves the accuracy of prognostic prediction of early-stage NSCLC survival.