Epigenetic alterations are associated with tumor mutation burden in non-small cell lung cancer

Refining PD-1/PD-L1 assessment for biomarker-guided immunotherapy: A review

Anti-programmed cell death ligand 1 (anti-PD-L1)  immunotherapy is an increasingly crucial in cancer treatment. To date, the Federal Drug Administration (FDA) has approved four PD-L1 immunohistochemistry (IHC) staining protocols, commercially available in the form of "kits", facilitating testing for PD-L1 expression. These kits comprise four PD-L1 antibodies on two separate IHC platforms, each utilizing distinct, non-interchangeable scoring systems. Several factors, including tumor heterogeneity and the size of the tissue specimens assessed, can lead to PD-L1 status misclassification, potentially hindering the initiation of therapy. Therefore, the development of more accurate predictive biomarkers to distinguish between responders and non-responders prior to anti-PD-1/PD-L1 therapy warrants further research. Achieving this goal necessitates refining sampling criteria, enhancing current methods of PD-L1 detection, and deepening our understanding of the impact of additional biomarkers. In this article, we review potential solutions to improve the predictive accuracy of PD-L1 assessment in order to more precisely anticipate patients' responses to anti-PD-1/PD-L1 therapy, monitor disease progression and predict clinical outcomes.

Biomarkers and experimental models for cancer immunology investigation

The rapid advancement of tumor immunotherapies poses challenges for the tools used in cancer immunology research, highlighting the need for highly effective biomarkers and reproducible experimental models. Current immunotherapy biomarkers encompass surface protein markers such as PD-L1, genetic features such as microsatellite instability, tumor-infiltrating lymphocytes, and biomarkers in liquid biopsy such as circulating tumor DNAs. Experimental models, ranging from 3D in vitro cultures (spheroids, submerged models, air-liquid interface models, organ-on-a-chips) to advanced 3D bioprinting techniques, have emerged as valuable platforms for cancer immunology investigations and immunotherapy biomarker research. By preserving native immune components or coculturing with exogenous immune cells, these models replicate the tumor microenvironment in vitro. Animal models like syngeneic models, genetically engineered models, and patient-derived xenografts provide opportunities to study in vivo tumor-immune interactions. Humanized animal models further enable the simulation of the human-specific tumor microenvironment. Here, we provide a comprehensive overview of the advantages, limitations, and prospects of different biomarkers and experimental models, specifically focusing on the role of biomarkers in predicting immunotherapy outcomes and the ability of experimental models to replicate the tumor microenvironment. By integrating cutting-edge biomarkers and experimental models, this review serves as a valuable resource for accessing the forefront of cancer immunology investigation.

Relationship among DDR gene mutations, TMB and PD-L1 in solid tumour genomes identified using clinically actionable biomarker assays

The DNA damage response (DDR) pathway regulates DNA repair and cell survival, and inactivating mutations in DDR genes can increase tumour mutational burden (TMB), a predictive biomarker of treatment benefit from anti-PD-1/PD-L1 immunotherapies. However, a better understanding of the relationship among specific DDR mutations, TMB and PD-L1 expression is needed to improve translational strategies. Here, we determined genomic alteration frequencies in selected DDR genes that are clinically actionable biomarkers and investigated their association with TMB and PD-L1 in bladder, colorectal, non-small cell lung, ovarian and prostate cancers using the FoundationInsights® web portal. Our results not only confirm known associations, such as mismatch repair and POLE gene mutations with high TMB, but also identify significant associations between mutations in the SWI/SNF chromatin remodelling genes ARID1A and SMARCA4 and high TMB in multiple tumour types. Mutations in the ATR gene were associated with high TMB in colorectal and prostate cancers; however, associations between individual DDR mutations and high PD-L1 expression were uncommon and tumour-type specific. Finally, we found that high TMB and high PD-L1 expression were poorly associated, emphasising their independence as predictive biomarkers for immune checkpoint inhibitor use.

Luteolin inhibits A549 cells proliferation and migration by down-regulating androgen receptors

BACKGROUND

Yi Fei Qing Hua Granules (YQG) is a traditional Chinese herbal medicine with the effects of inhibiting the proliferation of lung cancer cells. Luteolin is one of the active compounds of YQG. Luteolin is a common flavonoid extracted from natural herbs and it can promote cancer cells apoptosis has been reported. However, the underlying molecular mechanism and effects of luteolin on human lung cancer needs to be validated.

METHODS

Molecular docking, network pharmacology methods and quantitative structure-activity relationship (QSAR) model were used to identify the active components of YQG and their possible mechanisms of action. Western blot analysis was used to measure AR expression in A549 cells. Cell migration assays were used to detect A549 cells proliferation transfected by AR plasmid and AR mutation plasmid, respectively.

RESULTS

TCMSP search results revealed that there are 182 active compounds in YQG, which correspond to 232 target genes. Sixty-one genes were overlapping genes in the 2 datasets of TCMSP and GeneCards. Through bioinformatics tagging of these overlapping genes, a total of 1,951 GO functional tagging analysis and 133 KEGG pathways were obtained. Through molecular docking technology and QSAR model verification, the multi-target active compound luteolin was screened out as one of the active components of YQG for in vitro verification. Androgen receptor (AR) was the hub protein with the highest docking score of luteolin. Western blot showed that luteolin could inhibit AR protein expression in lung cancer cell line A549. After the phosphorylation site of AR protein 877 was inactivated, the ability of luteolin to inhibit the proliferation of lung cancer cells was weakened. Luteolin significantly inhibited the growth of A549 xenogeneic tumors at day 25 and 28 and inhibited the expression of AR.

CONCLUSION

In this study, we have explored luteolin as one of the active components of YQG, and may inhibit the proliferation and migration of A549 cells by decreasing the expression of AR and the regulation of phosphorylation at AR-binding sites.

FAM3 family genes are associated with prognostic value of human cancer: a pan-cancer analysis

Family with sequence similarity three member (FAM3) plays a crucial role in the malignant development of various cancers of human. However, there remains doubtful what specific role of FAM3 family genes in pan-cancer. Our study aimed to investigate the role of FAM3 family genes in prognosis, immune subtype, tumor immune microenvironment, stemness score, and anticancer drug sensitivity of pan-cancer. We obtained data from UCSC Xena GDC and CellMiner databases, and used them to study the correlation of the expression, survival, immune subtype, tumor microenvironment, stemness score, and anticancer drug sensitivity between FAM3 family genes with pan-cancer. Furthermore, we investigated the tumor cellular functions and clinical prognostic value FAMC3 in pancreatic cancer (PAAD) using cellular experiments and tissue microarray. Cell Counting Kit-8 (CCK-8), transwell invasion, wound-healing and apoptosis assays were performed to study the effect of FAM3C on SW1990 cells' proliferation, migration, invasion and apoptosis. Immunohistochemical staining was used to study the relationship between FAM3C expression and clinical characteristics of pancreatic cancer patients. The results revealed that FAM3 family genes are significantly differential expression in tumor and adjacent normal tissues in 7 cancers (CHOL, HNSC, KICH, LUAD, LUSC, READ, and STAD). The expression of FAM3 family genes were negatively related with the RNAss, and robust correlated with immune type, tumor immune microenvironment and drug sensitivity. The expression of FAM3 family genes in pan-cancers were significantly different in immune type C1 (wound healing), C2 (IFN-gamma dominant), C3 (inflammatory), C4 (lymphocyte depleted), C5 (immunologically quiet), and C6 (TGF-beta dominant). Meanwhile, overexpression FAM3C promoted SW1990 cells proliferation, migration, invasion and suppressed SW1990 cells apoptosis. While knockdown of FAM3C triggered opposite results. High FAM3C expression was associated with duodenal invasion, differentiation and liver metastasis. In summary, this study provided a new perspective on the potential therapeutic role of FAM3 family genes in pan-cancer. In particular, FAM3C may play an important role in the occurrence and progression of PAAD.

Potential biomarkers for immunotherapy in non-small-cell lung cancer

For individuals with advanced or metastatic non-small cell lung cancer (NSCLC), the primary treatment is platinum-based doublet chemotherapy. Immune checkpoint inhibitors (ICIs), primarily PD-1/PD-L1 and CTLA-4, have been found to be effective in patients with NSCLC who have no EGFR/ALK mutations. Furthermore, ICIs are considered a standard therapy. The quantity of fresh immunogenic antigens discovered by cytotoxic T cells was measured by PD-L1 expression and tumor mutational burden (TMB), which were the first biomarkers assessed in clinical trials. However, immunotherapy did not have response efficacy markers similar to targeted therapy, highlighting the significance of newly developed biomarkers. This investigation aims to review the research on immunotherapy for NSCLC, focusing primarily on the impact of biomarkers on efficacy prediction to determine whether biomarkers may be utilized to evaluate the effectiveness of immunotherapy.

DNA methylation-based patterns for early diagnostic prediction and prognostic evaluation in colorectal cancer patients with high tumor mutation burden

Background

Immune checkpoint inhibitor (ICI) therapy has proven to be a promising treatment for colorectal cancer (CRC). We aim to investigate the relationship between DNA methylation and tumor mutation burden (TMB) by integrating genomic and epigenetic profiles to precisely identify clinical benefit populations and to evaluate the effect of ICI therapy.

Methods

A total of 536 CRC tissues from the Cancer Genome Atlas (TCGA) with mutation data were collected and subjected to calculate TMB. 80 CRC patients with high TMB and paired normal tissues were selected as training sets and developed the diagnostic and prognostic methylation models, respectively. In the validation set, the diagnostic model was validated in our in-house 47 CRC tissues and 122 CRC tissues from the Gene Expression Omnibus (GEO) datasets, respectively. And a total of 38 CRC tissues with high TMB from the COLONOMICS dataset verified the prognostic model.

Results

A positive correlation between differential methylation positions and TMB level was observed in TCGA CRC cohort (r=0.45). The diagnostic score that consisted of methylation levels of four genes (ADHFE1, DOK6, GPR75, and MAP3K14-AS1) showed high diagnostic performance in the discovery (AUC=1.000) and two independent validation (AUC=0.946, AUC=0.857) datasets. Additionally, these four genes showed significant positive correlations with NK cells. The prognostic score containing three genes (POU3F3, SYN2, and TMEM178A) had significantly poorer survival in the high-risk TMB samples than those in the low-risk TMB samples (P=0.016). CRC patients with low-risk scores combined with TMB levels represent a favorable survival.

Conclusions

By integrating analyses of methylation and mutation data, it is suggested that DNA methylation patterns combined with TMB serve as a novel potential biomarker for early screening in more high-TMB populations and for evaluating the prognostic effect of CRC patients with ICI therapy.

Genomic instability drives tumorigenesis and metastasis and its implications for cancer therapy

Genetic instability can be caused by external factors and may also be associated with intracellular damage. At the same time, there is a large body of research investigating the mechanisms by which genetic instability occurs and demonstrating the relationship between genomic stability and tumors. Nowadays, tumorigenesis development is one of the hottest research areas. It is a vital factor affecting tumor treatment. Mechanisms of genomic stability and tumorigenesis development are relatively complex. Researchers have been working on these aspects of research. To explore the research progress of genomic stability and tumorigenesis, development, and treatment, the authors searched PubMed with the keywords "genome instability" "chromosome instability" "DNA damage" "tumor spread" and "cancer treatment". This extracts the information relevant to this study. Results: This review introduces genomic stability, drivers of tumor development, tumor cell characteristics, tumor metastasis, and tumor treatment. Among them, immunotherapy is more important in tumor treatment, which can effectively inhibit tumor metastasis and kill tumor cells. Breakthroughs in tumorigenesis development studies and discoveries in tumor metastasis will provide new therapeutic techniques. New tumor treatment methods can effectively prevent tumor metastasis and improve the cure rate of tumors.

DNA and histone modifications as potent diagnostic and therapeutic targets to advance non-small cell lung cancer management from the perspective of 3P medicine

Lung cancer has a very high mortality in females and males. Most (~ 85%) of lung cancers are non-small cell lung cancers (NSCLC). When lung cancer is diagnosed, most of them have either local or distant metastasis, with a poor prognosis. In order to achieve better outcomes, it is imperative to identify the molecular signature based on genetic and epigenetic variations for different NSCLC subgroups. We hypothesize that DNA and histone modifications play significant roles in the framework of predictive, preventive, and personalized medicine (PPPM; 3P medicine). Epigenetics has a significant impact on tumorigenicity, tumor heterogeneity, and tumor resistance to chemotherapy, targeted therapy, and immunotherapy. An increasing interest is that epigenomic regulation is recognized as a potential treatment option for NSCLC. Most attention has been paid to the epigenetic alteration patterns of DNA and histones. This article aims to review the roles DNA and histone modifications play in tumorigenesis, early detection and diagnosis, and advancements and therapies of NSCLC, and also explore the connection between DNA and histone modifications and PPPM, which may provide an important contribution to improve the prognosis of NSCLC. We found that the success of targeting DNA and histone modifications is limited in the clinic, and how to combine the therapies to improve patient outcomes is necessary in further studies, especially for predictive diagnostics, targeted prevention, and personalization of medical services in the 3P medicine approach. It is concluded that DNA and histone modifications are potent diagnostic and therapeutic targets to advance non-small cell lung cancer management from the perspective of 3P medicine.

New insights into epigenetic regulation of resistance to PD-1/PD-L1 blockade cancer immunotherapy: mechanisms and therapeutic opportunities

Programmed cell death protein 1(PD-1) is a type of immune-inhibitory checkpoint protein, which delivers inhibitory signals to cytotoxic T cells by binding to the programmed death ligand-1 (PD-L1) displayed on the surface of cancer cells. Antibodies blocking PD-1/PD-L1 interaction have been extensively used in treatment of human malignancies and have achieved promising outcomes in recent years. However, gradual development of resistance to PD-1/PD-L1 blockade has decreased the effectiveness of this immunotherapy in cancer patients. The underlying epigenetic mechanisms need to be elucidated for application of novel strategies overcoming this immunotherapy resistance. Epigenetic aberrations contribute to cancerogenesis by promoting different hallmarks of cancer. Moreover, these alterations may lead to therapy resistance, thereby leading to poor prognosis. Recently, the epigenetic regulatory drugs have been shown to decrease the resistance to PD-1/PD-L1 inhibitors in certain cancer patients. Inhibitors of the non-coding RNAs, DNA methyltransferases, and histone deacetylases combined with PD-1/PD-L1 inhibitors have shown considerable therapeutic efficacy against carcinomas as well as blood cancers. Importantly, DNA methylation-mediated epigenetic silencing can inhibit antigen processing and presentation, which promotes cancerogenesis and aggravates resistance to PD-1/PD-L1 blockade immunotherapy. These observations altogether suggest that the combination of the epigenetic regulatory drugs with PD-1/PD-L1 inhibitors may present potential solution to the resistance caused by monotherapy of PD-1/PD-L1 immunotherapy.

DNMT3b-mediated SPAG6 promoter hypermethylation affects lung squamous cell carcinoma development through the JAK/STAT pathway

BACKGROUND

DNA methylation controls the transcription of genes and is involved in the development of lung cancer. Our preliminary bioinformatics prediction revealed that sperm associated antigen 6 (SPAG6) was considerably hypermethylated in lung squamous cell carcinoma (LUSC). Thus, this study aimed to probe the mechanism underlying its hypermethylation.

METHODS

The effect of DNA methylation of SPAG6 on its expression in LUSC was analyzed. The contributors to SPAG6 DNA hypermethylation were sought. CCK-8, EdU, and Transwell assays were carried out to assess the malignant phenotype of LUSC cells. KEGG pathway enrichment analysis was used to screen for pathways affected by SPAG6, which were confirmed by dual-luciferase assays. Bioinformatics analysis was conducted to dissect the impact of SPAG6 on the immune response and cancer cell stemness in LUSC.

RESULTS

DNA methyltransferase 3b (DNMT3b)-mediated hypermethylation of the SPAG6 promoter in LUSC led to SPAG6 downregulation. SPAG6 reverted the malignant phenotype of LUSC cells. SPAG6 regulated the JAK/STAT pathway by inhibiting the transcription of STAT1 and STAT3. The expression of SPAG6 was positively related to immune infiltration in LUSC and inversely related to the expressions of the immunosuppressive genes CTLA4 and PDCD1. SPAG6 expression was negatively correlated with cancer cell stemness in LUSC, and its expression inhibited the expressions of Nanog, ALDH1, and Sox2, markers of cancer cell stemness.

CONCLUSIONS

DNMT3b-mediated SPAG6 promoter hypermethylation activates the JAK/STAT pathway to promote LUSC progression.

TP53 R273C Mutation Is Associated With Poor Prognosis in LGG Patients

Purpose: With the progress of cancer immunotherapy, hotspot mutations of common oncogenes and tumor suppressors are becoming new potential therapeutic targets. TP53 R273C mutation is one of the hotspot mutations of TP53, and it has a higher frequency in low-grade glioma (LGG). However, the function of this mutation and its prognostic significance in LGG are not still clear.

Methods: To address this question, RNA sequencing, clinical, and SNP data of LGG patients from the TCGA database were downloaded. The Kaplan–Meier (KM) method was used for survival analysis. Immune cell populations in this cohort were assessed via the MCP counter and CIBERSORT. DNA damage/repair scores were calculated by GSVA analysis. WGCNA was conducted to identify genes related to TMB.

Results: In the context of IDH1/2 mutation, LGG patients with TP53 R273C mutation had worse prognosis than other mutation types and wild types. This conclusion is still valid in LGG patients who had received chemotherapy or radiotherapy. Considering the 1p19q codeletion status, it was found that patients with both R273C mutation and 1p19q non-codeletion had the worst prognosis. Further analysis showed that LGG patients with TP53 R273C mutation had higher M2 macrophage infiltration and tumor mutation burden (TMB) than that of TP53 wild-type LGG patients, and higher TMB indicates poor prognosis in LGG patients. Furthermore, we identified genes which could be associated with higher M2 macrophage infiltration and TMB in LGG patients with TP53 R273C mutation.

Conclusion: The study indicates that TP53 R273C mutation is very likely oncogenic and may be used as an indicator of the prognosis of LGG.

Genomic profiles and their associations with TMB, PD-L1 expression, and immune cell infiltration landscapes in synchronous multiple primary lung cancers

Background

Diagnosing and treating patients with multiple primary lung cancers (MPLCs) bring challenges to the clinic, and the preliminary evidence has revealed unsatisfying outcomes after targeted therapy and immunotherapy. Therefore, we surveyed genomic profiles of MPLCs and their possible associations with tumor mutation burden (TMB), programmed death-ligand 1 (PD-L1), and the immune cell infiltration landscape.

Materials and methods

A total of 112 patients with MPLCs with surgically resected 294 tumors were eligible, and 255 tumors were sequenced using a 1021-gene panel. Immunohistochemistry staining was performed to evaluate the levels of PD-L1 and the density of CD3+/CD8+ tumor-infiltrating lymphocytes (TILs), and CD68+/CD163+ tumor-associated macrophages (TAMs) at the central tumor and invasive margin, and immunotypes were generated based on those variables.

Results

MPLCs often occur simultaneously in non-smoker women younger than 60 years and manifest as ground-glass opacities, adenocarcinoma, and stage I lung lesions. The most frequently mutated genes in the 255 tumors were EGFR (56%), ERBB2 (12%), TP53 (12%), BRAF (11%), RBM10 (11%), and KRAS (9%). We found 87 (77.7%) patients with diverse genomic profiles, and 61 (54.5%) who shared at least one putative driver gene between different tumors presented more aggressive tumors. The median TMB was 1.92 mutations/Mb, and high-TMB (≥3) lesions often harbored EGFR^L858R/KRAS^G12C/RBM10/TP53/LRP1B mutations or wild-type ERBB2. Only 8.1% of patients and 3.9% of lesions were positive for PD-L1 on tumor cells, and this positivity was more frequent in LRP1B/TP53-mutant tumors. EGFR^L858R/RBM10/TP53 mutations were positively associated with specific immune cells and an inflamed immunotype, but ERBB2 mutations were negatively correlated. TMB, CD3+TILs, and CD68+/CD163+ TAMs presented with significant heterogeneity among paired tumors (all kappa <0.2), but PD-L1 and CD8 +TILs were more uniformly present in tumor pairs.

Conclusion

MPLCs are driven by different molecular events and often exhibit low TMB, low PD-L1, and a heterogeneous immune infiltration landscape. Specific genomic profiles are associated with TMB and the tumor immune microenvironmental landscape in MPLCs. Our findings can help to guide MPLCs diagnoses and to identify patient populations that may benefit from immunotherapy and targeted therapy.

Multiomics analysis of tumor mutational burden across cancer types

Whether tumor mutational burden (TMB) is related to improved survival outcomes or the promotion of immunotherapy in various malignant tumors remains controversial, and we lack a comprehensive understanding of TMB across cancers. Based on the data obtained from The Cancer Genome Atlas (TCGA), we conducted a multiomics analysis of TMB across 21 cancer types to identify characteristics related to TMB and determine the mechanism as it relates to prognosis, gene expression, gene mutation and signaling pathways. In our study, TMB was found to have a significant relationship with prognosis for 21 tumors, and the relationship was different in different tumors. TMB may also be related to different outcomes for patients with different tumor subtypes. TMB was confirmed to be correlated with clinical information, such as age and sex. Mutations in GATA3 and MAP3K1 in beast invasive carcinoma (BRCA), TCF7L2 in colon adenocarcinoma (COAD), NFE2L2 in esophageal carcinoma (ESCA), CIC and IDH1 in brain lower grade glioma (LGG), CDH1 in stomach adenocarcinoma (STAD), and TP53 in uterine corpus endometrial carcinoma (UCEC) were demonstrated to be correlated with lower TMB. Moreover, we identified differentially expressed genes (DEGs) and differentially methylated regions (DMRs) according to different TMB levels in 21 cancers. We also investigated the correlation between enrichment of signaling pathways, immune cell infiltration and TMB. In conclusion, we identified multiomic characteristics related to the TMB in 21 tumors, providing support for a comprehensive understanding of the role of TMB in different tumors.

DNA methylation in lung cancer patients: Opening a "window of life" under precision medicine

DNA methylation is a work of adding a methyl group to the 5th carbon atom of cytosine in DNA sequence under the catalysis of DNA methyltransferase (DNMT) to produce 5-methyl cytosine. Some current studies have elucidated the mechanism of lung cancer occurrence and causes of lung cancer progression and metastasis from the perspective of DNA methylation. Moreover, many studies have shown that smoking can change the methylation status of some gene loci, leading to the occurrence of lung cancer, especially central lung cancer. This review mainly introduces the role of DNA methylation in the pathogenesis, early diagnosis and screening, progression and metastasis, treatment, and prognosis of lung cancer, as well as the latest progress. We point out that methylation markers, sample tests, and methylation detection limit the clinical application of DNA methylation. If the liquid biopsy is to become the main force in lung cancer diagnosis, it must make efficient use of limited samples and improve the sensitivity and specificity of the tests. In addition, we also put forward our views on the future development direction of DNA methylation.

NSCLC Biomarkers to Predict Response to Immunotherapy with Checkpoint Inhibitors (ICI): From the Cells to In Vivo Images

Lung cancer remains the leading cause of cancer-related death, and it is usually diagnosed in advanced stages (stage III or IV). Recently, the availability of targeted strategies and of immunotherapy with checkpoint inhibitors (ICI) has favorably changed patient prognosis. Treatment outcome is closely related to tumor biology and interaction with the tumor immune microenvironment (TME). While the response in molecular targeted therapies relies on the presence of specific genetic alterations in tumor cells, accurate ICI biomarkers of response are lacking, and clinical outcome likely depends on multiple factors that are both host and tumor-related. This paper is an overview of the ongoing research on predictive factors both from in vitro/ex vivo analysis (ranging from conventional pathology to molecular biology) and in vivo analysis, where molecular imaging is showing an exponential growth and use due to technological advancements and to the new bioinformatics approaches applied to image analyses that allow the recovery of specific features in specific tumor subclones.

Harnessing the epigenome to boost immunotherapy response in non-small cell lung cancer patients

The introduction of immune checkpoint inhibitor (ICI)-based therapy for non-oncogene addicted non-small cell lung cancer (NSCLC) has significantly transformed the treatment landscape of the disease. Inhibitors of the programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) immune checkpoint axis, which were initially considered as a late-line treatment option, gradually became the standard of care as first-line treatment for subgroups of NSCLC patients. However, a significant fraction of patients either fails to respond or progresses after a partial response to ICI treatment. Thus, the identification of mechanisms responsible for innate and acquired resistance to immunotherapy within a rapidly evolving tumor microenvironment (TME) is urgently required, as is the identification of reliable predictive biomarkers beyond PD-L1 expression. The deregulation of the epigenome is a key driver of cancer initiation and progression, and it has also been shown to drive therapeutic resistance. Tumor education of infiltrating myeloid cells towards an immuno-suppressive phenotype as well as induction of T-cell dysfunction in the TME is also driven by epigenome reprogramming. As it stands and, given their dynamic nature, epigenetic changes in cancer and non-cancer cells represent an attractive target to increase immunotherapy activity in NSCLC. Accordingly, clinical trials of combinatorial immuno-epigenetic drug regimens have been associated with tumor response in previously immunotherapy-resistant NSCLC patients irrespective of their PD-L1 status. Moreover, epigenetic signatures might represent valuable theragnostic biomarkers as they can be assayed easily in liquid biopsy and provide multiple layers of information. In this review, we discuss the current knowledge regarding the dysregulated epigenetic mechanisms contributing to immunotherapy resistance in NSCLC. Although the clinical data are still maturing, we highlight the attractive perspective that the synergistic model of immuno-epigenetic strategies might overcome the current limitations of immunotherapy alone and will be translated into durable clinical benefit for a broader NSCLC population.

Identification of a methylomics-associated nomogram for predicting overall survival of stage I-II lung adenocarcinoma

The aim of this paper was to identify DNA methylation based biomarkers for predicting overall survival (OS) of stage I–II lung adenocarcinoma (LUAD) patients. Methylation profile data of patients with stage I–II LUAD from The Cancer Genome Atlas (TCGA) database was used to determine methylation sites-based hallmark for stage I–II LUAD patients’ OS. The patients were separated into training and validation datasets by using median risk score as cutoff. Univariate Cox, least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses were employed to develop a DNA methylation signature for OS of patients with stage I–II LUAD. As a result, an 11-DNA methylation signature was determined to be critically associated with the OS of patients with stage I–II LUAD. Analysis of receiver operating characteristics (ROC) suggested a high prognostic effectiveness of the 11-DNA methylation signature in patients with stage I–II LUAD (AUC at 1, 3, 5 years in training set were (0.849, 0.879, 0.831, respectively), validation set (0.742, 0.807, 0.904, respectively), entire TCGA dataset (0.747, 0.818, 0.870, respectively). Kaplan–Meier survival analyses exhibited that survival was significantly longer in the low-risk cohort compared to the high-risk cohort in the training dataset (P = 7e − 07), in the validation dataset (P = 1e − 08), and in the all-cohort dataset (P = 6e − 14). In addition, a nomogram was developed based on molecular factor (methylation risk score) as well as clinical factors (age and cancer status) (AUC at 1, 3, 5 years entire TCGA dataset were 0.770, 0.849, 0.979, respectively). The result verified that our methylomics-associated nomogram had a strong robustness for predicting stage I–II LUAD patients’ OS. Furthermore, the nomogram combined clinical and molecular factors to determine an individualized probability of recurrence for patients with stage I–II LUAD, which stood for a major advance in the field of personalized medicine for pulmonary oncology. Collectively, we successfully identified a DNA methylation biomarker and a DNA methylation-based nomogram to predict the OS of patients with stage I–II LUAD.

Influence of low tumor content on tumor mutational burden estimation by whole-exome sequencing and targeted panel sequencing

BACKGROUND

Tumor mutational burden (TMB) is a promising biomarker for stratifying patient subpopulation who would benefit from immune checkpoint blockade (ICB) therapies. Although great efforts have been made for standardizing TMB measurement, mutation calling and TMB quantification can be challenging in samples with low tumor content including liquid biopsies. The effect of varying tumor content on TMB estimation by different assay methods has never been systematically investigated.

METHOD

We established a series of reference standard DNA samples derived from 11 pairs of tumor-normal matched human cell lines across different cancer types. Each tumor cell line was mixed with its matched normal at 0% (control), 1%, 2%, 5%, and 10% mass-to-mass ratio to mimic the clinical samples with low tumor content. TMB of these reference standards was evaluated by both ∼1000× whole-exome sequencing (wesTMB) and targeted panel sequencing (psTMB) at four different vendors. Both regression and classification analyses of TMB were performed for theoretical investigation and clinical practice purposes.

RESULTS

Linear regression model was established that demonstrated in silico psTMB determined by regions of interest (ROI) as a great representative of wesTMB based on TCGA dataset. It was also true in our reference standard samples as the predicted psTMB interval based on the observed wesTMB captured the intended 90% of the in silico psTMB values. Although ∼1000× deep WES was applied, reference standard samples with less than 5% of tumor proportions are below the assay limit of detection (LoD) of wesTMB quantification. However, predicted wesTMB based on observed psTMB accurately classify (>0.97 AUC) for TMB high and low patient stratification even in samples with 2% of tumor content, which is more clinically relevant, as TMB determination should be a qualitative assay for TMB high and low patient classification. One targeted panel sequencing vendor using an optimized blood psTMB pipeline can further classify TMB status accurately (>0.82 AUC) in samples with only 1% of tumor content.

CONCLUSIONS

We developed a linear model to establish the quantitative correlation between wesTMB and psTMB. A set of DNA reference standards was produced in aid to standardize TMB measurements in samples with low tumor content across different targeted sequencing panels. This study is a significant contribution aiming to harmonize TMB estimation and extend its future application in clinical samples with low tumor content including liquid biopsy.

Statistical and bioinformatic analysis of hemimethylation patterns in non-small cell lung cancer

Background

DNA methylation is an epigenetic event involving the addition of a methyl-group to a cytosine-guanine base pair (i.e., CpG site). It is associated with different cancers. Our research focuses on studying non-small cell lung cancer hemimethylation, which refers to methylation occurring on only one of the two DNA strands. Many studies often assume that methylation occurs on both DNA strands at a CpG site. However, recent publications show the existence of hemimethylation and its significant impact. Therefore, it is important to identify cancer hemimethylation patterns.

Methods

In this paper, we use the Wilcoxon signed rank test to identify hemimethylated CpG sites based on publicly available non-small cell lung cancer methylation sequencing data. We then identify two types of hemimethylated CpG clusters, regular and polarity clusters, and genes with large numbers of hemimethylated sites. Highly hemimethylated genes are then studied for their biological interactions using available bioinformatics tools.

Results

In this paper, we have conducted the first-ever investigation of hemimethylation in lung cancer. Our results show that hemimethylation does exist in lung cells either as singletons or clusters. Most clusters contain only two or three CpG sites. Polarity clusters are much shorter than regular clusters and appear less frequently. The majority of clusters found in tumor samples have no overlap with clusters found in normal samples, and vice versa. Several genes that are known to be associated with cancer are hemimethylated differently between the cancerous and normal samples. Furthermore, highly hemimethylated genes exhibit many different interactions with other genes that may be associated with cancer. Hemimethylation has diverse patterns and frequencies that are comparable between normal and tumorous cells. Therefore, hemimethylation may be related to both normal and tumor cell development.

Conclusions

Our research has identified CpG clusters and genes that are hemimethylated in normal and lung tumor samples. Due to the potential impact of hemimethylation on gene expression and cell function, these clusters and genes may be important to advance our understanding of the development and progression of non-small cell lung cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07990-7.

PD-L1 versus tumor mutation burden: Which is the better immunotherapy biomarker in advanced non-small cell lung cancer?

PD-L1 and tumor mutation burden (TMB) are the most widely used immunotherapy biomarkers to identify populations who would attain clinical benefit, with the higher values predicting better therapeutic efficacy. This review addresses the predictive values and unresolved challenges of these two biomarkers. PD-1 and PD-L1 inhibitors have induced durable and effective responses in patients with advanced non-small cell lung cancer, confirmed by multiple clinical trials and real-world studies. Different clinical trials, involving both PD-1/PD-L1 inhibitors alone and combination regimens, adopted either PD-L1 or TMB to stratify the patients, although the predictive capabilities of these two biomarkers are different. In the first-line setting, PD-L1 of 50% or more as a cut-off value can help select candidates for pembrolizumab or atezolizumab monotherapy; however, these two biomarkers poorly predict the efficacy of immunotherapy combination regimens as first-line treatments. In the second-line setting, although patients can benefit from nivolumab regardless of PD-L1 expression, both PD-L1 and blood TMB can be used as biomarkers to find patients suitable for atezolizumab. Except for inaccurate predictiveness, there are many unresolved problems with regard to the two biomarkers, such as the lack of standard detection methods, and their susceptibilities to other dynamic changes. The predictive values of TMB and PD-L1 were low in most circumstances; however, PD-L1 expression greater than ≥ 50% can help select appropriate patients for pembrolizumab and atezolizumab, respectively, as first-line monotherapies. Higher PD-L1 or TMB was associated with greater efficacy for atezolizumab as a second-line monotherapy.

Difference of copy number variation in blood of patients with lung cancer

BACKGROUND

Lung cancer is the leading cause of cancer-related deaths worldwide. Copy number variation (CNV) in several genetic regions correlate with cancer susceptibility. Hence, this study evaluated the association between CNV and non-small cell lung cancer (NSCLC) in the peripheral blood.

METHODS

Blood samples of 150 patients with NSCLC and 150 normal controls were obtained from a bioresource center (Seoul, Korea). Through an epigenome-wide analysis using the MethylationEPIC BeadChip method, we extracted CNVs by using an SVS8 software-supplied multivariate method. We compared CNV frequencies between the NSCLC and controls, and then performed stratification analyses according to smoking status.

RESULTS

We acquired 979 CNVs, with 582 and 967 copy-number gains and losses, respectively. We identified five nominally significant associations (ACOT1, NAA60, GSDMD, HLA-DPA1, and SLC35B3 genes). Among the current smokers, the NSCLC group had more CNV losses and gains at the GSDMD gene in chromosome 8 (P=0.02) and at the ACOT1 gene in chromosome 14 (P=0.03) than the control group. It also had more CNV losses at the NAA60 gene in chromosome 16 (P=0.03) among non-smokers. In the NSCLC group, current smokers had more CNV gains and losses at the ACOT1 gene in chromosome 14 (P=0.003) and at HLA-DPA1 gene in chromosome 6 (P=0.02), respectively, than non-smokers.

CONCLUSION

Five nominally significant associations were found between the NSCLC and CNVs. CNVs are associated with the mechanism of lung cancer development. However, the role of CNVs in lung cancer development needs further investigation.

EZH2 inhibitors reverse resistance to gefitinib in primary EGFR wild-type lung cancer cells

Background

Lung cancer is the leading cause of cancer-related deaths worldwide. Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. In traditional anti-cancer therapy, epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKI) have been proven to be beneficial for patients with EGFR mutations. However, patients with EGFR wild-type NSCLC were usually not respond to EGFR-TKIs. Enhancer of zeste homolog 2 (EZH2) is a key molecular in the PRC2 complex and plays an important role in epigenetic regulation and is overexpressed in variant tumors. EZH2 inhibitors have been reported to sensitize variant tumor cells to anticancer drugs. This study aimed to investigate whether the EZH2 inhibitors, GSK343 and DZNep when combined with gefitinib can reverse EGFR-TKIs resistance in EGFR wild-type NSCLC cells.

Methods

The RNA-sequencing data of patients with NSCLC [502 patients with lung squamous cell carcinoma, including 49 paracancerous lung tissues and 513 patients with lung adenocarcinoma (LUAD), including 59 paracancerous lung tissues] from the Cancer Genome Atlas (TCGA), were analyzed for EZH2 expression. EZH2 expression was verified in 40 NSCLC tissue cancer samples and their corresponding paracancerous tissues from our institute (TJMUGH) via RT-PCR. A549 and H1299 cells treated with siRNA or EZH2 inhibitors were subjected to cell viability and apoptosis analyses as well to EGFR pathway proteins expression analyses via western blotting.

Results

EZH2 was upregulated in human NSCLC tissues and correlated with poor prognosis in patients with LUAD based on data from both TCGA and TJMUGH. Both GSK343 and DZNep sensitized EGFR wild-type LUAD cells (A549 and H1299) to gefitinib and suppressed cell viability and proliferation in vitro by downregulating the phosphorylation of EGFR and AKT and by inducing cell apoptosis. Co-administration of EZH2 inhibitors (GSK343 or DZNep) with gefitinib exerted a stronger inhibitory effect on tumor activity, cell proliferation and cell migration than single drug administration in vitro and in vivo.

Conclusions

These data suggest that the combination of EZH2 inhibitors with EGFR-TKIs may be an effective method for treating NSCLC-patients with EGFR-wild type, who do not want to undergo traditional treatment with chemotherapy.

Expression Profile Analysis of m6A RNA Methylation Regulators Indicates They Are Immune Signature Associated and Can Predict Survival in Kidney Renal Cell Carcinoma

N6-Methyladenosine (m6A) refers to the methylation modification occurring at the nitrogen-6 position of adenosine. Many human physiological processes such as modulation of spermatogenesis are caused by m6A RNA modifications. However, the relationship between m6A RNA methylation regulators and kidney renal clear cell carcinoma (KIRC) remains rarely investigated. This work aimed to explore the influence of m6A RNA methylation regulators in KIRC. We examined abnormally expressed m6A RNA methylation regulators among different clinicopathological features of KIRC. We recognized three subgroups (KIRC1, KIRC2, and KIRC3) with significant differences in overall survival through consensus clustering of m6A RNA methylation regulators. Surprisingly, KIRC2 displayed elevated immune activity, but high proportions of immune-inhibitory cells (Tregs and myeloid-derived suppressor cell) based on single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT analysis. Moreover, the KIRC2 subgroup had the lowest tumor mutation burden levels and the highest expression levels of 80% (12/15) of co-inhibitory molecules. Next, correlation analysis indicated that RBM15B expression was negatively correlated with multiple immune signatures, which was verified by ssGSEA and CIBERSORT analyses. Multiple immune-related and cancer-related pathways were enriched in the group with high RBM15B expression. Furthermore, a four-m6A RNA methylation regulator-based risk signature was constructed based on an ArrayExpress (E-MTAB-3267) dataset and confirmed in the The Cancer Genome Atlas (TCGA) testing cohort. In conclusion, our study successfully classified TCGA samples into three subgroups with different immune signatures, and suggested that the worse prognosis of KIRC2 is probably mediated by immune evasion. These findings will facilitate personalized immunotherapy in patients with KIRC. In addition, the risk score system was revealed as an independent prognostic marker that can predict survival in KIRC patients.

A Methylation-Based Reclassification of Bladder Cancer Based on Immune Cell Genes

Simple Summary

Bladder cancer (BC) development is highly related to immune cell infiltration. In this study, we aimed to construct a new classification of bladder cancer molecular subtypes based on immune-cell-associated CpG(Methylation) sites. The classification was accurate and stable. BC patients were successfully divided into three subtypes based on the immune-cell-associated CpG sites. The clinicopathologic features, distribution of immune cells, level of expression of checkpoints, stromal score, immune score, ESTIMATEScore, tumor purity, APC co_inhibition, APC co_stimulation, HLA, MHC class_I, Type I IFN_respons, Type II IFN response, and DNA stemness score (DNAss) presented significant differences among the three subgroups. The specific genomic alteration was also different across subgroups. High-level immune infiltration showed a correlation with high-level methylation. A lower RNA stemness score (RNAss) was associated with higher immune infiltration. Cluster 2 demonstrated a better response to chemotherapy. The anti-cancer targeted drug therapy results are different among the three subgroups.

Abstract

Background: Bladder cancer is highly related to immune cell infiltration. This study aimed to develop a new classification of BC molecular subtypes based on immune-cell-associated CpG sites. Methods: The genes of 28 types of immune cells were obtained from previous studies. Then, methylation sites corresponding to immune-cell-associated genes were acquired. Differentially methylated sites (DMSs) were identified between normal samples and bladder cancer samples. Unsupervised clustering analysis of differentially methylated sites was performed to divide the sites into several subtypes. Then, the potential mechanism of different subtypes was explored. Results: Bladder cancer patients were divided into three groups. The cluster 3 subtype had the best prognosis. Cluster 1 had the poorest prognosis. The distribution of immune cells, level of expression of checkpoints, stromal score, immune score, ESTIMATEScore, tumor purity, APC co_inhibition, APC co_stimulation, HLA, MHC class_I, Type I IFN Response, Type II IFN Response, and DNAss presented significant differences among the three subgroups. The distribution of genomic alterations was also different. Conclusions: The proposed classification was accurate and stable. BC patients could be divided into three subtypes based on the immune-cell-associated CpG sites. Specific biological signaling pathways, immune mechanisms, and genomic alterations were varied among the three subgroups. High-level immune infiltration was correlated with high-level methylation. The lower RNAss was associated with higher immune infiltration. The study of the intratumoral immune microenvironment may provide a new perspective for BC therapy.

Predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors

Although the clinical development of immune checkpoint inhibitors (ICIs) therapy has ushered in a new era of anti-tumor therapy, with sustained responses and significant survival advantages observed in multiple tumors, most patients do not benefit. Therefore, more and more attention has been paid to the identification and development of predictive biomarkers for the response of ICIs, and more in-depth and comprehensive understanding has been continuously explored in recent years. Predictive markers of ICIs efficacy have been gradually explored from the expression of intermolecular interactions within tumor cells to the expression of various molecules and cells in tumor microenvironment, and been extended to the exploration of circulating and host systemic markers. With the development of high-throughput sequencing and microarray technology, a variety of biomarker strategies have been deeply explored and gradually achieved the process from the identification of single marker to the development of multifactorial synergistic predictive markers. Comprehensive predictive-models developed by integrating different types of data based on different components of tumor-host interactions is the direction of future research and will have a profound impact in the field of precision immuno-oncology. In this review, we deeply analyze the exploration course and research progress of predictive biomarkers as an adjunctive tool to tumor immunotherapy in effectively identifying the efficacy of ICIs, and discuss their future directions in achieving precision immuno-oncology.

A novel tumor mutational burden estimation model as a predictive and prognostic biomarker in NSCLC patients

BACKGROUND

Tumor mutational burden (TMB) has both prognostic value in resected non-small cell lung cancer (NSCLC) patients and predictive value for immunotherapy response. However, TMB evaluation by whole-exome sequencing (WES) is expensive and time-consuming, hampering its application in clinical practice. In our study, we aimed to construct a mutational burden estimation model, with a small set of genes, that could precisely estimate WES-TMB and, at the same time, has prognostic and predictive value for NSCLC patients.

METHODS

TMB estimation model was trained based on genomic data from 1056 NSCLC samples from The Cancer Genome Atlas (TCGA). Validation was performed using three independent cohorts, including Rizvi cohort and our own Asian cohorts, including 89 early-stage and n late-stage Asian NSCLC patients, respectively. TCGA data were obtained on September 3, 2018. The two Asian cohort studies were performed from September 1, 2018, to March 5, 2019. Pearson's correlation coefficient was used to assess the performance of estimated TMB with WES-TMB. The Kaplan-Meier survival analysis was applied to evaluate the association of estimated TMB with disease-free survival (DFS), overall survival (OS), and response to anti-programmed death-1 (PD-1) and anti-programmed death-ligand 1 (PD-L1) therapy.

RESULTS

The estimation model, consisted of only 23 genes, correlated well with WES-TMB both in the training set of TCGA cohort and validation set of Rizvi cohort and our own Asian cohort. Estimated TMB by the 23-gene panel was significantly associated with DFS and OS in patients with early-stage NSCLC and could serve as a predictive biomarker for anti-PD-1 and anti-PD-L1 treatment response.

CONCLUSIONS

The 23-gene panel, instead of WES or the currently used panel-based methods, could be used to assess the WES-TMB with a high relevance. This customized targeted sequencing panel could be easily applied into clinical practice to predict the immunotherapy response and prognosis of NSCLC.

A prognostic 11-DNA methylation signature for lung squamous cell carcinoma

Background

Lung squamous cell carcinoma (LUSC), as the second frequent subtype of lung cancer, causes lots of mortalities primarily due to a lack of precise prognostic markers and timely treatment intervention. Previous studies have constructed several risk prognostic models based on DNA methylation sites in multiple tumors, whereas, DNA methylation signature of LUSC remains to be built, and its predictive value need to be evaluated.

Methods

The genome-wide DNA methylation data of LUSC samples was obtained from The Cancer Genome Atlas dataset. Univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) were implemented to identify DNA methylation sites related to overall survival of LUSC patients. Thus, we performed multivariate Cox regression to establish a DNA methylation signature. The Kaplan-Meier (K-M) survival curves and time-dependent receiver operating characteristic (ROC) curves were plotted to estimate the prognostic power of the signature. Comparison with other known prognostic biomarkers, our DNA methylation signature showed higher predictive specificity and sensitivity. In addition, multivariate Cox regression screened out independent prognostic factors and constructed a nomogram.

Results

Several statistical methods were performed to construct an 11-DNA methylation signature. LUSC patients were divided into low- and high-risk group based on risk score, and high-risk group had a shorter survival time. According to the results of K-M and ROC analyses, the 11-DNA methylation signature showed significant sensitivity and specificity in predicting the LUSC patients’ overall survival. Finally, we integrated some independent prognostic factors (risk score, metastasis stage, and tobacco smoking history) to construct a nomogram, which has excellent prognostic power and may provide guidance for the therapeutic strategies.

Conclusions

We constructed the first risk prognosis model based on DNA methylation site in LUSC, which showed better predictive ability. In addition, a nomogram integrating the DNA methylation signature, metastasis stage, and tobacco smoking history was developed.

Upregulated expression of pyruvate kinase M2 mRNA predicts poor prognosis in lung adenocarcinoma

Background

Pyruvate kinase M2 (PKM2) is critical regulator contributing to Warburg effect. However, the expression pattern and prognostic value of PKM2 remain unknown in lung adenocarcinoma (LUAD). The aim of this study is to clarify the prognostic value of PKM2 via intergrated bioinformatics analysis.

Methods

Firstly, mRNA expression levels of PKM2 in LUAD were systematically analyzed using the ONCOMINE and TCGA databases. Then, the association between PKM2 expression and clinical parameters was investigated by UALCAN. The Kaplan-Meier Plotter was used to assess the prognostic significance of PKM2. Finally, the relationship between PKM2 expression and its genetic and epigenetic changes was evaluated with MEXPRESS and MethHC database.

Results

Pooled analysis showed that PKM2 is frequently upregulated expression in LUAD. Subsequently, PKM2 expression was identified to be positively associated with tumor stage and lymph node metastasis and also strongly correlated with worse OS (P = 2.80e-14), PPS (P = 0.022), FP (P = 1.30e-6) and RFS (P = 3.41e-8). Importantly, our results demonstrated that over-expressed PKM2 is associated with PKM2 hypomethylation and copy number variations (CNVs).

Conclusion

This study confirms that over-expressed PKM2 in LUAD is associated with poor prognosis, suggesting that PKM2 might act as a promising prognostic biomarker and novel therapeutic target for LUAD.