Epigenetic prediction of response to anti-PD-1 treatment in non-small-cell lung cancer: a multicentre, retrospective analysis

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Decision model for durable clinical benefit from front- or late-line immunotherapy alone or with chemotherapy in non-small cell lung cancer

BACKGROUND

Predictive biomarkers and models of immune checkpoint inhibitors (ICIs) have been extensively studied in non-small cell lung cancer (NSCLC). However, evidence for many biomarkers remains inconclusive, and the opaqueness of machine learning models hinders practicality. We aimed to provide compelling evidence for biomarkers and develop a transparent decision tree model.

METHODS

We consolidated data from 3,288 ICI-treated patients with NSCLC across real-world multicenter, public cohorts and the Choice-01 trial (ClinicalTrials.gov: NCT03856411). Over 50 features were examined for predicting durable clinical benefits (DCBs) from ICIs. Noteworthy biomarkers were identified to establish a decision tree model. Additionally, we explored the tumor microenvironment and peripheral CD8+ programmed death-1 (PD-1)+ T cell receptor (TCR) profiles.

FINDINGS

Multivariate logistic regression analysis identified tumor histology, PD-ligand 1 (PD-L1) expression, tumor mutational burden, line, and regimen of ICI treatment as significant factors. Mutation subtypes of EGFR, KRAS, KEAP1, STK11, and disruptive TP53 mutations were associated with DCB. The decision tree (DT10) model, using the ten clinicopathological and genomic markers, showed superior performance in predicting DCB in the training set (area under the curve [AUC] = 0.82) and consistently outperformed other models in test sets. DT10-predicted-DCB patients manifested longer survival, an enriched inflamed tumor immune phenotype (67%), and higher peripheral TCR diversity, whereas the DT10-predicted-NDB (non-durable benefit) group showed an enriched desert immune phenotype (86%) and higher peripheral TCR clonality.

CONCLUSIONS

The model effectively predicted DCB after front-/subsequent-line ICI treatment, with or without chemotherapy, for squamous and non-squamous lung cancer, offering clinicians valuable insights into efficacy prediction using cost-effective variables.

FUNDING

This study was supported by the National Key R&D Program of China.

Identification of a DNA-methylome-based signature for prognosis prediction in driver gene-negative lung adenocarcinoma

"Driver gene-negative" lung adenocarcinoma (LUAD) was of rare treatment options and a poor prognosis. Presently, for them, few biomarkers are available for stratification analysis to make appropriate treatment strategy. This study aimed to develop a DNA-methylome-based signature to realize the precise risk-stratifying. Here, an Illumina MethylationEPIC Beadchip was applied to obtain differentially methylated CpG sites (DMCs). A four-CpG-based signature, named as TLA, was successfully established, whose prognosis-predicting power was well verified in one internal (n = 78) and other external (n = 110) validation cohorts. Patients with high-risk scores had shorter overall survival (OS) in all cohorts [hazard ratio (HR): 11.79, 5.16 and 2.99, respectively]. Additionally, it can effectively divide patients into low-risk and high-risk groups, with significantly different OS in the diverse subgroups stratified by the standard clinical parameters. As an independent prognostic factor, TLA may assist in improving the nomogram's 5-year OS-predicting ability (AUC 0.756, 95% CI:0.695-0.816), superior to TNM alone (AUC 0.644, 95% CI: 0.590-0.698). Additionally, the relationship of TLA-related genes, TAC1, LHX9, and ALX1, with prognosis and tumour invasion made them serve as potential therapy targets for driver gene-negative LUAD.

DNA methylation in human diseases

Aberrant epigenetic modifications, particularly DNA methylation, play a critical role in the pathogenesis and progression of human diseases. The current review aims to reveal the role of aberrant DNA methylation in the pathogenesis and progression of diseases and to discuss the original data obtained from international research laboratories on this topic. In the review, we mainly summarize the studies exploring the role of aberrant DNA methylation as diagnostic and prognostic biomarkers in a broad range of human diseases, including monogenic epigenetics, autoimmunity, metabolic disorders, hematologic neoplasms, and solid tumors. The last section provides a general overview of the possibility of the DNA methylation machinery from the perspective of pharmaceutic approaches. In conclusion, the study of DNA methylation machinery is a phenomenal intersection that each of its ways can reveal the mysteries of various diseases, introduce new diagnostic and prognostic biomarkers, and propose a new patient-tailored therapeutic approach for diseases.

Circulating biomarkers as predictors of response to immune checkpoint inhibitors in NSCLC: Are we on the right path?

Immune checkpoints inhibitors (ICIs) have markedly improved the therapeutic management of advanced NSCLC and, more recently, they have demonstrated efficacy also in the early-stage disease. Despite better survival outcomes with ICIs compared to standard chemotherapy, a large proportion of patients can derive limited clinical benefit from these agents. So far, few predictive biomarkers, including the programmed death-ligand 1 (PD-L1), have been introduced in clinical practice. Therefore, there is an urgent need to identify novel biomarkers to select patients for immunotherapy, to improve efficacy and avoid unnecessary toxicity. A deeper understanding of the mechanisms involved in antitumor immunity and advances in the field of liquid biopsy have led to the identification of a wide range of circulating biomarkers that could potentially predict response to immunotherapy. Herein, we provide an updated overview of these circulating biomarkers, focusing on emerging data from clinical studies and describing modern technologies used for their detection.

5-Hydroxymethylcytosine in Cell-Free DNA Predicts Immunotherapy Response in Lung Cancer

Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurately predicting individual patient responses to ICIs remains a challenge. We performed the genome-wide profiling of 5-hydroxymethylcytosine (5hmC) in 85 plasma cell-free DNA (cfDNA) samples from lung cancer patients and developed a 5hmC signature that was significantly associated with progression-free survival (PFS). We built a 5hmC predictive model to quantify the 5hmC level and validated the model in the validation, test, and control sets. Low weighted predictive scores (wp-scores) were significantly associated with a longer PFS compared to high wp-scores in the validation [median 7.6 versus 1.8 months; p = 0.0012; hazard ratio (HR) 0.12; 95% confidence interval (CI), 0.03-0.54] and test (median 14.9 versus 3.3 months; p = 0.00074; HR 0.10; 95% CI, 0.02-0.50) sets. Objective response rates in patients with a low or high wp-score were 75.0% (95% CI, 42.8-94.5%) versus 0.0% (95% CI, 0.0-60.2%) in the validation set (p = 0.019) and 80.0% (95% CI, 44.4-97.5%) versus 0.0% (95% CI, 0.0-36.9%) in the test set (p = 0.0011). The wp-scores were also significantly associated with PFS in patients receiving single-agent ICI treatment (p < 0.05). In addition, the 5hmC predictive signature demonstrated superior predictive capability to tumor programmed death-ligand 1 and specificity to ICI treatment response prediction. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. This study provides proof-of-concept evidence that the cfDNA 5hmC signature is a robust biomarker for predicting ICI treatment response in lung cancer.

Effectiveness of Immunotherapy in Non-Small Cell Lung Cancer Patients with a Diagnosis of COPD: Is This a Hidden Prognosticator for Survival and a Risk Factor for Immune-Related Adverse Events?

The interplay between the immune system and chronic obstructive pulmonary disease (COPD) and non-small cell lung cancer (NSCLC) is complex and multifaceted. In COPD, chronic inflammation and oxidative stress can lead to immune dysfunction that can exacerbate lung damage, further worsening the respiratory symptoms. In NSCLC, immune cells can recognise and attack the cancer cells, which, however, can evade or suppress the immune response by various mechanisms, such as expressing immune checkpoint proteins or secreting immunosuppressive cytokines, thus creating an immunosuppressive tumour microenvironment that promotes cancer progression and metastasis. The interaction between COPD and NSCLC further complicates the immune response. In patients with both diseases, COPD can impair the immune response against cancer cells by reducing or suppressing the activity of immune cells, or altering their cytokine profile. Moreover, anti-cancer treatments can also affect the immune system and worsen COPD symptoms by causing lung inflammation and fibrosis. Immunotherapy itself can also cause immune-related adverse events that could worsen the respiratory symptoms in patients with COPD-compromised lungs. In the present review, we tried to understand the interplay between the two pathologies and how the efficacy of immunotherapy in NSCLC patients with COPD is affected in these patients.

Could the sperm epigenome become a diagnostic tool for evaluation of the infertile man?

Although male infertility is currently diagnosed when abnormal sperm parameters are found, the poor predictive ability of sperm parameters on natural fecundity and medically assisted reproduction outcome poses the need for improved diagnostic techniques for male infertility. The accumulating evidence about the role played by the sperm epigenome in modulation of the early phases of embryonic development has led researchers to focus on the epigenetic mechanisms within the sperm epigenome to find new molecular markers of male infertility. Indeed, sperm epigenome abnormalities could explain some cases of unexplained male infertility in men showing normal sperm parameters and were found to be associated with poor embryo development in IVF cycles. The present mini-review summarizes the current knowledge about this interesting topic, starting from a description of the epigenetic mechanisms of gene expression regulation (i.e. DNA methylation, histone modifications, and non-coding RNAs' activity). We also discuss possible mechanisms by which environmental factors might cause epigenetic changes in the human germline and affect embryonic development, as well as subsequent generations' phenotypes. Studies demonstrating sperm epigenome abnormalities in men with male infertility are reviewed, with particular emphasis on those with the more severe form of spermatogenic dysfunction. Observations demonstrate that the diagnostic and prognostic efficacy of sperm epigenome evaluation will help facilitate the management of men with male factor infertility.

Blood Group Antigen A Carriers Exhibit an Extended Progression-Free Survival with no more Immune-Related Adverse Events

Extensive investigations have been conducted regarding the potential correlation between blood type and the immune system, as well as cancer risk in the Southern Chinese population. However, the prognostic value of the blood group and its genetic determinants in the context of immune checkpoint inhibitor (ICI) treatment remains unclear. Therefore, the associations between the ABO blood group and its single nucleotide polymorphisms (SNPs) were examined in relation to ICI treatment outcomes in 370 eligible patients with cancer. This approach allowed us to derive the blood group from the SNPs responsible for blood group determination. In the discovery cohort (N = 168), antigen A carriers (blood types A and AB) exhibited an extended progression-free survival (PFS; hazard ratio (HR) = 0.58, 95% confidence interval (CI) = 0.34-0.98). The association results from the SNP-derived blood were consistent with those from the measured blood group. In the validation cohort (N = 202), Cox regression analysis revealed that the antigen A carriers (rs507666 AA+GA genotype carriers) experienced significantly extended PFS compared with the non-antigen A carriers (HR = 0.61, 95% CI = 0.40-0.93). Therefore, a longer PFS was observed in antigen A carriers (P value = 0.003, HR = 0.60, 95% CI = 0.44-0.84). Furthermore, haplotype 2 carriers (rs507666 GA and rs659104 GG) demonstrated both extended PFS and improved overall survival. Notably, the presence of antigen A was not associated with the occurrence of overall immune-related adverse events (irAEs) or organ-specific toxicity. In summary, our findings revealed that antigen A carriers did not experience a higher incidence of irAEs while exhibiting better immunotherapy efficacy.

SP1 Gene Methylation in Head and Neck Squamous Cell Cancer in HPV-Negative Patients

There is still much to learn about the epigenetic mechanisms controlling gene expression during carcinogenesis. When researching aberrant DNA methylation, active proliferative tumor cells from head and neck squamous cell cancer (HNSCC) can be used as a model. The aim of the study was to investigate the methylation status of CDKN1, CDKN2A, MYC, Smad3, SP1, and UBC genes in tumor tissue (control-normal tissue) in 50 patients (37 men and 13 women) with HPV-negative HNSCC. Methods: Bisulfite conversion methods and methyl-sensitive analysis of high-resolution melting curves were used to quantify the methylation of genes. In all patients and across various subgroups (tongue carcinoma, laryngeal and other types of carcinomas T2, T3, T4 status; age before and after 50 years; smoking and non-smoking), there are consistent differences in the methylation levels in the SP1 gene in tumor DNA compared to normal. Results: The methylation of the SP1 gene in tumor DNA suppresses its expression, hinders HNSCC cell proliferation regulation, and could be a molecular indicator of malignant cell growth. The study of DNA methylation of various genes involved in carcinogenesis is promising because hypermethylated promoters can serve as potential biomarkers of disease.

The innovative checkpoint inhibitors of lung adenocarcinoma, cg09897064 methylation and ZBP1 expression reduction, have implications for macrophage polarization and tumor growth in lung cancer

Lung cancer, a prevalent and aggressive disease, is characterized by recurrence and drug resistance. It is essential to comprehend the fundamental processes and discover novel therapeutic objectives for augmenting treatment results. Based on our research findings, we have identified a correlation between methylation of cg09897064 and decreased expression of ZBP1, indicating a link to unfavorable prognosis in patients with lung cancer. Furthermore, these factors play a role in macrophage polarization, with ZBP1 upregulated in M1 macrophages compared to both M0 and M2 polarized macrophages. We observed cg09897064 methylation in M2 polarization, but not in M0 and M1 polarized macrophages. ATACseq analysis revealed closed chromatin accessibility of ZBP1 in M0 polarized macrophages, while open accessibility was observed in both M1 and M2 polarized macrophages. Our findings suggest that ZBP1 is downregulated in M0 polarized macrophages due to closed chromatin accessibility and downregulated in M2 polarized macrophages due to cg09897064 methylation. Further investigations manipulating cg09897064 methylation and ZBP1 expression through overexpression plasmids and shRNAs provided evidence for their role in modulating macrophage polarization and tumor growth. ZBP1 inhibits M2 polarization and suppresses tumor growth, while cg09897064 methylation promotes M2 polarization and macrophage-induced tumor growth. In mechanism investigations, we found that cg09897064 methylation impairs CEBPA binding to the ZBP1 promoter, leading to decreased ZBP1 expression. Clinical experiments were conducted to validate the correlation between methylation at cg09897064, ZBP1 expression, and macrophage M2 polarization. Targeting these factors may hold promise as a strategy for developing innovative checkpoint inhibitors in lung cancer treatment.

NSCLC: from tumorigenesis, immune checkpoint misuse to current and future targeted therapy

Non-small cell lung cancer (NSCLC) is largely promoted by a multistep tumorigenesis process involving various genetic and epigenetic alterations, which essentially contribute to the high incidence of mortality among patients with NSCLC. Clinical observations revealed that NSCLC also co-opts a multifaceted immune checkpoint dysregulation as an important driving factor in NSCLC progression and development. For example, a deregulated PI3K/AKT/mTOR pathway has been noticed in 50-70% of NSCLC cases, primarily modulated by mutations in key oncogenes such as ALK, EGFR, KRAS, and others. Additionally, genetic association studies containing patient-specific factors and local reimbursement criteria expose/reveal mutations in EGFR/ALK/ROS/BRAF/KRAS/PD-L1 proteins to determine the suitability of available immunotherapy or tyrosine kinase inhibitor therapy. Thus, the expression of such checkpoints on tumors and immune cells is pivotal in understanding the therapeutic efficacy and has been extensively studied for NSCLC treatments. Therefore, this review summarizes current knowledge in NSCLC tumorigenesis, focusing on its genetic and epigenetic intricacies, immune checkpoint dysregulation, and the evolving landscape of targeted therapies. In the context of current and future therapies, we emphasize the significance of antibodies targeting PD-1/PD-L1 and CTLA-4 interactions as the primary therapeutic strategy for immune system reactivation in NSCLC. Other approaches involving the promising potential of nanobodies, probodies, affibodies, and DARPINs targeting immune checkpoints are also described; these are under active research or clinical trials to mediate immune regulation and reduce cancer progression. This comprehensive review underscores the multifaceted nature, current state and future directions of NSCLC research and treatment.

DNA-methylome-derived epigenetic fingerprint as an immunophenotype indicator of durable clinical immunotherapeutic benefits in head and neck squamous cell carcinoma

BACKGROUND

Cancer immunotherapy provides durable response and improves survival in a subset of head and neck squamous cell carcinoma (HNSC) patients, which may due to discriminative tumor microenvironment (TME). Epigenetic regulations play critical roles in HNSC tumorigenesis, progression, and activation of functional immune cells. This study aims to identify an epigenetic signature as an immunophenotype indicator of durable clinical immunotherapeutic benefits in HNSC patients.

METHODS

Unsupervised consensus clustering approach was applied to distinguish immunophenotypes based on five immune signatures in The Cancer Genome Atlas (TCGA) HNSC cohort. Two immunophenotypes (immune 'Hot' and immune 'Cold') that had different TME features, diverse prognosis, and distinct DNA methylation patterns were recognized. Immunophenotype-related methylated signatures (IPMS) were identified by the least absolute shrinkage and selector operation algorithm. Additionally, the IPMS score by deconvolution algorithm was constructed as an immunophenotype classifier to predict clinical outcomes and immunotherapeutic response.

RESULTS

The 'Hot' HNSC immunophenotype had higher immunoactivity and better overall survival (p = 0.00055) compared to the 'Cold' tumors. The immunophenotypes had distinct DNA methylation patterns, which was closely associated with HNSC tumorigenesis and functional immune cell infiltration. 311 immunophenotype-related methylated CpG sites (IRMCs) was identified from TCGA-HNSC dataset. IPMS score model achieved a strong clinical predictive performance for classifying immunophenotypes. The area under the curve value (AUC) of the IPMS score model reached 85.9% and 89.8% in TCGA train and test datasets, respectively, and robustness was verified in five HNSC validation datasets. It was also validated as an immunophenotype classifier for predicting durable clinical benefits (DCB) in lung cancer patients who received anti-PD-1/PD-L1 immunotherapy (p = 0.017) and TCGA-SKCM patients who received distinct immunotherapy (p = 0.033).

CONCLUSIONS

This study systematically analyzed DNA methylation patterns in distinct immunophenotypes to identify IPMS with clinical prognostic potential for personalized epigenetic anticancer approaches in HNSC patients. The IPMS score model may serve as a reliable epigenome prognostic tool for clinical immunophenotyping to guide immunotherapeutic strategies in HNSC.

Tumor mutation burden in the prognosis and response of lung cancer patients to immune-checkpoint inhibition therapies

Immune checkpoint inhibition (ICI) therapies have reshaped the therapeutic landscape in lung cancer management, providing first-time improvements in patient response, prognosis, and overall survival. Despite their clinical effectiveness, variability in treatment responsiveness, as well as drug resistance, have led to a compelling need for predictive biomarkers facilitating the individualized selection of the most efficient therapeutic approach. Significant progress has been made in the identification of such biomarkers, with tumor mutation burden (ΤΜΒ) appearing as the leading and most promising predictive biomarker for the efficacy of ICIs in non-small cell lung cancer (NSCLC) among other tumors. Anti-PD-1/PD-L1 and anti-CTLA-4 antibodies have been extensively studied and clinically utilized. However, the overall efficiency of these drugs remains unsatisfactory, urging for the investigation of novel inhibitors, such as those targeting LAG-3, TIM-3, TIGIT and VISTA, which could be used either as a monotherapy or synergistically with the PD-1/PD-L1 or CTLA-4 blockers. Here, we investigate the role of TMB and cancer neoantigens as predictive biomarkers in the response of lung cancer patients to different ICI therapies, specifically focusing on the most recent immune checkpoint inhibitors, against LAG-3, TIM-3, TIGIT and VISTA. We further discuss the new trends in immunotherapies, including CAR T-cell therapy and personalized tumor vaccines. We also review further potential biomarkers that could be used in lung cancer response to immunotherapy, such as PD-L1+ IHC, MSI/dMMR, tumor infiltrating lymphocytes (TILs), as well as the role of the microbiome and circulating tumor DNA (ctDNA). Finally, we discuss the limitations and challenges of each.

Epigenome-Driven Strategies for Personalized Cancer Immunotherapy

Fighting cancer remains one of the greatest challenges for science in the 21st century. Advances in immunotherapy against different types of cancer have greatly contributed to the treatment, remission, and cure of patients. In this context, knowledge of epigenetic phenomena, their relationship with tumor cells and how the immune system can be epigenetically modulated represent some of the greatest advances in the development of anticancer therapies. Epigenetics is a rapidly growing field that studies how environmental factors can affect gene expression without altering DNA sequence. Epigenomic changes include DNA methylation, histone modifications, and non-coding RNA regulation, which impact cellular function. Epigenetics has shown promise in developing cancer therapies, such as immunotherapy, which aims to stimulate the immune system to attack cancer cells. For example, PD-1 and PD-L1 are biomarkers that regulate the immune response to cancer cells and recent studies have shown that epigenetic modifications can affect their expression, potentially influencing the efficacy of immunotherapy. New therapies targeting epigenetic modifications, such as histone deacetylases and DNA methyltransferases, are being developed for cancer treatment, and some have shown promise in preclinical studies and clinical trials. With growing understanding of epigenetic regulation, we can expect more personalized and effective cancer immunotherapies in the future. This review highlights key advances in the use of epigenetic and epigenomic tools and modern immuno-oncology strategies to treat several types of tumors.

Impact of Different Treatment Regimens and Timeframes in the Plasmatic Metabolic Profiling of Patients with Lung Adenocarcinoma

In recent years, the treatment of advanced non-small cell lung cancer (NSCLC) has suffered a variety of alterations. Chemotherapy (CTX), immunotherapy (IT) and tyrosine kinase inhibitors (TKI) have shown remarkable results. However, not all patients with NSCLC respond to these drug treatments or receive durable benefits. In this framework, metabolomics has been applied to improve the diagnosis, treatment, and prognosis of lung cancer and particularly lung adenocarcinoma (AdC). In our study, metabolomics was used to analyze plasma samples from 18 patients with AdC treated with CTX or IT via 1H-NMR spectroscopy. Relevant clinical information was gathered, and several biochemical parameters were also evaluated throughout the treatments. During the follow-up of patients undergoing CTX or IT, imaging control is recommended in order to assess the effectiveness of the therapy. This evaluation is usually performed every three treatments. Based on this procedure, all the samples were collected before the beginning of the treatment and after three and six treatments. The identified and quantified metabolites in the analyzed plasma samples were the following: isoleucine, valine, alanine, acetate, lactate, glucose, tyrosine, and formate. Multivariate/univariate statistical analyses were performed. Our data are in accordance with previous published results, suggesting that the plasma glucose levels of patients under CTX become higher throughout the course of treatment, which we hypothesize could be related to the tumor response to the therapy. It was also found that alanine levels become lower during treatment with CTX regimens, a fact that could be associated with frailty. NMR spectra of long responders' profiles also showed similar results. Based on the results of the study, metabolomics can represent a potential option for future studies, in order to facilitate patient selection and the monitoring of therapy efficacy in treated patients with AdC. Further studies are needed to improve the prospective identification of predictive markers, particularly glucose and alanine levels, as well as confer guidance to NSCLC treatment and patient stratification, thus avoiding ineffective therapeutic strategies.

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.

Immune checkpoint inhibitors in the treatment of oesophageal squamous cell carcinoma: where are we and where are we going?

Oesophageal squamous cell carcinoma (ESCC) is a kind of malignant tumour with high invasiveness and a poor prognosis. Immunotherapy, especially immune checkpoint inhibitors (ICIs), is a rapidly growing therapeutic method that activates and enhances anti-tumour immunity to treat patients with malignancy. Several clinical trials have confirmed the efficacy of ICIs in the treatment of ESCC. ICIs have been approved for the treatment of patients with ESCC. However, only a subset of patients can obtain excellent benefits from ICI therapy. In recent years, there has been a growing interest in exploring predictive biomarkers of immunotherapy response. In this review, we highlighted the predictive biomarkers for the prognosis of ESCC patients treated with ICIs and pointed out the existing problems and the direction of future research in this field.

Cancer Cell-Intrinsic Alterations Associated with an Immunosuppressive Tumor Microenvironment and Resistance to Immunotherapy in Lung Cancer

Despite the great clinical success of immunotherapy in lung cancer patients, only a small percentage of them (<40%) will benefit from this therapy alone or combined with other strategies. Cancer cell-intrinsic and cell-extrinsic mechanisms have been associated with a lack of response to immunotherapy. The present study is focused on cancer cell-intrinsic genetic, epigenetic, transcriptomic and metabolic alterations that reshape the tumor microenvironment (TME) and determine response or refractoriness to immune checkpoint inhibitors (ICIs). Mutations in KRAS, SKT11(LKB1), KEAP1 and TP53 and co-mutations of these genes are the main determinants of ICI response in non-small-cell lung cancer (NSCLC) patients. Recent insights into metabolic changes in cancer cells that impose restrictions on cytotoxic T cells and the efficacy of ICIs indicate that targeting such metabolic restrictions may favor therapeutic responses. Other emerging pathways for therapeutic interventions include epigenetic modulators and DNA damage repair (DDR) pathways, especially in small-cell lung cancer (SCLC). Therefore, the many potential pathways for enhancing the effect of ICIs suggest that, in a few years, we will have much more personalized medicine for lung cancer patients treated with immunotherapy. Such strategies could include vaccines and chimeric antigen receptor (CAR) cells.

Potential non-invasive biomarkers in tumor immune checkpoint inhibitor therapy: response and prognosis prediction

Immune checkpoint inhibitors (ICIs) have dramatically enhanced the treatment outcomes for diverse malignancies. Yet, only 15-60% of patients respond significantly. Therefore, accurate responder identification and timely ICI administration are critical issues in tumor ICI therapy. Recent rapid developments at the intersection of oncology, immunology, biology, and computer science have provided an abundance of predictive biomarkers for ICI efficacy. These biomarkers can be invasive or non-invasive, depending on the specific sample collection method. Compared with invasive markers, a host of non-invasive markers have been confirmed to have superior availability and accuracy in ICI efficacy prediction. Considering the outstanding advantages of dynamic monitoring of the immunotherapy response and the potential for widespread clinical application, we review the recent research in this field with the aim of contributing to the identification of patients who may derive the greatest benefit from ICI therapy.

Reshaping the tumour immune microenvironment in solid tumours via tumour cell and immune cell DNA methylation: from mechanisms to therapeutics

In recent years, the tumour microenvironment (TME) of solid tumours has attracted more and more attention from researchers, especially those non-tumour components such as immune cells. Infiltration of various immune cells causes tumour immune microenvironment (TIME) heterogeneity, and results in different therapeutic effects. Accumulating evidence showed that DNA methylation plays a crucial role in remodelling TIME and is associated with the response towards immune checkpoint inhibitors (ICIs). During carcinogenesis, DNA methylation profoundly changes, specifically, there is a global loss of DNA methylation and increased DNA methylation at the promoters of suppressor genes. Immune cell differentiation is disturbed, and exclusion of immune cells from the TME occurs at least in part due to DNA methylation reprogramming. Therefore, pharmaceutical interventions targeting DNA methylation are promising. DNA methyltransferase inhibitors (DNMTis) enhance antitumor immunity by inducing transcription of transposable elements and consequent viral mimicry. DNMTis upregulate the expression of tumour antigens, mediate immune cells recruitment and reactivate exhausted immune cells. In preclinical studies, DNMTis have shown synergistic effect when combined with immunotherapies, suggesting new strategies to treat refractory solid tumours.

Intrinsic features of the cancer cell as drivers of immune checkpoint blockade response and refractoriness

Immune checkpoint blockade represents the latest revolution in cancer treatment by substantially increasing patients' lifetime and quality of life in multiple neoplastic pathologies. However, this new avenue of cancer management appeared extremely beneficial in a minority of cancer types and the sub-population of patients that would benefit from such therapies remain difficult to predict. In this review of the literature, we have summarized important knowledge linking cancer cell characteristics with the response to immunotherapy. Mostly focused on lung cancer, our objective was to illustrate how cancer cell diversity inside a well-defined pathology might explain sensitivity and refractoriness to immunotherapies. We first discuss how genomic instability, epigenetics and innate immune signaling could explain differences in the response to immune checkpoint blockers. Then, in a second part we detailed important notions suggesting that altered cancer cell metabolism, specific oncogenic signaling, tumor suppressor loss as well as tight control of the cGAS/STING pathway in the cancer cells can be associated with resistance to immune checkpoint blockade. At the end, we discussed recent evidences that could suggest that immune checkpoint blockade as first line therapy might shape the cancer cell clones diversity and give rise to the appearance of novel resistance mechanisms.

MYC activation impairs cell-intrinsic IFNγ signaling and confers resistance to anti-PD1/PD-L1 therapy in lung cancer

Elucidating the adaptive mechanisms that prevent host immune response in cancer will help predict efficacy of anti-programmed death-1 (PD1)/L1 therapies. Here, we study the cell-intrinsic response of lung cancer (LC) to interferon-γ (IFNγ), a cytokine that promotes immunoresponse and modulates programmed death-ligand 1 (PD-L1) levels. We report complete refractoriness to IFNγ in a subset of LCs as a result of JAK2 or IFNGR1 inactivation. A submaximal response affects another subset that shows constitutive low levels of IFNγ-stimulated genes (IγSGs) coupled with decreased H3K27ac (histone 3 acetylation at lysine 27) deposition and promoter hypermethylation and reduced IFN regulatory factor 1 (IRF1) recruitment to the DNA on IFNγ stimulation. Most of these are neuroendocrine small cell LCs (SCLCs) with oncogenic MYC/MYCL1/MYCN. The oncogenic activation of MYC in SCLC cells downregulates JAK2 and impairs IγSGs stimulation by IFNγ. MYC amplification tends to associate with a worse response to anti-PD1/L1 therapies. Hence alterations affecting the JAK/STAT pathway and MYC activation prevent stimulation by IFNγ and may predict anti-PD1/L1 efficacy in LC.

Systematic Review and Meta-analysis of Peripheral Blood DNA Methylation Studies in Inflammatory Bowel Disease

BACKGROUND AND AIMS

Over the past decade, the DNA methylome has been increasingly studied in peripheral blood of inflammatory bowel disease [IBD] patients. However, a comprehensive summary and meta-analysis of peripheral blood leukocyte [PBL] DNA methylation studies has thus far not been conducted. Here, we systematically reviewed all available literature up to February 2022 and summarized the observations by means of meta-analysis.

METHODS

We conducted a systematic search and critical appraisal of IBD-associated DNA methylation studies in PBL using the biomarker-based cross-sectional studies [BIOCROSS] tool. Subsequently, we performed meta-analyses on the summary statistics obtained from epigenome-wide association studies [EWAS] that included patients with Crohn's disease [CD], ulcerative colitis [UC] and/or healthy controls [HC].

RESULTS

Altogether, we included 15 studies for systematic review. Critical appraisal revealed large methodological and outcome heterogeneity between studies. Summary statistics were obtained from four studies based on a cumulative 552 samples [177 CD, 132 UC and 243 HC]. Consistent differential methylation was identified for 256 differentially methylated probes [DMPs; Bonferroni-adjusted p ≤ 0.05] when comparing CD with HC and 103 when comparing UC with HC. Comparing IBD [CD + UC] with HC resulted in 224 DMPs. Importantly, several of the previously identified DMPs, such as VMP1/TMEM49/MIR21 and RPS6KA2, were consistently differentially methylated across all studies.

CONCLUSION

Methodological homogenization of IBD epigenetic studies is needed to allow for easier aggregation and independent validation. Nonetheless, we were able to confirm previous observations. Our results can serve as the basis for future IBD epigenetic biomarker research in PBL.

Promises and challenges in pharmacoepigenetics

Pharmacogenetics, the study of how interindividual genetic differences affect drug response, does not explain all observed heritable variance in drug response. Epigenetic mechanisms, such as DNA methylation, and histone acetylation may account for some of the unexplained variances. Epigenetic mechanisms modulate gene expression and can be suitable drug targets and can impact the action of nonepigenetic drugs. Pharmacoepigenetics is the field that studies the relationship between epigenetic variability and drug response. Much of this research focuses on compounds targeting epigenetic mechanisms, called epigenetic drugs, which are used to treat cancers, immune disorders, and other diseases. Several studies also suggest an epigenetic role in classical drug response; however, we know little about this area. The amount of information correlating epigenetic biomarkers to molecular datasets has recently expanded due to technological advances, and novel computational approaches have emerged to better identify and predict epigenetic interactions. We propose that the relationship between epigenetics and classical drug response may be examined using data already available by (1) finding regions of epigenetic variance, (2) pinpointing key epigenetic biomarkers within these regions, and (3) mapping these biomarkers to a drug-response phenotype. This approach expands on existing knowledge to generate putative pharmacoepigenetic relationships, which can be tested experimentally. Epigenetic modifications are involved in disease and drug response. Therefore, understanding how epigenetic drivers impact the response to classical drugs is important for improving drug design and administration to better treat disease.

Circulating Biomarkers for Prediction of Immunotherapy Response in NSCLC

Non-small cell lung cancer (NSCLC) constitutes the majority of the lung cancer population and the prognosis is poor. In recent years, immunotherapy has become the standard of care for advanced NSCLC patients as numerous trials demonstrated that immune checkpoint inhibitors (ICI) are more efficacious than conventional chemotherapy. However, only a minority of NSCLC patients benefit from this treatment. Therefore, there is an unmet need for biomarkers that could accurately predict response to immunotherapy. Liquid biopsy allows repeated sampling of blood-based biomarkers in a non-invasive manner for the dynamic monitoring of treatment response. In this review, we summarize the efforts and progress made in the identification of circulating biomarkers that predict immunotherapy benefit for NSCLC patients. We also discuss the challenges with future implementation of circulating biomarkers into clinical practice.

Tumour-infiltrating lymphocytes: from prognosis to treatment selection

Tumour-infiltrating lymphocytes (TILs) are considered crucial in anti-tumour immunity. Accordingly, the presence of TILs contains prognostic and predictive value. In 2011, we performed a systematic review and meta-analysis on the prognostic value of TILs across cancer types. Since then, the advent of immune checkpoint blockade (ICB) has renewed interest in the analysis of TILs. In this review, we first describe how our understanding of the prognostic value of TIL has changed over the last decade. New insights on novel TIL subsets are discussed and give a broader view on the prognostic effect of TILs in cancer. Apart from prognostic value, evidence on the predictive significance of TILs in the immune therapy era are discussed, as well as new techniques, such as machine learning that strive to incorporate these predictive capacities within clinical trials.

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.

LRRC3B and its promoter hypomethylation status predicts response to anti-PD-1 based immunotherapy

Background

The leucine rich repeat containing 3B (LRRC3B) gene is a tumor suppressor gene involved in the anti-tumor immune microenvironment. Expression of LRRC3B and DNA methylation at the LRRC3B promoter region may serve as a useful marker to predict response to anti-PD-1 therapy. However, no studies have yet systematically explored the protective role of LRRC3B methylation in tumor progression and immunity.

Methods

Expression of LRRC3B of 33 cancer types in The Cancer Genome Atlas (TCGA) was downloaded from UCSC Xena (http://xena.ucsc.edu/). And, we evaluated the differential expression of LRRC3B according to tumor stage, overall survival, and characteristics of the tumor microenvironment. The immunotherapeutic cohorts included IMvigor21, GSE119144, and GSE72308 which were obtained from the Gene Expression Omnibus database. We conducted pearson correlation analysis of LRRC3B and tumor microenvironment (TME) in pan-cancer. Also, six immune cell types (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells) and tumor purity were analyzed using the Tumor IMmune Estimation Resource (TIMER1.0) (Tumor IMmune Estimation Resource (TIMER2.0). And, a "silencing score" model base on LRRC3B promoter methylation to predict overall survival (OS) by multivariate Cox regression analysis was constructed. Finally, the model was applied to predict anti-PD-1 therapy in non-small cell lung cancer (NSCLC) and breast cancer (BRCA).

Results

LRRC3B expression associated with less tumor invasion, less severe tumor stage, and decreased metastasis. The inactivation of LRRC3B promoted the enrichment of immuneosuppressive cells, including myeloid-derived suppressor cells (MDSCs), cancer-associated fibroblasts (CAFs), M2 subtype of tumor-associated macrophages (M2-TAMs), M1 subtype of tumor-associated macrophages (M1-TAMs), and regulatory T (Treg) cells. A high silencing score was significantly associated with immune inhibition, low expression of LRRC3B, poor patient survival, and activation of cancer-related pathways.

Conclusion

Our comprehensive analysis demonstrated the potential role of LRRC3B in the anti-tumor microenvironment, clinicopathological features of cancer, and disease prognosis. It suggested that LRRC3B methylation could be used as a powerful biomarker to predict immunotherapy responses in NSCLC and BRCA.

Lung cancer patients with chronic obstructive pulmonary disease benefit from anti-PD-1/PD-L1 therapy

Lung cancer (LC) and chronic obstructive pulmonary disease (COPD) are two of the most fatal respiratory diseases, seriously threatening human health and imposing a heavy burden on families and society. Although COPD is a significant independent risk factor for LC, it is still unclear how COPD affects the prognosis of LC patients, especially when LC patients with COPD receive immunotherapy. With the development of immune checkpoint inhibition (ICI) therapy, an increasing number of inhibitors of programmed cell death-1 (PD-1) and PD-1 ligand (PD-L1) have been applied to the treatment of LC. Recent studies suggest that LC patients with COPD may benefit more from immunotherapy. In this review, we systematically summarized the outcomes of LC patients with COPD after anti-PD-1/PD-L1 treatment and discussed the tumor immune microenvironment (TIME) regulated by COPD in LC immunotherapy, which provides novel insights for the clinical treatment of LC patients with COPD.

Predictive Biomarkers for Immunotherapy in Lung Cancer: Perspective From the International Association for the Study of Lung Cancer Pathology Committee

Immunotherapy including immune checkpoint inhibitors (ICIs) has become the backbone of treatment for most lung cancers with advanced or metastatic disease. In addition, they have increasingly been used for early stage tumors in neoadjuvant and adjuvant settings. Unfortunately, however, only a subset of patients experiences meaningful response to ICIs. Although programmed death-ligand 1 (PD-L1) protein expression by immunohistochemistry (IHC) has played a role as the principal predictive biomarker for immunotherapy, its performance may not be optimal, and it suffers multiple practical issues with different companion diagnostic assays approved. Similarly, tumor mutational burden (TMB) has multiple technical issues as a predictive biomarker for ICIs. Now, ongoing research on tumor- and host immune-specific factors has identified immunotherapy biomarkers that may provide better response and prognosis prediction, in particular in a multimodal approach. This review by the International Association for the Study of Lung Cancer Pathology Committee provides an overview of various immunotherapy biomarkers, including updated data on PD-L1 IHC and TMB, and assessments of neoantigens, genetic and epigenetic signatures, immune microenvironment by IHC and transcriptomics, and microbiome and pathologic response to neoadjuvant immunotherapies. The aim of this review is to underline the efficacy of new individual or combined predictive biomarkers beyond PD-L1 IHC and TMB.

Significance of macrophage infiltration in the prognosis of lung adenocarcinoma patients evaluated by scRNA and bulkRNA analysis

Purpose

To investigate the significance of macrophage infiltration to the prognosis of lung adenocarcinoma.

Methods

R language bioinformatics analysis technology, was used to obtain macrophage infiltration-related module genes through WGCNA (Weighted Gene Co-Expression Network Analysis). Marker genes of macrophage subtypes were identified using single-cell sequencing of lung adenocarcinoma tissue. Risk score models were constructed and validated using external data cohorts and clinical samples.

Results

Analysis of cohorts TCGA-LUAD, GSE11969, GSE31210, GSE50081, GSE72094 and GSE8894, revealed a negative correlation between macrophage infiltration and survival. Immunohistochemical analyses of clinical samples were consistent with these data. Based on cell-cluster-markers and TAMs-related-genes, TOP8 genes were obtained (C1QTNF6, CCNB1, FSCN1, HMMR, KPNA2, PRC1, RRM2, and TK1) with a significant association to prognosis. Risk score models including 9 factors (C1QTNF6, FSCN1, KPNA2, GLI2, TYMS, BIRC3, RBBP7, KRT8, GPR65) for prognosis were constructed. The efficacy, stability and generalizability of the risk score models were validated using multiple data cohorts (GSE19188, GSE26939, GSE31210, GSE50081, GSE42127, and GSE72094).

Conclusions

Macrophage infiltration negatively correlates with prognosis in patients with lung adenocarcinoma. Based on cell-cluster-markers and TAMs-related-genes, both TOP8 genes (C1QTNF6, CCNB1, FSCN1, HMMR, KPNA2, PRC1, RRM2, TK1) and risk score models using C1QTNF6, FSCN1, KPNA2, GLI2, TYMS, BIRC3, RBBP7, KRT8, GPR65 could predict disease prognosis.

Tumor Microenvironment CD14+ Cells Correlate with Poor Overall Survival in Patients with Early-Stage Lung Adenocarcinoma

Patients with early-stage lung adenocarcinoma have a high risk of recurrent or metastatic disease despite undergoing curative intent therapy. We hypothesized that increased CD14+ cells within the tumor microenvironment (TME) could stratify patient outcomes. Immunohistochemistry for CD14 was performed on 189 specimens from patients with lung adenocarcinoma who underwent curative intent surgery. Outcomes and associations with clinical and pathologic variables were determined. In vitro studies utilized a coculture system to model the lung cancer TME containing CD14+ cells. Patients with high levels of TME CD14+ cells experienced a median overall survival of 5.5 years compared with 8.3 and 10.7 years for those with moderate or low CD14 levels, respectively (p < 0.001). Increased CD14+ cell tumor infiltration was associated with a higher stage at diagnosis and more positive lymph nodes at the time of surgery. This prognostic capacity remained even for patients with early-stage disease. Using an in vitro model system, we found that CD14+ cells reduced chemotherapy-induced cancer cell death. These data suggest that CD14+ cells are a biomarker for poor prognosis in early-stage lung adenocarcinoma and may promote tumor survival. CD14+ cell integration into the lung cancer TME can occur early in the disease and may be a promising new therapeutic avenue.

Peripheral Blood DNA Methylation Profiles Do Not Predict Endoscopic Post-Operative Recurrence in Crohn's Disease Patients

Prediction of endoscopic post-operative recurrence (POR) in Crohn’s disease (CD) patients following ileocolonic resection (ICR) using clinical risk factors alone has thus far been inadequate. While peripheral blood leukocyte (PBL) DNA methylation has shown promise as a tool for predicting recurrence in cancer, no data in CD patients exists. Therefore, this study explored the association and predictive value of PBL DNA methylation in CD patients following ICR. From a cohort of 117 CD patients undergoing ICR, epigenome-wide PBL methylation profiles from 25 carefully selected patients presenting either clear endoscopic remission (n = 12) or severe recurrence (n = 13) were assessed using the Illumina MethylationEPIC (850K) array. No statistically significant differentially methylated positions (DMPs) or regions (DMRs) associated with endoscopic POR were identified (FDR p ≤ 0.05), further evidenced by the low accuracy (0.625) following elastic net classification analysis. Nonetheless, interrogating the most significant differences in methylation suggested POR-associated hypermethylation in the MBNL1, RAB29 and LEPR genes, respectively, which are involved in intestinal fibrosis, inflammation and wound healing. Notably, we observed a higher estimated proportion of monocytes in endoscopic POR compared to remission. Altogether, we observed limited differences in the genome-wide DNA methylome among CD patients with and without endoscopic POR. We therefore conclude that PBL DNA methylation is not a feasible predictive tool in post-operative CD.

High IGKC-Expressing Intratumoral Plasma Cells Predict Response to Immune Checkpoint Blockade

Resistance to Immune Checkpoint Blockade (ICB) constitutes the current limiting factor for the optimal implementation of this novel therapy, which otherwise demonstrates durable responses with acceptable toxicity scores. This limitation is exacerbated by a lack of robust biomarkers. In this study, we have dissected the basal TME composition at the gene expression and cellular levels that predict response to Nivolumab and prognosis. BCR, TCR and HLA profiling were employed for further characterization of the molecular variables associated with response. The findings were validated using a single-cell RNA-seq data of metastatic melanoma patients treated with ICB, and by multispectral immunofluorescence. Finally, machine learning was employed to construct a prediction algorithm that was validated across eight metastatic melanoma cohorts treated with ICB. Using this strategy, we have unmasked a major role played by basal intratumoral Plasma cells expressing high levels of IGKC in efficacy. IGKC, differentially expressed in good responders, was also identified within the Top response-related BCR clonotypes, together with IGK variants. These results were validated at gene, cellular and protein levels; CD138+ Plasma-like and Plasma cells were more abundant in good responders and correlated with the same RNA-seq-defined fraction. Finally, we generated a 15-gene prediction model that outperformed the current reference score in eight ICB-treated metastatic melanoma cohorts. The evidenced major contribution of basal intratumoral IGKC and Plasma cells in good response and outcome in ICB in metastatic melanoma is a groundbreaking finding in the field beyond the role of T lymphocytes.

Measuring functional outcomes in major trauma: can we do better?

PURPOSE

There is relatively limited large scale, long-term unified evidence to describe how quality of life (QoL) and functional outcomes are affected after polytrauma. The aim of this study is to review validated measures available to assess QoL and functional outcomes and make recommendations on how best to assess patents after major trauma.

METHODS

PubMed and EMBASE databases were interrogated to identify suitable patient-reported outcome measures (PROMs) for use in major trauma, and current practice in their use globally.

RESULTS

Overall, 81 papers met the criteria for inclusion and evaluation. Data from these were synthesised. A full set of validated PROMs tools were identified for patients with polytrauma, as well as critique of current tools available, allowing us to evaluate practice and recommend specific outcome measures for patients following polytrauma, and system changes needed to embed this in routine practice moving forward.

CONCLUSION

To achieve optimal outcomes for patients with polytrauma, we will need to focus on what matters most to them, including their needs (and unmet needs). The use of appropriate PROMs allows evaluation and improvement in the care we can offer. Transformative effects have been noted in cases where they have been used to guide treatment, and if embedded as part of the wider system, it should lead to better overall outcomes. Accordingly, we have made recommendations to this effect. It is time to seize the day, bring these measures even further into our routine practice, and be part of shaping the future.

Pediatric Pan-Central Nervous System Tumor Methylome Analyses Reveal Immune-Related LncRNAs

Pediatric central nervous system (CNS) tumors are the second most common cancer diagnosis among children. Long noncoding RNAs (lncRNAs) emerge as critical regulators of gene expression, and they play fundamental roles in immune regulation. However, knowledge on epigenetic changes in lncRNAs in diverse types of pediatric CNS tumors is lacking. Here, we integrated the DNA methylation profiles of 2,257 pediatric CNS tumors across 61 subtypes with lncRNA annotations and presented the epigenetically regulated landscape of lncRNAs. We revealed the prevalent lncRNA methylation heterogeneity across pediatric pan-CNS tumors. Based on lncRNA methylation profiles, we refined 14 lncRNA methylation clusters with distinct immune microenvironment patterns. Moreover, we found that lncRNA methylations were significantly correlated with immune cell infiltrations in diverse tumor subtypes. Immune-related lncRNAs were further identified by investigating their correlation with immune cell infiltrations and potentially regulated target genes. LncRNA with methylation perturbations potentially regulate the genes in immune-related pathways. We finally identified several candidate immune-related lncRNA biomarkers (i.e., SSTR5-AS1, CNTN4-AS1, and OSTM1-AS1) in pediatric cancer for further functional validation. In summary, our study represents a comprehensive repertoire of epigenetically regulated immune-related lncRNAs in pediatric pan-CNS tumors, and will facilitate the development of immunotherapeutic targets.

UBE3A deletion enhances the efficiency of immunotherapy in non-small-cell lung cancer

Immunotherapy significantly improves the prognosis of advanced lung cancer. It has become an important treatment option for advanced lung cancer. However, there remain many limitations in clinical treatment, and only a small portion of patients can benefit from immunotherapy. Our study aimed to identify markers that can precisely forecast the efficacy of immunotherapy in patients. We analyzed a non-small-cell lung cancer (NSCLC) immune checkpoint inhibitor (ICI) cohort (n=240). We used this discovery cohort to identify CNVs in genes associated with immunotherapy. We further analyzed immune biomarkers and immune infiltration in The Cancer Genome Atlas (TCGA)-NSCLC cohort and the Gene Expression Omnibus (GEO) cohorts. By analyzing an ICI dataset from MSKCC, we found that progression-free survival (PFS) was improved after UBE3A deletion (UBE3A-del). The analysis results showed that UBE3A-del had higher immunocyte infiltration levels and higher expression levels of immune checkpoint biomarkers and affected the enrichment levels of immune signaling pathways. Our results suggest that UBE3A-del can be used as a predictive biomarker of NSCLC to screen for NSCLC patients who may benefit from ICI therapy. 

Abbreviations: NSCLC: Non-small cell lung cancer; CNV: Copy number variation; ICIs: Immune checkpoint inhibitors; TCGA: The cancer genome atlas; GEO: Gene expression omnibus; GSEA: Gene set enrichment; PFS: Progression-free survival; OS: Overall survival; TMB: Tumor mutational burden; CTLA-4: Cytotoxic T lymphocyte antigen 4; PD-(L)1: Programmed cell death (ligand) 1; MSI: Microsatellite instability; dMMR: DNA mismatch repair; SCNAs: Somatic copy number alterations; TME: Tumor microenvironment; MSK-IMPACT: The Memorial Sloan Kettering-Integrated Mutation Profilng of Actionable; Cancer Targets; FDA: Food and Drug Administration; WES: Whole-exome sequencing; SNP: Single Nucleotide Polymorphisms; FDR: False discovery rate; DCR: Disease control rate; DDR: DNA damage response and repair; MDSCs: Myeloid-derived suppressor cells; FAO: Fatty acid oxidation

Biological and Molecular Factors Predicting Response to Adoptive Cell Therapies in Cancer

Adoptive cell therapy (ACT) constitutes a major breakthrough in cancer management that has expanded in the past years due to impressive results showing durable and even curative responses for some patients with hematological malignancies. ACT leverages antigen specificity and cytotoxic mechanisms of the immune system, particularly relying on the patient’s T lymphocytes to target and eliminate malignant cells. This personalized therapeutic approach exemplifies the success of the joint effort of basic, translational, and clinical researchers that has turned the patient’s immune system into a great ally in the search for a cancer cure. ACTs are constantly improving to reach a maximum beneficial clinical response. Despite being very promising therapeutic options for certain types of cancers, mainly melanoma and hematological malignancies, these individualized treatments still present several shortcomings, including elevated costs, technical challenges, management of adverse side effects, and a limited population of responder patients. Thus, it is crucial to discover and develop reliable and robust biomarkers to specifically and sensitively pinpoint the patients that will benefit the most from ACT as well as those at higher risk of developing potentially serious toxicities. Although unique readouts of infused cell therapy success have not yet been identified, certain characteristics from the adoptive cells, the tumor, and/or the tumor microenvironment have been recognized to predict patients’ outcome on ACT. Here, we comment on the importance of biomarkers to predict ACT chances of success to maximize efficacy of treatments and increase patients’ survival.

TET1 mutations as a predictive biomarker for immune checkpoint inhibitors in colon adenocarcinoma

BACKGROUND

The ten-eleven translocation 1 (TET1), which is essential for active DNA demethylation, plays a multifaceted role in the pathogenesis of colorectal cancer. The study has demonstrated the association of TET1 mutations with a high response to immune checkpoint inhibitors (ICIs) in diverse cancers. However, the relationship between TET1 mutations and the response to ICIs in colon cancer is still lacking.

METHODS

The prognosis, predictive markers, immune characteristics, mutation number of DNA damage repair (DDR) pathways, pathway enrichment, and drug sensitivity conditions were all compared between TET1-mutated and wild-type patients with colon adenocarcinoma (COAD).

RESULTS

The overall survival of patients with TET1 mutations in the ICI-treated cohort was significantly longer than those without (p = 0.0059). Compared with the wild-type patients, TET1-mutated patients had higher tumor mutational burden and neoantigen load, enhanced abundance of tumor-infiltrating immune cells, increased expression of immune-related genes, and mutation number of DDR pathways. Additionally, the patients with TET1 mutations were found to be more sensitive to lapatinib and 5-fluorouracil.

CONCLUSION

These findings suggest that TET1 mutations may serve as a potential biomarker for the response to ICIs in COAD patients.

Hyper-Methylated Hub Genes of T-Cell Receptor Signaling Predict a Poor Clinical Outcome in Lung Adenocarcinoma

Background

Immune checkpoint inhibitors (ICIs) emerge as the first-line treatment of lung adenocarcinoma (LUAD); selection of subpopulations acquiring clinical benefit is required. Associations between epigenetic modulation of tumor microenvironment (TME) and clinical outcome are far from clear. We focused on immune-related genes closely regulated by DNA methylation to identify the potential clinical outcome indicators.

Methods

We systematically calculated immunophenotype score (IMpS) and classified immunophenotypes based on seven TME features in three independent cohorts. The overlapping of differential expressed genes and methylated probes targeted genes was regarded as genes closely regulated by DNA methylation. Then, probe/gene pairs which highly correlated with each other and IMpS were identified and named as immune-related probe/gene pairs (mIMg). Prognostic mIMg were selected and verified in seven independent validation cohorts.

Results

Three immune phenotypes were clustered, and similar results were obtained in the three independent training cohorts. C2 displayed as an immunologically hot phenotype, whereas C3 corresponded with immunologically cold phenotype. Average methylation level was decreased from C2 to C3 (C2 > C1 > C3). Similarly, ICIs nonresponders showed global hypo-methylation compared with responders. Genes in mIMg were mainly enriched, especially in T-cell receptor activation, and repressed in noninflamed TME by hyper-methylation. Among mIMg, low expression and hyper-methylation of CD247, LCK, and PSTPIP1 were risk factors of overall survival (OS). ICIs nonresponders were more likely to be hyper-methylated in the three genes. By integrating with the oncogenes status, we demonstrated that EGFR wt and SRGN overexpressed patients were associated with chronic inflammation and immune evasion, showing an immunologically hot phenotype, which might lead to the short OS but derive clinical benefit from ICIs.

Conclusions

This study identifies hyper-methylation and concurrent repression of CD247, LCK, PSTPIP1 as immune negative indicators and risk factors for prognosis in LUAD. Moreover, EGFR/SRGN axis may participate in immune modification to influence ICIs response and clinical outcome in LUAD.

DNA methylation profiles differ in responders versus non-responders to anti-PD-1 immune checkpoint inhibitors in patients with advanced and metastatic head and neck squamous cell carcinoma

BACKGROUND

Biomarkers for response prediction to anti-programmed cell death 1 (PD-1) immune checkpoint inhibitors (ICI) in patients with head and neck squamous cell carcinoma (HNSCC) are urgently needed for a personalized therapy approach. We investigated the predictive potential of inflammatory parameters and DNA methylation profiling in patients with HNSCC treated with anti-PD-1 ICI.

METHODS

We identified patients with HNSCC that were treated with anti-PD-1 ICI therapy in the recurrent or metastatic setting after progression to platinum-based chemotherapy in two independent centers. We analyzed DNA methylation profiles of >850.000 CpG sites in tumor specimens of these patients by Infinium MethylationEPIC microarrays, immune cell density in the tumor microenvironment (CD8, CD3, CD45RO, forkhead box P3 (FOXP3), CD68), PD-1 and programmed cell death ligand 1 (PD-L1) expression by immunohistochemistry, and blood inflammation markers (platelet-to-lymphocyte ratio, leucocyte-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio). DNA methylation profiles and immunological markers were bioinformatically and statistically correlated with radiological response to anti-PD-1 ICI.

RESULTS

37 patients with HNSCC (median age of 62 years; range 49-83; 8 (21.6%) women, 29 (78.4%) men) were included (Center 1 N=26, 70.3%; Center 2 N=11, 29.7%). Median number of prior systemic therapies was 1 (range 1-4). Five out of 37 (13.5%) patients achieved an objective response to ICI. Median progression-free survival and median overall survival times were 3.7 months (range 0-22.9) and 9.0 months (range 0-38.8), respectively. Microarray analyses revealed a methylation signature including both hypomethylation and hypermethylation which was predictive for response to ICI and included several genes involved in cancer-related molecular pathways. Over-represented differentially methylated genes between responders and non-responders were associated with 'Axon guidance', 'Hippo signaling', 'Pathways in cancer' and 'MAPK signaling'. A statistically significant correlation of PD-L1 expression and response was present (p=0.0498).

CONCLUSIONS

Our findings suggest that tumor DNA methylation profiling may be useful to predict response to ICI in patients with HNSCC.

Genome-wide DNA methylation patterns reveal clinically relevant predictive and prognostic subtypes in human osteosarcoma

Aberrant methylation of genomic DNA has been reported in many cancers. Specific DNA methylation patterns have been shown to provide clinically useful prognostic information and define molecular disease subtypes with different response to therapy and long-term outcome. Osteosarcoma is an aggressive malignancy for which approximately half of tumors recur following standard combined surgical resection and chemotherapy. No accepted prognostic factor save tumor necrosis in response to adjuvant therapy currently exists, and traditional genomic studies have thus far failed to identify meaningful clinical associations. We studied the genome-wide methylation state of primary tumors and tested how they predict patient outcomes. We discovered relative genomic hypomethylation to be strongly predictive of response to standard chemotherapy. Recurrence and survival were also associated with genomic methylation, but through more site-specific patterns. Furthermore, the methylation patterns were reproducible in three small independent clinical datasets. Downstream transcriptional, in vitro, and pharmacogenomic analysis provides insight into the clinical translation of the methylation patterns. Our findings suggest the assessment of genomic methylation may represent a strategy for stratifying patients for the application of alternative therapies.

Epigenetic Profiling and Response to CD19 Chimeric Antigen Receptor T-Cell Therapy in B-Cell Malignancies

BACKGROUND

Chimeric antigen receptor (CAR) T cells directed against CD19 (CART19) are effective in B-cell malignancies, but little is known about the molecular factors predicting clinical outcome of CART19 therapy. The increasingly recognized relevance of epigenetic changes in cancer immunology prompted us to determine the impact of the DNA methylation profiles of CART19 cells on the clinical course.

METHODS

We recruited 114 patients with B-cell malignancies, comprising 77 patients with acute lymphoblastic leukemia and 37 patients with non-Hodgkin lymphoma who were treated with CART19 cells. Using a comprehensive DNA methylation microarray, we determined the epigenomic changes that occur in the patient T cells upon transduction of the CAR vector. The effects of the identified DNA methylation sites on clinical response, cytokine release syndrome, immune effector cell-associated neurotoxicity syndrome, event-free survival, and overall survival were assessed. All statistical tests were 2-sided.

RESULTS

We identified 984 genomic sites with differential DNA methylation between CAR-untransduced and CAR-transduced T cells before infusion into the patient. Eighteen of these distinct epigenetic loci were associated with complete response (CR), adjusting by multiple testing. Using the sites linked to CR, an epigenetic signature, referred to hereafter as the EPICART signature, was established in the initial discovery cohort (n = 79), which was associated with CR (Fisher exact test, P < .001) and enhanced event-free survival (hazard ratio [HR] = 0.36; 95% confidence interval [CI] = 0.19 to 0.70; P = .002; log-rank P = .003) and overall survival (HR = 0.45; 95% CI = 0.20 to 0.99; P = .047; log-rank P = .04;). Most important, the EPICART profile maintained its clinical course predictive value in the validation cohort (n = 35), where it was associated with CR (Fisher exact test, P < .001) and enhanced overall survival (HR = 0.31; 95% CI = 0.11 to 0.84; P = .02; log-rank P = .02).

CONCLUSIONS

We show that the DNA methylation landscape of patient CART19 cells influences the efficacy of the cellular immunotherapy treatment in patients with B-cell malignancy.

Polymersome-mediated cytosolic delivery of cyclic dinucleotide STING agonist enhances tumor immunotherapy

Cyclic dinucleotides (CDNs) as stimulator of interferon genes (STING) agonists capable of inducing strong antitumor innate immune response are highly promising for tumor immunotherapy. The efficacy of these CDNs is, however, reduced greatly by their fast clearance, poor cell uptake and inefficient cytosolic transportation. Here, we report that reduction-responsive biodegradable chimaeric polymersomes (CPs) markedly enhance tumor retention and cytosolic delivery of a synthetic CDN, ADU-S100, and bolster STING pathway activation in the tumor microenvironment and tumor draining lymph nodes, giving significantly better tumor repression and survival of B16F10 melanoma-bearing mice compared with free CDN control. The superiority of CPs-mediated CDN delivery is further verified in combination therapy with low-dose fractionated radiation, which brings about clearly stronger and longer-term immunotherapeutic effects and protection against tumor re-challenge. The development of nano-STING agonists that are able to overcome the delivery barriers of CDNs represents an effective strategy to potentiate cancer immunotherapy.

•

Chimaeric polymersomes (CPs) show efficient loading of STING agonist cyclic dinucleotide.

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Intratumoral injection of CPs-CDN gives notable tumor accumulation and cytosolic delivery of STING agonist.

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CPs-CDN activate STING pathway in tumor microenvironment and tumor draining lymph node, giving significant tumor repression and survival of melanoma mice.

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CPs-CDN combined with low-dose fractionated X ray irradiation led to further boosted immunotherapy with 3/7 cured mice.

•

Nano-STING agonists can overcome the delivery barriers of CDNs and potentiate durable cancer immunotherapy.

Current and Future Clinical Applications of ctDNA in Immuno-Oncology

Testing peripheral blood for circulating tumor DNA (ctDNA) offers a minimally invasive opportunity to diagnose, characterize, and monitor the disease in individual cancer patients. ctDNA can reflect the actual tumor burden and specific genomic state of disease and thus might serve as a prognostic and predictive biomarker for immune checkpoint inhibitor (ICI) therapy. Recent studies in various cancer entities (e.g., melanoma, non-small cell lung cancer, colon cancer, and urothelial cancer) have shown that sequential ctDNA analyses allow for the identification of responders to ICI therapy, with a significant lead time to imaging. ctDNA assessment may also help distinguish pseudoprogression under ICI therapy from real progression. Developing dynamic changes in ctDNA concentrations as a potential surrogate endpoint of clinical efficacy in patients undergoing adjuvant immunotherapy is ongoing. Besides overall ctDNA burden, further ctDNA characterization can help uncover tumor-specific determinants (e.g., tumor mutational burden and microsatellite instability) of responses or resistance to immunotherapy. In future studies, standardized ctDNA assessments need to be included in interventional clinical trials across cancer entities to demonstrate the clinical utility of ctDNA as a biomarker for personalized cancer immunotherapy.

Integrative Modeling of Multiomics Data for Predicting Tumor Mutation Burden in Patients with Lung Cancer

Immunotherapy has been widely used in the treatment of lung cancer, and one of the most effective biomarkers for the prognosis of immunotherapy currently is tumor mutation burden (TMB). Although whole-exome sequencing (WES) could be utilized to assess TMB, several problems prevent its routine clinical application. To develop a simplified TMB prediction model, patients with lung adenocarcinoma (LUAD) in The Cancer Genome Atlas (TCGA) were randomly split into training and validation cohorts and categorized into the TMB-high (TMB-H) and TMB-low (TMB-L) groups, respectively. Based on the 610 differentially expressed genes, 50 differentially expressed miRNAs and 58 differentially methylated CpG sites between TMB-H and TMB-L patients, we constructed 4 predictive signatures and established TMB prediction model through machine learning methods that integrating the expression or methylation profiles of 7 genes, 7 miRNAs, and 6 CpG sites. The multiomics model exhibited excellent performance in predicting TMB with the area under curve (AUC) of 0.911 in the training cohort and 0.859 in the validation cohort. Besides, the significant correlation between the multiomics model score and TMB was observed. In summary, we developed a prognostic TMB prediction model by integrating multiomics data in patients with LUAD, which might facilitate the further development of quantitative real time-polymerase chain reaction- (qRT-PCR-) based TMB prediction assay.

Experimental and Bioinformatic Approaches to Studying DNA Methylation in Cancer

DNA methylation is an essential epigenetic mark. Alterations of normal DNA methylation are a defining feature of cancer. Here, we review experimental and bioinformatic approaches to showcase the breadth and depth of information that this epigenetic mark provides for cancer research. First, we describe classical approaches for interrogating bulk DNA from cell populations as well as more recently developed approaches for single cells and multi-Omics. Second, we focus on the computational analysis from primary data processing to the identification of unique methylation signatures. Additionally, we discuss challenges such as sparse data and cellular heterogeneity.

Comparative Analysis of Predictive Biomarkers for PD-1/PD-L1 Inhibitors in Cancers: Developments and Challenges

Simple Summary

The development of immune checkpoint inhibitors (ICIs) has greatly changed the treatment landscape of multiple malignancies. However, the wide administration of ICIs is mainly obstructed by the low response rate and several life-threatening adverse events. Thus, there is an urgent need to identify sets of biomarkers to predict which patients will respond to ICIs. In this review, we discuss the recently investigated molecular and clinical determinants of ICI response, from the aspects of tumor features, clinical features, as well as tumor microenvironment.

Abstract

Immune checkpoint inhibitors (ICIs) targeting programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) have dramatically changed the landscape of cancer therapy. Both remarkable and durable responses have been observed in patients with melanoma, non-small-cell lung cancer (NSCLC), and other malignancies. However, the PD-1/PD-L1 blockade has demonstrated meaningful clinical responses and benefits in only a subset of patients. In addition, several severe and life-threatening adverse events were observed in these patients. Therefore, the identification of predictive biomarkers is urgently needed to select patients who are more likely to benefit from ICI therapy. PD-L1 expression level is the most commonly used biomarker in clinical practice for PD-1/PD-L1 inhibitors. However, negative PD-L1 expression cannot reliably exclude a response to a PD-1/PD-L1 blockade. Other factors, such as tumor microenvironment and other tumor genomic signatures, appear to impact the response to ICIs. In this review, we examine emerging data for novel biomarkers that may have a predictive value for optimizing the benefit from anti-PD-1/PD-L1 immunotherapy.