Gene signatures of tumor inflammation and epithelial-to-mesenchymal transition (EMT) predict responses to immune checkpoint blockade in lung cancer with high accuracy

Inflammatory response signature score model for predicting immunotherapy response and pan-cancer prognosis

Background

Inflammatory responses influence the outcome of immunotherapy and tumorigenesis by modulating host immunity. However, systematic inflammatory response assessment models for predicting cancer immunotherapy (CIT) responses and survival across human cancers remain unexplored. Here, we investigated an inflammatory response score model to predict CIT responses and patient survival in a pan-cancer analysis.

Methods

We retrieved 12 CIT response gene expression datasets from the Gene Expression Omnibus database (GSE78220, GSE19423, GSE100797, GSE126044, GSE35640, GSE67501, GSE115821 and GSE168204), Tumor Immune Dysfunction and Exclusion database (PRJEB23709, PRJEB25780 and phs000452.v2.p1), European Genome-phenome Archive database (EGAD00001005738), and IMvigor210 cohort. The tumor samples from six cancers types: metastatic urothelial cancer, metastatic melanoma, gastric cancer, primary bladder cancer, renal cell carcinoma, and non-small cell lung cancer.We further established a binary classification model to predict CIT responses using the least absolute shrinkage and selection operator (LASSO) computational algorithm.

Findings

The model had high predictive accuracy in both the training and validation cohorts. During sub-group analysis, area under the curve (AUC) values of 0.82, 0.80, 0.71, 0.7, 0.67, and 0.64 were obtained for the non-small cell lung cancer, gastric cancer, metastatic urothelial cancer, primary bladder cancer, metastatic melanoma, and renal cell carcinoma cohorts, respectively. CIT response rates were higher in the high-scoring training cohort subjects (51%) than the low-scoring subjects (27%). The five-year survival rates in the high- and low score groups of the training cohorts were 62% and 21%, respectively, while those of the validation cohorts were 54% and 22%, respectively (P < 0·001 in all cases). Inflammatory response signature score derived from on-treatment tumor specimens are highly predictive of response to CIT in patients with metastatic melanoma. A significant correlation was observed between the inflammatory response scores and tumor purity. Regardless of the tumor purity, patients in the low score group had a significantly poorer prognosis than those in the high score group. Immune cell infiltration analysis indicated that in the high score cohort, tumor-infiltrating lymphocytes were significantly enriched, particularly effector and natural killer cells. Inflammatory response scores were positively correlated with immune checkpoint genes, suggesting that immune checkpoint inhibitors may have benefited patients with high scores. Analysis of signature scores across different cancer types from The Cancer Genome Atlas revealed that the prognostic performance of inflammatory response scores for survival in patients who have not undergone immunotherapy can be affected by tumor purity. Interleukin 21 (IL21) had the highest weight in the inflammatory response model, suggesting its vital role in the prediction mode. Since the number of metastatic melanoma patients (n = 429) was relatively large among CIT cohorts, we further performed a co-culture experiment using a melanoma cell line and CD8 + T cell populations generated from peripheral blood monocytes. The results showed that IL21 therapy combined with anti-PD1 (programmed cell death 1) antibodies (trepril monoclonal antibodies) significantly enhanced the cytotoxic activity of CD8 + T cells against the melanoma cell line.

Conclusion

In this study, we developed an inflammatory response gene signature model that predicts patient survival and immunotherapy response in multiple malignancies. We further found that the predictive performance in the non-small cell lung cancer and gastric cancer group had the highest value among the six different malignancy subgroups. When compared with existing signatures, the inflammatory response gene signature scores for on-treatment samples were more robust predictors of the response to CIT in metastatic melanoma.

Prognostic value of body mass index for first-line chemoimmunotherapy combinations in advanced non-small cell lung cancer in Chinese population

Background

Few studies have examined the correlation between body mass index (BMI) and effectiveness of first-line chemoimmunotherapy in patients with advanced non-small cell lung cancer (NSCLC); moreover, the conclusion remains elusive and no such studies have been conducted in the Chinese population. Our study aimed to validate the predictive significance of BMI in Chinese patients with advanced NSCLC receiving first-line chemoimmunotherapy combinations.

Methods

Data of patients with advanced NSCLC treated with first-line chemoimmunotherapy between June 2018 and February 2022 at three centers were retrieved retrospectively. The association between baseline BMI with progression-free survival (PFS) and overall survival (OS) was evaluated using the Kaplan-Meier method and Cox regression models. BMI was categorized according to the World Health Organization criteria.

Results

Of the included 805 patients, 5.3 % were underweight, 63.4 % had normal weight, 27.8 % were overweight, and 3.5 % were obese. Survival analysis showed that patients in the high BMI group had significantly better PFS (p = 0.012) and OS (p = 0.014) than those in the low BMI group. Further, patients in the overweight subgroup had better PFS (p = 0.036) and OS (p = 0.043) compared to the normal weight population. The results of Cox regression analysis confirmed the correlations between BMI and prognosis of advanced NSCLC patients receiving first-line chemoimmunotherapy combinations.

Conclusions

Baseline BMI affected the clinical outcomes of first-line chemoimmunotherapy combinations in patients with advanced NSCLC, and was especially favorable for the overweight subgroup.

Elevated RACGAP1 Expression Enhances Malignant Potential in Lung Adenocarcinoma and Serves as a Prognostic Factor

Background: While RACGAP1 is identified as a potential oncogene, its specific role in lung adenocarcinoma (LUAD) remains unclear. Methods: First, we conducted a comprehensive analysis of the role of RACGAP1 across 33 types of cancer. Subsequently, we investigated the expression levels of RACGAP1 and its impact on prognosis using data from The Cancer Genome Atlas (TCGA) database. We utilized single-cell sequencing data to explore the tumor-related processes of RACGAP1 in LUAD and validated our findings through experimental verification. Employing a consensus clustering (CC) approach, we subdivided LUAD patients into two subtypes based on RACGAP1 cell cycle-related genes (RrCCGs). These subtypes exhibited significant differences in tumor characteristics, lymph node metastasis, and recurrence. Furthermore, we evaluated the prognostic influence of RrCCGs using univariate Cox regression and least absolute shrinkage and selection operator regression models (LASSO), successfully establishing a prognostic model. Results: RACGAP1 is frequently overexpressed in various tumors and can impact the prognosis of patients with LUAD. Additionally, experimental evidence has demonstrated that low expression of RACGAP1 favors tumor cell apoptosis and restoration of the cell cycle, while high expression promotes invasion and metastasis. Through CC analysis of RrCCGs, patients were classified into two groups, with survival analysis revealing distinct prognoses and stages between the two groups. Furthermore, Cox and LASSO regression successfully constructed a prognostic model with robust predictive capability.

Comprehensive pan-cancer analysis of mitochondrial outer membrane permeabilisation activity reveals positive immunomodulation and assists in identifying potential therapeutic targets for immunotherapy resistance

BACKGROUND

Mitochondrial outer membrane permeabilisation (MOMP) plays a pivotal role in cellular death and immune activation. A deeper understanding of the impact of tumour MOMP on immunity will aid in guiding more effective immunotherapeutic strategies.

METHODS

A comprehensive pan-cancer dataset comprising 30 cancer-type transcriptomic cohorts, 20 immunotherapy transcriptomic cohorts and three immunotherapy scRNA-seq datasets was collected and analysed to determine the influence of tumour MOMP activity on clinical prognosis, immune infiltration and immunotherapy effectiveness. Leveraging 65 scRNA-Seq datasets, the MOMP signature (MOMP.Sig) was developed to accurately reflect tumour MOMP activity. The clinical predictive value of MOMP.Sig was explored through machine learning models. Integration of the MOMP.Sig model and a pan-cancer immunotherapy CRISPR screen further investigated potential targets to overcome immunotherapy resistance, which subsequently underwent clinical validation.

RESULTS

Our research revealed that elevated MOMP activity reduces mortality risk in cancer patients, drives the formation of an anti-tumour immune environment and enhances the response to immunotherapy. This finding emphasises the potential clinical application value of MOMP activity in immunotherapy. MOMP.Sig, offering a more precise indicator of tumour cell MOMP activity, demonstrated outstanding predictive efficacy in machine-learning models. Moreover, with the assistance of the MOMP.Sig model, FOXO1 was identified as a core modulator that promotes immune resistance. Finally, these findings were successfully validated in clinical immunotherapy cohorts of skin cutaneous melanoma and triple-negative breast cancer patients.

CONCLUSIONS

This study enhances our understanding of MOMP activity in immune modulation, providing valuable insights for more effective immunotherapeutic strategies across diverse tumours.

Silibinin is a suppressor of the metastasis-promoting transcription factor ID3

BACKGROUND

ID3 (inhibitor of DNA binding/differentiation-3) is a transcription factor that enables metastasis by promoting stem cell-like properties in endothelial and tumor cells. The milk thistle flavonolignan silibinin is a phytochemical with anti-metastatic potential through largely unknown mechanisms.

HYPOTHESIS/PURPOSE

We have mechanistically investigated the ability of silibinin to inhibit the aberrant activation of ID3 in brain endothelium and non-small cell lung cancer (NSCLC) models.

METHODS

Bioinformatic analyses were performed to investigate the co-expression correlation between ID3 and bone morphogenic protein (BMP) ligands/BMP receptors (BMPRs) genes in NSCLC patient datasets. ID3 expression was assessed by immunoblotting and qRT-PCR. Luciferase reporter assays were used to evaluate the gene sequences targeted by silibinin to regulate ID3 transcription. In silico computational modeling and LanthaScreen TR-FRET kinase assays were used to characterize and validate the BMPR inhibitory activity of silibinin. Tumor tissues from NSCLC xenograft models treated with oral silibinin were used to evaluate the in vivo anti-ID3 effects of silibinin.

RESULTS

Analysis of lung cancer patient datasets revealed a top-ranked positive association of ID3 with the BMP9 endothelial receptor ACVRL1/ALK1 and the BMP ligand BMP6. Silibinin treatment blocked the BMP9-induced activation of the ALK1-phospho-SMAD1/5-ID3 axis in brain endothelial cells. Constitutive, acquired, and adaptive expression of ID3 in NSCLC cells were all significantly downregulated in response to silibinin. Silibinin blocked ID3 transcription via BMP-responsive elements in ID3 gene enhancers. Silibinin inhibited the kinase activities of BMPRs in the micromolar range, with the lower IC50 values occurring against ACVRL1/ALK1 and BMPR2. In an in vivo NSCLC xenograft model, tumoral overexpression of ID3 was completely suppressed by systematically achievable oral doses of silibinin.

CONCLUSIONS

ID3 is a largely undruggable metastasis-promoting transcription factor. Silibinin is a novel suppressor of ID3 that may be explored as a novel therapeutic approach to interfere with the metastatic dissemination capacity of NSCLC.

Epithelial-mesenchymal transition induced by tumor cell-intrinsic PD-L1 signaling predicts a poor response to immune checkpoint inhibitors in PD-L1-high lung cancer

BACKGROUND

We investigated the role of tumor cell-intrinsic PD-L1 signaling in the epithelial-mesenchymal transition (EMT) in non-small-cell lung cancer (NSCLC) and the role of EMT as a predictive biomarker for immune checkpoint inhibitor (ICI) therapy.

METHODS

PD-L1-overexpressing or PD-L1-knockdown NSCLC cells underwent RNA-seq and EMT phenotype assessment. Mouse lung cancer LLC cells were injected into nude mice. Two cohorts of patients with NSCLC undergoing ICI therapy were analyzed.

RESULTS

RNA-seq showed that EMT pathways were enriched in PD-L1-high NSCLC cells. EMT was enhanced by PD-L1 in NSCLC cells, which was mediated by transforming growth factor-β (TGFβ). PD-L1 promoted the activation of p38-MAPK by binding to and inhibiting the protein phosphatase PPM1B, thereby increasing the TGFβ production. Tumor growth and metastasis increased in nude mice injected with PD-L1-overexpressing LLC cells. In the ICI cohort, EMT signature was higher in patients with progressive disease than in those with responses, and EMT was significantly associated with poor survival in PD-L1-high NSCLC. In PD-L1-high NSCLC, EMT was associated with increased M2-macrophage and regulatory T-cell infiltrations and decreased cytotoxic T-cell infiltration.

CONCLUSIONS

Tumor cell-intrinsic PD-L1 function contributes to NSCLC progression by promoting EMT. EMT may predict an unfavorable outcome after ICI therapy in PD-L1-high NSCLC.

ILT2 and ILT4 Drive Myeloid Suppression via Both Overlapping and Distinct Mechanisms

Solid tumors are dense three-dimensional (3D) multicellular structures that enable efficient receptor-ligand trans interactions via close cell-cell contact. Immunoglobulin-like transcript (ILT)2 and ILT4 are related immune-suppressive receptors that play a role in the inhibition of myeloid cells within the tumor microenvironment. The relative contribution of ILT2 and ILT4 to immune inhibition in the context of solid tumor tissue has not been fully explored. We present evidence that both ILT2 and ILT4 contribute to myeloid inhibition. We found that although ILT2 inhibits myeloid cell activation in the context of trans-engagement by MHC-I, ILT4 efficiently inhibits myeloid cells in the presence of either cis- or trans-engagement. In a 3D spheroid tumor model, dual ILT2/ILT4 blockade was required for the optimal activation of myeloid cells, including the secretion of CXCL9 and CCL5, upregulation of CD86 on dendritic cells, and downregulation of CD163 on macrophages. Humanized mouse tumor models showed increased immune activation and cytolytic T-cell activity with combined ILT2 and ILT4 blockade, including evidence of the generation of immune niches, which have been shown to correlate with clinical response to immune-checkpoint blockade. In a human tumor explant histoculture system, dual ILT2/ILT4 blockade increased CXCL9 secretion, downregulated CD163 expression, and increased the expression of M1 macrophage, IFNγ, and cytolytic T-cell gene signatures. Thus, we have revealed distinct contributions of ILT2 and ILT4 to myeloid cell biology and provide proof-of-concept data supporting the combined blockade of ILT2 and ILT4 to therapeutically induce optimal myeloid cell reprogramming in the tumor microenvironment.

Identification of the novel biomarkers involved in the mitochondrial metabolism-related reactive oxygen species and their role in lung cancer T-cell exhaustion and immunotherapy

Purpose

To study the role of mitochondrial metabolism and obtain novel biomarkers in immunotherapy for non-small cell lung cancer (NSCLC).

Methods

We collected the 188 genes involved in mitochondrial metabolism(MMGs) from the MSIGDB project and then quantified the activity of mitochondrial metabolism. All the NSCLC patients were divided into C1 and C2 clusters based on the 26 prognosis-related MMGs. The differences in biology, differential immune microenvironment, chronic hypoxia and prognosis between C1 and C2 patients were also analyzed. In addition, we validated the results of bioinformatics analysis in lung cancer tissues and cell lines.

Results

Patients in the C2 cluster had a higher level of mitochondrial metabolism. Patients in the C2 cluster responded better to immunotherapy and had a lower level of T-cell exclusion. The markers of T-cell failure were upregulated in the C1 patients. Hypoxia can lead to a high percentage of C1 patients. ADH1C might be involved in mitochondrial metabolism and immunotherapy response, which can be affected by hypoxia, making it an underlying biomarker. The expression levels of ADH1C in BEAS-2B, H1299, A549 and H460 cells were detected, revealing that ADH1C is upregulated in lung cancer cells. We observed that patients with low ADH1C expression had a longer survival time. The enzyme activities of HK, PK, LDH and SDH were significantly reduced in H1299 and H460 cells with ADH1C knockdown, along with more ROS. Furthermore, the expression levels of PD-L1 and HHLA2 in tumor tissues were analyzed, which found that ADH1C was significantly positively correlated with the expression of PD-L1 and HHLA2.

Conclusions

In summary, our study comprehensively explored the molecules involved in mitochondrial metabolism and their role in immunotherapy and T lymphocyte failure.

Plasticity-induced repression of Irf6 underlies acquired resistance to cancer immunotherapy in pancreatic ductal adenocarcinoma

Acquired resistance to immunotherapy remains a critical yet incompletely understood biological mechanism. Here, using a mouse model of pancreatic ductal adenocarcinoma (PDAC) to study tumor relapse following immunotherapy-induced responses, we find that resistance is reproducibly associated with an epithelial-to-mesenchymal transition (EMT), with EMT-transcription factors ZEB1 and SNAIL functioning as master genetic and epigenetic regulators of this effect. Acquired resistance in this model is not due to immunosuppression in the tumor immune microenvironment, disruptions in the antigen presentation machinery, or altered expression of immune checkpoints. Rather, resistance is due to a tumor cell-intrinsic defect in T-cell killing. Molecularly, EMT leads to the epigenetic and transcriptional silencing of interferon regulatory factor 6 (Irf6), rendering tumor cells less sensitive to the pro-apoptotic effects of TNF-α. These findings indicate that acquired resistance to immunotherapy may be mediated by programs distinct from those governing primary resistance, including plasticity programs that render tumor cells impervious to T-cell killing.

Keratin gene signature expression drives epithelial-mesenchymal transition through enhanced TGF-β signaling pathway activation and correlates with adverse prognosis in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) stands as the foremost histological subtype of non-small-cell lung cancer, accounting for approximately 40% of all lung cancer diagnoses. However, there remains a critical unmet need to enhance the prediction of clinical outcomes and therapy responses in LUAD patients. Keratins (KRTs), serving as the structural components of the intermediate filament cytoskeleton in epithelial cells, play a crucial role in the advancement of tumor progression. This study investigated the prognostic significance of the KRT family gene and developed a KRT gene signature (KGS) for prognostic assessment and treatment guidance in LUAD.

Methods

Transcriptome profiles and associated clinical details of LUAD patients were meticulously gathered from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The KGS score was developed based on the expression of five prognostic KRT genes (KRT7, KRT8, KRT17, KRT18, and KRT80), and the upper quartile of the KGS score was chosen as the cutoff. The Kaplan-Meier method was evaluated to compare survival outcomes between KGS-high and KGS-low groups. The underlying mechanism was further investigated by GSEA, GSVA, and other bioinformatic algorithms.

Results

High expression of the KGS signature exhibited a robust association with poorer overall survival (OS) in the TCGA-LUAD dataset (HR: 1.81; 95% CI: 1.35-2.42, P = 0.00011). The association was further corroborated in three external GEO cohorts, including GSE31210 (HR: 3.31; 95% CI: 1.7-6.47, P = 0.00017), GSE72094 (HR: 1.95; 95% CI: 1.34-2.85, P = 0.00057) and GSE26939 (HR: 3.19; 95% CI: 1.74-5.84, P < 0.0001). Interestingly, KGS-high tumors revealed enrichments in TGF-β and WNT-β catenin signaling pathways, exhibited heightened activation of the epithelial-mesenchymal transition (EMT) pathway and proved intensified tumor stemness compared to their KGS-low counterparts. Additionally, KGS-high tumor cells exhibited increased sensitivity to several targeted agents, including gefitinib, erlotinib, lapatinib, and trametinib, in comparison to KGS-low cells.

Conclusion

This study developed a KGS score that independently predicts the prognosis in LUAD. High expression of KGS score, accompanied by upregulation of TGF-β and WNT-β catenin signaling pathways, confers more aggressive EMT and tumor progression.

Computational immunogenomic approaches to predict response to cancer immunotherapies

Cancer immunogenomics is an emerging field that bridges genomics and immunology. The establishment of large-scale genomic collaborative efforts along with the development of new single-cell transcriptomic techniques and multi-omics approaches have enabled characterization of the mutational and transcriptional profiles of many cancer types and helped to identify clinically actionable alterations as well as predictive and prognostic biomarkers. Researchers have developed computational approaches and machine learning algorithms to accurately obtain clinically useful information from genomic and transcriptomic sequencing data from bulk tissue or single cells and explore tumours and their microenvironment. The rapid growth in sequencing and computational approaches has resulted in the unmet need to understand their true potential and limitations in enabling improvements in the management of patients with cancer who are receiving immunotherapies. In this Review, we describe the computational approaches currently available to analyse bulk tissue and single-cell sequencing data from cancer, stromal and immune cells, as well as how best to select the most appropriate tool to address various clinical questions and, ultimately, improve patient outcomes.

Evaluation of cell surface vimentin positive circulating tumor cells as a prognostic biomarker for stage III/IV colorectal cancer

Currently, little is known about the phenotypes of circulating tumor cells (CTCs), particularly epithelial and mesenchymal phenotypes, and their impact on the prognosis of colorectal cancer (CRC) patients. This study aims to investigate the CTC phenotypes and their prognostic implications in stage III/IV CRC. Patients who were diagnosed with CRC and underwent CTC detection at two hospitals were included. CTCs were detected using a mesenchymal CTC kit, and the clinical and pathological characteristics of CTCs were compared with those of cell surface vimentin-positive CTCs (CSV-CTCs). Disease-free survival (DFS) was assessed and used as an indicator of CTC phenotype-related prognosis. Univariate and multivariate Cox regression analyses were made to identify risk factors, and nomogram models were employed for prognostic prediction. A total of 82 patients were enrolled, with a CTC detection rate of 86.6%. Among the detected CTCs, 60% were CSV-CTCs. The CSV-CTC count showed a positive correlation with the T-stage, the M-stage, and the location of the primary tumor (P = 0.01, P = 0.014, and P = 0.01, respectively). Kaplan-Meier survival analysis revealed that CSV-CTCs were associated with worse DFS in patients receiving first-line oxaliplatin chemotherapy (hazard ratio (HR) = 3.78, 95% CI 1.55-9.26, p = 0.04). When the cut-off value of the CSV-CTC count was 3, the optimal prognostic prediction was achieved. Compound models considering CSV-CTCs, TNM staging, the site of the primary tumor and the Ras gene status yielded the best results in both the receiver operating characteristic (ROC) analysis and the decision curve analysis (DCA). This study indicates that CSV-CTCs predominate in CTCs of CRC patients, and a count of CSV-CTCs ≥ 3 is an independent risk factor for worse prognosis.

Radiation-associated secondary malignancies: a novel opportunity for applying immunotherapies

Radiation is commonly used as a treatment intended to cure or palliate cancer patients. Despite remarkable advances in the precision of radiotherapy delivery, even the most advanced forms inevitably expose some healthy tissues surrounding the target site to radiation. On rare occasions, this results in the development of radiation-associated secondary malignancies (RASM). RASM are typically high-grade and carry a poorer prognosis than their non-radiated counterparts. RASM are characterized by a high mutation burden, increased T cell infiltration, and a microenvironment that bears unique inflammatory signatures of prior radiation, including increased expression of various cytokines (e.g., TGF-β, TNF-α, IL4, and IL10). Interestingly, these cytokines have been shown to up-regulate the expression of PD-1 and/or PD-L1-an immune checkpoint receptor/ligand pair that is commonly targeted by immune checkpoint blocking immunotherapies. Here, we review the current understanding of the tumor-immune interactions in RASM, highlight the distinct clinical and molecular characteristics of RASM that may render them immunologically "hot," and propose a rationale for the formal testing of immune checkpoint blockade as a treatment approach for patients with RASM.

The transcriptome signature analysis of the epithelial-mesenchymal transition and immune cell infiltration in colon adenocarcinoma

The epithelial-mesenchymal transition (EMT) process is tightly connected to tumors' immune microenvironment. In colon adenocarcinoma (COAD), both the EMT and immune cell infiltration contribute to tumor progression; however, several questions regarding the mechanisms governing the interaction between EMT and the immune response remain unanswered. Our study aims to investigate the cross-talk between these two processes in cases of COAD and identify the key regulators involved. We utilized the EMT and immune signatures of samples from the COAD-TCGA database to identify three subtypes of COAD: high mesenchymal, medium mesenchymal, and low mesenchymal. We observed that EMT was associated with increased tumor immune response and infiltration mediated by pro-inflammatory cytokines. However, EMT was also linked to immunosuppressive activity that involved regulatory T cells, dendritic cells, and the upregulated expression of multiple immune checkpoints, such as PD-1, PDL-1, CTLA-4, and others. Finally, we employed the multivariate random forest feature importance method to identify key genes, such as DOK2 and MSRB3, that may play crucial roles in both EMT and the intratumoral immune response.

Evaluation of ITGB1 expression as a predictor of the therapeutic effects of immune checkpoint inhibitors in gastric cancer

BACKGROUND

Gastric cancer (CC) is a disease with high incidence and mortality rate. Immunotherapy is an important method for gastric cancer while lack of effective predictor. Integrins play an important role in the development. We aimed to explore the predictive value of β1 integrin (ITGB1) as a predictor of immunnotherapy in gastric cancer.

METHODS

Differential expression analysis was conducted using the Gene Expression Profiling Interactive Analysis (GEPIA) 2.0 and GEO databases. GEPIA data were used to evaluate the prognostic value of ITGB1 in gastric cancer (GC). Transcriptomic and clinical data of GC and normal tissues were downloaded from The Cancer Genome Atlas database, and the TIMER database was used to evaluate the association between ITGB1 and immune infiltration. Time-dependent receiver operating characteristic (ROC) curve analysis was used to determine the prognostic value of ITGB1. To verify ITGB1 expression at the protein level, immunohistochemical staining was conducted. In addition, to analyze the correlation of ITGB1 with PD-1 and PD-L1, we examined levels of PD-1 and PD-L1 by IHC and determined the predictive value of ITGB1 for anti-PD-1 therapy in GC by ROC curve analysis.

RESULTS

Compared with normal tissues, analysis of GEPIA and data at protein levels showed significantly higher expression of ITGB1 in GC. In addition, higher expression of ITGB1 was associated with worse pathological G-staging and tumor T-staging, which suggested that ITGB1 is a risk factor for poor prognosis in GC. The level of ITGB1 expression was positively correlated with CD8 + T cells, neutrophils, macrophages, and dendritic cells. ITGB1 expression was also correlated with PD-L1 expression, and this was further verified at the protein level by immunohistochemical analysis. The area under the ROC curve was 0.808.

CONCLUSION

ITGB1 may be a promising prognostic biomarker and effective predictor for anti-PD-1 therapy in GC.

TRIAL REGISTRATION

Retrospectively registered.

High level of C-reactive protein as a predictive factor for immune-related adverse events of immune checkpoint inhibitors in non-small cell lung cancer: a retrospective study

Background

Several risk factors for the immune-related adverse events (irAEs) during treatment with immune checkpoint inhibitors (ICIs) have been reported, of which include high levels of C-reactive protein (CRP). In this study, we aim to evaluate CRP levels before ICIs treatments as potential predictive biomarkers of irAEs incidence rate and overall survival (OS) in patients with advanced non-small cell lung cancer (NSCLC).

Methods

Between December 1, 2015 to December 31, 2019, we retrospectively collected all adult patients with NSCLC who received at least one dose of an ICI targeting the PD-1/PD-L1 axis at the Iwate Medical University Hospital in Japan. In this study the patients were categorized into low and high groups with a cut-off value of 10 mg/L as the baseline level of CRP before the ICI treatment. The primary endpoint was relationship between CRP levels at baseline and incidence of irAEs. The secondary endpoints were the relationship of progression-free survival (PFS) and OS.

Results

A total of 101 irAEs, and 25 severe irAEs were observed. The incidence of the most irAEs was higher in the high CRP group compared to the low CRP group (54.4% vs. 34.5%, respectively, P=0.003). The most frequent irAEs were skin rush (28.8%), followed by pneumonitis (19.2%), hypothyroidism (15.4%), and hepatotoxicity (9.6%). The most common grade 3 or 4 irAEs was pneumonitis (7.9%), which tended to be more frequent in the high CRP group. In multivariate analysis, patients with high CRP levels had an adjusted OR of 2.41 and were associated with an increased risk of developing irAEs (95% CI: 1.16-4.43, P=0.020). The high CRP group was related with shorter PFS compared to the low CRP group (2.2 vs. 3.3 months, respectively, P=0.006). The high CRP group were also related with shorter OS compared to the low CRP group (8.9 vs. 39.1 months, respectively, P<0.001).

Conclusions

The results suggest that higher level of pretreatment CRP is involved in the development of irAE and poor prognosis. Identification of patients at high risk of irAEs would be of great help. Future multicenter prospective studies are needed to expand on this study.

Plasticity-induced repression of Irf6 underlies acquired resistance to cancer immunotherapy

Acquired resistance to immune checkpoint immunotherapy remains a critical yet incompletely understood biological mechanism. Here, using a mouse model of pancreatic ductal adenocarcinoma (PDAC) to study tumor relapse following immunotherapy-induced responses, we found that tumors underwent an epithelial-to-mesenchymal transition (EMT) that resulted in reduced sensitivity to T cell-mediated killing. EMT-transcription factors (EMT-TFs) ZEB1 and SNAIL function as master genetic and epigenetic regulators of this tumor-intrinsic effect. Acquired resistance was not due to immunosuppression in the tumor immune microenvironment, disruptions in the antigen presentation machinery, or altered expression of immune checkpoints. Rather, EMT was associated with epigenetic and transcriptional silencing of interferon regulatory factor 6 (Irf6), which renders tumor cells less sensitive to the pro-apoptotic effects of TNF-α. These findings show how resistance to immunotherapy in PDAC can be acquired through plasticity programs that render tumor cells impervious to T cell killing.

The tumor microbiome as a predictor of outcomes in patients with metastatic melanoma treated with immune checkpoint inhibitors

Emerging evidence supports the important role of the tumor microbiome in oncogenesis, cancer immune phenotype, cancer progression, and treatment outcomes in many malignancies. In this study, we investigated the metastatic melanoma tumor microbiome and potential roles in association with clinical outcomes, such as survival, in patients with metastatic disease treated with immune checkpoint inhibitors (ICIs). Baseline tumor samples were collected from 71 patients with metastatic melanoma before treatment with ICIs. Bulk RNA-seq was conducted on the formalin-fixed paraffin-embedded (FFPE) tumor samples. Durable clinical benefit (primary clinical endpoint) following ICIs was defined as overall survival ≥24 months and no change to the primary drug regimen (responders). We processed RNA-seq reads to carefully identify exogenous sequences using the {exotic} tool. The 71 patients with metastatic melanoma ranged in age from 24 to 83 years, 59% were male, and 55% survived >24 months following the initiation of ICI treatment. Exogenous taxa were identified in the tumor RNA-seq, including bacteria, fungi, and viruses. We found differences in gene expression and microbe abundances in immunotherapy responsive versus non-responsive tumors. Responders showed significant enrichment of several microbes including Fusobacterium nucleatum, and non-responders showed enrichment of fungi, as well as several bacteria. These microbes correlated with immune-related gene expression signatures. Finally, we found that models for predicting prolonged survival with immunotherapy using both microbe abundances and gene expression outperformed models using either dataset alone. Our findings warrant further investigation and potentially support therapeutic strategies to modify the tumor microbiome in order to improve treatment outcomes with ICIs.

A novel Chr1-miR-200 driven whole transcriptome signature shapes tumor immune microenvironment and predicts relapse in early-stage lung adenocarcinoma

BACKGROUND

In Lung adenocarcinoma (LUAD), targeted therapies and immunotherapies have moved from metastatic to early stage and stratification of the relapse risk becomes mandatory. Here we identified a miR-200 based RNA signature that delineates Epithelial-to-mesenchymal transition (EMT) heterogeneity and predicts survival beyond current classification systems.

METHODS

A miR-200 signature was identified using RNA sequencing. We scored the miR-200 signature by WISP (Weighted In Silico Pathology), used GSEA to identify pathway enrichments and MCP-counter to characterize immune cell infiltrates. We evaluate the clinical value of this signature in our series of LUAD and using TCGA and 7 published datasets.

RESULTS

We identified 3 clusters based on supervised classification: I is miR-200-sign-down and enriched in TP53 mutations IIA and IIB are miR-200-sign-up: IIA is enriched in EGFR (p < 0.001), IIB is enriched in KRAS mutation (p < 0.001). WISP stratified patients into miR-200-sign-down (n = 65) and miR-200-sign-up (n = 42). Several biological processes were enriched in MiR-200-sign-down tumors, focal adhesion, actin cytoskeleton, cytokine/receptor interaction, TP53 signaling and cell cycle pathways. Fibroblast, immune cell infiltration and PDL1 expression were also significantly higher suggesting immune exhaustion. This signature stratified patients into high-vs low-risk groups, miR-200-sign-up had higher DFS, median not reached at 60 vs 41 months and within subpopulations with stage I, IA, IB, or II. Results were validated on TCGA data on 7 public datasets.

CONCLUSION

This EMT and miR-200-related prognostic signature refines prognosis evaluation independently of tumor stage and paves the way towards assessing the predictive value of this LUAD clustering to optimize perioperative treatment.

Analysis of immune subtypes in non-small-cell lung cancer based on TCGA database

Immunotherapy is one of the main therapeutic approaches for non-small-cell lung cancer (NSCLC). Based on the poor response of immunotherapy, it is crucial to determine the most accurate and widespread predictive characteristics of NSCLC. We retrieved lung squamous cell carcinoma and lung adenocarcinoma gene expression profiles and clinical data from the cancer genome atlas database and classified them into 3 subtypes based on 29 immune gene sets. Combined with previous studies, the expression differences of related pathways and genes in different subtypes were analyzed. We classified them into 3 subtypes: Immunity High, Immunity Medium, and Immunity Low. Immunity High had the strongest immune cell infiltration and antitumor immune activity. Gene ontology enrichment analyses revealed enriched immune-related signaling pathways in lung squamous cell carcinoma. The hyperactivation of cancer-related pathways did not occur in any NSCLC. In addition, the Hippo signaling pathway was negatively correlated with immune signature, whereas epithelial-to-mesenchymal transition was positively correlated. In addition, we found significant differences in immune signatures between males and females; however, no correlation was observed with other clinical data. The identification of NSCLC subtypes based on immune signatures has potential clinical implications for NSCLC treatment.

Prognosis prediction of icotinib as targeted therapy for advanced EGFR-positive non-small cell lung cancer patients

Clinical trials on icotinib, a first-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), have shown promising results as targeted therapy for non-small cell lung cancer (NSCLC). This study aimed to establish an effective scoring system to predict the one-year progression-free survival (PFS) of advanced NSCLC patients with EGFR mutations treated with icotinib as targeted therapy. A total of 208 consecutive patients with advanced EGFR-positive NSCLC treated with icotinib were enrolled in this study. Baseline characteristics were collected within 30 days before icotinib treatment. PFS was taken as the primary endpoint and the response rate as the secondary endpoint. Least absolute shrinkage and selection operator (LASSO) regression analysis and Cox proportional hazards regression analysis were used to select the optimal predictors. We evaluated the scoring system using a five-fold cross-validation. PFS events occurred in 175 patients, with a median PFS of 9.9 months (interquartile range, 6.8-14.5). The objective response rate (ORR) was 36.1%, and the disease control rate (DCR) was 67.3%. The final ABC-Score consisted of three predictors: age, bone metastases and carbohydrate antigen 19-9 (CA19-9). Upon comparison of all three factors, the combined ABC-score (area under the curve (AUC)= 0.660) showed a better predictive accuracy than age (AUC = 0.573), bone metastases (AUC = 0.615), and CA19-9 (AUC = 0.608) individually. A five-fold cross-validation showed good discrimination with AUC = 0.623. The ABC-score developed in this study was significantly effective as a prognostic tool for icotinib in advanced NSCLC patients with EGFR mutations.

Identification of CircRNA signature associated with tumor immune infiltration to predict therapeutic efficacy of immunotherapy

Circular RNAs (circRNAs) play important roles in the regulation of cancer. However, the clinical implications and regulatory networks of circRNAs in cancer patients receiving immune checkpoint blockades (ICB) have not been fully elucidated. Here, we characterize circRNA expression profiles in two independent cohorts of 157 ICB-treated advanced melanoma patients and reveal overall overexpression of circRNAs in ICB non-responders in both pre-treatment and early during therapy. Then, we construct circRNA-miRNA-mRNA regulatory networks to reveal circRNA-related signaling pathways in the context of ICB treatment. Further, we construct an ICB-related circRNA signature (ICBcircSig) score model based on progression-free survival-related circRNAs to predict immunotherapy efficacy. Mechanistically, the overexpression of ICBcircSig circTMTC3 and circFAM117B could increase PD-L1 expression via the miR-142-5p/PD-L1 axis, thus reducing T cell activity and leading to immune escape. Overall, our study characterizes circRNA profiles and regulatory networks in ICB-treated patients, and highlights the clinical utility of circRNAs as predictive biomarkers of immunotherapy.

Immunotherapy in malignant peritoneal mesothelioma (Review)

Over the last decade, there has been a movement in cancer treatment away from cytotoxic therapies toward strategies that enhance the immune system against cancer. Immune checkpoint inhibitors (ICIs) have been incorporated into the treatment regimens for patients with various solid tumors. Mesothelioma trials revealed encouraging efficacy; however, patients with peritoneal mesothelioma are usually excluded, slowing the progress of improving the treatment of this aggressive cancer and compelling oncologist to rely on retrospective studies despite their flaws and limitations. Currently, there is no consensus on the role of ICIs in the treatment of malignant peritoneal mesothelioma (MPeM). The present review discusses data from clinical studies that examined immunotherapy in MPeM and evaluates what is known about the relevance of the tumor microenvironment and clinically validated biomarkers for ICIs efficacy. Furthermore, a proposed strategy for utilizing immunotherapy in treating MPeM is discussed.

Identification of the six-hormone secretion-related gene signature as a prognostic biomarker for colon adenocarcinoma

BACKGROUND

Colon adenocarcinoma (COAD) is a globally prevalent cancer, with hormone secretion playing a crucial role in its progression. Despite this, there is limited understanding of the impact of hormone secretion on COAD prognosis. This study aimed to establish a prognostic signature based on hormone secretion-related genes and to elucidate the potential functional mechanisms of these genes in COAD.

METHODS

Using data from The Cancer Genome Atlas COAD cohort (TCGA-COAD), six hormone secretion-related genes were identified (CYP19A1, FOXD1, GRP, INHBB, SPP1, and UCN). These genes were used to develop a Hormone secretion score (HSS), which was then evaluated using the Kaplan-Meier curve and multivariable Cox analysis. The HSS model was further validated with external GEO cohorts (GSE41258, GSE39582, and GSE87211). Functional enrichment analyses were performed, and the CIBERSORT and TIDE algorithms were used to assess tumor infiltration.

RESULTS

The study developed a prognostic signature, dividing patients into HSS-high and HSS-low groups. The HSS-high group showed a notably worse prognosis within the TCGA-COAD dataset and in three independent datasets: GSE41258, GSE39582, and GSE87211. Moreover, the HSS-high group predicted a shorter overall survival rate in patients maintaining microsatellite stability (MSS). The functional analysis associated HSS-high with the hypoxic, epithelial-mesenchymal transition (EMT), and TGF-β signaling pathways and correlated with distant and lymph node metastases. The tumor immune microenvironment analysis revealed an elevated CIBERSORT score in the HSS-high group, suggesting an association with tumor metastasis. Further, the HSS-high group showed a higher TIDE score, indicating that patients with high HSS scores are less likely to benefit from Immune Checkpoint Inhibitor (ICI) therapy.

CONCLUSIONS

This study demonstrated the prognostic significance of a HSS signature based on six hormone secretion-related genes in COAD. The findings suggest that this gene signature may serve as a reliable biomarker for predicting survival outcomes in COAD patients.

Comprehensive analysis of glycoprotein VI-mediated platelet activation signaling pathway for predicting pan-cancer survival and response to anti-PD-1 immunotherapy

Platelets play a vital role in cancer and immunity. However, few comprehensive studies have been conducted on the role of platelet-related signaling pathways in various cancers and their responses to immune checkpoint blockade (ICB) therapy. In the present study, we focused on the glycoprotein VI-mediated platelet activation (GMPA) signaling pathway and comprehensively evaluated its roles in 19 types of cancers listed in The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Cox regression and meta-analyses showed that for all 19 types of cancers, patients with high GMPA scores tended to have a good prognosis. Furthermore, the GMPA signature score could serve as an independent prognostic factor for patients with skin cutaneous melanoma (SKCM). The GMPA signature was linked to tumor immunity in all 19 types of cancers, and was correlated with SKCM tumor histology. Compared to other signature scores, the GMPA signature scores for on-treatment samples were more robust predictors of the response to anti-PD-1 blockade in metastatic melanoma. Moreover, the GMPA signature scores were significantly negatively correlated with EMMPRIN (CD147) and positively correlated with CD40LG expression at the transcriptomic level in most cancer patient samples from the TCGA cohort and on-treatment samples from anti-PD1 therapy cohorts. The results of this study provide an important theoretical basis for the use of GMPA signatures, as well as GPVI-EMMPRIN and GPVI-CD40LG pathways, to predict the responses of cancer patients to various types of ICB therapy.

TGF-β: A novel predictor and target for anti-PD-1/PD-L1 therapy

Transforming growth factor-β (TGF-β) signaling regulates multiple physiological processes, such as cell proliferation, differentiation, immune homeostasis, and wound healing. Besides, TGF-β plays a vital role in diseases, including cancer. Accumulating evidence indicates that TGF-β controls the composition and behavior of immune components in the tumor microenvironment (TME). Advanced cancers leverage TGF-β to reshape the TME and escape immune surveillance. TGF-β-mediated immune evasion is an unfavorable factor for cancer immunotherapy, especially immune checkpoint inhibitors (ICI). Numerous preclinical and clinical studies have demonstrated that hyperactive TGF-β signaling is closely associated with ICI resistance. It has been validated that TGF-β blockade synergizes with ICI and overcomes treatment resistance. TGF-β-targeted therapies, including trap and bispecific antibodies, have shown immense potential for cancer immunotherapy. In this review, we summarized the predictive value of TGF-β signaling and the prospects of TGF-β-targeted therapies for cancer immunotherapy.

Novel plasma exosome biomarkers for prostate cancer progression in co-morbid metabolic disease

Comorbid Type 2 diabetes (T2D), a metabolic complication of obesity, associates with worse cancer outcomes for prostate, breast, head and neck, colorectal and several other solid tumors. However, the molecular mechanisms remain poorly understood. Emerging evidence shows that exosomes carry miRNAs in blood that encode the metabolic status of originating tissues and deliver their cargo to target tissues to modulate expression of critical genes. Exosomal communication potentially connects abnormal metabolism to cancer progression. Here, we hypothesized that T2D plasma exosomes induce epithelial-mesenchymal transition (EMT) and immune checkpoints in prostate cancer cells. We demonstrate that plasma exosomes from subjects with T2D induce EMT features in prostate cancer cells and upregulate the checkpoint genes CD274 and CD155. We demonstrate that specific exosomal miRNAs that are differentially abundant in plasma of T2D adults compared to nondiabetic controls (miR374a-5p, miR-93-5p and let-7b-3p) are delivered to cancer cells, thereby regulating critical target genes. We build on our previous reports showing BRD4 controls migration and dissemination of castration-resistant prostate cancer, and transcription of key EMT genes, to show that T2D exosomes require BRD4 to drive EMT and immune ligand expression. We validate our findings with gene set enrichment analysis of human prostate tumor tissue in TGCA genomic data. These results suggest novel, non-invasive approaches to evaluate and potentially block progression of prostate and other cancers in patients with comorbid T2D.

Identification and validation of a genomic mutation signature as a predictor for immunotherapy in NSCLC

Currently, the benefits of immune checkpoint inhibitor (ICI) therapy prediction via emerging biomarkers have been identified, and the association between genomic mutation signatures (GMS) and immunotherapy benefits has been widely recognized as well. However, the evidence about non-small cell lung cancer (NSCLC) remains limited. We analyzed 310 immunotherapy patients with NSCLC from the Memorial Sloan Kettering Cancer Center (MSKCC) cohort. Lasso Cox regression was used to construct a GMS, and the prognostic value of GMS could be able to verify in the Rizvi cohort (N=240) and Hellmann cohort (N=75). We further conducted immunotherapy-related characteristics analysis in The Cancer Genome Atlas (TCGA) cohort (N=1052). A total of seven genes (ZFHX3, NTRK3, EPHA7, MGA, STK11, EPHA5, TP53) were identified for GMS model construction. Compared with GMS-high patients, patients with GMS-low had longer overall survival (OS; P<0.001) in the MSKCC cohort and progression-free survival (PFS; P<0.001) in the validation cohort. Multivariate Cox analysis revealed that GMS was an independent predictive factor for NSCLC patients in both the MSKCC and validation cohort. Meanwhile, we found that GMS-low patients reflected enhanced antitumor immunity in TCGA cohort. The results indicated that GMS had not only potential predictive value for the benefit of immunotherapy but also may serve as a potential biomarker to guide clinical ICI treatment decisions for NSCLC.

Pan-cancer analysis of UBE2T with a focus on prognostic and immunological roles in lung adenocarcinoma

Background

Ubiquitin-conjugating enzyme E2 T (UBE2T) is a potential oncogene. However, Pan-cancer analyses of the functional, prognostic and predictive implications of this gene are lacking.

Methods

We first analyzed UBE2T across 33 tumor types in The Cancer Genome Atlas (TCGA) project. We investigated the expression level of UBE2T and its effect on prognosis using the TCGA database. The correlation between UBE2T and cell cycle in pan-cancer was investigated using the single-cell sequencing data in Cancer Single-cell State Atlas (CancerSEA) database. The Weighted Gene Co-expression Network analysis (WGCNA), Univariate Cox and Least absolute shrinkage and selection operator (LASSO) Cox regression models, and receiver operating characteristic (ROC) were applied to assess the prognostic impact of UBE2T-related cell cycle genes (UrCCGs). Furthermore, the consensus clustering (CC) method was adopted to divide TCGA-lung adenocarcinoma (LUAD) patients into subgroups based on UrCCGs. Prognosis, molecular characteristics, and the immune panorama of subgroups were analyzed using Single-sample Gene Set Enrichment Analysis (ssGSEA). Results derived from TCGA-LUAD patients were validated in International Cancer Genome Consortium (ICGC)-LUAD data.

Results

UBE2T is highly expressed and is a prognostic risk factor in most tumors. CancerSEA database analysis revealed that UBE2T was positively associated with the cell cycle in various cancers(r > 0.60, p < 0.001). The risk signature of UrCCGs can reliably predict the prognosis of LUAD (AUC1 year = 0.720, AUC3 year = 0.700, AUC5 year = 0.630). The CC method classified the TCGA-LUAD cohort into 4 UrCCG subtypes (G1–G4). Kaplan–Meier survival analysis demonstrated that G2 and G4 subtypes had worse survival than G3 (Log-rank test PTCGA training set < 0.001, PICGC validation set < 0.001). A comprehensive analysis of immune infiltrates, immune checkpoints, and immunogenic cell death modulators unveiled different immune landscapes for the four subtypes. High immunophenoscore in G3 and G4 tumors suggested that these two subtypes were immunologically “hot,” tending to respond to immunotherapy compared to G2 subtypes (p < 0.001).

Conclusions

UBE2T is a critical oncogene in many cancers. Moreover, UrCCG classified the LUAD cohort into four subgroups with significantly different survival, molecular features, immune infiltrates, and immunotherapy responses. UBE2T may be a therapeutic target and predictor of prognosis and immunotherapy sensitivity.

Integrated Analysis of Single-Cell and Bulk RNA-Sequencing Reveals a Tissue-Resident Macrophage-Related Signature for Predicting Immunotherapy Response in Breast Cancer Patients

Immune checkpoint therapy (ICT) is among the widely used treatments for breast cancer (BC), but most patients do not respond to ICT and the availability of the predictive biomarkers is limited. Emerging evidence indicates that tissue-resident macrophages (RTMs) inhibit BC progression, suggesting that their presence may predict immunotherapy response. A single-cell RNA-sequencing analysis of BC samples was performed to identify five RTM clusters with a mixed phenotype of M1-M2 macrophages. The comprehensive results showed that a high score of each RTM cluster was associated with a high infiltration of CD8+ T cells, M1 macrophages, and dendritic cells, and improved overall survival. In addition, a low score of each RTM cluster was associated with a high infiltration of M0 macrophages, naïve B cells and Tregs, and poor overall survival. Gene signatures from each RTM cluster were significantly enriched in responders compared with nonresponders. Each RTM cluster expression was significantly higher in responders than in nonresponders. The analyses of bulk RNA-seq datasets of BC samples led to identification and validation of a gene expression signature, named RTM.Sig, which contained the related genes of RTM clusters for predicting response to immunotherapy. This study highlights RTM.Sig could provide a valuable tool for clinical decisions in administering ICT.

RAB4A GTPase regulates epithelial-to-mesenchymal transition by modulating RAC1 activation

Epithelial-to-mesenchymal transition (EMT) is a critical underpinning process for cancer progression, recurrence and resistance to drug treatment. Identification of new regulators of EMT could lead to the development of effective therapies to improve the outcome of advanced cancers. In the current study we discovered, using a variety of in vitro and in vivo approaches, that RAB4A function is essential for EMT and related manifestation of stemness and invasive properties. Consistently, RAB4A suppression abolished the cancer cells' self-renewal and tumor forming ability. In terms of downstream signaling, we found that RAB4A regulation of EMT is achieved through its control of activation of the RAC1 GTPase. Introducing activated RAC1 efficiently rescued EMT gene expression, invasion and tumor formation suppressed by RAB4A knockdown in both the in vitro and in vivo cancer models. In summary, this study identifies a RAB4A-RAC1 signaling axis as a key regulatory mechanism for the process of EMT and cancer progression and suggests a potential therapeutic approach to controlling these processes.

The function and clinical implication of circular RNAs in lung cancer

Lung cancer is the leading cause of cancer-related deaths worldwide. Despite the recent advent of promising new targeted therapies, lung cancer diagnostic strategies still have difficulty in identifying the disease at an early stage. Therefore, the characterizations of more sensible and specific cancer biomarkers have become an important goal for clinicians. Circular RNAs are covalently close, endogenous RNAs without 5' end caps or 3'poly (A) tails and have been characterized by high stability, abundance, and conservation as well as display cell/tissue/developmental stage-specific expressions. Numerous studies have confirmed that circRNAs act as microRNA (miRNA) sponges, RNA-binding protein, and transcriptional regulators; some circRNAs even act as translation templates that participate in multiple pathophysiological processes. Growing evidence have confirmed that circRNAs are involved in the pathogenesis of lung cancers through the regulation of proliferation and invasion, cell cycle, autophagy, apoptosis, stemness, tumor microenvironment, and chemotherapy resistance. Moreover, circRNAs have emerged as potential biomarkers for lung cancer diagnosis and prognosis and targets for developing new treatments. In this review, we will summarize recent progresses in identifying the biogenesis, biological functions, potential mechanisms, and clinical applications of these molecules for lung cancer diagnosis, prognosis, and targeted therapy.

Keratin 80 Promotes Migration and Invasion of Non-Small Cell Lung Cancer Cells by Regulating the TGF-β/SMAD Pathway

Upregulation of keratin 80 (KRT80) expression levels and carcinogenic function has been found in several types of tumors. However, its contribution and mechanism in NSCLC remain to be outlined. In this study, bioinformatic investigation from the TCGA dataset revealed that KRT80 was confirmed to be elevated in human NSCLC tissues. The results of qRT-PCR and Western blot assays disclosed that KRT80 was uplifted in NSCLC cells. Data from CCK-8 and colony formation assays exhibited that depletion of KRT80 restrained NSCLC cell proliferation. Findings from Transwell and Western blot assays illustrated that downregulation of KRT80 inhibited NSCLC cell migration, invasion, and EMT. Further mechanism exploration implied that KRT80 may be included within the regulation of EMT of NSCLC cells by affecting the TGF-β/SMAD pathway. Moreover, depletion of KRT80 attenuated xenograft tumor growth and the expressions of KRT80, Ki-67, and TGFBR1. In conclusion, depletion of KRT80 repressed NSCLC cell proliferation, invasion, and EMT, possibly mediated by the TGF-β/SMAD signaling pathway, indicating that KRT80 may be a potentially useful target for NSCLC.

Cellular dissociation grading on biopsies of pulmonary squamous cell carcinoma provides prognostic information across all stages and is congruent with resection specimen grading

Grading of squamous cell carcinomas (SCCs) based on tumour budding and cell nest size has been termed cellular dissociation grading (CDG) and was suggested as a robust outcome predictor when assessed in biopsies and resections of various extrapulmonary SCCs. In pulmonary SCC (pSCC), this has so far been shown only for resected cancers. As most lung cancers are inoperable, it is of utmost importance to clarify whether the prognostic impact of CDG is retained in the biopsy setting. Two independent pSCC biopsy cohorts from Munich (n = 134, non-resected) and Heidelberg (n = 135, resected) were assessed. Tumour budding and cell nest size measures were assembled into the three-tiered CDG system (G1-G3). Data were correlated with clinicopathological parameters and overall- (OS), disease-specific- (DSS), and disease-free survival (DFS). Interobserver variability and concordance between biopsy and resection specimen were also investigated. CDG was highly congruent between biopsy and resection specimens (κ = 0.77, p < 0.001). In both pSCC cohorts, biopsy-derived CDG strongly impacted on OS, DSS, and DFS (e.g. DFS: p < 0.001). In multivariate survival analyses, CDG remained a stage independent predictor of survival in both cohorts (DFS: p < 0.001 respectively; hazard ratio Munich cohort: CDG-G2: 4.31, CDG-G3; 5.14; Heidelberg cohort: CDG-G2: 5.87, CDG-G3: 9.07). Interobserver agreement for CDG was almost perfect (κ = 0.84, p < 0.001). We conclude that assessment of CDG based on tumour budding and cell nest size is feasible on pSCC biopsies and harbours stage independent prognostic information in resectable as well as non-resectable pSCC. Integration of this grading approach into clinicopathological routine should be considered.

Association of ATRX mutations with immunologically active characteristics in patients with MSI-prone tumors

OBJECTIVES

The role of DNA damage repair deficiency in improving immune checkpoint inhibitors (ICIs) efficacy has been widely recognized. Studies have confirmed the association of gene mutations in homologous recombination (HR) with an immune-activated microenvironment. Given the crucial role of the tumor microenvironment in ICIs response, our study aimed to identify specific HR gene mutations that influence the tumor microenvironment and thus serve as potential biomarkers for ICIs in tumors that are prone to occur with microsatellite instability (MSI) events (MSI-prone tumors).

METHODS

The multi-omics and clinical data of MSI-prone tumors were extracted from ICIs-treated and non-ICIs-treated cohorts. We depicted the mutation landscape of HR genes in MSI-prone tumors and identified the prognosis related HR gene mutations. We integrated multiple immunotherapy-related indicators by bioinformatics methods to characterize the anti-tumor immunity and tumor microenvironment.

RESULTS

ATRX, ARID1A, BRCA2 and ATM were the common top four frequently mutated HR genes in MSI-prone tumors, among which ATRX mutations were identified to have prognostic value for ICIs treatment. The bioinformatics analyses suggested that patients with ATRX mutilations (ATRX-mt) have enhanced anti-tumor immunity and inflamed tumor microenvironment in MSI-prone tumors. MSI-stratified analyses revealed the immunologically active features in both microsatellite instability-high (MSI-H) and non-MSI-H populations. There may exist a synergistic effect between ATRX mutations and MSI-H status in immune activation.

CONCLUSIONS

Our work found the association of ATRX mutations with immunologically active characteristics in MSI-prone tumors. The combined use of ATRX mutations and MSI-H status might have potential clinical utility for ICIs selection in MSI-prone tumors.

An immunotherapy response prediction model derived from proliferative CD4+ T cells and antigen-presenting monocytes in ccRCC

Most patients with clear cell renal cell carcinoma (ccRCC) have an impaired response to immune checkpoint blockade (ICB) therapy. Few biomarkers can predict responsiveness, and there is insufficient evidence to extend them to ccRCC clinical use. To explore subtypes and signatures of immunocytes with good predictive performance for ICB outcomes in the ccRCC context, we reanalyzed two ccRCC single-cell RNA sequencing (scRNA-seq) datasets from patients receiving ICB treatment. A subtype of proliferative CD4⁺ T cells and regulatory T cells and a subtype of antigen-presenting monocytes that have good predictive capability and are correlated with ICB outcomes were identified. These findings were corroborated in independent ccRCC ICB pretreatment bulk RNA-seq datasets. By incorporating the cluster-specific marker genes of these three immunocyte subtypes, we developed a prediction model, which reached an AUC of 93% for the CheckMate cohort (172 samples). Our study shows that the ICB response prediction model can serve as a valuable clinical decision-making tool for guiding ICB treatment of ccRCC patients.

Identification of metastasis-related long non-coding RNAs in lung cancer through a novel tumor mesenchymal score

Long non-coding RNAs (lncRNAs) have been proven to play critical roles in epithelial-mesenchymal transition (EMT) and metastasis of lung cancer. However, the biological functions and related mechanisms of lncRNAs are unclear. In addition, the EMT-based prognosis prediction in lung cancer still lacks investigation. Here, we established the methodology of identifying critical metastasis-related lncRNAs using comprehensive datasets of cancer transcriptome, genome and epigenome, and also provided tools for prognosis prediction in lung cancer. Initially, important mesenchymal marker genes were identified to compose the tumor mesenchymal score, which predicted patient prognosis in lung cancer, especially lung adenocarcinoma (LUAD). The score was also correlated with several crucial biological and physiological processes, such as tumor immune and hypoxia. Based on the score, lung cancer patients was classified into epithelial and mesenchymal subtypes, and lncRNAs which exhibited expressional dysregulation, promotor methylation alteration and copy number variation between the two subtypes in LUAD were identified and underwent further prognostic analyses. Finally, we identified 14 lncRNAs as EMT-related and significant biomarkers in prognosis prediction of LUAD. As validation, lncRNA RBPMS-AS1 was proven to be co-expressed with epithelial biomarkers, suppressive for A549 cell migration, invasion and EMT, and also significantly associated with better outcomes of LUAD patients, suggesting the potential of RBPMS-AS1 to serve as a lncRNA epithelial biomarker in metastasis of LUAD. Based on the identified lncRNAs, an EMT-linked lncRNA prognostic signature was further established. Taken together, our study provides robust predictive tools, potential lncRNA targets and feasible screening strategies for future study of lung cancer metastasis.

Five EMT-related genes signature predicts overall survival and immune environment in microsatellite instability-high gastric cancer

BACKGROUND

Microsatellite instability-high (MSI-H) subgroup of gastric cancer (GC) is characterized by a high tumor mutational burden, increased lymphocytic infiltration, and enhanced inflammatory cytokines. GC patients with MSI-H status have a good response to immune checkpoint blockade management. However, heterogeneity within the subtype and the underlying mechanisms of shaping tumor microenvironments remain poorly understood.

METHODS

RNA expression levels and clinical parameters of GC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The data were analyzed using single-sample Gene Set Enrichment Analysis (ssGSEA), univariate Cox regression, multivariate Cox regression, and Least Absolute Shrinkage Selection Operator (LASSO) regression. In addition, multiplex immunohistochemistry (mIHC) was used in our clinical cohort for the tumor microenvironment study.

RESULTS

By ssGSEA and survival analysis, the EMT signaling pathway was identified as a representative pathway, which can stratify the patients with MSI-H GC with significant survival predictive power. Then, a novel representative EMT-related five-gene signature (namely CALU, PCOLCE2, PLOD2, SGCD, and THBS2) was established from EMT signaling gene set, which sensitivity and specificity were further validated in the independent GEO database (GSE62254) cohort for disease outcome prediction. Based on public single-cell data and in situ immunohistochemistry, we found that most of these five genes were abundantly expressed in cancer-associated fibroblasts. Furthermore, patients with high or low risk divided by this five-gene signature exhibited a strong correlation of the distinct patterns of tumor immune microenvironment. By mIHC staining of sections from 30 patients with MSI-H status, we showed that the patients with better prognoses had the increased infiltration of CD8⁺ cells in the primary tumoral tissue.

CONCLUSION

Our study developed a simple five-gene signature for stratifying MSI-H GC patients with survival predictive power.

The Molecular Role of IL-35 in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and a common cause of cancer-related death. Better understanding of the molecular mechanisms, pathogenesis, and treatment of NSCLC can help improve patient outcomes. Significant progress has been made in the treatment of NSCLC, and immunotherapy can prolong patient survival. However, the overall cure and survival rates are low, especially in patients with advanced metastases. Interleukin-35 (IL-35), an immunosuppressive factor, is associated with the onset and prognosis of various cancers. Studies have shown that IL-35 expression is elevated in NSCLC, and it is closely related to the progression and prognosis of NSCLC. However, there are few studies on the mechanism of IL-35 in NSCLC. This study discusses the role of IL-35 and its downstream signaling pathways in the pathogenesis of NSCLC and provides new insights into its therapeutic potential.

A tEMTing target? Clinical and experimental evidence for epithelial-mesenchymal transition in the progression of cutaneous squamous cell carcinoma (a scoping systematic review)

Cutaneous squamous cell carcinoma (cSCC) is a disease with globally rising incidence and poor prognosis for patients with advanced or metastatic disease. Epithelial-mesenchymal transition (EMT) is a driver of metastasis in many carcinomas, and cSCC is no exception. We aimed to provide a systematic overview of the clinical and experimental evidence for EMT in cSCC, with critical appraisal of type and quality of the methodology used. We then used this information as rationale for potential drug targets against advanced and metastatic cSCC. All primary literature encompassing clinical and cell-based or xenograft experimental studies reporting on the role of EMT markers or related signalling pathways in the progression of cSCC were considered. A screen of 3443 search results yielded 86 eligible studies comprising 44 experimental studies, 22 clinical studies, and 20 studies integrating both. From the clinical studies a timeline illustrating the alteration of EMT markers and related signalling was evident based on clinical progression of the disease. The experimental studies reveal connections of EMT with a multitude of factors such as genetic disorders, cancer-associated fibroblasts, and matrix remodelling via matrix metalloproteinases and urokinase plasminogen activator. Additionally, EMT was found to be closely tied to environmental factors as well as to stemness in cSCC via NFκB and β-catenin. We conclude that the canonical EGFR, canonical TGF-βR, PI3K/AKT and NFκB signalling are the four signalling pillars that induce EMT in cSCC and could be valuable therapeutic targets. Despite the complexity, EMT markers and pathways are desirable biomarkers and drug targets for the treatment of advanced or metastatic cSCC.

Stearoyl-CoA desaturase 1 regulates malignant progression of cervical cancer cells

The primary regulatory gene for fatty acid synthesis, stearoyl-CoA desaturase 1 (SCD1), has been linked to the progression of several malignancies. Its role in cervical cancer remains unclear till now. This paper aimed to explore the role and mechanism of SCD1 in cervical cancer. The GEPIA database was used to perform a bioinformatics analysis of the role of SCD1 in cervical cancer staging and prognosis. The influences of SCD1 knockdown on cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) progress were then investigated. Following transcription factor Kruppel like factor 9 (KLF9) was discovered to be negatively correlated with SCD1, the regulatory role of KLF9 in the effects of SCD1 on cervical cancer cells and the signaling pathway was evaluated. According to the GEPIA database, SCD1 level was associated with the cervical cancer stage, the overall survival level, and the disease-free survival level. Cell proliferation, migration, invasion, and EMT progress were all hindered when its expression was knocked down. Novelty, KLF9 reversed the effects of SCD1 on cells, as well as the Akt/glycogen synthase kinase 3β (GSK3β) signaling pathway. Together, SCD1 was negatively regulated by KLF9 and it activated the Akt/GSK3β signaling pathway to promote the malignant progression of cervical cancer cells. Developing SCD1 inhibitors offers novel ideas for the biological treatment of cervical cancer.

Association of a novel 27-gene immuno-oncology assay with efficacy of immune checkpoint inhibitors in advanced non-small cell lung cancer

Background

Immune checkpoint inhibitor (ICI) therapies represent a major advance in treating a variety of advanced-stage malignancies. Nevertheless, only a subset of patients benefit, even when selected based on approved biomarkers such as PD-L1 and tumor mutational burden. New biomarkers are needed to maximize the therapeutic ratio of these therapies.

Methods

In this retrospective cohort, we assessed a 27-gene RT-qPCR immuno-oncology (IO) gene expression assay of the tumor immune microenvironment and determined its association with the efficacy of ICI therapy in 67 advanced-stage NSCLC patients. The 27-gene IO test score (IO score), programmed cell death ligand 1 immunohistochemistry tumor proportion score (PD-L1 TPS), and tumor mutational burden (TMB) were analyzed as continuous variables for response and as binary variables for one-year progression free survival. The threshold for the IO score was prospectively set based upon a previously described training cohort. Prognostic implications of the IO score were evaluated in a separate cohort of 104 advanced-stage NSCLC patients from The Cancer Genome Atlas (TCGA) who received non-ICI therapy.

Results

The IO score was significantly different between responders or non-responders (p = 0.007) and associated with progression-free survival (p = 0.001). Bivariate analysis established that the IO score was independent of PD-L1 TPS and TMB in identifying patients benefiting from ICI therapy. In a separate cohort of late-stage NSCLC patients from TCGA, the IO score was not prognostic of outcome from non-ICI-treated patients.

Conclusions

This study is the first application of this 27-gene IO RT-qPCR assay in a clinical cohort with outcome data. IO scores were significantly associated with response to ICI therapy and prolonged progression-free survival. Together, these data suggest the IO score should be further studied to define its role in informing clinical decision-making for ICI treatment in NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09470-y.

Retinoic Acid Induces an IFN-Driven Inflammatory Tumour Microenvironment, Sensitizing to Immune Checkpoint Therapy

With immune checkpoint therapy (ICT) having reshaped the treatment of many cancers, the next frontier is to identify and develop novel combination therapies to improve efficacy. Previously, we and others identified beneficial immunological effects of the vitamin A derivative tretinoin on anti-tumour immunity. Although it is known that tretinoin preferentially depletes myeloid derived suppressor cells in blood, little is known about the effects of tretinoin on the tumour microenvironment, hampering the rational design of clinical trials using tretinoin in combination with ICT. Here, we aimed to identify how tretinoin changed the tumour microenvironment in mouse tumour models, using flow cytometry and RNAseq, and we sought to use that information to establish optimal dosing and scheduling of tretinoin in combination with several ICT antibodies in multiple cancer models. We found that tretinoin rapidly induced an interferon dominated inflammatory tumour microenvironment, characterised by increased CD8+ T cell infiltration. This phenotype completely overlapped with the phenotype that was induced by ICT itself, and we confirmed that the combination further amplified this inflammatory milieu. The addition of tretinoin significantly improved the efficacy of anti-CTLA4/anti-PD-L1 combination therapy, and staggered scheduling was more efficacious than concomitant scheduling, in a dose-dependent manner. The positive effects of tretinoin could be extended to ICT antibodies targeting OX40, GITR and CTLA4 monotherapy in multiple cancer models. These data show that tretinoin induces an interferon driven, CD8+ T cell tumour microenvironment that is responsive to ICT.

Inhibition of DCLK1 kinase reverses epithelial-mesenchymal transition and restores T-cell activity in pancreatic ductal adenocarcinoma

Immunotherapy has recently become a promising cancer therapy with extensive applications of immune checkpoint inhibitors (ICIs). However, pancreatic ductal adenocarcinoma (PDAC) appears to be unresponsive to immunotherapy due to the immunosuppressive microenvironment. Recent studies showed that cancer stem cell marker DCLK1 promoted the initiation and development of PDAC. Nevertheless, the mechanism driving this process remains unclear. Here, by performing gain-of-function investigations in PDAC cell lines, we demonstrate that both DCLK1 long (DCLK1-iso1, DCLK1-AS) and short (DCLK1-iso4, DCLK1-BL) isoforms can efficiently activate EMT leading to tumor migration and invasion. Consistent with experiments in vitro, bioinformatic analysis demonstrates that DCLK1 may act as a driver of EMT activation in PDAC. Further analysis showed that EMT was associated with an immunosuppressive microenvironment, which includes more immunosuppressive cells and chemokines, and patients with a higher EMT score were less sensitive to immune checkpoint inhibitors according to the TIDE (Tumor Immune Dysfunction and Exclusion) algorithm. Multiplexed immunofluorescence results demonstrated the close correlation between DCLK1, EMT and immunosuppression in PDAC patients. The findings were further confirmed in vivo reflected by decreased CD4+, CD8+ T cells and increased M2 macrophages as well as E-cad loss in DCLK1-overexpressing subcutaneous tumors. Importantly, the highly-specific DCLK1 inhibitor (DCLK1-IN-1) was able to effectively block EMT process and restore T-cell activity. Altogether, our data demonstrate that DCLK1 is strongly associated with tumor immune escape in PDAC and inhibiting DCLK1 kinase activity may be a promising therapeutic modality.

Understanding the Critical Role of Glycolysis-Related lncRNAs in Lung Adenocarcinoma Based on Three Molecular Subtypes

Background

Glycolysis is closely associated with tumor progression, but the roles of lncRNAs in glycolysis have not been comprehensively investigated in lung adenocarcinoma (LUAD). This study is aimed at studying the possible mechanisms of glycolysis-related lncRNAs in tumor development and providing a guidance for targeted therapy.

Methods

Unsupervised consensus clustering was used to identify molecular subtypes. Gene enrichment analysis was applied to screen important pathways involved in tumor progression. A series of immune analysis was performed to assess immune infiltration. Critical transcription factors (TFs) interacting with lncRNAs were selected by Pearson correlation analysis. A first-order partial correlation analysis was implemented to identify critical lncRNAs with prognostic significance.

Results

Three molecular subtypes (C1, C2, and C3) were identified with distinct overall survival. Three subtypes showed differential immune infiltration, and C3 subtype was the optimal for immunotherapy treatment. Ten lncRNA-TF pairs among four glycolysis-related lncRNAs (FTX, LINC00472, PSMA3-AS1, and SNHG14) and six TFs (FOXP1, SP1, MYC, FOXM1, HIF1A, and FOS) were involved in tumor progression. We identified four critical glycolysis-related lncRNAs significantly associated with prognosis.

Conclusions

This study identified three molecular subtypes that could guide personalized therapy. The four-lncRNA prognostic model can serve as an indicator for predicting prognosis or early screening of lung adenocarcinoma patients. The current results improve the understanding of the relation between lncRNAs and glycolysis.

Therapeutic Implications of Tumor Microenvironment in Lung Cancer: Focus on Immune Checkpoint Blockade

In the last decade, the treatment of non-small cell lung cancer (NSCLC) has been revolutionized by the introduction of immune checkpoint inhibitors (ICI) directed against programmed death protein 1 (PD-1) and its ligand (PD-L1), or cytotoxic T lymphocyte antigen 4 (CTLA-4). In spite of these improvements, some patients do not achieve any benefit from ICI, and inevitably develop resistance to therapy over time. Tumor microenvironment (TME) might influence response to immunotherapy due to its prominent role in the multiple interactions between neoplastic cells and the immune system. Studies investigating lung cancer from the perspective of TME pointed out a complex scenario where tumor angiogenesis, soluble factors, immune suppressive/regulatory elements and cells composing TME itself participate to tumor growth. In this review, we point out the current state of knowledge involving the relationship between tumor cells and the components of TME in NSCLC as well as their interactions with immunotherapy providing an update on novel predictors of benefit from currently employed ICI or new therapeutic targets of investigational agents. In first place, increasing evidence suggests that TME might represent a promising biomarker of sensitivity to ICI, based on the presence of immune-modulating cells, such as Treg, myeloid derived suppressor cells, and tumor associated macrophages, which are known to induce an immunosuppressive environment, poorly responsive to ICI. Consequently, multiple clinical studies have been designed to influence TME towards a pro-immunogenic state and subsequently improve the activity of ICI. Currently, the mostly employed approach relies on the association of "classic" ICI targeting PD-1/PD-L1 and novel agents directed on molecules, such as LAG-3 and TIM-3. To date, some trials have already shown promising results, while a multitude of prospective studies are ongoing, and their results might significantly influence the future approach to cancer immunotherapy.

Immune micro-environment and drug analysis of peritoneal endometriosis based on epithelial-mesenchymal transition classification

BACKGROUND

Epithelial-mesenchymal transition (EMT) is a complex event that drives polar epithelial cells transform from adherent cells to motile mesenchymal cells, in which are involved immune cells and stroma cells. EMT plays crucial roles in migration and invasion of endometriosis. The interaction of endometrial implants with the surrounding peritoneal micro-environment probably affects the development of peritoneal endometriosis. To date, very few studies have been carried out on peritoneal endometriosis sub-type classification and micro-environment analysis based on EMT. The purpose of this study is to investigate the potential application of EMT-based classification in precise diagnosis and treatment of peritoneal endometriosis.

METHOD

Based on EMT hallmark genes, 76 peritoneal endometriosis samples were classified into two clusters by consistent cluster classification. EMT scores, which calculated by Z score of 8 epithelial cell marker genes and 8 mesenchymal cell marker genes, were compared in two clusters. Then, immune scores and the abundances of corresponding immune cells, stroma scores and the abundances of corresponding stroma cells were analyzed by the "xCell" package. Futhermore, a diagnostic model was constructed based on 9 diagnostic markers which related to immune score and stroma score by Lasso-Logistic regression analysis. Finally, based on EMT classification, a total of 8 targeted drugs against two clusters were screened out by drug susceptibility analysis via "pRRophetic" package.

RESULTS

Hallmark epithelial-mesenchymal transition was the mainly enriched pathway of differentially expressed genes between peritoneal endometriosis tissues and endometrium tissues. Compared with cluster 2, EMT score and the abundances of most infiltrating stroma cell were significantly higher, while the abundances of most infiltrating immune cells were dramatically less. The diagnostic model could accurately distinguish cluster 1 from cluster 2. Pathway analysis showed drug candidates targeting cluster 1 mainly act on the IGF-1 signaling pathway, and drug candidates targeting cluster 2 mainly block the EGFR signaling pathway.

CONCLUSION

In peritoneal endometriosis, EMT was probably promoted by stroma cell infiltration and inhibited by immune cell infiltration. Besides, our study highlighted the potential uses of the EMT classification in the precise diagnosis and treatment of peritoneal endometriosis.

CTCF Expression and Dynamic Motif Accessibility Modulates Epithelial-Mesenchymal Gene Expression

Epithelial-mesenchymal transition (EMT) and its reversal, mesenchymal-epithelial transition (MET) drive tissue reorganization critical for early development. In carcinomas, processing through EMT, MET, or partial states promotes migration, invasion, dormancy, and metastatic colonization. As a reversible process, EMT is inherently regulated at epigenetic and epigenomic levels. To understand the epigenomic nature of reversible EMT and its partial states, we characterized chromatin accessibility dynamics, transcriptomic output, protein expression, and cellular phenotypes during stepwise reversible EMT. We find that the chromatin insulating protein machinery, including CTCF, is suppressed and re-expressed, coincident with broad alterations in chromatin accessibility, during EMT/MET, and is lower in triple-negative breast cancer cell lines with EMT features. Through an analysis of chromatin accessibility using ATAC-seq, we identify that early phases of EMT are characterized by enrichment for AP-1 family member binding motifs, but also by a diminished enrichment for CTCF binding motifs. Through a loss-of-function analysis, we demonstrate that the suppression of CTCF alters cellular plasticity, strengthening the epithelial phenotype via the upregulation of epithelial markers E-cadherin/CDH1 and downregulation of N-cadherin/CDH2. Conversely, the upregulation of CTCF leads to the upregulation of EMT gene expression and an increase in mesenchymal traits. These findings are indicative of a role of CTCF in regulating epithelial-mesenchymal plasticity and gene expression.