Epithelial-to-mesenchymal transition promotes immune escape by inducing CD70 in non-small cell lung cancer

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.

LPS-induced monocarboxylate transporter-1 inhibition facilitates lactate accumulation triggering epithelial-mesenchymal transformation and pulmonary fibrosis

The epithelial-mesenchymal transformation (EMT) process of alveolar epithelial cells is recognized as involved in the development of pulmonary fibrosis. Recent evidence has shown that lipopolysaccharide (LPS)-induced aerobic glycolysis of lung tissue and elevated lactate concentration are associated with the pathogenesis of sepsis-associated pulmonary fibrosis. However, it is uncertain whether LPS promotes the development of sepsis-associated pulmonary fibrosis by promoting lactate accumulation in lung tissue, thereby initiating EMT process. We hypothesized that monocarboxylate transporter-1 (MCT1), as the main protein for lactate transport, may be crucial in the pathogenic process of sepsis-associated pulmonary fibrosis. We found that high concentrations of lactate induced EMT while moderate concentrations did not. Besides, we demonstrated that MCT1 inhibition enhanced EMT process in MLE-12 cells, while MCT1 upregulation could reverse lactate-induced EMT. LPS could promote EMT in MLE-12 cells through MCT1 inhibition and lactate accumulation, while this could be alleviated by upregulating the expression of MCT1. In addition, the overexpression of MCT1 prevented LPS-induced EMT and pulmonary fibrosis in vivo. Altogether, this study revealed that LPS could inhibit the expression of MCT1 in mouse alveolar epithelial cells and cause lactate transport disorder, which leads to lactate accumulation, and ultimately promotes the process of EMT and lung fibrosis.

Regulation and therapeutic potentials of microRNAs to non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, accounting for 80%-85% of total cases and leading to millions of deaths worldwide. Drug resistance is the primary cause of treatment failure in NSCLC, which urges scientists to develop advanced approaches for NSCLC treatment. Among novel approaches, the miRNA-based method has emerged as a potential approach as it allows researchers to modulate target gene expression. Subsequently, cell behaviors are altered, which leads to the death and the depletion of cancer cells. It has been reported that miRNAs possess the capacity to regulate multiple genes that are involved in various signaling pathways, including the phosphoinositide 3-kinase, receptor tyrosine kinase/rat sarcoma virus/mitogen-activated protein kinase, wingless/integrated, retinoblastoma, p53, transforming growth factor β, and nuclear factor-kappa B pathways. Dysregulation of these signaling pathways in NSCLC results in abnormal cell proliferation, tissue invasion, and drug resistance while inhibiting apoptosis. Thus, understanding the roles of miRNAs in regulating these signaling pathways may enable the development of novel NSCLC treatment therapies. However, a comprehensive review of potential miRNAs in NSCLC treatment has been lacking. Therefore, this review aims to fill the gap by summarizing the up-to-date information on miRNAs regarding their targets, impact on cancer-associated pathways, and prospective outcomes in treating NSCLC. We also discuss current technologies for delivering miRNAs to the target cells, including virus-based, non-viral, and emerging extracellular vesicle-based delivery systems. This knowledge will support future studies to develop an innovative miRNA-based therapy and select a suitable carrier to treat NSCLC effectively.

Dual inhibition of KIF11 and BCL2L1 induces apoptosis in lung adenocarcinoma cells

EGFR-mutant lung adenocarcinoma (LUAD) mostly depends on EGFR for survival and consequently responds well to EGFR inhibitors. However, resistance to the drugs develops almost universally during treatment. We previously demonstrated that EGFR-mutant LUAD cell lines, HCC827 and H1975, have subpopulations of cells, which we termed HCC827 GR2 and H1975 WR7 cells, that can thrive independently of EGFR signaling. These EGFR-independent EGFR-mutant cancer cells are difficult to treat because they lack sensitivity to EGFR inhibitors. Therefore, the development of novel strategies to target EGFR-independent EGFR-mutant LUAD is particularly important. We found that high expression of kinesin family member 11 (KIF11) correlated with poor survival in patients with LUAD. We also observed that KIF11 silencing caused cell cycle arrest at G2/M in HCC827 GR2 and H1975 WR7 cells. Furthermore, dual silencing of KIF11 plus BCL2L1, an anti-apoptotic BCL2 family member, in these two EGFR-independent sublines resulted in marked apoptosis levels. Dual inhibition of KIF11 plus BCL2L1 also induced apoptosis in HCC827 and H1975 parental cells and a KRAS-mutant LUAD cell line, H441. These findings collectively suggest that dual inhibition of KIF11 plus BCL2L1 may be a new approach for the treatment of LUAD.

Machine learning-based integration develops a metabolism-derived consensus model for improving immunotherapy in pancreatic cancer

BACKGROUND

Pancreatic cancer (PAC) is one of the most malignant cancer types and immunotherapy has emerged as a promising treatment option. PAC cells undergo metabolic reprogramming, which is thought to modulate the tumor microenvironment (TME) and affect immunotherapy outcomes. However, the metabolic landscape of PAC and its association with the TME remains largely unexplored.

METHODS

We characterized the metabolic landscape of PAC based on 112 metabolic pathways and constructed a novel metabolism-related signature (MBS) using data from 1,188 patients with PAC. We evaluated the predictive performance of MBS for immunotherapy outcomes in 11 immunotherapy cohorts from both bulk-RNA and single-cell perspectives. We validated our results using immunohistochemistry, western blotting, colony-formation assays, and an in-house cohort.

RESULTS

MBS was found to be negatively associated with antitumor immunity, while positively correlated with cancer stemness, intratumoral heterogeneity, and immune resistant pathways. Notably, MBS outperformed other acknowledged signatures for predicting immunotherapy response in multiple immunotherapy cohorts. Additionally, MBS was a powerful and robust biomarker for predicting prognosis compared with 66 published signatures. Further, we identified dasatinib and epothilone B as potential therapeutic options for MBS-high patients, which were validated through experiments.

CONCLUSIONS

Our study provides insights into the mechanisms of immunotherapy resistance in PAC and introduces MBS as a robust metabolism-based indicator for predicting response to immunotherapy and prognosis in patients with PAC. These findings have significant implications for the development of personalized treatment strategies in patients with PAC and highlight the importance of considering metabolic pathways and immune infiltration in TME regulation.

Immune Checkpoint Blockade Therapy for Breast Cancer: Lessons from Epithelial-Mesenchymal Transition

Immune checkpoint blockade therapies have generated efficacious responses in certain tumor types; however, the responses of breast carcinomas have been largely limited. Moreover, the identity of various parameters that can predict responses to immunotherapies, and at the same time, serve as putative biomarkers that can be therapeutically targeted to enhance the effectiveness of immunotherapies for breast cancers, remains to be comprehensively delineated. Activation of epithelial-mesenchymal plasticity in cancer cells, including those of the breast, increases their tumor-initiating potential and promotes their aggressiveness and resistance to multiple treatment regimens. Moreover, the residence of cancer cells in alternating epithelial or mesenchymal plastic phenotypic states can also influence their immuno-modulatory properties and susceptibilities to immune checkpoint blockade therapies. In this current opinion, we discuss the lessons that can be learnt from epithelial-mesenchymal transition to potentiate the efficacy of immunotherapy for breast cancers. We also discuss strategies to sensitize more-mesenchymal cancer cells to anti-tumor immunity and immune checkpoint blockade therapies, with the hope that these can serve as new translational avenues for the treatment of human breast tumors.

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.

Oncogenic miR-93-5p/Gal-9 axis drives CD8 (+) T-cell inactivation and is a therapeutic target for hepatocellular carcinoma immunotherapy

Evading immune destruction is an emerging hallmark of cancer and a potential key step in tumorigenesis. Immune checkpoint blocker (ICB)-based combination therapies revolutionize the landscape of systemic therapy for HCC. However, the molecular underpinnings governing immune evasion and responses remain unclear. Our study aims to find new regulatory molecules that drive HCC immune escape and tumorigenesis and find new promising immunotherapeutic approaches for HCC. In our study, laser capture microdissection (LCM) and miRNA sequencing combined with in vitro and in vivo experiments identified miR-93-5p as a crucial initiating oncogene during liver progenitor cell (LPC) malignant transformation and immune escape. Mechanistically, miR-93-5p could directly target canonical tumour suppressors such as APC to promote LPC malignant transformation and hepatocarcinogenesis. More importantly, miR-93-5p could induce deviant GAL-9 augmentation to inactivate infiltrated CD8(+) T cells and induce immune evasion by targeting several epigenetic regulators, such as AEBP2, and then regulating H3K4me3/H3K27me3 bivalency. Experiments in C57BL/6 mice demonstrated that blockade of Gal-9 abrogated miR-93-5p-induced HCC progression and improved their prognosis. Clinically, we identified a unique subtype of HCC closely associated with high GAL-9 expression and anti-PD1 treatment resistance. Our study highlights the pivotal role of the miR-93-5p/Gal-9 axis in driving HCC immune escape and tumorigenesis. Blocking GAL-9 is an effective and promising immunotherapeutic approach for HCC.

Newly identified form of phenotypic plasticity of cancer: immunogenic mimicry

Cancer plasticity is now a recognized new hallmark of cancer which is due to disturbances of cell differentiation programs. It is manifested not only in various forms like the best-known epithelial-mesenchymal transition (EMT) but also in vasculogenic and megakaryocytic mimicries regulated by EMT-specific or less-specific transcription factors such as HIF1a or STAT1/2. Studies in the past decades provided ample data that cancer plasticity can be manifested also in the expression of a vast array of immune cell genes; best-known examples are PDL1/CD274, CD47, or IDO, and we termed it immunogenic mimicry (IGM). However, unlike other types of plasticities which are epigenetically regulated, expression of IGM genes are frequently due to gene amplifications. It is important that the majority of the IGM genes are regulated by interferons (IFNs) suggesting that their protein expressions are regulated by the immune microenvironment. Most of the IGM genes have been shown to be involved in immune escape of cancers broadening the repertoire of these mechanisms and offering novel targets for immunotherapeutics.

Nomograms for Predicting the Risk and Prognosis of Liver Metastases in Pancreatic Cancer: A Population-Based Analysis

The liver is the most prevalent location of distant metastasis for pancreatic cancer (PC), which is highly aggressive. Pancreatic cancer with liver metastases (PCLM) patients have a poor prognosis. Furthermore, there is a lack of effective predictive tools for anticipating the diagnostic and prognostic techniques that are needed for the PCLM patients in current clinical work. Therefore, we aimed to construct two nomogram predictive models incorporating common clinical indicators to anticipate the risk factors and prognosis for PCLM patients. Clinicopathological information on pancreatic cancer that referred to patients who had been diagnosed between the years of 2004 and 2015 was extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression analyses and a Cox regression analysis were utilized to recognize the independent risk variables and independent predictive factors for the PCLM patients, respectively. Using the independent risk as well as prognostic factors derived from the multivariate regression analysis, we constructed two novel nomogram models for predicting the risk and prognosis of PCLM patients. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, the consistency index (C-index), and the calibration curve were then utilized to establish the accuracy of the nomograms’ predictions and their discriminability between groups. Using a decision curve analysis (DCA), the clinical values of the two predictors were examined. Finally, we utilized Kaplan–Meier curves to examine the effects of different factors on the prognostic overall survival (OS). As many as 1898 PCLM patients were screened. The patient’s sex, primary site, histopathological type, grade, T stage, N stage, bone metastases, lung metastases, tumor size, surgical resection, radiotherapy, and chemotherapy were all found to be independent risks variables for PCLM in a multivariate logistic regression analysis. Using a multivariate Cox regression analysis, we discovered that age, histopathological type, grade, bone metastasis, lung metastasis, tumor size, and surgery were all independent prognostic variables for PCLM. According to these factors, two nomogram models were developed to anticipate the prognostic OS as well as the risk variables for the progression of PCLM in PCLM patients, and a web-based version of the prediction model was constructed. The diagnostic nomogram model had a C-index of 0.884 (95% CI: 0.876–0.892); the prognostic model had a C-index of 0.686 (95% CI: 0.648–0.722) in the training cohort and a C-index of 0.705 (95% CI: 0.647–0.758) in the validation cohort. Subsequent AUC, calibration curve, and DCA analyses revealed that the risk and predictive model of PCLM had high accuracy as well as efficacy for clinical application. The nomograms constructed can effectively predict risk and prognosis factors in PCLM patients, which facilitates personalized clinical decision-making for patients.