Cancer cells escape the immune system by increasing stemness through epigenetic reprogramming

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

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

Protumorigenic Interferon-Stimulated Genes in Cancer: A Comprehensive Review

Interferon-stimulated genes (ISGs), whose production is triggered by interferons, are known to defend the host from pathogenic and cancer-specific antigens, one of which is by inducing apoptosis in infected or mutated cells. It has been reported recently that specific ISGs aid cancer cells in evading immunosurveillance and inflammatory cells by inhibiting the apoptosis process. This report reviewed four apoptosis-regulating ISG proteins: interferon-stimulated gene 15 (ISG15), interferon alpha-inducible protein 27 (IFI27), interferon alpha-inducible protein 6 (IFI6), and radical S-adenosyl methionine domain containing 2 (RSAD2), demonstrating anti-apoptosis function, and considered them protumorigenic.

Functional Nucleic Acid-Based Immunomodulation for T Cell-Mediated Cancer Therapy

T cell-mediated immunity plays a pivotal role in cancer immunotherapy. The anticancer actions of T cells are coordinated by a sequence of biological processes, including the capture and presentation of antigens by antigen-presenting cells (APCs), the activation of T cells by APCs, and the subsequent killing of cancer cells by activated T cells. However, cancer cells have various means to evade immune responses. Meanwhile, these vulnerabilities provide potential targets for cancer treatments. Functional nucleic acids (FNAs) make up a class of synthetic nucleic acids with specific biological functions. With their diverse functionality, good biocompatibility, and high programmability, FNAs have attracted widespread interest in cancer immunotherapy. This Review focuses on recent research progress in employing FNAs as molecular tools for T cell-mediated cancer immunotherapy, including corresponding challenges and prospects.

Chimeric Antigen Receptor T Cell Therapy in Acute Myeloid Leukemia: Trials and Tribulations

Acute myeloid leukemia (AML) is a heterogeneous hematological malignancy that is often associated with relapse and drug resistance after standard chemotherapy or targeted therapy, particularly in older patients. Hematopoietic stem cell transplants are looked upon as the ultimate salvage option with curative intent. Adoptive cell therapy using chimeric antigen receptors (CAR) has shown promise in B cell malignancies and is now being investigated in AML. Initial clinical trials have been disappointing in AML, and we review current strategies to improve efficacy for CAR approaches. The extensive number of clinical trials targeting different antigens likely reflects the genetic heterogeneity of AML. The limited number of patients reported in multiple early clinical studies makes it difficult to draw conclusions about CAR safety, but it does suggest that the efficacy of this approach in AML lags behind the success observed in B cell malignancies. There is a clear need not only to improve CAR design but also to identify targets in AML that show limited expression in normal myeloid lineage cells.

DASES: a database of alternative splicing for esophageal squamous cell carcinoma

Esophageal carcinoma ranks as the sixth leading cause of cancer-related mortality globally, with esophageal squamous cell carcinoma (ESCC) being particularly prevalent among Asian populations. Alternative splicing (AS) plays a pivotal role in ESCC development and progression by generating diverse transcript isoforms. However, the current landscape lacks a specialized database focusing on alternative splicing events (ASEs) derived from a large number of ESCC cases. Additionally, most existing AS databases overlook the contribution of long non-coding RNAs (lncRNAs) in ESCC molecular mechanisms, predominantly focusing on mRNA-based ASE identification. To address these limitations, we deployed DASES (http://www.hxdsjzx.cn/DASES). Employing a combination of publicly available and in-house ESCC RNA-seq datasets, our extensive analysis of 346 samples, with 93% being paired tumor and adjacent non-tumor tissues, led to the identification of 257 novel lncRNAs in esophageal squamous cell carcinoma. Leveraging a paired comparison of tumor and adjacent normal tissues, DASES identified 59,094 ASEs that may be associated with ESCC. DASES fills a critical gap by providing comprehensive insights into ASEs in ESCC, encompassing lncRNAs and mRNA, thus facilitating a deeper understanding of ESCC molecular mechanisms and serving as a valuable resource for ESCC research communities.

Immune evasion by cancer stem cells ensures tumor initiation and failure of immunotherapy

Cancer stem cells (CSCs) are a small subpopulation of cells that drive the formation and progression of tumors. However, during tumor initiation, how CSCs communicate with neighbouring immune cells to overcome the powerful immune surveillance barrier in order to form, spread, and maintain the tumor, remains poorly understood. It is, therefore, absolutely necessary to understand how a small number of tumor-initiating cells (TICs) survive immune attack during (a) the “elimination phase” of “tumor immune-editing”, (b) the establishment of regional or distant tumor after metastasis, and (c) recurrence after therapy. Mounting evidence suggests that CSCs suppress the immune system through a variety of distinct mechanisms that ensure the survival of not only CSCs but also non-stem cancer cells (NSCCs), which eventually form the tumor mass. In this review article, the mechanisms via which CSCs change the immune landscape of the tissue of origin, which contains macrophages, dendritic cells (DCs), myeloid-derived suppressor cells (MDSCs), natural killer (NK) cells, and tumor-infiltrating lymphocytes, in favour of tumorigenesis were discussed. The failure of cancer immunotherapy might also be explained by such interaction between CSCs and immune cells. This review will shed light on the critical role of CSCs in tumor immune evasion and emphasize the importance of CSC-targeted immunotherapy as a cutting-edge technique for battling cancer by restricting communication between immune cells and CSCs.

TERC haploid cell reprogramming: a novel therapeutic strategy for aplastic anemia

The telomerase RNA component (TERC) gene plays an important role in telomerase-dependent extension and maintenance of the telomeres. In the event of TERC haploinsufficiency, telomere length is often affected; this, in turn, can result in the development of progeria-related diseases such as aplastic anemia (AA) and congenital keratosis. Cell reprogramming can reverse the differentiation process and can, therefore, transform cells into pluripotent stem cells with stronger differentiation and self-renewal abilities; further, cell reprograming can also extend the telomere length of these cells, which may be crucial in the diagnosis and treatment of telomere depletion diseases such as AA. In this study, we summarized the effects of TERC haploid cell reprogramming on telomere length and the correlation between this alteration and the pathogenesis of AA; by investigating the role of cell reprogramming in AA, we aimed to identify novel diagnostic indicators and therapeutic strategies for patients with AA.

Tumor heterogeneity: preclinical models, emerging technologies, and future applications

Heterogeneity describes the differences among cancer cells within and between tumors. It refers to cancer cells describing variations in morphology, transcriptional profiles, metabolism, and metastatic potential. More recently, the field has included the characterization of the tumor immune microenvironment and the depiction of the dynamics underlying the cellular interactions promoting the tumor ecosystem evolution. Heterogeneity has been found in most tumors representing one of the most challenging behaviors in cancer ecosystems. As one of the critical factors impairing the long-term efficacy of solid tumor therapy, heterogeneity leads to tumor resistance, more aggressive metastasizing, and recurrence. We review the role of the main models and the emerging single-cell and spatial genomic technologies in our understanding of tumor heterogeneity, its contribution to lethal cancer outcomes, and the physiological challenges to consider in designing cancer therapies. We highlight how tumor cells dynamically evolve because of the interactions within the tumor immune microenvironment and how to leverage this to unleash immune recognition through immunotherapy. A multidisciplinary approach grounded in novel bioinformatic and computational tools will allow reaching the integrated, multilayered knowledge of tumor heterogeneity required to implement personalized, more efficient therapies urgently required for cancer patients.

Active ingredients of traditional Chinese medicine for enhancing the effect of tumor immunotherapy

Immunotherapy is a type of treatment that uses our own immune system to fight cancer. Studies have shown that traditional Chinese medicine (TCM) has antitumor activity and can enhance host immunity. This article briefly describes the immunomodulatory and escape mechanisms in tumors, as well as highlights and summarizes the antitumor immunomodulatory activities of some representative active ingredients of TCM. Finally, this article puts forward some opinions on the future research and clinical application of TCM, aiming to promote the clinical applications of TCM in tumor immunotherapy and to provide new ideas for the research of tumor immunotherapy using TCM.

Machine learning methods revealed the roles of immune-metabolism related genes in immune infiltration, stemness, and prognosis of neuroblastoma

BACKGROUND

Immunometabolism plays an important role in neuroblastoma (NB). However, the mechanism of immune-metabolism related genes (IMRGs) in NB remains unclear. This study aimed to explore the effects of IMRGs on the prognosis, immune infiltration and stemness of patients with NB using machine learning methods.

METHODS

R software (v4.2.1) was used to identify the differentially expressed IMRGs, and machine learning algorithm was used to screen the prognostic genes from IMRGs. Then we constructed a prognostic model and calculated the risk scores. The NB patients were grouped according to the prognosis scores. In addition, the genes most associated with the immune infiltration and stemness of NB were analyzed by weighted gene co-expression network analysis (WGCNA).

RESULTS

There were 89 differentially expressed IMRGs between the MYCN amplification and the MYCN non-amplification group, among which CNR1, GNAI1, GLDC and ABCC4 were selected by machine learning algorithm to construct the prognosis model due to their better prediction effect. Both the K-M survival curve and the 5-year Receiver operating characteristic (ROC) curve indicated that the prognosis model could predict the prognosis of NB patients, and there was significant difference in immune infiltration between the two groups according to the median of risk score.

CONCLUSIONS

We verified the effects of IMRGs on the prognosis, immune infiltration and stemness of NB. These findings could provide help for predicting prognosis and developing immunotherapy in NB.