Targeting immunosenescence for improved tumor immunotherapy.

Tumor immunotherapy has significantly transformed the field of oncology over the past decade. An optimal tumor immunotherapy would ideally elicit robust innate and adaptive immune responses within tumor immune microenvironment (TIME). Unfortunately, immune system experiences functional decline with chronological age, a process termed "immunosenescence," which contributes to impaired immune responses against pathogens, suboptimal vaccination outcomes, and heightened vulnerability to various diseases, including cancer. In this context, we will elucidate hallmarks and molecular mechanisms underlying immunosenescence, detailing alterations in immunosenescence at molecular, cellular, organ, and disease levels. The role of immunosenescence in tumorigenesis and senescence-related extracellular matrix (ECM) has also been addressed. Recognizing that immunosenescence is a dynamic process influenced by various factors, we will evaluate treatment strategies targeting hallmarks and molecular mechanisms, as well as methods for immune cell, organ restoration, and present emerging approaches in immunosenescence for tumor immunotherapy. The overarching goal of immunosenescence research is to prevent tumor development, recurrence, and metastasis, ultimately improving patient prognosis. Our review aims to reveal latest advancements and prospective directions in the field of immunosenescence research, offering a theoretical basis for development of practical anti-immunosenescence and anti-tumor strategies.

Multi-stage mechanisms of tumor metastasis and therapeutic strategies.

The cascade of metastasis in tumor cells, exhibiting organ-specific tendencies, may occur at numerous phases of the disease and progress under intense evolutionary pressures. Organ-specific metastasis relies on the formation of pre-metastatic niche (PMN), with diverse cell types and complex cell interactions contributing to this concept, adding a new dimension to the traditional metastasis cascade. Prior to metastatic dissemination, as orchestrators of PMN formation, primary tumor-derived extracellular vesicles prepare a fertile microenvironment for the settlement and colonization of circulating tumor cells at distant secondary sites, significantly impacting cancer progression and outcomes. Obviously, solely intervening in cancer metastatic sites passively after macrometastasis is often insufficient. Early prediction of metastasis and holistic, macro-level control represent the future directions in cancer therapy. This review emphasizes the dynamic and intricate systematic alterations that occur as cancer progresses, illustrates the immunological landscape of organ-specific PMN creation, and deepens understanding of treatment modalities pertinent to metastasis, thereby identifying some prognostic and predictive biomarkers favorable to early predict the occurrence of metastasis and design appropriate treatment combinations.

Circadian disruption in cancer hallmarks: Novel insight into the molecular mechanisms of tumorigenesis and cancer treatment.

Circadian rhythms are 24-h rhythms governing temporal organization of behavior and physiology generated by molecular clocks composed of autoregulatory transcription-translation feedback loops (TTFLs). Disruption of circadian rhythms leads to a spectrum of pathologies, including cancer by triggering or being involved in different hallmarks. Clock control of phenotypic plasticity involved in tumorigenesis operates in aberrant dedifferentiating to progenitor-like cell states, generation of cancer stem cells (CSCs) and epithelial-to-mesenchymal transition (EMT) events. Circadian rhythms might act as candidates for regulatory mechanisms of cellular senescent and functional determinants of senescence-associated secretory phenotype (SASP). Reciprocal control between clock and epigenetics sheds light on post-transcriptional regulation of circadian rhythms and opens avenues for novel anti-cancer strategies. Additionally, disrupting circadian rhythms influences microbiota communities that could be associated with altered homeostasis contributing to cancer development. Herein, we summarize recent advances in support of the nexus between disruptions of circadian rhythms and cancer hallmarks of new dimensions, thus providing novel perspectives on potentially effective treatment approaches for cancer management.

Proteogenomics offers a novel avenue in neoantigen identification for cancer immunotherapy.

Cancer neoantigens are tumor-specific non-synonymous mutant peptides that activate the immune system to produce an anti-tumor response. Personalized cancer vaccines based on neoantigens are currently one of the most promising therapeutic approaches for cancer treatment. By utilizing the unique mutations within each patient's tumor, these vaccines aim to elicit a strong and specific immune response against cancer cells. However, the identification of neoantigens remains challenging due to the low accuracy of current prediction tools and the high false-positive rate of candidate neoantigens. Since the concept of "proteogenomics" emerged in 2004, it has evolved rapidly with the increased sequencing depth of next-generation sequencing technologies and the maturation of mass spectrometry-based proteomics technologies to become a more comprehensive approach to neoantigen identification, allowing the discovery of high-confidence candidate neoantigens. In this review, we summarize the reason why cancer neoantigens have become attractive targets for immunotherapy, the mechanism of cancer vaccines and the advances in cancer immunotherapy. Considerations relevant to the application emerging of proteogenomics technologies for neoantigen identification and challenges in this field are described.

Exploring the effect of part differences on metabolite molecule changes in refrigerated pork: Identifying key metabolite compounds and their conversion pathways.

Effect of part differences on metabolite molecule alterations in refrigerated pork was investigated. A metabolomics methodology combined with chemometric analysis was successfully established to identify key compounds and their conversion pathways, including precursors and volatile metabolites, in the Longissimus lumborum as well as the breast and flank stored for 11 days. In total, 12 discriminative precursors were identified using the Short Time-series Expression Miner. In tandem with Random Forest and ANOVA analyses, nine volatile metabolites were identified as key compounds that could be attributed to differences in pork sections. Bidirectional orthogonal partial least squares analysis revealed a potential correlation between these key metabolites and discriminative precursors. Metabolic pathway enrichment analysis demonstrated that the primary metabolic process affected by variations in pork sections is linoleic acid metabolism, which participates in the metabolism of cysteine and glutamic acid to produce methoxy-phenyl-oxime. This study provides valuable insights into the identification of differential metabolites.

Development of a rhodamine-based fluorescent probe for ATP detection for potential applications in meat freshness assessment.

Adenosine triphosphate (ATP) plays a vital role in physiological processes and is an essential indicator of microbial content in food. Herein, a new sensitive, rapid and water-soluble probe for ATP detection was developed. Rhodamine B and pentaethylenehexamine were employed to design and synthesise the probe rhodamine-pentaethylenehexamine (RP) for selective ATP detection. The synthesised probe RP was characterized using Fourier transform infrared, NMR and dynamic light scattering size distributions. Upon the addition of ATP, the probe exhibited a distinct change in fluorescence intensity, with fluorescence emission at 580 nm. A linear relationship was observed between fluorescence intensity and ATP concentrations at 0-50 µmol/L, with a limit of detection of 10.97 × 10-9 mol/L. The results of the zeta potential and molecular dynamics simulation demonstrated that the detection mechanism of the probe RP is associated with the electrostatic adsorption interaction between the multi-positively charged sites of RP and the negatively charged triphosphate structure of ATP. Our study provides new insights into improving charge site identification in small molecule detection. Furthermore, the successful detection of ATP on meat surfaces indicates that RP has the potential to assess meat freshness.

Tertiary lymphoid structural heterogeneity determines tumour immunity and prospects for clinical application.

Tertiary lymphoid structures (TLS) are clusters of immune cells that resemble and function similarly to secondary lymphoid organs (SLOs). While TLS is generally associated with an anti-tumour immune response in most cancer types, it has also been observed to act as a pro-tumour immune response. The heterogeneity of TLS function is largely determined by the composition of tumour-infiltrating lymphocytes (TILs) and the balance of cell subsets within the tumour-associated TLS (TA-TLS). TA-TLS of varying maturity, density, and location may have opposing effects on tumour immunity. Higher maturity and/or higher density TLS are often associated with favorable clinical outcomes and immunotherapeutic response, mainly due to crosstalk between different proportions of immune cell subpopulations in TA-TLS. Therefore, TLS can be used as a marker to predict the efficacy of immunotherapy in immune checkpoint blockade (ICB). Developing efficient imaging and induction methods to study TA-TLS is crucial for enhancing anti-tumour immunity. The integration of imaging techniques with biological materials, including nanoprobes and hydrogels, alongside artificial intelligence (AI), enables non-invasive in vivo visualization of TLS. In this review, we explore the dynamic interactions among T and B cell subpopulations of varying phenotypes that contribute to the structural and functional diversity of TLS, examining both existing and emerging techniques for TLS imaging and induction, focusing on cancer immunotherapies and biomaterials. We also highlight novel therapeutic approaches of TLS that are being explored with the aim of increasing ICB treatment efficacy and predicting prognosis.

Pyroptosis-Derived Long Noncoding RNA Profiles Reveal a Novel Signature for Evaluating the Prognosis of Patients With Lung Adenocarcinoma.

PURPOSE: Long noncoding RNAs (lncRNAs) were recently implicated in modifying pyroptosis. Nonetheless, pyroptosis-related lncRNAs and their possible clinical relevance persist largely uninvestigated in lung adenocarcinoma (LUAD). MATERIALS AND METHODS: A sum of 921 samples were collected from three independent data sets. We obtained pyroptosis-related genes from both the Molecular Signatures Database and relevant literature sources and used four machine learning techniques, comprising stepwise Cox, ridge regression, least absolute shrinkage and selection operator, and random forest. Multiple bioinformatics approaches were used to further investigate the underlying mechanisms. RESULTS: In total, 39 differentially expressed pyroptosis genes were identified by comparing normal and tumor samples. Correlation analysis revealed 933 pyroptosis-related lncRNAs. Furthermore, univariate Cox regression determined 11 lncRNAs that exhibited stable associations with prognosis in the three cohorts, which were used to construct the pyroptosis-derived lncRNA signature. After analyzing the optimal results from four machine learning algorithms, we ultimately selected random forest to develop the pyroptosis-derived lncRNA signature. This signature was proven to be an independent prognostic factor and exhibited robust performance in three cohorts. CONCLUSION: We provided novel insight and established a pyroptosis-derived lncRNA signature for patients with LUAD, exhibiting strong predictive capabilities in both the training and validation sets.

Single-cell RNA sequencing integrated with bulk RNA sequencing analysis identifies a tumor immune microenvironment-related lncRNA signature in lung adenocarcinoma.

BACKGROUND: Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD). METHODS: Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs. A total of 1368 LUAD patients are enrolled from 6 independent datasets. An integrative machine learning framework is introduced to develop a TIME-related lncRNA signature (TRLS). RESULTS: This study identified TIME-related lncRNAs from integrated analysis of single­cell and bulk RNA sequencing data. According to these lncRNAs, a TIME-related lncRNA signature was developed and validated from an integrative procedure in six independent cohorts. TRLS exhibited a robust and reliable performance in predicting overall survival. Superior prediction performance barged TRLS to the forefront from comparison with general clinical features, molecular characters, and published signatures. Moreover, patients with low TRLS displayed abundant immune cell infiltration and active lipid metabolism, while patients with high TRLS harbored significant genomic alterations, high PD-L1 expression, and elevated DNA damage repair (DDR) relevance. Notably, subclass mapping analysis of nine immunotherapeutic cohorts demonstrated that patients with high TRLS were more sensitive to immunotherapy. CONCLUSIONS: This study developed a promising tool based on TIME-related lncRNAs, which might contribute to tailored treatment and prognosis management of LUAD patients.

Cellular Ligand-Receptor Perturbations Unravel MEIS2 as a Key Factor for the Aggressive Progression and Prognosis in Stage II/III Colorectal Cancer.

Approximately 10-15% of stage II and 25-30% of stage III colorectal cancer (CRC) patients experience recurrence within 5 years after surgery, and existing taxonomies are insufficient to meet the needs of clinical precision treatment. Thus, robust biomarkers and precise management were urgently required to stratify stage II and III CRC and identify potential patients who will benefit from postoperative adjuvant therapy. Alongside, interactions of ligand-receptor pairs point to an emerging direction in tumor signaling with far-reaching implications for CRC, while their impact on tumor subtyping has not been elucidated. Herein, based on multiple large-sample multicenter cohorts and perturbations of the ligand-receptor interaction network, four well-characterized ligand-receptor-driven subtypes (LRDS) were established and further validated. These molecular taxonomies perform with unique heterogeneity in terms of molecular characteristics, immune and mutational landscapes, and clinical features. Specifically, MEIS2, a key LRDS4 factor, performs significant associations with proliferation, invasion, migration, and dismal prognosis of stage II/III CRC, revealing promising directions for prognostic assessment and individualized treatment of CRC patients. Overall, our study sheds novel insights into the implications of intercellular communication on stage II/III CRC from a ligand-receptor interactome perspective and revealed MEIS2 as a key factor in the aggressive progression and prognosis for stage II/III CRC.

Three-Dimensional Printed Poly (Lactic-co-Glycolic Acid)-Magnesium Composite Scaffolds for the Promotion of Osteogenesis Through Immunoregulation.

Scaffolds play an important role in bone tissue engineering. The ideal engineered scaffold needs to be biocompatible, bioactive, and able to regulate immune cells to enhance bone regeneration. In this study, magnesium (Mg)-contained poly(lactic-co-glycolic acid) (PLGA) scaffolds (hereinafter, referred to as PLGA-2Mg) were fabricated by 3-dimensional printing using a mixture of PLGA and MgSO 4 powder. Poly(lactic-co-glycolic acid) scaffolds (hereinafter, referred to as PLGA) were also fabricated by 3-dimensional printing and were used as control. The biocompatibility, immunoregulatory ability, and osteogenic properties of PLGA-2Mg were analyzed and compared with those of PLGA. The results indicate that the incorporation of Mg increased the Young modulus and surface roughness of the scaffold, but did not affect its degradation. The PLGA-2Mg further promoted the adhesion and proliferation of MC3T3-E1 cells compared with PLGA, which indicates its improved biocompatibility and bioactivity. In addition, PLGA-2Mg inhibited the polarization of RAW 264.7 cells toward the M1 phenotype by down-regulating the IL-1ß , IL-6 , and iNOs gene expression when challenged with lipopolysaccharide stimulation. In contrast, it promoted the polarization of RAW 264.7 cells toward the M2 phenotype by up-regulating the TGF-ß , IL-10 , and Arg-1 gene expression without lipopolysaccharide stimulation. Finally, MC3T3-E1 cells were cocultured with RAW 264.7 cells and scaffolds using a transwell system. It was found that the expression level of osteogenic-related genes ( ALP , COL-1 , BMP2 , and BSP ) was significantly upregulated in the PLGA-2Mg group compared with that in the PLGA group. Consequently, PLGA-2Mg with increased biocompatibility and bioactivity can promote osteogenesis through immunoregulation and has the potential to be used as a novel scaffold in bone tissue engineering.

FeNC nanozyme-based electrochemical immunoassay for sensitive detection of human epidermal growth factor receptor 2.

The proof-of-concept of sensitive electrochemical immunoassay for the quantitative monitoring of human epidermal growth factor receptor 2 (HER2) is reported. The assay is carried out on iron nitrogen-doped carbon (FeNC) nanozyme-modified screen-printed carbon electrode using chronoamperometry. Introduction of target HER2 can induce the sandwiched immunoreaction between anti-HER2 monoclonal antibody-coated microplate and biotinylated anti-HER2 polyclonal antibody. Thereafter, streptavidin-glucose oxidase (GOx) conjugate is bonded to the detection antibody. Upon addition of glucose, 3,3',5,5'-tetramethylbenzidine (TMB) is oxidized through the produced H2O2 with the assistance of GOx and FeNC nanozyme. The oxidized TMB is determined via chronoamperometry. Experimental results revealed that electrochemical immunosensing system exhibited good amperometric response, and allowed the detection of target HER2 as low as 4.5 pg/mL. High specificity and long-term stability are acquired with FeNC nanozyme-based sensing strategy. Importantly, our system provides a new opportunity for protein diagnostics.

A tumor-infiltrating immune cells-related pseudogenes signature based on machine-learning predicts outcomes and immunotherapy responses in ovarian cancer.

Previous researches have provided evidence for the significant involvement of pseudogenes in immune-related functions across different types of cancer. However, the mechanisms by which pseudogenes regulate immunity in ovarian cancer (OV) and their potential impact on clinical outcomes remain unclear. To address this gap in knowledge, our study utilized a novel computational framework to analyze a total of 491 samples from three public datasets. We employed a combination of 10 machine-learning algorithms to construct a signature known as the tumor-infiltrating immune cells-related pseudogenes signature (TIICPS). The TIICPS, consisting of 12 pseudogenes, demonstrated independent prognostic value for overall survival, surpassing conventional clinical traits, 62 published signatures, and TP53 and BRCA mutation status in three cohorts. Patients with low TIICPS exhibited heightened immune-related pathways, intricate genomic alterations, substantial immune infiltration, and greater potential for immunotherapy efficacy. Consequently, TIICPS holds promise as a predictive tool for prognosis and immunotherapy response in ovarian cancer.

Ferroptosis and EMT: key targets for combating cancer progression and therapy resistance.

Iron-dependent lipid peroxidation causes ferroptosis, a form of regulated cell death. Crucial steps in the formation of ferroptosis include the accumulation of ferrous ions (Fe2+) and lipid peroxidation, of which are controlled by glutathione peroxidase 4 (GPX4). Its crucial role in stopping the spread of cancer has been shown by numerous studies undertaken in the last ten years. Epithelial-mesenchymal transition (EMT) is the process by which epithelial cells acquire mesenchymal characteristics. EMT is connected to carcinogenesis, invasiveness, metastasis, and therapeutic resistance in cancer. It is controlled by a range of internal and external signals and changes the phenotype from epithelial to mesenchymal like. Studies have shown that mesenchymal cancer cells tend to be more ferroptotic than their epithelial counterparts. Drug-resistant cancer cells are more easily killed by inducers of ferroptosis when they undergo EMT. Therefore, understanding the interaction between ferroptosis and EMT will help identify novel cancer treatment targets. In-depth discussion is given to the regulation of ferroptosis, the potential application of EMT in the treatment of cancer, and the relationships between ferroptosis, EMT, and signaling pathways associated with tumors. Invasion, metastasis, and inflammation in cancer all include ferroptosis and EMT. The goal of this review is to provide suggestions for future research and practical guidance for applying ferroptosis and EMT in clinical practice.

Multifaceted role of redox pattern in the tumor immune microenvironment regarding autophagy and apoptosis.

The reversible oxidation-reduction homeostasis mechanism functions as a specific signal transduction system, eliciting related physiological responses. Disruptions to redox homeostasis can have negative consequences, including the potential for cancer development and progression, which are closely linked to a series of redox processes, such as adjustment of reactive oxygen species (ROS) levels and species, changes in antioxidant capacity, and differential effects of ROS on downstream cell fate and immune capacity. The tumor microenvironment (TME) exhibits a complex interplay between immunity and regulatory cell death, especially autophagy and apoptosis, which is crucially regulated by ROS. The present study aims to investigate the mechanism by which multi-source ROS affects apoptosis, autophagy, and the anti-tumor immune response in the TME and the mutual crosstalk between these three processes. Given the intricate role of ROS in controlling cell fate and immunity, we will further examine the relationship between traditional cancer therapy and ROS. It is worth noting that we will discuss some potential ROS-related treatment options for further future studies.

Radiogenomics: a key component of precision cancer medicine.

Radiogenomics, focusing on the relationship between genomics and imaging phenotypes, has been widely applied to address tumour heterogeneity and predict immune responsiveness and progression. It is an inevitable consequence of current trends in precision medicine, as radiogenomics costs less than traditional genetic sequencing and provides access to whole-tumour information rather than limited biopsy specimens. By providing voxel-by-voxel genetic information, radiogenomics can allow tailored therapy targeting a complete, heterogeneous tumour or set of tumours. In addition to quantifying lesion characteristics, radiogenomics can also be used to distinguish benign from malignant entities, as well as patient characteristics, to better stratify patients according to disease risk, thereby enabling more precise imaging and screening. Here, we have characterised the radiogenomic application in precision medicine using a multi-omic approach. we outline the main applications of radiogenomics in diagnosis, treatment planning and evaluations in the field of oncology with the aim of developing quantitative and personalised medicine. Finally, we discuss the challenges in the field of radiogenomics and the scope and clinical applicability of these methods.

Genome-scale CRISPR-Cas9 screening stratifies pancreatic cancer with distinct outcomes and immunotherapeutic efficacy.

Pancreatic cancer (PC) was featured by dramatic heterogeneity and dismal outcomes. An ideal classification strategy capable of achieving risk stratification and individualized treatment is urgently needed to significantly improve prognosis. In this study, using the 105 prognostic cancer essential genes identified by genome-scale CRISPR-Cas9 screening and univariate Cox analysis, we established and verified three heterogeneous subtypes via non-negative matrix factorization (NMF) and nearest template prediction (NTP) algorithms in the TCGA-PAAD cohort (176 samples) and four multi-center cohorts (233 samples), respectively. Among them, C1 with the worst prognosis was enriched in immune-related pathways, possessed superior infiltration abundance of immune cells and immune checkpoint molecules expression, and might be most sensitive to immunotherapy. C3, owing a moderate prognosis, might be featured by proliferative biological function, and despite its highest immunogenicity, the defects in antigen processing and presentation ability coupled with barren immune environment render it ineffective for immunotherapy, while it had potential sensitivity to paclitaxel and methotrexate. Besides, C2 harbored the best prognosis and was characterized by metabolism-related functions. These results could deepen our understanding of PC molecular heterogeneity and provide a trustworthy reference for prognostic stratification management and precision medicine in clinical practice.