Tumor Microenvironment, Metabolism, and Immunotherapy

Immunogenomic profiles and therapeutic options of the pan-programmed cell death-related lncRNA signature for patients with bladder cancer

Programmed cell death (PCD) is a process that eliminates infected, damaged, or possibly neoplastic cells to sustain homeostatic multicellular organisms. Although long noncoding RNAs (lncRNAs) are involved in various types of PCD and regulate tumor growth, invasion, and migration, the role of PCD-related lncRNAs in bladder cancer still lacks systematic exploration. In this research, we integrated multiple types of PCD as pan-PCD and identified eight pan-PCD-related lncRNAs (LINC00174, HCP5, HCG27, UCA1, SNHG15, GHRLOS, CYB561D2, and AGAP11). Then, we generated a pan-PCD-related lncRNA prognostic signature (PPlncPS) with excellent predictive power and reliability, which performed equally well in the E-MTAB-4321 cohort. In comparison with the low-PPlncPS score group, the high-PPlncPS score group had remarkably higher levels of angiogenesis, matrix, cancer-associated fibroblasts, myeloid cell traffic, and protumor cytokine signatures. In addition, the low-PPlncPS score group was positively correlated with relatively abundant immune cell infiltration, upregulated expression levels of immune checkpoints, and high tumor mutation burden (TMB). Immunogenomic profiles revealed that patients with both low PPlncPS scores and high TMB had the best prognosis and may benefit from immune checkpoint inhibitors. Furthermore, for patients with high PPlncPS scores, docetaxel, staurosporine, and luminespib were screened as potential therapeutic candidates. In conclusion, we generated a pan-PCD-related lncRNA signature, providing precise and individualized prediction for clinical prognosis and some new insights into chemotherapy and immune checkpoint inhibitor therapy for bladder cancer.

Antitumor activity of dictamnine against colorectal cancer through induction of ferroptosis and inhibition of M2 macrophage polarization via the MAPK signaling

Colorectal cancer (CRC) is an aggressive cancer type globally. Surgery and chemotherapy are often ineffective at curing CRC. Dictamnine is a natural product derived from Dictamnus dasycarpus Turcz. root bark and possesses multi-pharmacological properties, including anticancer effects. Nevertheless, the biological roles and the possible mechanism of dictamnine in CRC are still unclear. Here, we demonstrated that dictamnine blocked cell viability and proliferation in DLD-1 human colorectal adenocarcinoma cells and LoVo human colon cancer cells. Dictamnine triggered CRC cell ferroptosis, as evidenced by enhanced levels of reactive oxygen species, malondialdehyde, and Fe2+ levels, alongside downregulation of glutathione peroxidase 4 protein expression. In addition, CD163 (HPA ID: HPA046404) was highly expressed and CD68 (HPA ID: CAB000051) was lowly expressed in CRC tissues and CRC cell culture medium-cultured THP-1 monocytes-derived macrophages. The patients with CD163 low-expression lived much longer than those with CD163 high-expression, indicating that M2 polarization of macrophages was related to poor prognosis of CRC. Dictamnine markedly inhibited CD163 protein expression, transforming growth factor-β and arginase 1 mRNA expressions and IL-10 production in macrophages with CRC cell co-culture, suggesting that dictamnine impeded M2 polarization of macrophages. Mechanistically, dictamnine repressed ERK phosphorylation in CRC cells. The treatment with the ERK activator tBHQ counteracted the effects of dictamnine on CRC cell proliferation and ferroptosis, as well as its inhibitory effect on M2 polarization of macrophages. Results of a xenograft model showed that dictamnine effectively hindered CRC tumor growth in vivo. Collectively, these data provide evidence for the clinical trials of dictamnine as a novel drug for CRC therapy.

Stimulus-Responsive Nanodelivery and Release Systems for Cancer Gene Therapy: Efficacy Improvement Strategies

Introduction of exogenous genes into target cells to overcome various tumor diseases caused by genetic defects or abnormalities and gene therapy, a new treatment method, provides a promising strategy for tumor treatment. Over the past decade, gene therapy has made exciting progress; however, it still faces the challenge of low nucleic acid delivery and release efficiencies. The emergence of nonviral vectors, primarily nanodelivery and release systems (NDRS), has resulted in a historic breakthrough in the application of gene therapy. NDRS, especially stimulus-responsive NDRS that can respond in a timely manner to changes in the internal and external microenvironment (eg, low pH, high concentration of glutathione/reactive oxygen species, overexpressed enzymes, temperature, light, ultrasound, and magnetic field), has shown excellent loading and release advantages in the precision and efficiency of tumor gene therapy and has been widely applied. The only disadvantage is that poor transfection efficiency limits the in-depth application of gene therapy in clinical practice, owing to the presence of biological barriers in the body. Therefore, this review first introduces the development history of gene therapy, the current obstacles faced by gene delivery, strategies to overcome these obstacles, and conventional vectors, and then focuses on the latest research progress in various stimulus-responsive NDRS for improving gene delivery efficiency. Finally, the future challenges and prospects that stimulus-responsive NDRS may face in clinical application and transformation are discussed to provide references for enhancing in-depth research on tumor gene therapy.

The potential therapeutic targets of glutamine metabolism in head and neck squamous cell carcinoma

Targeting metabolic reprogramming may be an effective strategy to enhance cancer treatment efficacy. Glutamine serves as a vital nutrient for cancer cells. Inhibiting glutamine metabolism has shown promise in preventing tumor growth both in vivo and in vitro through various mechanisms. Therefore, this review collates recent scientific literature concerning the correlation between glutamine metabolism and cancer treatment. Novel treatment modalities based on amino acid transporters, metabolites, and glutaminase are discussed. Moreover, we demonstrate the relationship between glutamine metabolism and tumor proliferation, drug resistance, and the tumor immune microenvironment, offering new perspectives for the clinical treatment of head and neck squamous cell carcinoma, particularly for combined therapies. Identifying innovative approaches for enhancing the efficacy of glutamine-based metabolic therapy is crucial to improving HNSCC treatment.

Impact and potential value of immunosenescence on solid gastrointestinal tumors

Solid gastrointestinal tumors often respond poorly to immunotherapy for the complex tumor microenvironment (TME), which is exacerbated by immune system alterations. Immunosenescence is the process of increased diversification of immune genes due to aging and other factors, leading to a decrease in the recognition function of the immune system. This process involves immune organs, immune cells, and the senescence-associated secretory phenotype (SASP). The most fundamental change is DNA damage, resulting in TME remodeling. The main manifestations are worsening inflammation, increased immunosuppressive SASP production, decreased immune cell antitumor activity, and the accumulation of tumor-associated fibroblasts and myeloid-derived suppressor cells, making antitumor therapy less effective. Senotherapy strategies to remove senescent cells and block key senescence processes can have synergistic effects with other treatments. This review focuses on immunoenescence and its impact on the solid TME. We characterize the immunosenescent TME and discuss future directions for antitumor therapies targeting senescence.

The role of RNA methylation in tumor immunity and its potential in immunotherapy

RNA methylation, a prevalent post-transcriptional modification, has garnered considerable attention in research circles. It exerts regulatory control over diverse biological functions by modulating RNA splicing, translation, transport, and stability. Notably, studies have illuminated the substantial impact of RNA methylation on tumor immunity. The primary types of RNA methylation encompass N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1-methyladenosine (m1A), and N7-methylguanosine (m7G), and 3-methylcytidine (m3C). Compelling evidence underscores the involvement of RNA methylation in regulating the tumor microenvironment (TME). By affecting RNA translation and stability through the "writers", "erasers" and "readers", RNA methylation exerts influence over the dysregulation of immune cells and immune factors. Consequently, RNA methylation plays a pivotal role in modulating tumor immunity and mediating various biological behaviors, encompassing proliferation, invasion, metastasis, etc. In this review, we discussed the mechanisms and functions of several RNA methylations, providing a comprehensive overview of their biological roles and underlying mechanisms within the tumor microenvironment and among immunocytes. By exploring how these RNA modifications mediate tumor immune evasion, we also examine their potential applications in immunotherapy. This review aims to provide novel insights and strategies for identifying novel targets in RNA methylation and advancing cancer immunotherapy efficacy.

The Macrophage migration inhibitory factor is a vital player in Pan-Cancer by functioning as a M0 Macrophage biomarker

BACKGROUND

The role of the macrophage migration inhibitory factor (MIF) has recently attracted considerable attention in cancer research; nonetheless, the insights provided by current investigations remain constrained. Our main objective was to investigate its role and the latent mechanisms within the pan-cancer realm.

METHODS

We used comprehensive pan-cancer bulk sequencing data and online network tools to investigate the association between MIF expression and patient prognosis, genomic instability, cancer cell stemness, DNA damage repair, and immune infiltration. Furthermore, we validated the relationship between MIF expression and M0 macrophages using single-cell datasets, the SpatialDB database, and fluorescence staining. Additionally, we assessed the therapeutic response using the ROC plotter tool.

RESULTS

We observed the upregulation of MIF expression across numerous cancer types. Notably, elevated MIF levels were associated with a decline in genomic stability. We found a significant correlation between increased MIF expression and increased expression of mismatch repair genes, stemness features, and homologous recombination genes across diverse malignancies. Subsequently, through an analysis using ESTIMATE and cytokine results, we revealed the involvement of MIF in immune suppression. Then, we validated MIF as a hallmark of the M0 macrophages involved in tumor immunity. Our study suggests an association with other immune-inhibitory cellular populations and restraint of CD8 + T cells. In addition, we conducted a comparative analysis of MIF expression before and after treatment in three distinct sets of therapy responders and non-responders. Intriguingly, we identified notable disparities in MIF expression patterns in bladder urothelial carcinoma and ovarian cancer following particular therapeutic interventions.

CONCLUSION

Comprehensive pan-cancer analysis revealed notable enrichment of MIF within M0 macrophages, exerting a profound influence on tumor-associated immunosuppression and the intricate machinery of DNA repair.

Recent Progress in Anti-Tumor Nanodrugs Based on Tumor Microenvironment Redox Regulation

The growth state of tumor cells is strictly affected by the specific abnormal redox status of the tumor microenvironment (TME). Moreover, redox reactions at the biological level are also central and fundamental to essential energy metabolism reactions in tumors. Accordingly, anti-tumor nanodrugs targeting the disruption of this abnormal redox homeostasis have become one of the hot spots in the field of nanodrugs research due to the effectiveness of TME modulation and anti-tumor efficiency mediated by redox interference. This review discusses the latest research results of nanodrugs in anti-tumor therapy, which regulate the levels of oxidants or reductants in TME through a variety of therapeutic strategies, ultimately breaking the original "stable" redox state of the TME and promoting tumor cell death. With the gradual deepening of study on the redox state of TME and the vigorous development of nanomaterials, it is expected that more anti-tumor nano drugs based on tumor redox microenvironment regulation will be designed and even applied clinically.

Targeting PRKDC activates the efficacy of antitumor immunity while sensitizing to chemotherapy and targeted therapy in liver hepatocellular carcinoma

BACKGROUND

Liver hepatocellular carcinoma (LIHC) ranks among the malignancies with the highest mortality rates, primarily due to chemoresistance culminating in treatment failure. Despite its impact, predictive models addressing disease progression, tumor microenvironment, and drug sensitivity remain elusive for LIHC patients. Recognizing the significant influence of various programmed cell death (PCD) modes on tumor evolution, this study investigates PCD genes to elucidate their implications on the prognosis and immune landscape of LIHC.

METHODS

To develop the classification and model, we employed a total of 17 genes associated with PCD patterns. To collect data, we acquired gene expression profiles, somatic mutation information, copy number variation data, and corresponding clinical data from the TCGA database, specifically from LIHC patients. Moreover, we obtained spatial transcriptome data and additional bulk datasets from the Gene Expression Omnibus (GEO) database to conduct further analysis. Various experiments were conducted to validate the role of the PCD gene PRKDC in proliferation, migration, invasion, EMT, cell cycle, therapeutic sensitivity, and antitumor immunity.

RESULTS

A novel LIHC classification based on these genes divided patients into two clusters, C1 and C2. The C2 cluster exhibited characteristics indicative of poor prognosis and an immune-activated microenvironment. This group showed greater response potential to immune checkpoint inhibitors, displaying higher levels of certain immune signatures and receptors. A programmed cell death index (PCDI) was constructed using 17 selected PCD genes. This index could effectively predict patient prognosis, with higher PCDI indicating poorer survival rates and a more pro-tumor microenvironment. Immune landscapes revealed varying interactions with PCDI, suggesting therapeutic targets and insights into treatment resistance. Moreover, experiments results suggested that PRKDC can augment the invasive nature and growth of malignant cells and it can serve as a potential target for therapy, offering hope for ameliorating the prognosis of LIHC patients.

CONCLUSIONS

The study uncovers the insights of programmed cell death in the prognosis and potential therapeutic interventions. And we found that PRKDC can serve as a target for enhancing the efficacy of antitumor immunity while sensitizing chemotherapy and targeted therapy in liver hepatocellular carcinoma.

Molecular subtypes of clear cell renal carcinoma based on PCD-related long non-coding RNAs expression: insights into the underlying mechanisms and therapeutic strategies

BACKGROUND

PCD-related long non-coding RNAs (PRLs) are rarely investigated in relation to clear cell renal carcinoma (ccRCC). As part of this study, we evaluated the immunological potential of PRL signatures as a biomarker for ccRCC prognosis and immunological function.

MATERIALS AND METHODS

Data were downloaded from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases. A Pearson correlation analysis was conducted on the 27 PCD-associated genes to determine whether lncRNAs were significantly associated with PCD. Kaplan-Meier analysis, biological function identification, immune infiltration analysis, estimation of efficacy of immunotherapy and targeted drug screening, and exploration of the landscape of mutation status were conducted by analyzing the risk scores.

RESULTS

Seven PRLs, LINC02747, AP001636.3, AC022126.1, LINC02657, LINC02609, LINC02154, and ZNNT1, were used to divide patients with ccRCC into groups with high and low risk. High-risk patients had a worse prognosis than low-risk patients, according to the results, and the PRL signature showed promising predictive ability. More immune cells were clustered in the high-risk group, whereas the immune cell function of the low-risk group was significantly suppressed. The high-risk group was less sensitive to immunotherapy, whereas the low-risk group had positive responses to most drugs.

CONCLUSIONS

Collectively, we established and verified a PRL signature that could competently guide the prognostic survival and immunotherapy of ccRCC. In addition, molecular subtypes were determined for ccRCC based on PRL expression, which may help elucidate the underlying molecular mechanism of ccRCC and develop targeted treatments.

Hydralazine loaded nanodroplets combined with ultrasound-targeted microbubble destruction to induce pyroptosis for tumor treatment

Pyroptosis, a novel type of programmed cell death (PCD), which provides a feasible therapeutic option for the treatment of tumors. However, due to the hypermethylation of the promoter, the critical protein Gasdermin E (GSDME) is lacking in the majority of cancer cells, which cannot start the pyroptosis process and leads to dissatisfactory therapeutic effects. Additionally, the quick clearance, systemic side effects, and low concentration at the tumor site of conventional pyroptosis reagents restrict their use in clinical cancer therapy. Here, we described a combination therapy that induces tumor cell pyroptosis via the use of ultrasound-targeted microbubble destruction (UTMD) in combination with DNA demethylation. The combined application of UTMD and hydralazine-loaded nanodroplets (HYD-NDs) can lead to the rapid release of HYD (a demethylation drug), which can cause the up-regulation of GSDME expression, and produce reactive oxygen species (ROS) by UTMD to cleave up-regulated GSDME, thereby inducing pyroptosis. HYD-NDs combined with ultrasound (US) group had the strongest tumor inhibition effect, and the tumor inhibition rate was 87.15% (HYD-NDs group: 51.41 ± 3.61%, NDs + US group: 32.73%±7.72%), indicating that the strategy had a more significant synergistic anti-tumor effect. In addition, as a new drug delivery carrier, HYD-NDs have great biosafety, tumor targeting, and ultrasound imaging performance. According to the results, the combined therapy reasonably regulated the process of tumor cell pyroptosis, which offered a new strategy for optimizing the therapy of GSDME-silenced solid tumors.

Necroptosis-related lncRNA-based novel signature to predict the prognosis and immune landscape in soft tissue sarcomas

BACKGROUND

Necroptosis-related long noncoding RNAs (lncRNAs) play crucial roles in cancer initiation and progression. Nevertheless, the role and mechanism of necroptosis-related lncRNAs in soft tissue sarcomas (STS) is so far unknown and needs to be explored further.

METHODS

Clinical and genomic data were obtained from the UCSC Xena database. All STS patients' subclusters were performed by unsupervised consensus clustering method based on the prognosis-specific lncRNAs, and then assessed their survival advantage and immune infiltrates. In addition, we explored the pathways and biological processes in subclusters through gene set enrichment analysis. At last, we established the necroptosis-related lncRNA-based risk signature (NRLncSig) using the least absolute shrinkage and selection operator (LASSO) method, and explored the prediction performance and immune microenvironment of this signature in STS.

RESULTS

A total of 911 normal soft tissue samples and 259 STS patients were included in current study. 39 prognosis-specific necroptosis-related lncRNAs were selected. Cluster 2 had a worse survival than the cluster 1 and characterized by different immune landscape in STS. A worse outcome in the high-risk group was observed by survival analysis and indicated an immunosuppressive microenvironment. The ROC curve analyses illustrated that the NRLncSig performing competitively in prediction of prognosis for STS patients. In addition, the nomogram presents excellent performance in predicting prognosis, which may be more beneficial towards STS patients' treatment.

CONCLUSIONS

Our result indicated that the NRLncSig could be a good independent predictor of prognosis, and significantly connected with immune microenvironment, thereby providing new insights into the roles of necroptosis-related lncRNAs in STS.

FAT1 upregulation is correlated with an immunosuppressive tumor microenvironment and predicts unfavorable outcome of immune checkpoint therapy in non-small cell lung cancer

Background

Previous studies found that FAT1 was recurrently mutated and aberrantly expressed in multiple cancers, and the loss function of FAT1 promoted the formation of cancer-initiating cells in several cancers. However, in some types of cancer, FAT1 upregulation could lead to epithelial-mesenchymal transition (EMT). The role of FAT1 in cancer progression, which appears to be cancer-type-specific, is largely unknown.

Methods

QRT-PCR and immunochemistry were used to verify the expression of FAT1 in non-small cell lung cancer (NSCLC). QRT-PCR and Western blot were used to detect the influence of siFAT1 knockdown on the expression of potential targets of FAT1 in NSCLC cell lines. GEPIA, KM-plotter, CAMOIP, and ROC-Plotter were used to evaluate the association between FAT1 and clinical outcomes based on expression and clinical data from TCGA and immune checkpoint inhibitors (ICI) treated cohorts.

Results

We found that FAT1 upregulation was associated with the activation of TGF-β and EMT signaling pathways in NSCLC. Patients with a high FAT1 expression level tend to have a poor prognosis and hard to benefit from ICI therapy. Genes involved in TGF-β/EMT signaling pathways (SERPINE1, TGFB1/2, and POSTN) were downregulated upon knockdown of FAT1. Genomic and immunologic analysis showed that high cancer-associated fibroblast (CAF) abundance, decreased CD8+ T cells infiltration, and low TMB/TNB were correlated with the upregulation of FAT1, thus promoting an immunosuppressive tumor microenvironment (TME) which influence the effect of ICI-therapy.

Conclusion

Our findings revealed the pattern of FAT1 upregulation in the TME of patients with NSCLC, and demonstrated its utility as a biomarker for unfavorable clinical outcomes, thereby providing a potential therapeutic target for NSCLC treatment.

Biological functions and clinical significance of tRNA-derived small fragment (tsRNA) in tumors: Current state and future perspectives

A new class of noncoding RNAs, tsRNAs are not only abundant in humans but also have high tissue specificity. Recently, an increasing number of studies have explored the correlations between tsRNAs and tumors, showing that tsRNAs can affect biological behaviors of tumor cells, such as proliferation, apoptosis and metastasis, by modulating protein translation, RNA transcription or posttranscriptional regulation. In addition, tsRNAs are widely distributed and stably expressed, which endows them with broad application prospects in diagnosing and predicting the prognosis of tumors, and they are expected to become new biomarkers. However, notably, the current research on tsRNAs still faces problems that need to be solved. In this review, we describe the characteristics of tsRNAs as well as their unique features and functions in tumors. Moreover, we also discuss the potential opportunities and challenges in clinical applications and research of tsRNAs.

Dietary elaidic acid boosts tumoral antigen presentation and cancer immunity via ACSL5

Immunomodulatory effects of long-chain fatty acids (LCFAs) and their activating enzyme, acyl-coenzyme A (CoA) synthetase long-chain family (ACSL), in the tumor microenvironment remain largely unknown. Here, we find that ACSL5 functions as an immune-dependent tumor suppressor. ACSL5 expression sensitizes tumors to PD-1 blockade therapy in vivo and the cytotoxicity mediated by CD8+ T cells in vitro via regulation of major histocompatibility complex class I (MHC-I)-mediated antigen presentation. Through screening potential substrates for ACSL5, we further identify that elaidic acid (EA), a trans LCFA that has long been considered harmful to human health, phenocopies to enhance MHC-I expression. EA supplementation can suppress tumor growth and sensitize PD-1 blockade therapy. Clinically, ACSL5 expression is positively associated with improved survival in patients with lung cancer, and plasma EA level is also predictive for immunotherapy efficiency. Our findings provide a foundation for enhancing immunotherapy through either targeting ACSL5 or metabolic reprogramming of antigen presentation via dietary EA supplementation.

Unveiling NRlncRNAs as prognostic biomarkers and therapeutic targets for head-and-neck squamous cell carcinoma through machine learning

Head-and-neck squamous cell carcinoma (HNSCC) patients often exhibit insensitivity to immunotherapy, leading to treatment failure. Identifying potential biomarkers that can predict prognosis and improve the efficacy of treatment is crucial. In this study, we aimed to identify necroptosis-related long noncoding RNAs (NRlncRNAs) as potential therapeutic targets to improve the prognosis of HNSCC patients. By exploring the Genotype-Tissue Expression Project (GTEx) and the Cancer Genome Atlas (TCGA) databases, we identified NRlncRNAs and developed a risk model comprising 17 NRlncRNAs to predict the prognosis of HNSCC patients and to classify patients into two clusters based on their expression levels. We conducted various analyses, such as the Kaplan-Meier analysis, GSEA and IC50 prediction, to evaluate the differences in sensitivity to immunotherapy between the two clusters. Our findings suggest that NRlncRNAs have potential as therapeutic targets for improving the prognosis of HNSCC patients, and that individualized treatment approaches based on NRlncRNA expression levels can improve the sensitivity of immunotherapy and overall treatment outcomes. This study highlights new perspectives within clinical cancer informatics and provides insight into potential therapeutic strategies for HNSCC patients.

Insights into the management of penile squamous cell carcinoma: from conventional approaches to emerging novel therapies

INTRODUCTION

Penile squamous cell carcinoma (PSCC), a rare genitourinary cancer, is associated with poor outcomes due to limited treatment effectiveness, especially in advanced stages.

AREAS COVERED

While chemotherapy and/or surgery remain the standard of care, emerging therapies like immunotherapy, targeted therapy, and human papillomavirus (HPV) directed therapies show promise. Key to advancing treatment is understanding the immune microenvironment to gain insights into tumor resistance mechanisms and potential therapeutic targets. The scarcity of data on PSCC is a major obstacle in advancing research for this rare cancer.

EXPERT OPINION

Future research should prioritize collaborative efforts across various research centers and countries. Enhancing data sharing and pooling resources can lead to a more comprehensive understanding of PSCC, ultimately supporting the development of precision medicine strategies tailored to this specific cancer type. This collaborative approach is essential for making significant strides in PSCC treatment and care.

Ultrasound combined with microbubble mediated immunotherapy for tumor microenvironment

The tumor microenvironment (TME) plays an important role in dynamically regulating the progress of cancer and influencing the therapeutic results. Targeting the tumor microenvironment is a promising cancer treatment method in recent years. The importance of tumor immune microenvironment regulation by ultrasound combined with microbubbles is now widely recognized. Ultrasound and microbubbles work together to induce antigen release of tumor cell through mechanical or thermal effects, promoting antigen presentation and T cells' recognition and killing of tumor cells, and improve tumor immunosuppression microenvironment, which will be a breakthrough in improving traditional treatment problems such as immune checkpoint blocking (ICB) and himeric antigen receptor (CAR)-T cell therapy. In order to improve the therapeutic effect and immune regulation of TME targeted tumor therapy, it is necessary to develop and optimize the application system of microbubble ultrasound for organs or diseases. Therefore, the combination of ultrasound and microbubbles in the field of TME will continue to focus on developing more effective strategies to regulate the immunosuppression mechanisms, so as to activate anti-tumor immunity and/or improve the efficacy of immune-targeted drugs, At present, the potential value of ultrasound combined with microbubbles in TME targeted therapy tumor microenvironment targeted therapy has great potential, which has been confirmed in the experimental research and application of breast cancer, colon cancer, pancreatic cancer and prostate cancer, which provides a new alternative idea for clinical tumor treatment. This article reviews the research progress of ultrasound combined with microbubbles in the treatment of tumors and their application in the tumor microenvironment.

Targeting natural killer cells: from basic biology to clinical application in hematologic malignancies

Natural killer (NK) cell belongs to innate lymphoid cell family that contributes to host immunosurveillance and defense without pre-immunization. Emerging studies have sought to understand the underlying mechanism behind NK cell dysfunction in tumor environments, and provide numerous novel therapeutic targets for tumor treatment. Strategies to enhance functional activities of NK cell have exhibited promising efficacy and favorable tolerance in clinical treatment of tumor patients, such as immune checkpoint blockade (ICB), chimeric antigen receptor NK (CAR-NK) cell, and bi/trispecific killer cell engager (BiKE/TriKE). Immunotherapy targeting NK cell provides remarkable advantages compared to T cell therapy, including a decreased rate of graft versus-host disease (GvHD) and neurotoxicity. Nevertheless, advanced details on how to support the maintenance and function of NK cell to obtain better response rate and longer duration still remain to be elucidated. This review systematically summarizes the profound role of NK cells in tumor development, highlights up-to-date advances and current challenges of therapy targeting NK cell in the clinical treatment of hematologic malignancies.

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

Tumor-to-stroma cd8+ t cells ratio combined with cancer-associated fibroblasts: an innovative approach to predicting lymph node metastases of cervical cancer

PURPOSE

Precise identification of lymph node metastases is vital for the management of cervical cancer. However, the existing diagnostic methods for lymph node metastases have certain drawbacks. In this study, we aim to explore the expression of cancer-associated fibroblasts (CAFs) and tumor-to-stroma CD8+ T cells ratio (CD8+ T cells T:S ratio) and its association with lymph node metastases of cervical cancer.

METHODS

Hundred and ten cervical cancer tissues and 39 biopsy tissues from patients were investigated immunocytochemically for the expression of CAFs and CD8+ T cells. The statistical correlation analysis was carried out using the SPSS system.

RESULTS

A strong and statistically significant negative correlation (r= - 0.690; P < 0.001) was observed between CAF density and CD8+ T cells T:S ratio. Not only were CAFs density and CD8+ T cells T:S ratio correlated with lymph node metastases respectively (P < 0.001), but the combination of them also significantly correlated with lymph node metastases (P < 0.001). Then, we constructed the combined diagnosis model (Logit (P) = - 4.446 + 0.300 × CAFs + 0.752 × CD8+ T cells T:S Ratio) of cervical cancer lymph node metastases. ROC curves analysis showed that the ROC curves areas for CAFs, CD8+ T cells T:S ratio, and a combination of both are 0.879, 0.747, and 0.951. Then, the prediction model was verified by biopsy specimens and consistent results were obtained.

CONCLUSIONS

The combination of CAF density and CD8+ T cells T:S ratio has a significant predictive value for lymph node metastases in patients with cervical cancer.

Advances in Nanoplatforms for Immunotherapy Applications Targeting the Tumor Microenvironment

Cancer immunotherapy is a treatment method that activates or enhances the autoimmune response of the body to fight tumor growth and metastasis, has fewer toxic side effects and a longer-lasting efficacy than radiotherapy and chemotherapy, and has become an important means for the clinical treatment of cancer. However, clinical results from immunotherapy have shown that most patients lack responsiveness to immunotherapy and cannot benefit from this treatment strategy. The tumor microenvironment (TME) plays a critical role in the response to immunotherapy. The TME typically prevents effective lymphocyte activation, reducing their infiltration, and inhibiting the infiltration of effector T cells. According to the characteristic differences between the TME and normal tissues, various nanoplatforms with TME targeting and regulation properties have been developed for more precise regulation of the TME and have the ability to codeliver a variety of active pharmaceutical ingredients, thereby reducing systemic toxicity and improving the therapeutic effect of antitumor. In addition, the precise structural design of the nanoplatform can integrate specific functional motifs, such as surface-targeted ligands, degradable backbones, and TME stimulus-responsive components, into nanomedicines, thereby reshaping the tumor microenvironment, improving the body's immunosuppressive state, and enhancing the permeability of drugs in tumor tissues, in order to achieve controlled and stimulus-triggered release of load cargo. In this review, the physiological characteristics of the TME and the latest research regarding the application of TME-regulated nanoplatforms in improving antitumor immunotherapy will be described. Furthermore, the existing problems and further applications perspectives of TME-regulated platforms for cancer immunotherapy will also be discussed.

Upregulation of CCNB2 and a novel lncRNAs-related risk model predict prognosis in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the main type of renal cell carcinoma. Cyclin B2 (CCNB2) is a subtype of B-type cyclin that is associated with the prognosis of several cancers. This study aimed to identify the relationship between CCNB2 and progression of ccRCC and construct a novel lncRNAs-related model to predict prognosis of ccRCC patients.

METHODS

The data were obtained from public databases. We identified CCNB2 in ccRCC using Kaplan-Meier survival analysis, univariate and multivariate Cox regression, and Gene Ontology analysis. External validation was then performed. The risk model was constructed based on prognostic lncRNAs by the LASSO algorithm and multivariate Cox regression. Receiver operating characteristics (ROC) curves were used to evaluate the model. Consensus clustering analysis was performed to re-stratify the patients. Finally, we analyzed the tumor-immune microenvironment and performed screening of potential drugs.

RESULTS

CCNB2 associated with late clinicopathological parameters and poor prognosis in ccRCC and was an independent predictor for disease-free survival. In addition, CCNB2 shared the same expression pattern with known suppressive immune checkpoints. A risk model dependent on the expression of three prognostic CCNB2-related lncRNAs (SNHG17, VPS9D1-AS1, and ZMIZ1-AS1) was constructed. The risk signature was an independent predictor of ccRCC. The area under the ROC (AUC) curve for overall survival at 1-, 3-, 5-, and 8-year was 0.704, 0.702, 0.741, and 0.763. The high-risk group and cluster 2 had stronger immunogenicity and were more sensitive to immunotherapy.

CONCLUSION

CCNB2 could be an important biomarker for predicting prognosis in ccRCC patients. Furthermore, we developed a novel lncRNAs-related risk model and identified two CCNB2-related molecular clusters. The risk model performed well in predicting overall survival and immunological microenvironment of ccRCC.

The role of stromal cells in epithelial-mesenchymal plasticity and its therapeutic potential

The epithelial-mesenchymal transition (EMT) is a critical tumor invasion and metastasis process. EMT enables tumor cells to migrate, detach from their original location, enter the circulation, circulate within it, and eventually exit from blood arteries to colonize in foreign sites, leading to the development of overt metastases, ultimately resulting in death. EMT is intimately tied to stromal cells around the tumor and is controlled by a range of cytokines secreted by stromal cells. This review summarizes recent research on stromal cell-mediated EMT in tumor invasion and metastasis. We also discuss the effects of various stromal cells on EMT induction and focus on the molecular mechanisms by which several significant stromal cells convert from foes to friends of cancer cells to fuel EMT processes via their secretions in the tumor microenvironment (TME). As a result, a better knowledge of the role of stromal cells in cancer cells' EMT may pave the path to cancer eradication.

ALDOB/KAT2A interactions epigenetically modulate TGF-β expression and T cell functions in hepatocellular carcinogenesis

BACKGROUND AND AIMS

Cross talk between tumor cells and immune cells enables tumor cells to escape immune surveillance and dictate responses to immunotherapy. Previous studies have identified that downregulation of the glycolytic enzyme fructose-1,6-bisphosphate aldolase B (ALDOB) in tumor cells orchestrated metabolic programming to favor HCC. However, it remains elusive whether and how ALDOB expression in tumor cells affects the tumor microenvironment in HCC.

APPROACH AND RESULTS

We found that ALDOB downregulation was negatively correlated with CD8 + T cell infiltration in human HCC tumor tissues but in a state of exhaustion. Similar observations were made in mice with liver-specific ALDOB knockout or in subcutaneous tumor models with ALDOB knockdown. Moreover, ALDOB deficiency in tumor cells upregulates TGF-β expression, thereby increasing the number of Treg cells and impairing the activity of CD8 + T cells. Consistently, a combination of low ALDOB and high TGF-β expression exhibited the worst overall survival for patients with HCC. More importantly, the simultaneous blocking of TGF-β and programmed cell death (PD) 1 with antibodies additively inhibited tumorigenesis induced by ALDOB deficiency in mice. Further mechanistic experiments demonstrated that ALDOB enters the nucleus and interacts with lysine acetyltransferase 2A, leading to inhibition of H3K9 acetylation and thereby suppressing TGFB1 transcription. Consistently, inhibition of lysine acetyltransferase 2A activity by small molecule inhibitors suppressed TGF-β and HCC.

CONCLUSIONS

Our study has revealed a novel mechanism by which a metabolic enzyme in tumor cells epigenetically modulates TGF-β signaling, thereby enabling cancer cells to evade immune surveillance and affect their response to immunotherapy.

Endothelial-to-mesenchymal transition in tumour progression and its potential roles in tumour therapy

Tumour-associated endothelial cells (TECs) are a critical stromal cell type in the tumour microenvironment and play central roles in tumour angiogenesis. Notably, TECs have phenotypic plasticity, as they have the potential to transdifferentiate into cells with a mesenchymal phenotype through a process termed endothelial-to-mesenchymal transition (EndoMT). Many studies have reported that EndoMT influences multiple malignant biological properties of tumours, such as abnormal angiogenesis and tumour metabolism, growth, metastasis and therapeutic resistance. Thus, the value of targeting EndoMT in tumour treatment has received increased attention. In this review, we comprehensively explore the phenomenon of EndoMT in the tumour microenvironment and identify influencing factors and molecular mechanisms responsible for EndoMT induction. Furthermore, the pathological functions of EndoMT in tumour progression and potential therapeutic strategies for targeting EndoMT in tumour treatment are also discussed to highlight the pivotal roles of EndoMT in tumour progression and therapy.

Identification and immune landscape analysis of fatty acid metabolism genes related subtypes of gastric cancer

Fatty acid metabolism (FAM) is associated with prognosis and immune microenvironment remodeling in many tumors. It is currently unknown how FAM affects the immunological microenvironment and prognosis of Gastric cancer (GC). Therefore, the current work aims to categorize GC samples based on the expression status of genes involved in FAM and to identify populations that might benefit from immunotherapy. In total, 50 FAM genes associated with overall survival (OS) were determined through univariate Cox proportional hazard regression analysis by mining the public TCGA and GEO databases. The GSE84437 and TCGA-STAD cohort samples were divided into two clusters using the "NMF" R package. According to the survival curve, patients in Cluster-1 showed considerably longer OS than those in Cluster-2. Patients in Cluster-1 exhibited earlier T stages, more intestinal GCs, and were older. MSI molecular subtypes were mainly distributed in Cluster-1, while GS molecular subtypes were distributed primarily in Cluster-2. There were 227 upregulated and 22 down-regulated genes (logFC > 1 or logFC < - 1, FDR < 0.05) in Cluster-2 compared with Cluster-1. One hub module (edges = 64, nodes = 12) was identified with a module score of 11.636 through Cytoscape plug-in MCODE. KEGG and GO analysis showed that the hub genes were associated with the cell cycle and cell division. Different immune cell infiltrates profile, and immune pathway enrichment existed between the subtypes. In conclusion, the current findings showed that practically all immunological checkpoint and immunoregulatory genes were elevated in patients with Cluster-2 GC, indicating that FAM subtypes may be crucial in GC immunotherapy.

Amino acid metabolism reprogramming: shedding new light on T cell anti-tumor immunity

Metabolic reprogramming of amino acids has been increasingly recognized to initiate and fuel tumorigenesis and survival. Therefore, there is emerging interest in the application of amino acid metabolic strategies in antitumor therapy. Tremendous efforts have been made to develop amino acid metabolic node interventions such as amino acid antagonists and targeting amino acid transporters, key enzymes of amino acid metabolism, and common downstream pathways of amino acid metabolism. In addition to playing an essential role in sustaining tumor growth, new technologies and studies has revealed amino acid metabolic reprograming to have wide implications in the regulation of antitumor immune responses. Specifically, extensive crosstalk between amino acid metabolism and T cell immunity has been reported. Tumor cells can inhibit T cell immunity by depleting amino acids in the microenvironment through nutrient competition, and toxic metabolites of amino acids can also inhibit T cell function. In addition, amino acids can interfere with T cells by regulating glucose and lipid metabolism. This crucial crosstalk inspires the exploitation of novel strategies of immunotherapy enhancement and combination, owing to the unprecedented benefits of immunotherapy and the limited population it can benefit. Herein, we review recent findings related to the crosstalk between amino acid metabolism and T cell immunity. We also describe possible approaches to intervene in amino acid metabolic pathways by targeting various signaling nodes. Novel efforts to combine with and unleash potential immunotherapy are also discussed. Hopefully, some strategies that take the lead in the pipeline may soon be used for the common good.

S100A6 is a potential diagnostic and prognostic biomarker for human glioma

S100 calcium-binding protein A6 (S100A6) is a protein that belongs to the S100 family. The present study aimed to investigate the function of S100A6 in the diagnosis and survival prediction of glioma and elucidated the potential processes affecting glioma development. The Cancer Genome Atlas database was searched to identify the relationship among S100A6 expression, immune cell infiltration, clinicopathological parameters and glioma prognosis. Several clinical cases were used to verify these findings. S100A6 gene expression was high in glioma tissues, suggesting its diagnostic significance. In particular, S100A6 upregulation in glioma tissues exhibited a significant and positive correlation with the World Health Organization (WHO) grade, histological type, age, sex, primary treatment outcomes, 1p/19q codeletion, isocitrate dehydrogenase (IDH) status, overall survival (OS), progression-free interval and disease-specific survival. Kaplan-Meier and Cox regression analyses revealed that S100A6 gene expression can independently function as a risk factor affecting the prognosis of patients with glioma. Furthermore, Gene Ontology functional enrichment analysis revealed that S100A6 is implicated in immune responses and that the expression profiles of S100A6 are linked to the immune microenvironment. Furthermore, immunohistochemistry revealed that increased S100A6 protein levels are correlated with age, 1p/19q codeletion, IDH status, WHO grade and OS. The present findings suggest that increased S100A6 expression is an indicator of the dismal prognosis of patients with glioma and that it can be used as a potential diagnostic biomarker for this condition.

Ferroptosis-related STEAP3 acts as predictor and regulator in diffuse large B cell lymphoma through immune infiltration

Diffuse large B cell lymphoma (DLBCL) is a usual-seen hematological malignant tumor possessing molecular and genetic heterogeneity. Ferroptosis induction has been increasingly acknowledged to be an advantageous therapeutic method in tumor treatment by triggering cell death of tumor cells. However, studies on the function of ferroptosis in DLBCL remain scarce, especially the interaction with the tumor immune microenvironment (TIME). The clinical and biological functions of ferroptosis-related genes in DLBCL were still warranted to be explored. A ferroptosis-related risk model was constructed, followed by functional enrichment analyses and evaluation of immune profile. Quantitative real-time PCR, western blotting, and immunohistochemistry were conducted to examine the RNA and protein levels. Dysregulated expression of the major ferroptosis-related genes was found in DLBCL. A prognostic risk model based on 10 ferroptosis-related genes was constructed. The risk score served as an independent prognostic indicator for DLBCL patients in univariate and multivariate Cox regression analysis. Patients with low-risk scores presented a more favorable prognosis. Functional enrichment analysis revealed that immune-related pathways were significantly enriched, and the high-risk group exhibited less immunocyte infiltration, lower immunoscore, and downregulated PD-L1 expression relative to the low-risk group. Two molecular subtypes were determined through consensus clustering of the expression of ferroptosis-related genes. Cluster 1 was relevant to favorable prognosis, higher immunoscore, and elevated PD-L1 expression. More importantly, STEAP3 was screened as a reliable biomarker for DLBCL, and its enhanced expression levels of mRNA and protein were verified in public databases and clinical specimens. Our study demonstrated the crucial role of ferroptosis-related genes including STEAP3 in the TIME of DLBCL and identified promising novel molecular targets for DLBCL treatment.

Integrating angiogenesis signature and tumor mutation burden for improved patient stratification in immune checkpoint blockade therapy for muscle-invasive bladder cancer

BACKGROUND

Muscle-invasive bladder cancer (MIBC) patients have benefitted greatly from immune checkpoint blockade (ICB) therapy. However, there is a pressing need to identify factors underlying the heterogeneity of clinical responses to ICB.

METHODS

We conducted a study on 848 MIBC patients from 4 independent cohorts to investigate the key biological characteristics affecting ICB responses. The IMvigor210 cohort (n = 234) was used to identify the key factor, followed by exploration of the correlation between tumor angiogenesis and immune suppression in the IMvigor210, TCGA (n = 391), and UNC-108 (n = 89) cohorts. The ZSHS cohort (n = 134) was used for validation. Additionally, we integrated angiogenesis signature with tumor mutation burden (TMB) to decipher the heterogeneity of clinical outcomes to ICB in MIBC patients.

RESULTS

Our analysis revealed that nonresponders to PD-L1 blockade were enriched with angiogenesis signature. Furthermore, we observed a correlation between angiogenesis signature and decreased neoantigen load, downregulated T-cell antigen recognition, and noninflamed immunophenotype. We identified a subgroup of patients resistant to ICB, characterized by high angiogenesis signature and low tumor mutation burden (TMB), and found the activation of TGF-β signaling and downregulation of T-cell cytolytic signatures in this subgroup.

CONCLUSIONS

The study concluded that angiogenesis signature is closely associated with an immunosuppressive microenvironment, leading to resistance to ICB therapy in MIBC patients. The study further suggested that the combination of angiogenesis signature and TMB can serve as an integrated biomarker for better stratification of patients' clinical outcomes to ICB therapy.

Construction of a novel cancer-associated fibroblast-related signature to predict clinical outcome and immune response in colon adenocarcinoma

The interaction between the tumour and the surrounding microenvironment determines the malignant biological behaviour of the tumour. Cancer-associated fibroblasts (CAFs) coordinate crosstalk between cancer cells in the tumour immune microenvironment (TIME) and are extensively involved in tumour malignant behaviours, such as immune evasion, invasion and drug resistance. Here, we performed differential and prognostic analyses of genes associated with CAFs and constructed CAF-related signatures (CAFRs) to predict clinical outcomes in individuals with colon adenocarcinoma (COAD) based on machine learning algorithms. The CAFRs were further validated in an external independent cohort, GSE17538. Additionally, Cox regression, receiver operating characteristic (ROC) and clinical correlation analysis were utilised to systematically assess the CAFRs. Moreover, CIBERSORT, single sample Gene Set Enrichment Analysis (ssGSEA) and Estimation of Stromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) analysis were utilised to characterise the TIME in patients with COAD. Microsatellite instability (MSI) and tumour mutation burden were also analysed. Furthermore, Gene Set Variation Analysis (GSVA), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) elucidated the biological functions and signalling pathways involved in the CAFRs. Consensus clustering analysis was used for the immunological analysis of patients with COAD. Finally, the pRRophic algorithm was used for sensitivity analysis of common drugs. The CAFRs constructed herein can better predict the prognosis in COAD. The cluster analysis based on the CAFRs can effectively differentiate between immune 'hot' and 'cold' tumours, determine the beneficiaries of immune checkpoint inhibitors (ICIs) and provide insight into individualised treatment for COAD.

Cancer Cell Membrane Nanodiscs for Antitumor Vaccination

Cell membrane-based nanovaccines have demonstrated attractive features due to their inherently multiantigenic nature and ability to be formulated with adjuvants. Here, we report on cellular nanodiscs fabricated from cancer cell membranes and incorporated with a lipid-based adjuvant for antitumor vaccination. The cellular nanodiscs, with their small size and discoidal shape, are readily taken up by antigen-presenting cells and drain efficiently to the lymph nodes. Due to its highly immunostimulatory properties, the nanodisc vaccine effectively stimulates the immune system and promotes tumor-specific immunity. Using a murine colorectal cancer model, strong control of tumor growth is achieved in both prophylactic and therapeutic settings, particularly in combination with checkpoint blockades. Considerable therapeutic efficacy is also observed in treating a weakly immunogenic metastatic melanoma model. This work presents a new paradigm for the design of multiantigenic nanovaccines that can effectively activate antitumor immune responses and may be applicable to a wide range of cancers.

Comprehensive analyses of fatty acid metabolism-related lncRNA for ovarian cancer patients

Ovarian cancer (OC) is a disease with difficult early diagnosis and treatment and poor prognosis. OC data profiles were downloaded from The Cancer Genome Atlas. Eight key fatty acid metabolism-related long non-coding RNAs (lncRNAs) were finally screened for building a risk scoring model by univariate/ multifactor and least absolute shrinkage and selection operator (LASSO) Cox regression. To make this risk scoring model more applicable to clinical work, we established a nomogram containing the clinical characteristics of OC patients after confirming that the model has good reliability and validity and the ability to distinguish patient prognosis. To further explore how these key lncRNAs are involved in OC progression, we explored their relationship with LUAD immune signatures and tumor drug resistance. The structure shows that the risk scoring model established based on these 8 fatty acid metabolism-related lncRNAs has good reliability and validity and can better predict the prognosis of patients with different risks of OC, and LINC00861in these key RNAs may be a hub gene that affects the progression of OC and closely related to the sensitivity of current OC chemotherapy drugs. In addition, combined with immune signature analysis, we found that patients in the high-risk group are in a state of immunosuppression, and Tfh cells may play an important role in it. We innovatively established a prognostic prediction model with excellent reliability and validity from the perspective of OC fatty acid metabolism reprogramming and lncRNA regulation and found new molecular/cellular targets for future OC treatment.

Differences in serum cytokine levels distinguish between clinically noninvasive lung adenocarcinoma and invasive lung adenocarcinoma: A cross-sectional study

Background

Lung cancer incidence and mortality remain high and are now the leading cause of cancer-related death. Lung adenocarcinoma (LUAD) is one of the main histological subtypes of lung cancer. Previous studies have shown the role of inflammation in the development of lung cancer, but the relationship between cytokines and LUAD is still unclear. To further differentiate and explore the association of cytokines with the risk of non-invasive and invasive LUAD, we studied and assessed serum cytokine levels in patients with two types of LUAD.

Methods

A cohort study of 90 non-invasive LUAD and 90 invasive LUAD was retrospectively included, and the clinical characteristics were recorded in detail. The differences in the levels of 12 serum cytokines (IFN-α, IFN-γ, IL-10, IL-12P70, IL-17A, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, and TNF-α) between the two groups of patients with LUAD were analyzed and evaluated. And we evaluated the clinical value of cytokine differential diagnosis of invasive LUAD based on receiver operating characteristics (ROC) curves.

Results

The mean age of the patients was 56.6 years, and the proportions of males and females were 38.9% and 61.1%, respectively. IFN-α, IL-1β, IL-2, IL-6, TNF-α, IL-4, and IL-8 were significantly increased in patients with invasive LUAD compared with the non-invasive LUAD group. Further research found that smoking is an important factor, with changes in the four cytokines IL-1β, IL-6, IL-8, and TNF-α being significantly higher in the smoking group of patients with invasive LUAD. It can be seen from the area under the curve that IL-1β and IL-2 have a significant differential diagnosis.

Conclusions

We observed differences in preoperative serum cytokine levels between patients with invasive and non-invasive LUAD, which may serve as potential serum biomarkers for clinical differential diagnosis and disease progression assessment.

Integrating Single-Cell RNA-Seq and Bulk RNA-Seq Data to Explore the Key Role of Fatty Acid Metabolism in Breast Cancer

Cancer immune escape is associated with the metabolic reprogramming of the various infiltrating cells in the tumor microenvironment (TME), and combining metabolic targets with immunotherapy shows great promise for improving clinical outcomes. Among all metabolic processes, lipid metabolism, especially fatty acid metabolism (FAM), plays a major role in cancer cell survival, migration, and proliferation. However, the mechanisms and functions of FAM in the tumor immune microenvironment remain poorly understood. We screened 309 fatty acid metabolism-related genes (FMGs) for differential expression, identifying 121 differentially expressed genes. Univariate Cox regression models in The Cancer Genome Atlas (TCGA) database were then utilized to identify the 15 FMGs associated with overall survival. We systematically evaluated the correlation between FMGs' modification patterns and the TME, prognosis, and immunotherapy. The FMGsScore was constructed to quantify the FMG modification patterns using principal component analysis. Three clusters based on FMGs were demonstrated in breast cancer, with three patterns of distinct immune cell infiltration and biological behavior. An FMGsScore signature was constructed to reveal that patients with a low FMGsScore had higher immune checkpoint expression, higher immune checkpoint inhibitor (ICI) scores, increased immune microenvironment infiltration, better survival advantage, and were more sensitive to immunotherapy than those with a high FMGsScore. Finally, the expression and function of the signature key gene NDUFAB1 were examined by in vitro experiments. This study significantly demonstrates the substantial impact of FMGs on the immune microenvironment of breast cancer, and that FMGsScores can be used to guide the prediction of immunotherapy efficacy in breast cancer patients. In vitro experiments, knockdown of the NDUFAB1 gene resulted in reduced proliferation and migration of MCF-7 and MDA-MB-231 cell lines.

Association of ERCC family mutations with prognosis and immune checkpoint inhibitors response in multiple cancers

The proteins encoded by the excision repair cross-complementing (ERCC) family are pivotal in DNA damage repair and maintaining genome stability. However, the precise role of the ERCC family in tumor prognosis and the effectiveness of immune checkpoint inhibitors (ICI) therapy remain uncertain. This study aimed to explore the connection between ERCC mutations and prognosis as well as the response to ICI. We observed that patients with ERCC mutations exhibited enhanced progression-free survival (PFS) and overall survival (OS) in two independent pan-cancer cohorts. Furthermore, this mutant subgroup showed higher tumor mutation burden (TMB) compared to the wild-type subgroup. Notably, ERCC mutations were associated with better OS (HR 0.54, 95% CI 0.42-0.70; P < 0.001) in pan-cancer patients who underwent ICI therapy (N = 1661). These findings were validated in a separate cohort, where patients in the ERCC mutant subgroup demonstrated improved clinical outcomes (HR 0.56, 95% CI 0.37-0.84; P = 0.03) and higher response rates (51.9% vs. 26.8%) than the wild-type subgroup. Further analysis revealed that patients with ERCC mutations displayed elevated tumor neoantigen burden (TNB) levels and increased infiltration of immune-response cells. Our study suggests that ERCC mutations are linked to enhanced immunogenicity and improved ICI efficacy, thus potentially serving as a biomarker for ICI therapy.

Pan-cancer analysis and experimental validation revealed the m6A methyltransferase KIAA1429 as a potential biomarker for diagnosis, prognosis, and immunotherapy

BACKGROUND

KIAA1429, also known as VIRMA (vir-like m6A methyltransferase associated), plays a crucial role in tumorigenesis by modulating the level of m6A methylation. Previous studies have reported the prevalent overexpression of KIAA1429 in multiple cancers, related to a poor prognosis. Nevertheless, the precise role of KIAA1429 in tumor progression and its impact on the immune response remains unclear.

METHODS

A differential analysis of KIAA1429 expression was performed across cancers using data from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. We evaluated the role of KIAA1429 in the diagnosis, prognosis, and immunotherapy of tumor patients using bioinformatics methods. In addition, we also analyzed the associations between KIAA1429 and DNA methylation, immunotherapy. RT-qPCR was used to study the expression levels of KIAA1429 mRNA in 11 cell lines.

RESULTS

KIAA1429 is found to be overexpressed in 28 cancer types, but its expression is relatively low in patients with acute myeloid leukemia (LAML) and ovarian serous cystadenocarcinoma (OV). Moreover, KIAA1429 demonstrates a positive correlation with advanced stages of multiple cancers. Kaplan-Meier (KM) analysis suggested that patients with elevated KIAA1429 expression had shorter survival. Furthermore, KIAA1429 shows strong associations with DNA methylation, tumor-infiltrating immune cells (TIICs), and the tumor microenvironment (TME). RT-qPCR results indicated significantly higher expression of KIAA1429 in tumor cells compared to matched-normal cells.

CONCLUSIONS

In summary, our work illustrates that KIAA1429 expression is positively connected with poor prognosis in multiple cancers. Moreover, KIAA1429 could serve as a diagnostic factor and a predictor of immune response for specific tumor types.

Characterizing cancer metabolism from bulk and single-cell RNA-seq data using METAFlux

Cells often alter metabolic strategies under nutrient-deprived conditions to support their survival and growth. Characterizing metabolic reprogramming in the tumor microenvironment (TME) is of emerging importance in cancer research and patient care. However, recent technologies only measure a subset of metabolites and cannot provide in situ measurements. Computational methods such as flux balance analysis (FBA) have been developed to estimate metabolic flux from bulk RNA-seq data and can potentially be extended to single-cell RNA-seq (scRNA-seq) data. However, it is unclear how reliable current methods are, particularly in TME characterization. Here, we present a computational framework METAFlux (METAbolic Flux balance analysis) to infer metabolic fluxes from bulk or single-cell transcriptomic data. Large-scale experiments using cell-lines, the cancer genome atlas (TCGA), and scRNA-seq data obtained from diverse cancer and immunotherapeutic contexts, including CAR-NK cell therapy, have validated METAFlux's capability to characterize metabolic heterogeneity and metabolic interaction amongst cell types.

The linkage of NF-κB signaling pathway-associated long non-coding RNAs with tumor microenvironment and prognosis in cervical cancer

BACKGROUND

NF-κB signaling pathway participate closely in regulating inflammation and immune response in many cancers. Long non-coding RNAs (lncRNAs) associated with NF-κB signaling have not been characterized in cervical cancer. This study revealed the linkage between tumor microenvironment and NF-κB signaling-associated lncRNAs in cervical cancer.

MATERIALS AND METHODS

The expression profiles of cervical cancer samples from The Cancer Genome Atlas (TCGA) database were downloaded. NF-κB signaling-associated lncRNAs were screened as a basis to perform molecular subtyping. Immune cell infiltration was assessed by ESTIMATE, Microenvironment Cell Populations (MCP)-counter and single sample gene set enrichment analysis (ssGSEA). The key NF-κB signaling-associated lncRNAs were identified by univariate analysis, least absolute shrinkage and selection operator, and stepAIC.

RESULTS

Three molecular subtypes or clusters (cluster 3, cluster 2, and cluster 1) were categorized based on 27 prognostic NF-κB signaling-associated lncRNAs. Cluster 2 had the worst prognosis, highest immune infiltration, as well as the highest expression of most of immune checkpoints. Three clusters showed different sensitivities to immunotherapy and chemotherapy. Six key NF-κB signaling-associated lncRNAs were screened to establish a six-lncRNA risk model for predicting cervical cancer prognosis.

CONCLUSIONS

NF-κB signaling-associated lncRNAs played an important role in regulating immune microenvironment. The subtyping based on NF-κB signaling-associated lncRNAs may assist in the selection of optimal treatments. The six key NF-κB signaling-associated lncRNAs could act as prognostic biomarkers in prognostic prediction for cervical cancer.

Necrotic related-lncRNAs: Prediction of prognosis and differentiation between cold and hot tumors in head and neck squamous cell carcinoma

Treatment of head and neck squamous cell carcinoma (HNSCC) is a substantial clinical challenge due to the high local recurrence rate and chemotherapeutic resistance. This project seeks to identify new potential biomarkers of prognosis prediction and precision medicine to improve this condition. A synthetic data matrix for RNA transcriptome datasets and relevant clinical information on HNSCC and normal tissues was downloaded from the Genotypic Tissue Expression Project and The Cancer Genome Atlas (TCGA). The necrosis-associated long-chain noncoding RNAs (lncRNAs) were identified by Pearson correlation analysis. Then 8-necrotic-lncRNA models in the training, testing and entire sets were established through univariate Cox (uni-Cox) regression and Lasso-Cox regression. Finally, the prognostic ability of the 8-necrotic-lncRNA model was evaluated via survival analysis, nomogram, Cox regression, clinicopathological correlation analysis, and receiver operating characteristic (ROC) curve. Gene enrichment analysis, principal component analysis, immune analysis and prediction of risk group semi-maximum inhibitory concentration (IC50) were also conducted. Correlations between characteristic risk score and immune cell infiltration, immune checkpoint molecules, somatic gene mutations, and anti-cancer drug sensitivity were analyzed. Eight necrosis-associated lncRNAs (AC099850.3, AC243829.2, AL139095.4, SAP30L-AS1, C5orf66-AS1, LIN02084, LIN00996, MIR4435-2HG) were developed to improve the prognosis prediction of HNSCC patients. The risk score distribution, survival status, survival time, and relevant expression standards of these lncRNAs were compared between low- and high-risk groups in the training, testing and entire sets. Kaplan-Meier analysis showed the low-risk patients had significantly better prognosis. The ROC curves revealed the model had an acceptable predictive value in the TCGA training and testing sets. Cox regression and stratified survival analysis indicated that the 8 necrosis-associated lncRNAs were risk factors independent of various clinical parameters. We recombined the patients into 2 clusters through Consensus ClusterPlus R package according to the expressions of necrotic lncRNAs. Significant differences were found in immune cell infiltration, immune checkpoint molecules, and IC50 between clusters, suggesting these characteristics can be used to evaluate the clinical efficacy of chemotherapy and immunotherapy. This risk model may serve as a prognostic signature and provide clues for individualized immunotherapy for HNSCC patients.

Predicting prognosis, immunotherapy and distinguishing cold and hot tumors in clear cell renal cell carcinoma based on anoikis-related lncRNAs

Background

Clear cell renal cell carcinoma (ccRCC) is the most frequently occurring malignant tumor within the kidney cancer subtype. It has low sensitivity to traditional radiotherapy and chemotherapy, the optimal treatment for localized ccRCC has been surgical resection, but even with complete resection the tumor will be eventually developed into metastatic disease in up to 40% of localized ccRCC. For this reason, it is crucial to find early diagnostic and treatment markers for ccRCC.

Methods

We obtained anoikis-related genes (ANRGs) integrated from Genecards and Harmonizome dataset. The anoikis-related risk model was constructed based on 12 anoikis-related lncRNAs (ARlncRNAs) and verified by principal component analysis (PCA), Receiver operating characteristic (ROC) curves, and T-distributed stochastic neighbor embedding (t-SNE), and the role of the risk score in ccRCC immune cell infiltration, immune checkpoint expression levels, and drug sensitivity was evaluated by various algorithms. Additionally, we divided patients based on ARlncRNAs into cold and hot tumor clusters using the ConsensusClusterPlus (CC) package.

Results

The AUC of risk score was the highest among various factors, including age, gender, and stage, indicating that the model we built to predict survival was more accurate than the other clinical features. There was greater sensitivity to targeted drugs like Axitinib, Pazopanib, and Sunitinib in the high-risk group, as well as immunotherapy drugs. This shows that the risk-scoring model can accurately identify candidates for ccRCC immunotherapy and targeted therapy. Furthermore, our results suggest that cluster 1 is equivalent to hot tumors with enhanced sensitivity to immunotherapy drugs.

Conclusion

Collectively, we developed a risk score model based on 12 prognostic lncRNAs, expected to become a new tool for evaluating the prognosis of patients with ccRCC, providing different immunotherapy strategies by screening for hot and cold tumors.

T-cell dysfunction in natural killer/T-cell lymphoma

Natural killer/T-cell lymphoma (NKTCL) is an incurable aggressive T-cell lymphoma closely correlated with Epstein‒Barr virus (EBV) infection. Chronic and consistent viral infection induces T-cell exhaustion. Herein, we describe T-cell dysfunction in NKTCL patients for the first time. Peripheral blood mononuclear cells (PBMCs) from age-matched healthy donors (HDs) and NKTCL patients were collected, and lymphocyte distributions, multiple surface inhibitory receptors (IRs), effector cytokine production and cell proliferation were determined by flow cytometry. PBMCs from HDs were cocultured with NKTCL cell lines to verify the clinical findings. IR expression was further assessed in NKTCL tumor biopsies using multiplex immunohistochemistry (mIHC). NKTCL patients have higher frequencies than HDs of inhibitory T regulatory cells (Tregs) and myeloid-derived suppressor cells (MDSCs). T-cell distribution also varies between NKTCL patients and HDs. T cells from NKTCL patients demonstrated higher expression levels of multiple IRs than HDs. Meanwhile, T-cell proliferation and interferon-γ production was significantly reduced in NKTCL patients. More importantly, the number of EBV-specific cytotoxic cells was lower in NTKCL patients, and these cells demonstrated upregulation of multiple IRs and secreted fewer effector cytokines. Interestingly, NKTCL cells caused normal PBMCs to acquire T-cell exhaustion phenotypes and induced generation of Tregs and MDSCs. In line with ex vivo finding, mIHC results showed that CD8+ T cells from NKTCL tumor biopsies expressed much higher level of IRs compared with reactive lymphoid hyperplasia individuals. The immune microenvironment of NKTCL patients exhibited T-cell dysfunction and accumulation of inhibitory cell components, which may contribute to impaired antitumor immunity.

Unveiling the interplay between mutational signatures and tumor microenvironment: a pan-cancer analysis

Background

While recent studies have separately explored mutational signatures and the tumor microenvironment (TME), there is limited research on the associations of both factors in a pan-cancer context.

Materials and methods

We performed a pan-cancer analysis of over 8,000 tumor samples from The Cancer Genome Atlas (TCGA) project. Machine learning methods were employed to systematically explore the relationship between mutational signatures and TME and develop a risk score based on TME-associated mutational signatures to predict patient survival outcomes. We also constructed an interaction model to explore how mutational signatures and TME interact and influence cancer prognosis.

Results

Our analysis revealed a varied association between mutational signatures and TME, with the Clock-like signature showing the most widespread influence. Risk scores based on mutational signatures mainly induced by Clock-like and AID/APOBEC activity exhibited strong pan-cancer survival stratification ability. We also propose a novel approach to predict transcriptome decomposed infiltration levels using genome-derived mutational signatures as an alternative approach for exploring TME cell types when transcriptome data are unavailable. Our comprehensive analysis revealed that certain mutational signatures and their interaction with immune cells significantly impact clinical outcomes in particular cancer types. For instance, T cell infiltration levels only served as a prognostic biomarker in melanoma patients with high ultraviolet radiation exposure, breast cancer patients with high homologous recombination deficiency signature, and lung adenocarcinoma patients with high tobacco-associated mutational signature.

Conclusion

Our study comprehensively explains the complex interplay between mutational signatures and immune infiltration in cancer. The results highlight the importance of considering both mutational signatures and immune phenotypes in cancer research and their significant implications for developing personalized cancer treatments and more effective immunotherapy.

MMP14 is a diagnostic gene of intrahepatic cholangiocarcinoma associated with immune cell infiltration

BACKGROUND

Intrahepatic cholangiocarcinoma (ICC) is a malignant tumor of the hepatobiliary system with concealed onset, strong invasiveness and poor prognosis.

AIM

To explore the disease characteristic genes that may be helpful in the diagnosis of ICC and affect immune cell infiltration.

METHODS

We downloaded two ICC-related human gene expression profiles from GEO database as the training group (GSE26566 and GSE32958 datasets) for difference analysis, and performed enrichment analysis on differential genes. The least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF), three machine learning algorithms, were used to screen the characteristic genes. Double verification was carried out on GSE107943 and The Cancer Genome Atlas, two verification groups. Receiver operating characteristic curve and area under the curve (AUC) were used to evaluate the diagnostic efficacy of genes for ICC. CIBERSORT and ssGSEA algorithms were used to evaluate the effect of characteristic genes on immune infiltration pattern. Human Protein Atlas (HPA) was used to analyze the protein expression level of the target gene.

RESULTS

A total of 1091 differential genes were obtained in the training group. Enrichment analysis showed that the above genes were mainly enriched in small molecular catabolism, complement and coagulation cascade, bile secretion and other functions and pathways. Twenty-five characteristic genes were screened by LASSO regression, 19 by SVM-RFE algorithm, and 30 by RF algorithm. Three algorithms were used in combination to determine the characteristic gene of ICC: MMP14. The verification group confirmed that the genes had a high diagnostic accuracy (AUC values of the training group and the verification group were 0.960, 0.999, and 0.977, respectively). Comprehensive analysis of immune infiltration showed that MMP14 could affect the infiltration of monocytes, activated memory CD4 T cells, resting memory CD4 T cells, and other immune cells, and was closely related to the expression of CD200, cytotoxic T-lymphocyte-associated antigen 4, CD14, CD44, and other immune checkpoints. The results of immunohistochemistry in HPA database showed was indeed overexpressed in ICC.

CONCLUSION

MMP14 can be used as a disease characteristic gene of ICC, and may regulate the distribution of immune-infiltrating cells in the ICC tumor microenvironment, which provides a new method for the determination of ICC diagnostic markers and screening of therapeutic targets.

A potential biological signature of 7-methylguanosine-related lncRNA to predict the immunotherapy effects in bladder cancer

Background

Bladder urothelial carcinoma (BLCA) is the second prevalent genitourinary carcinoma globally. N7-methylguanosine (m7G) is important for tumorigenesis and progression. This study aimed to build a predictive model for m7G-related long non-coding RNAs (lncRNAs), elucidate their role in the tumor immune microenvironment (TIME), and predict immunotherapy response in BLCA.

Methods

We first used univariate Cox regression and coexpression analyses to identify m7G-related lncRNAs. Next, the prognostic model was built by utilizing LASSO regression analysis. Then, the prognostic significance of the model was examined utilizing Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves, nomogram, and univariate, multivariate Cox regression. We also analyzed Gene set enrichment analyses (GSEA), immune analysis and principal component analysis (PCA) in risk groups. To further predict immunotherapy effectiveness, we evaluated the predictive ability for immunotherapy in 2 risk groups and clusters using tumor immune dysfunction and exclusion (TIDE) score and Immunophenoscore (IPS).

Results

Seven lncRNAs related to m7G were used to create a model. The calibration plots for the model suggested a strong fit with the prediction of overall survival (OS). The area under the curve (AUC) for first, second, and third years was respectively, 0.722, 0.711, and 0.686. In addition, the risk score had strong correlation with TIME features and genes linked to immune checkpoint blockade (ICB). TIDE scores were dramatically different between two risk groups (p < 0.05), and IPS scores were markedly different between two clusters (p < 0.05).

Conclusion

Our research constructed a novel m7G-related lncRNAs that could be used to predict patient outcomes and the effectiveness of immunotherapy in BLCA. Immunotherapy may be more effective for the low-risk group and cluster 2.

Chemotherapy-Sensitized In Situ Vaccination for Malignant Osteosarcoma Enabled by Bioinspired Calcium Phosphonate Nanoagents

How to effectively treat malignant osteosarcoma remains clinically challenging. Programmed delivery of chemotherapeutic agents and immunostimulants may offer a universal strategy for killing osteosarcoma cells while simultaneously eliciting in situ antitumor immunity. However, targeted chemoimmunotherapy lacks a reliable delivery system. To address this issue, we herein developed a bioinspired calcium phosphonate nanoagent that was synthesized by chemical reactions between Ca²⁺ and phosphonate residue from zoledronic acid using bovine serum albumin as a scaffold. In addition, methotrexate combination with a phosphorothioate CpG immunomodulator was also loaded for pH-responsive delivery to enable synergistic chemoimmunotherapy of osteosarcoma. The calcium phosphonate nanoagents were found to effectively accumulate in osteosarcoma for nearly 1 week, which is favorable for exerting the vaccination effects in situ by maturing dendritic cells and priming CD8⁺ T cells to suppress the osteosarcoma progression and pulmonary metastasis through controlled release of the three loaded agents in the acidic tumor microenvironment. The current study may thus offer a reliable delivery platform for achieving targeted chemotherapy-induced in situ antitumor immunity.

Nanomaterial-Based Antivascular Therapy in the Multimodal Treatment of Cancer

Abnormal tumor vasculature and a hypoxic tumor microenvironment (TME) limit the effectiveness of conventional cancer treatment. Recent studies have shown that antivascular strategies that focus on antagonizing the hypoxic TME and promoting vessel normalization effectively synergize to increase the antitumor efficacy of conventional therapeutic regimens. By integrating multiple therapeutic agents, well-designed nanomaterials exhibit great advantages in achieving higher drug delivery efficiency and can be used as multimodal therapy with reduced systemic toxicity. In this review, strategies for the nanomaterial-based administration of antivascular therapy combined with other common tumor treatments, including immunotherapy, chemotherapy, phototherapy, radiotherapy, and interventional therapy, are summarized. In particular, the administration of intravascular therapy and other therapies with the use of versatile nanodrugs is also described. This review provides a reference for the development of multifunctional nanotheranostic platforms for effective antivascular therapy in combined anticancer treatments.

Dissecting the roles and clinical potential of YY1 in the tumor microenvironment

Yin-Yang 1 (YY1) is a member of the GLI-Kruppel family of zinc finger proteins and plays a vital dual biological role in cancer as an oncogene or a tumor suppressor during tumorigenesis and tumor progression. The tumor microenvironment (TME) is identified as the “soil” of tumor that has a critical role in both tumor growth and metastasis. Many studies have found that YY1 is closely related to the remodeling and regulation of the TME. Herein, we reviewed the expression pattern of YY1 in tumors and summarized the function and mechanism of YY1 in regulating tumor angiogenesis, immune and metabolism. In addition, we discussed the potential value of YY1 in tumor diagnosis and treatment and provided a novel molecular strategy for the clinical diagnosis and treatment of tumors.