Development of a prediction model for radiotherapy response among patients with head and neck squamous cell carcinoma based on the tumor immune microenvironment and hypoxia signature

Identification of PATL1 as a prognostic and immunotherapeutic predictive factor for nasal-type natural killer/T-cell lymphoma and head and neck squamous cell carcinoma

This research examines the function of protein associated with topoisomerase II homolog 1 (PATL1) in nasal-type natural killer/T-cell lymphoma (NKTCL) and head and neck squamous cell carcinoma (HNSCC). We analyzed bulk RNA-seq data from NKTCL, nasal polyps, and normal nasal mucosa, identifying 439 differentially expressed genes. Machine learning algorithms highlighted PATL1 as a hub gene. PATL1 exhibited significant upregulation in NKTCL and HNSCC tumor samples in comparison to normal tissues, showing high diagnostic accuracy (AUC = 1.000) for NKTCL. Further analysis of local hospital data identified PATL1 as an independent prognostic risk factor for NKTCL. Data analysis of TCGA and GEO datasets revealed that high PATL1 expression correlated with poorer prognosis in HNSCC patients (p < 0.05). We also constructed a PATL1-based nomogram, which emerged as an independent prognostic predictor for HNSCC after addressing missing values. Additionally, we found a strong correlation between PATL1 and various immune cell infiltrates (e.g., activated.CD4 T cell), and a significant association with the expression of 37 immune checkpoints genes (e.g., CTLA4, PDCD1) and 20 N6-methyladenosine-related genes (e.g., ZC3H13, METTL3) (all p < 0.05). Both TCIA and TIDE algorithms suggested that PATL1 could potentially predict immunotherapy efficacy (p < 0.05). Cellular experiments demonstrated that transfection with a silencing plasmid of PATL1 significantly inhibited the malignant behaviors of SNK6 and FaDu cell lines(p < 0.05). In conclusion, our findings suggest that PATL1 may serve as a valuable prognostic and predictive biomarker in NKTCL and HNSCC, highlighting its significant role in these cancers.

Type I conventional dendritic cells and CD8+ T cells predict favorable clinical outcome of head and neck squamous cell carcinoma patients

Head and neck squamous cell carcinoma (HNSCC) is one of the most common tumor entities worldwide, with human papillomavirus (HPV) infection contributing to cancer development. Conventional therapies achieve only limited efficiency, especially in recurrent or metastatic HNSCC. As the immune landscape decisively impacts the survival of patients and treatment efficacy, this study comprehensively investigated the immunological tumor microenvironment (TME) and its association with patient outcome, with special focus on several dendritic cell (DC) and T lymphocyte subpopulations. Therefore, formalin-fixed paraffin-embedded tumor samples of 56 HNSCC patients, who have undergone resection and adjuvant radiotherapy, were analyzed by multiplex immunohistochemistry focusing on the detailed phenotypic characterization and spatial distribution of DCs, CD8+ T cells, and T-helper cell subsets in different tumor compartments. Immune cell densities and proportions were correlated with clinical characteristics of the whole HNSCC cohort and different HPV- or hypoxia-associated subcohorts. Tumor stroma was highly infiltrated by plasmacytoid DCs and T lymphocytes. Among the T-helper cells and CD8+ T cells, stromal regulatory T cells and intraepithelial exhausted CD8+ T cells expressing programmed cell death protein-1 (PD-1+) and/or lymphocyte-activation gene-3 (LAG-3+) were the predominant phenotypes, indicating an immunosuppressive TME. HPV-associated tumors showed significantly higher infiltration of type I and type II conventional DCs (cDC1, cDC2) as well as several CD8+ T cell phenotypes including exhausted, activated, and proliferating T cells. On the contrary, tumors with hypoxia-associated gene signatures exhibited reduced infiltration for these immune cells. By multivariate Cox regression, immune-related prognostic factors were identified. Patient clusters defined by high infiltration of DCs and T lymphocytes combined with HPV positivity or low hypoxia showed significantly prolonged survival. Thereby, cDC1 and CD8+ T cells emerged as independent prognostic factors for local and distant recurrence. These results might contribute to the implementation of an immune cell infiltration score predicting HNSCC patients' survival and such patient stratification might improve the design of future individualized radiochemo-(immuno)therapies.

Exploring the frontiers: tumor immune microenvironment and immunotherapy in head and neck squamous cell carcinoma

The global prevalence of head and neck malignancies positions them as the sixth most common form of cancer, with the head and neck squamous cell carcinoma (HNSCC) representing the predominant histological subtype. Despite advancements in multidisciplinary approaches and molecular targeted therapies, the therapeutic outcomes for HNSCC have only marginally improved, particularly in cases of recurrent or metastatic HNSCC (R/MHNSCC). This situation underscores the critical necessity for the development of innovative therapeutic strategies. Such strategies are essential not only to enhance the efficacy of HNSCC treatment but also to minimize the incidence of associated complications, thus improving overall patient prognosis. Cancer immunotherapy represents a cutting-edge cancer treatment that leverages the immune system for targeting and destroying cancer cells. It's applied to multiple cancers, including melanoma and lung cancer, offering precision, adaptability, and the potential for long-lasting remission through immune memory. It is observed that while HNSCC patients responsive to immunotherapy often experience prolonged therapeutic benefits, only a limited subset demonstrates such responsiveness. Additionally, significant clinical challenges remain, including the development of resistance to immunotherapy. The biological characteristics, dynamic inhibitory changes, and heterogeneity of the tumor microenvironment (TME) in HNSCC play critical roles in its pathogenesis, immune evasion, and therapeutic resistance. This review aims to elucidate the functions and mechanisms of anti-tumor immune cells and extracellular components within the HNSCC TME. It also introduces several immunosuppressive agents commonly utilized in HNSCC immunotherapy, examines factors influencing the effectiveness of these treatments, and provides a comprehensive summary of immunotherapeutic strategies relevant to HNSCC.

Gradient Tumor Microenvironment-Promoted Penetrating Micelles for Hypoxia Relief and Immunosuppression Reversion in Pancreatic Cancer Treatment

The tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC) is the main block for the penetration of chemotherapy. In the tumor microenvironment, a dense matrix composed of fibrin is formed on the exterior, while the interior is featured by high reduction, hypoxia and low pH. How to match the special microenvironment to on-demand drug release is the key to improve chemotherapeutic efficacy. Herein, a microenvironment-responsive micellar system is developed to deepen tumoral penetration. Briefly, the conjugation of a fibrin-targeting peptide to PEG-poly amino acid has been utilized to achieve accumulation of micelles in the tumor stroma. By modification of micelles with hypoxia-reducible nitroimidazole which becomes protonated under acidic conditions, their surface charge is more positive, facilitating deeper penetration into tumors. Paclitaxel was loaded onto the micelles via a disulfide bond to enable glutathione (GSH)-responsive release. Therefore, the immunosuppressive microenvironment is relived through the alleviation of hypoxia and depletion of GSH. Hopefully, this work could establish paradigms by designing sophisticated drug-delivery systems to tactfully employ and retroact the tamed tumoral microenvironment to improve the therapeutic efficacy based on understanding the multiple hallmarks and learning the mutual regulation. STATEMENT OF SIGNIFICANCE: : Tumor microenvironment(TME) is an unique pathological feature of pancreatic cancer and an inherent barrier to chemotherapy. Numerous studies regard TME as the targets for drug delivery. In this work, we propose a hypoxia-responsive nanomicellar drug delivery system that aiming hypoxia TME of pancreatic cancer. The nanodrug delivery system could respond to the hypoxic microenvironment and enhance the penetration of the inner tumor at the same time preserving the outer tumor stroma, thus achieving targeted treatment of PDAC by preserving the integrity of the outer stroma. Simultaneously, the responsive group can reverse the degree of hypoxia in TME by disrupting the redox balance in the tumor region, thus achieving precise treatment of PDAC by matching the pathological characteristics of TME. We believe our article would provide new design ideas for the future treatments for pancreatic cancer.

Downregulation of zinc finger protein 71 in laryngeal squamous cell carcinoma tissues and its potential molecular mechanism and clinical significance: a study based on immunohistochemistry staining and data mining

Background

The molecular mechanism of laryngeal squamous cell carcinoma (LSCC) is not completely clear, which leads to poor prognosis and treatment difficulties for LSCC patients. To date, no study has reported the exact expression level of zinc finger protein 71 (ZNF71) and its molecular mechanism in LSCC.

Methods

In-house immunohistochemistry (IHC) staining (33 LSCC samples and 29 non-LSCC samples) was utilized in analyzing the protein expression level of ZNF71 in LSCC. Gene chips and high-throughput sequencing data collected from multiple public resources (313 LSCC samples and 192 non-LSCC samples) were utilized in analyzing the exact mRNA expression level of ZNF71 in LSCC. Single-cell RNA sequencing (scRNA-seq) data was used to explore the expression status of ZNF71 in different LSCC subpopulations. Enrichment analysis of ZNF71, its positively and differentially co-expressed genes (PDCEGs), and its downstream target genes was employed to detect the potential molecular mechanism of ZNF71 in LSCC. Moreover, we conducted correlation analysis between ZNF71 expression and immune infiltration.

Results

ZNF71 was downregulated at the protein level (area under the curve [AUC] = 0.93, p < 0.0001) and the mRNA level (AUC = 0.71, p = 0.023) in LSCC tissues. Patients with nodal metastasis had lower protein expression level of ZNF71 than patients without nodal metastasis (p < 0.05), and male LSCC patients had lower mRNA expression level of ZNF71 than female LSCC patients (p < 0.01). ZNF71 was absent in different LSCC subpopulations, including cancer cells, plasma cells, and tumor-infiltrated immune cells, based on scRNA-seq analysis. Enrichment analysis showed that ZNF71 and its PDCEGs may influence the progression of LSCC by regulating downstream target genes of ZNF71. These downstream target genes of ZNF71 were mainly enriched in tight junctions. Moreover, downregulation of ZNF71 may influence the development and even therapy of LSCC by reducing immune infiltration.

Conclusion

Downregulation of ZNF71 may promote the progression of LSCC by reducing tight junctions and immune infiltration; this requires further study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02823-8.

A novel hypoxia- and lactate metabolism-related signature to predict prognosis and immunotherapy responses for breast cancer by integrating machine learning and bioinformatic analyses

Background

Breast cancer is the most common cancer worldwide. Hypoxia and lactate metabolism are hallmarks of cancer. This study aimed to construct a novel hypoxia- and lactate metabolism-related gene signature to predict the survival, immune microenvironment, and treatment response of breast cancer patients.

Methods

RNA-seq and clinical data of breast cancer from The Cancer Genome Atlas database and Gene Expression Omnibus were downloaded. Hypoxia- and lactate metabolism-related genes were collected from publicly available data sources. The differentially expressed genes were identified using the “edgeR” R package. Univariate Cox regression, random survival forest (RSF), and stepwise multivariate Cox regression analyses were performed to construct the hypoxia-lactate metabolism-related prognostic model (HLMRPM). Further analyses, including functional enrichment, ESTIMATE, CIBERSORTx, Immune Cell Abundance Identifier (ImmuCellAI), TIDE, immunophenoscore (IPS), pRRophetic, and CellMiner, were performed to analyze immune status and treatment responses.

Results

We identified 181 differentially expressed hypoxia-lactate metabolism-related genes (HLMRGs), 24 of which were valuable prognostic genes. Using RSF and stepwise multivariate Cox regression analysis, five HLMRGs were included to establish the HLMRPM. According to the medium-risk score, patients were divided into high- and low-risk groups. Patients in the high-risk group had a worse prognosis than those in the low-risk group (P &lt; 0.05). A nomogram was further built to predict overall survival (OS). Functional enrichment analyses showed that the low-risk group was enriched with immune-related pathways, such as antigen processing and presentation and cytokine-cytokine receptor interaction, whereas the high-risk group was enriched in mTOR and Wnt signaling pathways. CIBERSORTx and ImmuCellAI showed that the low-risk group had abundant anti-tumor immune cells, whereas in the high-risk group, immunosuppressive cells were dominant. Independent immunotherapy datasets (IMvigor210 and GSE78220), TIDE, IPS and pRRophetic analyses revealed that the low-risk group responded better to common immunotherapy and chemotherapy drugs.

Conclusions

We constructed a novel prognostic signature combining lactate metabolism and hypoxia to predict OS, immune status, and treatment response of patients with breast cancer, providing a viewpoint for individualized treatment.

Development of a prediction model for radiotherapy response among patients with head and neck squamous cell carcinoma based on the tumor immune microenvironment and hypoxia signature

INTRODUCTION

The immune system and hypoxia are major factors influencing radiosensitivity in patients with different cancer types. This study aimed at developing a model to predict radiotherapy response in patients with head and neck squamous cell carcinoma (HNSCC) based on the tumor immune microenvironment and hypoxia signature.

MATERIALS AND METHODS

We first evaluated the hypoxia status and tumor immune microenvironment in the Cancer Genome Atlas (TCGA) cohort by using transcriptomic data. Differentially expressed genes (DEGs) were identified between the "high immunity and low hypoxia" and "low immunity and high hypoxia" groups and those DEGs significantly associated with disease-specific survival in the univariate Cox regression analysis were selected as the prognostic DEGs. We selected the immune hypoxia-related genes (IHRGs) by intersecting prognostic DEGs with immune and hypoxia gene sets. We used the IHRGs to train a multivariate Cox regression model in the TCGA cohort, based on which we calculated the IHRG prognostic index (IHRGPI) for each patient and validated its efficacy in predicting radiotherapy response in the Gene Expression Omnibus cohorts. Furthermore, we explored potential mechanisms and effective combinational treatment strategies for different IHRGPI groups.

RESULTS

Five IHRGs were used to construct the IHRGPI, which was used to dichotomize the cohorts. The patients with lower IHRGPI showed a better radiotherapy response across different cohorts and endpoints, including overall survival, progression-free survival, and recurrence-free survival (p < 0.05). Patients with higher IHRGPI showed greater hypoxia and lesser immune cell infiltration. A lower IHRGPI indicated a better immunotherapy response, while a higher IHRGPI indicated a better chemotherapy response.

CONCLUSIONS

IHRGPI is promising for predicting radiotherapy response and guiding combinational treatment strategies in patients with HNSCC.

A novel necroptosis-related LncRNA signature for prediction of prognosis and therapeutic responses of head and neck squamous cell carcinoma

Background: Long non-coding RNAs (lncRNAs) play an essential role in the occurrence and prognosis of tumors, and it has great potential as biomarkers of tumors. However, the roles of Necroptosis-related lncRNA (NRLs) in Head and neck squamous cell carcinoma (HNSCC) remain elusive. Methods: We comprehensively analyzed the gene expression and clinical information of 964 HNSCC in four cohorts. LASSO regression was utilized to construct a necroptosis-related lncRNA prognosis signature (NLPS). We used univariate and multivariate regression to assess the independent prognostic value of NLPS. Based on the optimal cut-off, patients were divided into high- and low-risk groups. In addition, the immune profile, multi-omics alteration, and pharmacological landscape of NLPS were further revealed. Results: A total of 21 NRLs associated with survival were identified by univariate regression in four cohorts. We constructed and validated a best prognostic model (NLPS). Compared to the low-risk group, patients in the high group demonstrated a more dismal prognosis. After adjusting for clinical features by multivariate analysis, NLPS still displayed independent prognostic value. Additionally, further analysis found that patients in the low-risk group showed more abundant immune cell infiltration and immunotherapy response. In contrast, patients in the high-risk group were more sensitive to multiple chemotherapeutic agents. Conclusion: As a promising tool, the establishment of NLPS provides guidance and assistance in the clinical management and personalized treatment of HNSCC.

Identification of the alpha linolenic acid metabolism-related signature associated with prognosis and the immune microenvironment in nasopharyngeal carcinoma

BACKGROUND

Tumor metabolism is important for cancer progression. Nevertheless, the role of the metabolism pathway and related molecules in nasopharyngeal carcinoma (NPC) is limited.

METHODS

Open-accessed data was downloaded from The Cancer Genome Atlas database. All the analysis was performed using the R software and the package in R environments.

RESULTS

In our study, we firstly explored the role of 21 metabolism-related pathways in NPC patients. We found that the steroid biosynthesis and biosynthesis of unsaturated fatty acids were risk factors, while the alpha linolenic acid metabolism was a protective factor. Then, the alpha linolenic acid metabolism aroused our interest. A total of 128 differentially expressed genes (DEGs) were identified, including 71 downregulated and 57 upregulated genes identified between high and low alpha linolenic acid metabolism level. Based on these DEGs, we constructed a prognosis model including DEFB4B, FOXL2NB, MDGA2, RTL1, SLURP2, TMEM151B and TSPAN19, which showed great prediction efficiency in both training and validation cohorts. Clinical correlation analysis showed that high-risk patients might have worse clinical pathology parameters. Pathway enrichment analysis showed that riskscore was positively correlated with angiogenesis, DNA repair, G2/M checkpoints, IL6/JAK/STAT3 signaling, KRAS signaling up, WNT beta-catenin signaling, PI3K/AKT/mTOR signaling, yet positively correlated with inflammatory response, xenobiotic metabolism, TNF-α signaling via NFKB and interferon-gamma response. Immune infiltration analysis showed that the riskscore was positively correlated with the M2 and M0 macrophages, but negatively correlated with neutrophils, plasma cells, follicular helper T cells and resting dendritic cells Moreover, we found that the low-risk patients might be more sensitive to immunotherapy and lapatinib.

CONCLUSIONS

In all, our study identified the genes associated with alpha linolenic acid metabolism and constructed an effective prognosis model which could robustly predict NPC patients prognosis.