Tumor microenvironment predicts local tumor extensiveness in PD-L1 positive nasopharyngeal cancer

Investigating Radiotherapy Effects on PD-L1 Expression in Circulating Tumor Cells: An Exploratory Study

INTRODUCTION

Circulating tumor cells (CTCs) and Programmed death-ligand 1 (PD-L1) play pivotal roles in cancer biology and therapy response. This exploratory study aimed to elucidate the influence of neoadjuvant radiotherapy on PD-L1 expression in tumor tissues and CTCs of patients with inoperable locally advanced breast cancer.

METHODS

We conducted a prospective cohort study at Universitas Andalas Hospital Padang from January to December 2022 with 27 patients. Biopsies and blood draws were executed before and after the tenth fractions of neoadjuvant radiotherapy. Following radiotherapy, CTCs were isolated using magnetic beads enrichment, followed by an RT-PCR analysis for PD-L1 expression. Correlations between PD-L1 expression and tumor response, evaluated via local response and RECIST criteria before and after radiotherapy breast CT scan, were examined using Fisher's exact and chi-square tests.

RESULTS

Our data revealed no significant alterations in PD-L1 expression in either tumor tissues or CTCs during radiotherapy (p=0.848 for tissue, p=0.548 for CTCs). Notably, PD-L1 expression in tumor tissue before treatment was significantly associated with RECIST (p=0.021), while other correlations with local response and RECIST were not statistically significant.

CONCLUSION

The study implies radiotherapy may not significantly influence PD-L1 expression in tumor tissue and CTCs. However, pre-treatment PD-L1 expression in tumor tissue correlates with RECIST criteria. These findings highlight the need for additional, comprehensive studies to elucidate further the interplay between PD-L1, CTCs, and radiotherapy response.

Cold Tumour Phenotype Explained Through Whole Genome Sequencing in Clinical Nasopharyngeal Cancer: A Preliminary Study

Introduction

Nasopharyngeal cancer (NPC) is a complex cancer due to its unique genomic features and association with the Epstein-Barr virus (EBV). Despite therapeutic advancements, NPC prognosis remains poor, necessitating a deeper understanding of its genomics. Here, we present a comprehensive whole genome sequencing (WGS) view of NPC genomics and its correlation with the phenotype.

Methods

This study involved WGS of a clinical NPC biopsy specimen. Sequencing was carried out using a long read sequencer from Oxford Nanopore. Analysis of the variants involved correlation with the phenotype of NPC.

Results

A loss of genes within chromosome 6 from copy number variation (CNV) was found. The lost genes included HLA-A, HLA-B, and HLA-C, which work in the antigen presentation process. This loss of the major histocompatibility complex (MHC) apparatus resulted in the tumour's ability to evade immune recognition. The tumour exhibited an immunologically "cold" phenotype, with mild tumour-infiltrating lymphocytes, supporting the possible etiology of loss of antigen presentation capability. Furthermore, the driver mutation PIK3CA gene was identified along with various other gene variants affecting numerous signaling pathways.

Discussion

Comprehensive WGS was able to detect various mutations and genomic losses, which could explain tumour progression and immune evasion ability. Furthermore, the study identified the loss of other genes related to cancer and immune pathways, emphasizing the complexity of NPC genomics. In conclusion, this study underscores the significance of MHC class I gene loss and its probable correlation with the cold tumour phenotype observed in NPC.

Deciphering Driver of Nasopharyngeal Cancer Development

A great deal of progress has been made on understanding nasopharyngeal cancer in recent decades. Genomic, transcriptomic, and proteomic studies have enabled us to gain a deeper understanding on the biology of nasopharyngeal cancer, and though this new information is elaborate and detailed, an overall picture of the driver of nasopharyngeal cancer that includes all this information is lacking. This review will focus on providing a broad overview, with plausible and simple language, on nasopharyngeal carcinogenesis based on current updated information. This will help readers to gain a broad understanding, which may be necessary to provide common ground for further research on nasopharyngeal cancer.

Immune cells markers within local tumor microenvironment are associated with EBV oncoprotein in nasopharyngeal cancer

Introduction

EBV infection in nasopharyngeal cancer ensued in latent infection mode. In this latent infection various EBV oncoproteins such as EBNA1 and LMP1 was expressed. EBV oncoproteins could theoretically recruit immune cells, which might help to control cancer. Therefore, this study was aimed to elucidate the association with EBV oncoproteins (EBNA1 and LMP1), immune markers (CD4, CD8, and FOXP3) from nasopharyngeal cancer microenvironment with tumor progression.

Method

Nasopharyngeal biopsy was obtained from patients suspected to have nasopharyngeal cancer. Those samples with microscopically confirmed nasopharyngeal cancer were tested for EBNA1, LMP1, CD4, CD8, and FOXP3 concentration with ELISA, then verified with IHC. Each patient tumor volume was assessed for primary nasopharyngeal tumor volume (GTVp) and neck nodal metastases tumor volume (GTVn). Correlation test with Spearman correlation and scatterplot were carried out.

Result

Total 23 samples with nasopharyngeal cancer were analyzed. There was moderate correlation (ρ = 0.45; p value = 0.032) between LMP1 and GTVp. There was strong correlation (ρ = 0.81; p value < 0.001) between CD8 and GTVp. There was also moderate correlation (ρ = 0.6; p value = 0.002) between FOXP3 and GTVp. The CD8 concentration has moderate correlation with both EBNA1 (ρ = 0.46; p value = 0.026) and LMP1 (ρ = 0.47; p value = 0.023). While FOXP3 has moderate correlation with only LMP1 (ρ = 0.58; p value = 0.004). No correlation was found between all the markers tested here with GTVn.

Discussion

We found larger primary nasopharyngeal tumor was associated with higher CD8 marker. This was thought due to the presence of abundance CD8 T cells in the nasopharynx, but those abundance CD8 T cells were suspected to be dysfunctional. The nasopharyngeal cancer was also known to upregulate chemokines that could recruit T regulatory FOXP3 cells. Furthermore, T regulatory FOXP3 cells differentiation was induced through several pathways which was triggered by EBNA1. The correlation found in this study could guide further study to understand nasopharyngeal carcinogenesis and the relationship with our immune system.

A novel multifunctional anti-PD-L1-CD16a-IL15 induces potent cancer cell killing in PD-L1-positive tumour cells

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Anti-PD-L1 single-domain antibodies were identified from hPD-L1-immunized camels.

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Three novel multifunctional antibodies, anti-PD-L1-CD16a, anti-PD-L1-IL15, and anti-PD-L1-CD16a-IL15, target PD-L1-positive cancer cells.

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Anti-PD-L1-IL15 and anti-PD-L1-CD16a-IL15, but not anti-PD-L1-CD16a, stimulate immune cell proliferation in vitro.

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The anti-PD-L1 antibodies can bind PD-L1-positive cells.

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Anti-PD-L1-CD16a-IL15 has the strongest antitumour activity, both in vitro and in vivo.

Cancer is the most acute disease and the leading cause of patient death worldwide. Both chemotherapy and molecular-based therapies play an important role in curing cancer. However, the median and overall survival of patients is poor. To date, immune therapies have changed the treatment methods for cancer patients. Programmed death ligand 1 (PD-L1, also known as B-H1, CD274) is a well-studied tumor antigen. PD-L1 is overexpressed in colon cancer, lung cancer, and so on and plays a vital role in cancer development. In this study, anti-PD-L1 single-domain antibodies were identified from recombinant human PD-L1 (rhPD-L1)-immunized llamas. Then, we generated a novel multifunctional anti-PD-L1-CD16a-IL15 antibody targeting PD-L1-positive tumor cells. Anti-PD-L1-CD16a-IL15 was constructed by linking the Interleukin-2 (IL-2) signal peptide, anti-PD-L1 single domain antibody (anti-PD-L1-VHH) and anti-cluster of differentiation 16a single domain antibody (anti-CD16a-VHH), and Interleukin-15/Interleukin-15 receptor alpha (IL15/IL-15Rα). This anti-PD-L1-CD16a-IL15 fusion protein can be expressed and purified from HEK-293F cells. In vitro, our data showed that the anti-PD-L1-CD16a-IL15 fusion protein can recruit T cells and drive natural killer cells (NK) with specific killing of PD-L1-overexpressing tumor cells. Furthermore, in the xenograft model, the anti-PD-L1-CD16a-IL15 fusion protein inhibited tumor growth with human peripheral blood mononuclear cells (PBMCs). These data suggested that the anti-PD-L1-CD16a-IL15 fusion protein has a latent function in antitumour activity, with better guidance for future cancer immunotherapy.

Epstein–Barr Virus (EBV) Viral Load in Tumor Cells Did Not Predict Tumor Extensiveness in Nasopharyngeal Cancer

Background: Nasopharyngeal cancer is commonly associated with Epstein–Barr virus (EBV) infection, especially undifferentiated non-keratinized histology. EBV DNA quantification through nasopharyngeal brushing was previously reported to be not related to disease stage. This study aimed to reinvestigate the relationship of EBV viral load in tumor tissue with tumor extensiveness by more accurate EBV DNA quantification through microscopically confirmed tumor cells from nasopharyngeal biopsy. Method: The specimens for EBV DNA quantification were derived from histopathology slides which were pre-treated following the QIAsymphony® SP protocol for tissue DNA extraction. Then, the extracted DNA underwent real-time polymerase chain reaction (RT-PCR) using the artus® EBV RG PCR Kit for EBV DNA quantification. The tumor volume was determined by delineating the gross tumor based on 3D imaging of the patient’s nasopharynx. Result: Twenty-four subjects were included in this study. All subjects were stage III and above, with more males (75%) than females. EBV viral load in tumor cells was found to have no correlation to tumor volume both in local and nodal regions. The median local tumor volume was 81.3 cm3 ± 80 cm3. The median EBV viral load in tumor cells was 95,644.8 ± 224,758.4 copies/100 ng of DNA. The median nodal or regional tumor volume was 35.7 ± 73.63 cm3. Conclusion: EBV viral load from tumor cells from nasopharyngeal biopsy has no relationship with tumor extensiveness in nasopharyngeal cancer. The presence and amount of EBV in tumor cells did not translate into larger or smaller tumors. The EBV viral proteins and RNAs were perhaps more likely to confer some prognostic information due to the fact that those molecules were related to carcinogenesis.

Tackling Resistance to Cancer Immunotherapy: What Do We Know?

Cancer treatment has evolved tremendously in the last few decades. Immunotherapy has been considered to be the forth pillar in cancer treatment in addition to conventional surgery, radiotherapy, and chemotherapy. Though immunotherapy has resulted in impressive response, it is generally limited to a small subset of patients. Understanding the mechanisms of resistance toward cancer immunotherapy may shed new light to counter that resistance. In this review, we highlighted and summarized two major hurdles (recognition and attack) of cancer elimination by the immune system. The mechanisms of failure of some available immunotherapy strategies were also described. Moreover, the significance role of immune compartment for various established cancer treatments were also elucidated in this review. Then, the mechanisms of combinatorial treatment of various conventional cancer treatment with immunotherapy were discussed. Finally, a strategy to improve immune cancer killing by characterizing cancer immune landscape, then devising treatment based on that cancer immune landscape was put forward.

Bioinformatics profiling integrating a four immune-related long non-coding RNAs signature as a prognostic model for papillary renal cell carcinoma

Background: Papillary renal cell carcinoma (pRCC) was the 2^nd most common subtype, accounting for approximately 15% incidence of renal cell carcinoma (RCC). Immune related long non-coding RNAs (IR-lncRs) plentiful in immune cells and immune microenvironment (IME) are potential in evaluating prognosis and assessing the effects of immunotherapy. A completed and meaningful IR-lncRs analysis based on abundant pRCC gene samples from The Cancer Genome Atlas (TCGA) will provide insight in this field.

Results: 17 IR-lncRs were selected by Pearson correlation analysis of immune score and the lncRNA expression level, and 5 sIRlncRs were significantly correlated with the OS of pRCC patients. 4 sIRlncRs (AP001267.3, AC026471.3, SNHG16 and ADAMTS9-AS1) with the most remarkable prognostic values were identified to establish the IRRS model and the OS of the low-risk group was longer than that in the high-risk group. The IRRS was certified as an independent prognosis factor and correlated with the OS. The high-risk group and low-risk group showed significantly different distributions and immune status through PCA and GSEA. In addition, we further found the expression levels of SNHG16 was remarkably enhanced in female patients with more advanced T-stages, but ADAMTS9-AS1 showed the opposite results.

Conclusion: The IRRS model based on the identified 4 sIRlncRs showed the significant values on forecasting prognoses of pRCC patients, with the longer OS in the low-risk group.

Methods: We integrated the expression profiles of LncRNA and overall survival (OS) in the 322 pRCC patients based on the TCGA dataset. The immune scores calculated on account of the expression level of immune-related genes were used to verify the most relevant IR-lncRs. Survival-related IR-lncRs (sIRlncRs) were estimated by COX regression analysis in pRCC patients. The high-risk group and low-risk group were identified by the median immune-related risk score (IRRS) model established by the screened sIRlncRs. Functional annotation was displayed by gene set enrichment analysis (GSEA) and principal component analysis (PCA), and the immune composition and purity of the tumor were evaluated through microenvironment cell count records. The expression levels of sIRlncRs of pRCC samples were verified by real-time quantitative PCR.