Hyperion imaging system reveals heterogeneous tumor microenvironment of oral squamous cell carcinoma patients at T1N0M0 stage

[Application value of whole exon sequencing and immune related indicators in the precision treatment of oral squamous cell carcinoma]

OBJECTIVE

To explore the significance and feasibility of whole exon sequencing and immune related indexes in personalized precision treatment of oral squamous cell carcinoma (OSCC).

METHODS

We retrospectively screened the patients who underwent surgery for oral cancer in Peking University Hospital of Stomatology and underwent genetic and immune biomarkers tests between January 2021 and June 2022. Combined with the clinicopathological characteristics of patients, potential targeted drugs and immunotherapy drugs were screened to evaluate the possibility of gene testing benefiting OSCC. The main evaluation indicators included the number of gene mutations, combined positive score (CPS), tumor mutation burden (TMB), microsatellite sequence status and human leukocyte antigen B (HLA-B) locus. Excel was used for statistical analysis.

RESULTS

A total of 10 patients were enrolled and 9 were included in this study, including 6 males and 3 females, with an average age of (55.44±9.59) years. The tumor location was buccal (5 cases), tongue (3 cases) and gingival (1 case). The results of genetic testing showed that 3 (33.3%) patients had no gene mutations in the tumor tissue, 5 (55.6%) patients had unique TP53 gene mutations, and 1 (11.1%) patient had TP53 and CHEK1 mutations. However, no drugs were available for targeted therapy of the mutated genes. The genetic tumor gene testing results showed that no genetic tumor gene was found in all the patients, suggesting that OSCC had a low possibi-lity of hereditary tumor. In terms of immune efficacy related markers, CPS test results showed that 8 patients had CPS≥1. TMB detection results showed that the median value of TMB value was 0.72 mutations/Mb, and the range was 0 to 4.32 mutations/Mb. The negative and positive control results of microsatellite sequence status were consistent, indicating that all the tumor tissues detected were microsatellite stability. The results of HLA-B detection showed that only one patient had B62 gene mutation, suggesting that the B44 and B62 related genotypes of HLA-B in OSCC tissue samples were low.

CONCLUSION

The present results do not support the wide application and promotion of genetic testing and immune related indexes in OSCC.

A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer

Intratumor heterogeneity associates with poor patient outcome. Stromal stiffening also accompanies cancer. Whether cancers demonstrate stiffness heterogeneity, and if this is linked to tumor cell heterogeneity remains unclear. We developed a method to measure the stiffness heterogeneity in human breast tumors that quantifies the stromal stiffness each cell experiences and permits visual registration with biomarkers of tumor progression. We present Spatially Transformed Inferential Force Map (STIFMap) which exploits computer vision to precisely automate atomic force microscopy (AFM) indentation combined with a trained convolutional neural network to predict stromal elasticity with micron-resolution using collagen morphological features and ground truth AFM data. We registered high-elasticity regions within human breast tumors colocalizing with markers of mechanical activation and an epithelial-to-mesenchymal transition (EMT). The findings highlight the utility of STIFMap to assess mechanical heterogeneity of human tumors across length scales from single cells to whole tissues and implicates stromal stiffness in tumor cell heterogeneity.

Bioinformatics based exploration of hsa-miR-194-5p regulation of CHD4 through PI3K/AKT signal pathway to enhance tumor resistance to apoptosis due to loss of nests and participate in poor prognosis of oral squamous cell carcinoma

Background

Recent evidence shows that CHD4 is involved in a variety of biological events of tumors. Our aim was to investigate the correlation between CHD4 and oral squamous cell carcinoma (OSCC).

Methods

After CHD4 was screened as a differentially expressed gene in The Cancer Genome Atlas (TGCA) database, the correlations of its expression level with the clinical parameters and prognosis of patients with OSCC were analyzed. The outcomes of the multivariate analysis were used to construct a nomogram, and the accuracy of the model was evaluated with the calibration curve. The GeneMANIA and STRING databases were used to generate network diagrams depicting interactions of genes with CHD4, and heat maps of genes co-expressed with CHD4 were generated using the TCGA database. TargetScan was then used to look into the miRNAs that interact with the 3' untranslated region of CHD4 mRNA. Finally, GSEA enrichment analysis was used to explore the possible mechanism.

Results

The differentially expressed molecule CHD4 was screened by TCGA database for OSCC. CHD4 was overexpressed in OSCC tumor tissues, and OSCC patients with low expression of CHD4 have better OS and DSS. The nomogram had a C-index of 0.575 (0.548-0.602), which indicated some degree of predictive reliability. CHD4 has certain correlation with exons of OSCC related genes, including TP53, NOTCH1, CASP8, PTEN, TP63, ANXA1, CDH1, CTNNB1, GDF15 and EGFR. According to the TargetScan database, hsa-miR-194-5p is the miRNA that regulates CHD4 upstream the most. GSEA analysis showed that CHD4 may participate in the poor prognosis of OSCC by participating in PI3K/AKT pathway, protein adhesion regulation, MAPK pathway, cytokine and inflammatory response regulation, angiogenesis and platelet regulation.

Conclusions

The decreased expression of CHD4 may indicate a better prognosis in OSCC patients and could serve as a novel predictive biomarker for OSCC. Also, hsa-miR-194-5p was found to contribute to the poor prognosis of OSCC by regulating CHD4 and enhancing tumor anoikis resistance via the PI3K/AKT signaling pathway. These findings suggest that CHD4 might be a therapeutic target for the effective treatment of OSCC.

The Role of Pathology-Based Methods in Qualitative and Quantitative Approaches to Cancer Immunotherapy

Simple Summary

Immunotherapy has become the filar of modern oncological treatment, and programmed death-ligand 1 expression is one of the primary immune markers assessed by pathologists. However, there are still some issues concerning the evaluation of the marker and limited information about the interaction between the tumour and associated immune cells. Recent studies have focused on cancer immunology to try to understand the complex tumour microenvironment, and multiplex imaging methods are more widely used for this purpose. The presented article aims to provide an overall review of a different multiplex in situ method using spectral imaging, supported by automated image-acquisition and software-assisted marker visualisation and interpretation. Multiplex imaging methods could improve the current understanding of complex tumour-microenvironment immunology and could probably help to better match patients to appropriate treatment regimens.

Abstract

Immune checkpoint inhibitors, including those concerning programmed cell death 1 (PD-1) and its ligand (PD-L1), have revolutionised the cancer therapy approach in the past decade. However, not all patients benefit from immunotherapy equally. The prediction of patient response to this type of therapy is mainly based on conventional immunohistochemistry, which is limited by intraobserver variability, semiquantitative assessment, or single-marker-per-slide evaluation. Multiplex imaging techniques and digital image analysis are powerful tools that could overcome some issues concerning tumour-microenvironment studies. This novel approach to biomarker assessment offers a better understanding of the complicated interactions between tumour cells and their environment. Multiplex labelling enables the detection of multiple markers simultaneously and the exploration of their spatial organisation. Evaluating a variety of immune cell phenotypes and differentiating their subpopulations is possible while preserving tissue histology in most cases. Multiplexing supported by digital pathology could allow pathologists to visualise and understand every cell in a single tissue slide and provide meaning in a complex tumour-microenvironment contexture. This review aims to provide an overview of the different multiplex imaging methods and their application in PD-L1 biomarker assessment. Moreover, we discuss digital imaging techniques, with a focus on slide scanners and software.

An overview of multiplexed analyses of CAR T-cell therapies: insights and potential

INTRODUCTION

Cancer immunotherapy is a rapidly growing field with exponential advancement in engineered immune cell-based therapies. For instance, an engineered chimeric antigen receptor (CAR) can be introduced in T-cells or other immune cells and adoptively transferred to target and kill cancer cells in hematologic malignancies or solid tumors. The first CAR-T-cell (CAR-T) therapy has been developed against CD19, a B-cell marker expressed on lymphoma and lymphoblastic leukemia. To allow for personalized treatment, proteomics approaches could provide insights into biomarkers for CAR-T therapy efficacy and toxicity.

AREAS COVERED

We researched the most recent technology methods of biomarker evaluation used in the laboratory and clinical setting. Publications of CAR-T biomarkers were then systematically reviewed to provide a narrative of the most validated biomarkers of CAR-T efficacy and toxicity. Examples of biomarkers include CAR-T functionality and phenotype as well as interleukin-6 and other cytokines.

EXPERT COMMENTARY

Biomarkers of CAR-T efficacy and toxicity have been identified, but still need to be validated and standardized across institutions. Moreover, few are used in the clinical setting due to limitations in real-time technology. Expansion of biomarker research could provide better understanding of patient response and risk of life-threatening side effects with potential for improved precision medicine.

The Pandora's box of novel technologies that may revolutionize lung cancer

Non-small cell lung cancer (NSCLC) is one of the most common cancers globally and has a 5-year survival rate ~20%. Immunotherapies have demonstrated long-term and durable responses in NSCLC patients, although they appear to be effective in only a subset of patients. A more comprehensive understanding of the underlying tumour biology may contribute to identifying those patients likely to achieve optimal outcomes. Profiling the tumour microenvironment (TME) has shown to be beneficial in addressing fundamental tumour-immune cell interactions. Advances in multiplexing immunohistochemistry and molecular barcoding has led to recent advances in profiling genes and proteins in NSCLC. Here, we review the recent advancements in spatial profiling technologies for the analysis of NSCLC tissue samples to gain new insights and therapeutic options for NSCLC. The combination of spatial transcriptomics combined with advanced imaging is likely to lead to deep insights into NSCLC tissue biology, which can be a powerful tool to predict likelihood of response to therapy.

Hyperion Image Analysis Depicts a Preliminary Landscape of Tumor Immune Microenvironment in OSCC with Lymph Node Metastasis

Background

Oral squamous cell carcinoma (OSCC) constitutes the most common types of oral cancer. Because its prognosis varies significantly, identification of a tumor immune microenvironment could be a critical tool for treatment planning and predicting a more accurate prognosis. This study is aimed at utilizing the Hyperion imaging system to depict a preliminary landscape of the tumor immune microenvironment in OSCC with lymph node metastasis.

Methods

We collected neoplasm samples from OSCC patients. Their formalin-fixed, paraffin-embedded (FFPE) tissue sections were obtained and stained utilizing a panel of 26 clinically relevant metal-conjugated antibodies. Detection and analysis were performed for these stained cells with the Hyperion imaging system.

Results

Four patients met our inclusion criteria. We depicted a preliminary landscape of their tumor immune microenvironment and identified 25 distinct immune cell subsets from these OSCC patients based on phenotypic similarity. All these patients had decreased expression of CD8⁺ T cells in tumor specimens. Variety in cell subsets was seen, and more immune activated cells were found in patient A and patient B than those in patient C and patient D. Such differences in tumor immune microenvironments can contribute to forecasting of individual prognoses.

Conclusion

The Hyperion imaging system helped to delineate a preliminary and multidimensional landscape of the tumor immune microenvironment in OSCC with lymph node metastasis and provided insights into the influence of the immune microenvironment in determination of prognoses. These results reveal possible contributory factors behind different prognoses of OSCC patients with lymph node metastasis and provide reference for individual treatment planning.

Targeting Neuroinflammation in Brain Cancer: Uncovering Mechanisms, Pharmacological Targets, and Neuropharmaceutical Developments

Gliomas are one of the most lethal types of cancers accounting for ∼80% of all central nervous system (CNS) primary malignancies. Among gliomas, glioblastomas (GBM) are the most aggressive, characterized by a median patient survival of fewer than 15  months. Recent molecular characterization studies uncovered the genetic signatures and methylation status of gliomas and correlate these with clinical prognosis. The most relevant molecular characteristics for the new glioma classification are IDH mutation, chromosome 1p/19q deletion, histone mutations, and other genetic parameters such as ATRX loss, TP53, and TERT mutations, as well as DNA methylation levels. Similar to other solid tumors, glioma progression is impacted by the complex interactions between the tumor cells and immune cells within the tumor microenvironment. The immune system’s response to cancer can impact the glioma’s survival, proliferation, and invasiveness. Salient characteristics of gliomas include enhanced vascularization, stimulation of a hypoxic tumor microenvironment, increased oxidative stress, and an immune suppressive milieu. These processes promote the neuro-inflammatory tumor microenvironment which can lead to the loss of blood-brain barrier (BBB) integrity. The consequences of a compromised BBB are deleteriously exposing the brain to potentially harmful concentrations of substances from the peripheral circulation, adversely affecting neuronal signaling, and abnormal immune cell infiltration; all of which can lead to disruption of brain homeostasis. In this review, we first describe the unique features of inflammation in CNS tumors. We then discuss the mechanisms of tumor-initiating neuro-inflammatory microenvironment and its impact on tumor invasion and progression. Finally, we also discuss potential pharmacological interventions that can be used to target neuro-inflammation in gliomas.

High Dimensional Imaging Mass Cytometry Panel to Visualize the Tumor Immune Microenvironment Contexture

The integrative analysis of tumor immune microenvironment (TiME) components, their interactions and their microanatomical distribution is mandatory to better understand tumor progression. Imaging Mass Cytometry (IMC) is a high dimensional tissue imaging system which allows the comprehensive and multiparametric in situ exploration of tumor microenvironments at a single cell level. We describe here the design of a 39-antibody IMC panel for the staining of formalin-fixed paraffin-embedded human tumor sections. We also provide an optimized staining procedure and details of the experimental workflow. This panel deciphers the nature of immune cells, their functions and their interactions with tumor cells and cancer-associated fibroblasts as well as with other TiME structural components known to be associated with tumor progression like nerve fibers and tumor extracellular matrix proteins. This panel represents a valuable innovative and powerful tool for fundamental and clinical studies that could be used for the identification of prognostic biomarkers and mechanisms of resistance to current immunotherapies.