Characteristics of lymphocyte-infiltrating papillary thyroid cancer

BRAFV600E/pTERT double mutated papillary thyroid cancers exhibit immune gene suppression

Introduction

BRAFV600E mutation (BRAFmut) is common in papillary thyroid cancer (PTC), and most patients have an excellent outcome. However, a TERT-promoter mutation (pTERTmut) in the presence of BRAFmut (BRAFmutpTERTmut) has been demonstrated to confer a more aggressive behavior to PTC. Lymphocytic infiltration is often present in PTC. In this study, we sought to decipher the relationship between the BRAF and pTERT mutations and immune gene dysregulation in tumor samples from a cohort of 147 samples of PTC.

Methods

The abundance of 770 immune gene transcripts was determined by multiprex capture/detection and digital counting of mRNA transcripts using the NanoString nCounter® PanCancer Immune Profiling Panel.

Results

We identified 40 immune transcripts differentially expressed in BRAFmutpTERTmut vs BRAFmutpTERT wildtype (pTERTwt) (P<0.05). Transcripts induced by BRAFmut alone were significantly repressed in BRAFmutpTERTmut samples, such as genes expressed by lymphoid cells, antigen-presenting cells, and cytotoxic cells, including chemokines, cytokines, checkpoint control proteins, interferon downstream markers, TNF superfamily proteins and BMP markers. A validation analysis using 444 samples from The Cancer Genome Atlas (TCGA) PTC dataset yielded similar results. Deconvolution analysis confirmed differences in the immune cell populations such as increased presence of M2 macrophages in the BRAFmutpTERTmut Mayo cohort and a lower abundance of M1 macrophages in the BRAFmutpTERTmut TCGA cohort compared to BRAFmutpTERTwt. Most of the immune gene pathways were enriched in the BRAFmutpTERTwt tumors in both Mayo and TCGA cohorts but not in BRAFmutpTERTmut. BRAFmutpTERTwt had higher stromal lymphocytes infiltration as compared to BRAFwtpTERTwt tumors, corroborating the transcriptomic findings.

Discussion

To our knowledge this is the first report of a potential link between TERT and the immune microenvironment, offering an explanation for the aggressive nature of BRAFmutpTERTmut PTC.

Machine Vision-Detected Peritumoral Lymphocytic Aggregates Are Associated With Disease-Free Survival in Patients With Papillary Thyroid Carcinoma

Papillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer, with a disease recurrence rate of around 20%. Lymphoid formations, which occur in nonlymphoid tissues during chronic inflammatory, infectious, and immune responses, have been linked with tumor suppression. Lymphoid aggregates potentially enhance the body's antitumor response, offering an avenue for attracting tumor-infiltrating lymphocytes and fostering their coordination. Increasing evidence highlights the role of lymphoid aggregate density in managing tumor invasion and metastasis, with a favorable impact noted on overall and disease-free survival (DFS) across various cancer types. In this study, we present a machine vision model to predict recurrence in different histologic subtypes of PTC using measurements related to peritumoral lymphoid aggregate density. We demonstrated that quantifying peritumoral lymphocytic presence not only is associated with better prognosis but also, along with tumor-infiltrating lymphocytes within the tumor, adds additional prognostic value in the absence of well-known second mutations including TERT. Annotations of peritumoral lymphoid aggregates on 171 well-differentiated PTCs in the Cancer Genome Atlas Thyroid Carcinoma (TCGA-THCA) data set were used to train a deep-learning model to predict regions of lymphoid aggregates across the entire tissue. The fractional area of the tissue regions covered by these lymphocytes was dichotomized to determine the following 2 risk groups: a significant and low density of peritumoral lymphocytes. DFS prognosticated using these risk groups via the Kaplan-Meier analysis revealed a hazard ratio (HR) of 2.51 (95% CI: 2.36, 2.66), tested on 170 new patients also from the TCGA-THCA data set. The prognostic performance of peritumoral lymphocyte aggregate density was compared against the univariate Kaplan-Meier analysis of DFS using the fractional area of intratumoral lymphocytes within the primary tumor with an HR of 2.04 (95% CI: 1.89, 2.19). Combining the lymphocyte features in and around the tumor yielded a statistically significant improvement in prognostic performance (HR, 3.17 [95% CI: 3.02, 3.32]) on training and were independently evaluated against 62 patients outside TCGA-THCA with an HR of 2.44 (95% CI: 2.19, 2.69). Multivariable Cox regression analysis on the validation set revealed that the density of peritumoral and intratumoral lymphocytes was prognostic independent of histologic subtype with a concordance index of 0.815.

A novel computational pathology approach for identifying gene signatures prognostic of disease-free survival for papillary thyroid carcinomas

INTRODUCTION

Papillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer, with the classical and follicular variants representing most cases. Despite generally favorable prognoses, approximately 10% of patients experience recurrence post-surgery and radioactive iodine therapy. Attempts to stratify risk of recurrence have relied on gene expression-based prognostic and predictive signatures with a focus on mutations of well-known driver genes, while hallmarks of tumor morphology have been ignored.

OBJECTIVES

We introduce a new computational pathology approach to develop prognostic gene signatures for PTC that is informed by quantitative features of tumor and immune cell morphology.

METHODS

We quantified nuclear and immune-related features of tumor morphology to develop a pathomic signature, which was then used to inform an RNA-expression signature model provides a notable advancement in risk stratification compared to both standalone and pathology-informed gene-expression signatures.

RESULTS

There was a 17.8% improvement in the C-index (from 0.605 to 0.783) for 123 cPTCs and 15% (from 0.576 to 0.726) for 38 fvPTCs compared to the standalone gene-expression signature. Hazard ratios also improved for cPTCs from 0.89 (0.67,0.99) to 4.43 (3.65,6.68) and fvPTC from 0.98 (0.76,1.32) to 2.28 (1.87,3.64). We validated the image-based risk model on an independent cohort of 32 cPTCs with hazard ratio 1.8 (1.534,2.167).

Revolutionary multi-omics analysis revealing prognostic signature of thyroid cancer and subsequent in vitro validation of SNAI1 in mediating thyroid cancer progression through EMT

Thyroid carcinoma (TC), the most commonly diagnosed malignancy of the endocrine system, has witnessed a significant rise in incidence over the past few decades. The integration of scRNA-seq with other sequencing approaches offers researchers a distinct perspective to explore mechanisms underlying TC progression. Therefore, it is crucial to develop a prognostic model for TC patients by utilizing a multi-omics approach. We acquired and processed transcriptomic data from the TCGA-THCA dataset, including mRNA expression profiles, lncRNA expression profiles, miRNA expression profiles, methylation chip data, gene mutation data, and clinical data. We constructed a tumor-related risk model using machine learning methods and developed a consensus machine learning-driven signature (CMLS) for accurate and stable prediction of TC patient outcomes. 2 strains of undifferentiated TC cell lines and 1 strain of PTC cell line were utilized for in vitro validation. mRNA, protein levels of hub genes, epithelial-mesenchymal transition (EMT)-associated phenotypes were detected by a series of in vitro experiments. We identified 3 molecular subtypes of TC based on integrated multi-omics clustering algorithms, which were associated with overall survival and displayed distinct molecular features. We developed a CMLS based on 28 hub genes to predict patient outcomes, and demonstrated that CMLS outperformed other prognostic models. TC patients of relatively lower CMLS score had significantly higher levels of T cells, B cells, and macrophages, indicating an immune-activated state. Fibroblasts were predominantly enriched in the high CMLS group, along with markers associated with immune suppression and evasion. We identified several drugs that could be suitable for patients with high CMLS, including Staurosporine_1034, Rapamycin_1084, gemcitabine, and topotecan. SNAI1 was elevated in both undifferentiated TC cell lines, comparing to PTC cells. Knockdown of SNAI1 reduced the cell proliferation and EMT phenotypes of undifferentiated TC cells. Our findings highlight the importance of multi-omics analysis in understanding the molecular subtypes and immune characteristics of TC, and provide a novel prognostic model and potential therapeutic targets for this disease. Moreover, we identified SNAI1 in mediating TC progression through EMT in vitro.

Tumor microenvironment in thyroid cancer: Immune cells, patterns, and novel treatments

The tumor immune microenvironment of thyroid cancer is the heterogeneous histological space in which tumor cells coexist with host cells. Published data from this review were identified by search and selection database of Pubmed, Elsevier, and Science Direct. Searching was made in two steps using different keywords. In thyroid pathology, the inflammatory response is very important, and might have a key role finding new diagnostic and therapeutic methods, particularly in thyroid cancer. Different immune cells may be more or less present in different types of thyroid cancer and may even have different functions, hence the importance of knowing their presence in different thyroid tumor pathologies. Cancer-related inflammation could be a useful target for new diagnostic and therapeutic strategies by analyzing peritumoral and intratumoral immune cells in different types of thyroid tumors. Moreover, novel strategies for thyroid cancer treatments, such as monoclonal antibodies targeting checkpoint inhibitors, are emerging as promising alternatives.

Prognostic Roles of Inflammatory Biomarkers in Radioiodine-Refractory Thyroid Cancer Treated with Lenvatinib

BACKGRUOUND

Inflammatory biomarkers, such as the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR), serve as valuable prognostic indicators in various cancers. This multicenter, retrospective cohort study assessed the treatment outcomes of lenvatinib in 71 patients with radioactive iodine (RAI)-refractory thyroid cancer, considering the baseline inflammatory biomarkers.

METHODS

This study retrospectively included patients from five tertiary hospitals in Korea whose complete blood counts were available before lenvatinib treatment. Progression-free survival (PFS) and overall survival (OS) were evaluated based on the median value of inflammatory biomarkers.

RESULTS

No significant differences in baseline characteristics were observed among patients grouped according to the inflammatory biomarkers, except for older patients with a higher-than-median NLR (≥2) compared to their counterparts with a lower NLR (P= 0.01). Patients with a higher-than-median NLR had significantly shorter PFS (P=0.02) and OS (P=0.017) than those with a lower NLR. In multivariate analysis, a higher-than-median NLR was significantly associated with poor OS (hazard ratio, 3.0; 95% confidence interval, 1.24 to 7.29; P=0.015). However, neither the LMR nor the PLR was associated with PFS. A higher-than-median LMR (≥3.9) was significantly associated with prolonged OS compared to a lower LMR (P=0.036). In contrast, a higher-than-median PLR (≥142.1) was associated with shorter OS compared to a lower PLR (P=0.039).

CONCLUSION

Baseline inflammatory biomarkers can serve as predictive indicators of PFS and OS in patients with RAI-refractory thyroid cancer treated with lenvatinib.

Papillary Thyroid Carcinoma Landscape and Its Immunological Link With Hashimoto Thyroiditis at Single-Cell Resolution

The tumor microenvironment heterogeneity of papillary thyroid cancer (PTC) is poorly characterized. The relationship between PTC and Hashimoto thyroiditis (HT) is also in doubt. Here, we used single-cell RNA sequencing to map the transcriptome landscape of PTC from eight PTC patients, of which three were concurrent with HT. Predicted copy number variation in epithelial cells and mesenchymal cells revealed the distinct molecular signatures of carcinoma cells. Carcinoma cells demonstrated intertumoral heterogeneity based on BRAF V600E mutation or lymph node metastasis, and some altered genes were identified to be correlated with disease-free survival in The Cancer Genome Atlas datasets. In addition, transcription factor regulons of follicular epithelial cells unveil the different transcription activation state in PTC patients with or without concurrent HT. The immune cells in tumors exhibited distinct transcriptional states, and the presence of tumor-infiltrating B lymphocytes was predominantly linked to concurrent HT origin. Trajectory analysis of B cells and plasma cells suggested their migration potential from HT adjacent tissues to tumor tissues. Furthermore, we revealed diverse ligand–receptor pairs between non-immune cells, infiltrating myeloid cells, and lymphocytes. Our results provided a single-cell landscape of human PTC. These data would deepen the understanding of PTC, as well as the immunological link between PTC and HT.

Radio-Iodide Treatment: From Molecular Aspects to the Clinical View

Simple Summary

This year marks the 80th commemoration of the first time that radio-iodide treatment (RAI) was used. RAI is one of the most effective targeted internal radiation anticancer therapies ever devised and it has been used for many decades, however, a thorough understanding of the underlying molecular mechanisms involved could greatly improve the success of this therapy. This is an in-depth innovative review focusing on the molecular mechanisms underlying radio-iodide therapy in thyroid cancer and how the alteration of these mechanisms affects the results in the clinic.

Abstract

Thyroid radio-iodide therapy (RAI) is one of the oldest known and used targeted therapies. In thyroid cancer, it has been used for more than eight decades and is still being used to improve thyroid tumor treatment to eliminate remnants after thyroid surgery, and tumor metastases. Knowledge at the molecular level of the genes/proteins involved in the process has led to improvements in therapy, both from the point of view of when, how much, and how to use the therapy according to tumor type. The effectiveness of this therapy has spread into other types of targeted therapies, and this has made sodium/iodide symporter (NIS) one of the favorite theragnostic tools. Here we focus on describing the molecular mechanisms involved in radio-iodide therapy and how the alteration of these mechanisms in thyroid tumor progression affects the diagnosis and results of therapy in the clinic. We analyze basic questions when facing treatment, such as: (1) how the incorporation of radioiodine in normal, tumor, and metastatic thyroid cells occurs and how it is regulated; (2) the pros and cons of thyroid hormonal deprivation vs. recombinant human Thyroid Stimulating Hormone (rhTSH) in radioiodine residence time, treatment efficacy, thyroglobulin levels and organification, and its influence on diagnostic imaging tests and metastasis treatment; and (3) the effect of stunning and the possible causes. We discuss the possible incorporation of massive sequencing data into clinical practice, and we conclude with a socioeconomical and clinical vision of the above aspects.

Immune Cell Confrontation in the Papillary Thyroid Carcinoma Microenvironment

Background

Papillary thyroid cancer has been associated with chronic inflammation. A systematic understanding of immune cell infiltration in PTC is essential for subsequent immune research and new diagnostic and therapeutic strategies.

Methods

Three different algorithms, single-sample gene set enrichment analysis (ssGSEA), immune cell marker and CIBERSORT, were used to evaluate immune cell infiltration levels (abundance and proportion) in 10 data sets (The Cancer Genome Atlas [TCGA], GSE3467, GSE3678, GSE5364, GSE27155, GSE33630, GSE50901, GSE53157, GSE58545, and GSE60542; a total of 799 PTC and 194 normal thyroid samples). Consensus unsupervised clustering divided PTC patients into low-immunity and high-immunity groups. Weighted gene coexpression network analysis (WGCNA) and gene set enrichment analysis (GSEA) were used to analyze the potential mechanisms causing differences in the immune response.

Results

Compared with normal tissues, PTC tissues had a higher overall immune level and higher abundance levels and proportions of M2 macrophages, Tregs, monocytes, neutrophils, dendritic cells (DCs), mast cells (MCs), and M0 macrophages. Compared with early PTC, advanced PTC showed higher immune infiltration and higher abundance levels and proportions of M2 macrophages, Tregs, monocytes, neutrophils, DCs, MCs, and M0 macrophages. Compared to the low-immunity group, the high-immunity group exhibited more advanced stages, larger tumor sizes, greater lymph node metastases, higher tall-cell PTCs, lower follicular PTC proportions, more BRAF mutations, and fewer RAS mutations. Epstein-Barr virus (EBV) infection was the most significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway for key module genes.

Conclusions

In human PTC, M2 macrophages, Tregs, monocytes, neutrophils, DCs, MCs, and M0 macrophages appear to play a tumor-promoting role, while M1 macrophages, CD8+ T cells, B cells, NK cells, and T follicular helper (TFH) cells (including eosinophils, γδ T cells, and Th17 cells with weak supporting evidence) appear to play an antitumor role. During the occurrence and development of PTC, the overall immune level was increased, and the abundance and proportion of tumor-promoting immune cells were significantly increased, indicating that immune escape had been aggravated. Finally, we speculate that EBV may play an important role in changing the immune microenvironment of PTC tumors.

Immune and Inflammatory Cells in Thyroid Cancer Microenvironment

A hallmark of cancer is the ability of tumor cells to avoid immune destruction. Activated immune cells in tumor microenvironment (TME) secrete proinflammatory cytokines and chemokines which foster the proliferation of tumor cells. Specific antigens expressed by cancer cells are recognized by the main actors of immune response that are involved in their elimination (immunosurveillance). By the recruitment of immunosuppressive cells, decreasing the tumor immunogenicity, or through other immunosuppressive mechanisms, tumors can impair the host immune cells within the TME and escape their surveillance. Within the TME, cells of the innate (e.g., macrophages, mast cells, neutrophils) and the adaptive (e.g., lymphocytes) immune responses are interconnected with epithelial cancer cells, fibroblasts, and endothelial cells via cytokines, chemokines, and adipocytokines. The molecular pattern of cytokines and chemokines has a key role and could explain the involvement of the immune system in tumor initiation and progression. Thyroid cancer-related inflammation is an important target for diagnostic procedures and novel therapeutic strategies. Anticancer immunotherapy, especially immune checkpoint inhibitors, unleashes the immune system and activates cytotoxic lymphocytes to kill cancer cells. A better knowledge of the molecular and immunological characteristics of TME will allow novel and more effective immunotherapeutic strategies in advanced thyroid cancer.

Immune Gene Signature Delineates a Subclass of Papillary Thyroid Cancer with Unfavorable Clinical Outcomes

Papillary thyroid carcinoma (PTC) represents a heterogeneous disease with diverse clinical outcomes highlighting a need to identify robust biomarkers with clinical relevance. We applied non-negative matrix factorization-based deconvolution to publicly available gene expression profiles of thyroid cancers in the Cancer Genome Atlas (TCGA) consortium. Among three metagene signatures identified, two signatures were enriched in canonical BRAF-like and RAS-like thyroid cancers with up-regulation of genes involved in oxidative phosphorylation and cell adhesions, respectively. The third metagene signature representing up-regulation of immune-related genes further segregated BRAF-like and RAS-like PTCs into their respective subgroups of immunoreactive (IR) and immunodeficient (ID), respectively. BRAF-IR PTCs showed enrichment of tumor infiltrating immune cells, tall cell variant PTC, and shorter recurrence-free survival compared to BRAF-ID PTCs. RAS-IR and RAS-ID PTC subtypes included majority of normal thyroid tissues and follicular variant PTC, respectively. Immunopathological features of PTC subtypes such as immune cell fraction, repertoire of T cell receptors, cytolytic activity, and expression level of immune checkpoints such as and PD-L1 and CTLA-4 were consistently observed in two different cohorts. Taken together, an immune-related metagene signature can classify PTCs into four molecular subtypes, featuring the distinct histologic type, genetic and transcriptional alterations, and potential clinical significance.