Infiltration of B cell may underlie the contrary sex- and age-related biological behavior of papillary thyroid carcinoma

doi:10.21203/rs.3.rs-3217113/v1

Download PDF

Research Article

Infiltration of B cell may underlie the contrary sex- and age-related biological behavior of papillary thyroid carcinoma

https://doi.org/10.21203/rs.3.rs-3217113/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background and purpose

Sex and age play complex and contrary roles in the pathogenesis, lymph node metastasis (LNM), and prognosis of papillary thyroid carcinoma (PTC). This study aimed to explore the underlying mechanism of this phenomenon.

Method

The risk factors for LNM were explored by combining local data and the Surveillance, Epidemiology, and End Results (SEER) database of PTC. The gene expression information of 497 samples from The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) was used to explore the differentially expressed genes (DEGs) among different phenotypes. The single-cell RNA sequencing (scRNA-seq) data obtained from the Gene Expression Omnibus (GEO) database was used to explore the aimed gene expression in specific cell types. The flow cytometry was used to explore peripheral lymphocyte subsets in PTC.

Results

The clinical data showed that the younger age and the male sex were the risk factors for LNM (P < 0.05). In the bulk gene analysis, the age- and sex-related DEGs in contrary trends between different tissues and LNM state were two intersection genes:TCL1A and CR2. The analysis of scRNA-seq from the GEO database showed that the genes TCL1A and CR2 were mainly expressed in B cells, and the infiltration of B cells varied among different tissues. The peripheral blood lymphocyte subsets showed that the composition of circulating lymphocytes was different in different lymph node metastasis states and age levels.

Conclusion

The infiltration of TCL1A and CR2 related B cells for different ages and sexes might explain the contradictory biological behavior, including tumor pathogenesis, LNM, and prognosis of PTC.

papillary thyroid carcinoma

lymph nodes metastasis

gender

age

immunemicroenvironment

Papillary thyroid carcinoma (PTC) has become one of the most common malignant endocrine tumors, the incidence of which has increased worldwide in recent years(Kitahara and Sosa 2016; La Vecchia, et al. 2015). The incidence rate of PTC has a strong bias in women. Also, elderly people still comprise a high-incidence group, although a large number of young people have been reported with thyroid cancer in recent years (Cui, et al. 2021; Kilfoy, et al. 2009). Papillary thyroid carcinoma has a high rate of lymph node metastasis (LNM), which is an important aggressive marker and prognostic indicator of the tumor (Adam, et al. 2015; Ho, et al. 2021). Many studies explored the risk of LNM in PTC, most of which pointed out younger age and male sex as risk factors (Hu, et al. 2022; Tan, et al. 2022). In addition, our previous study (Yan, et al. 2022) found that the risk factors of LNM were different in different age backgrounds. Moreover, male patients showed more invasive clinical features, such as vascular and capsule invasion and invasive pathological subtypes, than female patients(Gajowiec, et al. 2021; Zahedi, et al. 2020). Thyroid cancer has a better prognosis in young and female patients, especially in premenopausal women, the advantage of which is weakened after menopause (Jonklaas, et al. 2012; Zhang, et al. 2018). However, the internal mechanism underlying such contradictory results is still unclear.

Although the prognosis of thyroid cancer in an early stage is satisfactory (Banerjee, et al. 2014), some patients still die from metastatic advanced cancer. Some tumors are resistant to the treatment with radioactive iodine (¹³¹I), and only a few are sensitive to the targeted treatment (Chen, et al. 2020; Rajoria, et al. 2012; Schlumberger, et al. 2015). Therefore, more information is needed to explore the biological behavior of PTC. This study aimed to combine the clinical data and public gene expression database and discover the mechanisms of tumor pathogenesis and LNM in PTC.

2.1 Clinical data

A total of 2070 patients diagnosed with PTC from 2014 to 2023 were enrolled. This study obtained informed consent from the patients and passed the ethical review of the Declaration of Helsinki. In our center, all patients diagnosed with PTC underwent routine prophylactic central compartment lymph node dissection, and all pathological results were obtained separately by two experienced pathologists. All included patients was initial thyroid cancer surgery and with a completed personal and surgical information. Then, 368 patients was performed flow cytometry analysis to label lymphocyte subsets in peripheral blood. In addition, 17,738 patients with PTC were screened from the Surveillance, Epidemiology, and End Results (SEER) database diagnosed from 2006 to 2015 using the same criteria.

2.2 Public data of gene expression

We downloaded the bulk gene expression data and clinical data of PTC from the TCGA database UCSC (https://xenabrowser.net/) and deleted the cases without LNM information. Further, 497 cases with complete age and sex information were selected, and the included genes were normally detected in at least 75% of participants. scRNA-seq data were extracted from the Gene Expression Omnibus (GEO) dataset (GSE184362)(Pu, et al. 2021), and the quality control was performed according to the standard Seurat process.

2.3 Statistical analysis and immune infiltration evaluation

The SPSS 22.0 software was used for analyzing the statistical data. The continuous measurement data were expressed as ‾x ± S, and a chi-square test was performed for single-factor analysis. A P value < 0.05 indicated a statistically significant difference. The DEGs from the TCGA database were screened using the "DESeq2" package in R 4.2.2 software. The DEGs were defined as the average gene expression ratio and two times the standard deviation, with P < 0.05. We evaluated the correlations between genes and immune infiltration using TIMER2.0. The GENEMANIA was used to construct the collaborative gene-to-gene relationship.

3.1 Clinical data and single-factor analysis of LNM

We set the cutoff age at 45 years, which was in line with the AJCC 7th edition and a starting point for menopause. Based on the clinical features, all 2070 participants in the local database were divided as follows: 556 were men and 1514 were women, with a male-to-female ratio of 1:2.72. The age range was 18–89 years, and the average age was 45 years. Further, 1052 were younger than 45 years, and 1018 were older than 45 years. Also, 907 (44%) participants did not have LNM, and 1163 (56%) had LNM. In the SEER database, 4356 were men and 13,882 were women, with a male-to-female ratio of 1:3.19. The age range was 18–95; 7716 were younger than 45 years, and 10,112 were older than 45 years. Further, 10,053 (57%) participants did not have LNM, and 7635 (43%) had LNM (Table 1).

Table 1

Predictive factors for LNM in patients with PTC in the chi-square analysis
	Local database
Parameter	LNM (+) (n = 1163)	LNM (–) (n = 907)	P	OR (95% CI)
Age(year)			0.000	1.91 (1.61–2.28)
༜45	673	379
≥ 45	490	528
Sex			0.000	1.91 (1.56–2.34)
Male	375	181
Female	788	726
	SEER database
Parameter	CLNM (+) (n = 7,635)	CLNM (–) (n = 10,053)	P	OR (95% CI)
Age(year)			0.000	1.48 (1.40–1.57)
༜45	3,741	3,975
≥ 45	3,894	6,128
Sex			0.000	2.18 (2.04–2.34)
Male	2,508	1,848
Female	5,127	8,255

The chi-square analysis revealed that the male sex [odds ratio (OR) = 1.91, 95% confidence interval (CI): 1.56–2.34; P < 0.05] and the younger age (OR = 1.91, 95% CI: 1.61–2.28; P < 0.05) were the risk factors for LNM in the local database. We achieved a similar conclusion in the SEER database that the male sex (OR = 1.48, 95% CI: 1.40–1.57; P < 0.05) and the younger age (OR = 2.18, 95% CI: 2.04–2.34; P < 0.05) were the risk factors for LNM (Table 1).

3.2 TCGA bulk gene expression and DEGs

Among the 497 samples, 444 were tumor tissues and 53 were para-tumor tissues. All participants were divided into different groups according to the different tissue sources, LNM, sex, and age. The baseline for the analysis was established by considering nonmetastasis of lymph nodes, female sex, younger age, and normal tissues. Genes were defined as upregulated, downregulated, and unchanged in different groups according to the definition of DEGs. Volcano maps were used to visualize these DEGs (Fig. 1), and the DEGs of four groups were constituted into Venn maps by intersecting genes (Fig. 2a-c). A total of 14 intersection age-and-sex-related genes were found, and 12 of them with the same trends between different tissues and LNM state(Fig. 2d). At the same time, only two age-and-sex-related genes with the contrary trends between different tissues and LNM state were :TCL1A and CR. These two genes were upregulated in para-tumor tissues, tumors with LNM, female and younger subgroups. What’s more, there were 187 genes with the same regulate trends between different tissues and LNM state, but 15 genes with the opposite trends(Fig. 2e).

3.3 TIMER and GENEMANIA

We explored TCL1A and CR2 in TIMER 2.0 Web Tools, which was used to evaluate the correlation between different genes and immune cell infiltration. TCL1A had a moderate correlation with CD8+ (cor = 0.47, p < 0.05), and dendritic cells (cor = 0.57, P < 0.05). At the same time, CR2 had a weaker correlation with CD8+ (cor = 0.33, P < 0.05), and dendritic cells (cor = 0.35, P < 0.05). We explored the correlation between the expression of TCL1A and CR2 and found a weak correlation (cor = 0.27, P < 0.05) (Fig. 3a-c). In GENEMANIA Web Tools, which was used to construct the interaction network among aimed proteins, we explored the relationship among the opposite regulate trend genes between lymph node metastasis and normal-tumor tissues groups (Fig. 3d-e).

3.4 GEO database of single-cell RNA sequencing

We obtained the scRNA-seq data of 23 samples from the GSE184362 and extracted tumor and para-tumor tissues, which were divided into four subgroups according to LNM: tumor tissues with LNM; para-tumor tissues with LNM; tumor tissues without LNM; and para-tumor tissues without lymph node metastasis. Based on the expression of marker genes, we assorted all cells into the following groups: thyroid cells (TG, TPO, and TSHR), T cells (CD3D and CD3E), B cells (CD79A and CD79B), and other undefined cells. We found that the expression of TCL1A and CR2 was higher in para-tumor tissues than in tumor tissues (Fig. 4, a vs b and c vs d); also, the expression was higher in tissues with LNM than in tissues without LNM (Fig. 5, a vs c and b vs d). Based on the marker genes, we labeled the cell cluster and found that TCL1A and CR2 were mainly expressed in the B cell (CD79A and CD79B) population (Fig. 5).

we extracted the subsets of B cells by marker genes CD79A and CD79B from a para-tumor tissue with lymph node metastasis and divided to the TCL1A-Related-cell and TCL1A-Non-Related-cell. Based on the stage-specific genes of B-cell development, we formed a pseudotime analysis map and a TCL1A gene expression map, and listed the stage-specific genes(CD74 and MS4A1) expression information (Fig. 6).

3.5 Peripheral blood lymphocyte subpopulation

We sampled the peripheral blood of 368 cases of PTC for lymphocyte subsets classification. According to the complement on the surface of lymphocyte, the cells were divided into (CD3+/CD4 + T lymphocytes; CD3+/CD8 + T lymphocytes; CD19 + B lymphocytes), and were calculated by its ratios. Our research found that in different lymph node metastasis states and different age levels the percent of CD3+/CD8 + cells and the ratio of CD3+/CD4 + to CD3+/CD8 + in peripheral blood were significantly different (P < 0.05), and show that there were a higher percent of CD3+/CD8 + in the subgroup with lymph node metastasis and the younger ones(Fig. 7).

Previous studies reported that age and sex had an opposite influence on the biological behavior of tumor pathogenesis, LNM, and long-term survival time of PTC (Rahbari, et al. 2010; Suteau, et al. 2021). Some studies speculated that this contradictory behavior originated from the difference in hormone levels and immune status in different sexes and ages. In women, the levels of estrogen and its receptor reached a peak value in reproductive age and then decreased with the advent of menopause (Caini, et al. 2015; Liu, et al. 2014; Rubio, et al. 2018). Moreover, estrogen and its receptors play an important role in autoimmune diseases, including Hashimoto's thyroiditis, which frequently occurs in women, especially in childbearing age (Doukas, et al. 2013; Khan and Ahmed 2016; Moulton 2018). Some studies found that Hashimoto's thyroiditis was a risk factor for PTC (Antonelli, et al. 2015; Noureldine and Tufano 2015). However, our previous study found that Hashimoto's thyroiditis was a protective factor for LNM in young groups (Yan, et al. 2022), which has been confirmed in several other studies (Kim, et al. 2011; Wang, et al. 2022). Some studies found that PTC with Hashimoto's thyroiditis as a background had a better prognosis (Lun, et al. 2013). Immune cell infiltration, including T and B cells, is an important component of autoimmunity. The changes in the immune microenvironment cause tumor pathogenesis, and the metastasis of lymph nodes varies in different sexes and ages.

In our study, LNM was more likely to occur in male and younger patients, which was consistent with other studies (Hu, et al. 2022; Tan, et al. 2022). In addition, we found TCL1A and CR2 with contrary trends between normal and tumor tissues and LNM, which might explain the reason why the biological behavior of thyroid tumors was contradictory in different ages and sexes. The scRNA-seq analysis showed that TCL1A and CR2 were mainly expressed in B lymphocytes and differed in different tissues, which strengthened the evidence of the influence of immunity on thyroid cancer. B cells play an important role in autoimmune diseases, not only by producing antibodies to participate in autoimmune reactions but also by secreting cytokines and chemokines to recruit T cells (Luu, et al. 2014). In addition, some marker proteins were expressed during the maturation of B cells, and were used to identify different subtypes; the dysfunction of B cells led to changes in autoimmune tolerance (Jiang, et al. 2020; Kang, et al. 2021).

TCL1A is a proto-oncogene, physiologically, which is only expressed in embryonic tissues and pre-mature B cells or early-T cells (Teitell 2005), and is overexpressed in some T cell or B cell lymphomas and epithelial solid tumors (Stachelscheid, et al. 2021). Some studies pointed out that TCL1A participated in the NANOG–TCL1A–Akt pathway (Lee, et al. 2015; Noh, et al. 2012; Song, et al. 2020), leading to epithelial–mesenchymal transition, tumor proliferation, and immune escape. The high expression of TCL1A was related to the LNM in breast cancer and the poorer prognosis in colon cancer (Li, et al. 2017; Srour, et al. 2020). However, a study on cervical cancer showed that the high expression of TCL1A in B cells was associated with an improved survival time (Punt, et al. 2015). Our study found that the infiltration of B cells related to TCL1A expression was significantly higher in para-tumor tissues and tissues with LNM than in corresponding tumor tissues and tissues without LNM. Previous studies found that the expression of TCL1A was downregulated during the maturation process and silenced in terminally differentiated B cells (Stachelscheid, et al. 2021). On the contrary, TCL1A participated in the conversion of T and B lymphocytes by changing the expression of proinflammatory cytokines and chemokines, which promoted the development of autoimmune diseases (Ho, et al. 2017). Also, the expression of TCL1A in lymphocytes was induced by estrogen, which depended on single-nucleotide polymorphism (Ho, et al. 2016). The regulation and imbalance of TCL1A were modified by various transcription and translation processes.

CR2 is a transmembrane glycoprotein expressed by mature B cells and dendritic follicular cells (Hannan 2016). It acts as a complement receptor to bind C3d and cooperate with BCR and then participates in complement-induced immune response (Bower and Ross 2006). In mice, the expression of CR2 lowers the activation threshold of B cells and significantly enhances the humoral immune response (Carroll and Isenman 2012). In human beings, the binding of BCR and CR2 is dose dependent and inhibits the activation of B cells under a weak stimulation of BCR (Kovacs, et al. 2021). In addition, CR2 regulates the tolerance of B cells and participates in autoimmunity. The expression of CR2 is reduced in patients with rheumatoid arthritis and systemic lupus erythematosus compared with healthy individuals (Asokan, et al. 2013; Asokan, et al. 2006; Prokopec, et al. 2010). In tumor immunity, CR2 can combine with the Fc receptor to assist in receptor-mediated tumor killing (Imai, et al. 2007).

Our study found that young and female patients had more TCL1A- and CR2-related B cell infiltration in para-tumor tissues and tissues with LNM than in tumor and nonmetastatic tissues. We explored whether LNM activates the tumor immune system by recruiting more lymphocytes. The influence of immune factors on the biological behavior of thyroid cancer has been confirmed, but the mechanism and pathway are complex and vague. Some studies on the single-cell RNA sequencing of thyroid cancer found different patterns of immune infiltration in thyroid cancer (Pan, et al. 2021), which affected the pathogenesis and metastasis of thyroid cancer. In addition, our study found a different proportion of CD3 + / CD8 + lymphocytes in peripheral blood with different lymph node states, which may help to evaluate the lymph node metastasis status before surgery. Our study supplemented this view on the dynamic changes in age and sex, and provided a direction for the natural evolution of thyroid cancer.

Our findings might help understand the role of sex and age in tumor pathogenesis and LNM of PTC, which is related to the expression of TCL1A and CR2 in B cells. The results enriched our knowledge of immune factors in PTC. However, our study was a single-center study, and hence the findings require further validation. Also, our study was conducted only on the transcription level. Hence, further proteomics research may help in obtaining more realistic results.

The infiltration of TCL1A and CR2 related B cells for different ages and sexes might explain the contradictory biological behavior, including tumor pathogenesis, LNM, and prognosis of PTC.

Funding

No foundation supported.

Disclosure

The authors declare no conflict of interest.

Author Contributions

CG-Y, JJ-S and XH-H contributed to the conception and design of the study. CG-Y, CY-L, and LN-J organized the database. CG-Y performed the statistical analyses, wrote the first draft of the manuscript, and wrote sections of the manuscript. All authors contributed to manuscript revision and read and approved the submitted version. All authors contributed to the article and approved the submitted version.

Data availability

The datasets generated during and/or analyzed during the study are available from the corresponding author.

Acknowledgments

I would like to express my special thanks to my partners for the encouragement and support they gave me during my study.

Adam MA, Pura J, Goffredo P, Dinan MA, Reed SD, Scheri RP, Hyslop T, Roman SA & Sosa JA 2015 Presence and Number of Lymph Node Metastases Are Associated With Compromised Survival for Patients Younger Than Age 45 Years With Papillary Thyroid Cancer. Journal of Clinical Oncology 33 2370-U2366.https://doi.org/10.1200/jco.2014.59.8391
Antonelli A, Ferrari SM, Corrado A, Di Domenicantonio A & Fallahi P 2015 Autoimmune thyroid disorders. Autoimmunity Reviews 14 174-180.https://doi.org/10.1016/j.autrev.2014.10.016
Asokan R, Banda NK, Szakonyi G, Chen XS & Holers VM 2013 Human complement receptor 2 (CR2/CD21) as a receptor for DNA: implications for its roles in the immune response and the pathogenesis of systemic lupus erythematosus (SLE). Mol Immunol 53 99-110.https://doi.org/10.1016/j.molimm.2012.07.002
Asokan R, Hua J, Young KA, Gould HJ, Hannan JP, Kraus DM, Szakonyi G, Grundy GJ, Chen XS, Crow MK, et al. 2006 Characterization of human complement receptor type 2 (CR2/CD21) as a receptor for IFN-alpha: a potential role in systemic lupus erythematosus. J Immunol 177 383-394.https://doi.org/10.4049/jimmunol.177.1.383
Banerjee M, Muenz DG, Worden FP, Wong SL & Haymart MR 2014 Conditional survival in patients with thyroid cancer. Thyroid 24 1784-1789.https://doi.org/10.1089/thy.2014.0264
Bower JF & Ross TM 2006 A minimum CR2 binding domain of C3D enhances immunity following vaccination. In Current Topics in Complement, pp 249-264. Ed JD Lambris.
Caini S, Gibelli B, Palli D, Saieva C, Ruscica M & Gandini S 2015 Menstrual and reproductive history and use of exogenous sex hormones and risk of thyroid cancer among women: a meta-analysis of prospective studies. Cancer Causes & Control 26 511-518.https://doi.org/10.1007/s10552-015-0546-z
Carroll MC & Isenman DE 2012 Regulation of humoral immunity by complement. Immunity 37 199-207.https://doi.org/10.1016/j.immuni.2012.08.002
Chen J, Ji Q, Bai C, Zheng X, Zhang Y, Shi F, Li X, Tang P, Xu Z, Huang R, et al. 2020 Surufatinib in Chinese Patients with Locally Advanced or Metastatic Differentiated Thyroid Cancer and Medullary Thyroid Cancer: A Multicenter, Open-Label, Phase II Trial. Thyroid 30 1245-1253.https://doi.org/10.1089/thy.2019.0453
Cui Y, Mubarik S, Li R, Nawsherwan & Yu C 2021 Trend dynamics of thyroid cancer incidence among China and the U.S. adult population from 1990 to 2017: a joinpoint and age-period-cohort analysis. BMC Public Health 21 624.https://doi.org/10.1186/s12889-021-10635-w
Doukas C, Saltiki K, Mantzou A, Cimponeriu A, Terzidis K, Sarika L, Mavrikakis M, Sfikakis P & Alevizaki M 2013 Hormonal parameters and sex hormone receptor gene polymorphisms in men with autoimmune diseases. Rheumatology International 33 575-582.https://doi.org/10.1007/s00296-012-2386-4
Gajowiec A, Chromik A, Furga K, Skuza A, Gasior-Perczak D, Walczyk A, Palyga I, Trybek T, Mikina E, Szymonek M, et al. 2021 Is Male Sex A Prognostic Factor in Papillary Thyroid Cancer? J Clin Med 10.https://doi.org/10.3390/jcm10112438
Hannan JP 2016 The Structure-Function Relationships of Complement Receptor Type 2 (CR2; CD21). Current Protein & Peptide Science 17 463-487.https://doi.org/10.2174/1389203717666151201192124
Ho AS, Luu M, Shafqat I, Mallen-St Clair J, Chen MM, Chen Y, Jain M, Ali N, Patio C, Filarski CF, et al. 2021 Predictive Impact of Metastatic Lymph Node Burden on Distant Metastasis Across Papillary Thyroid Cancer Variants. Thyroid 31 1549-1557.https://doi.org/10.1089/thy.2021.0131
Ho MF, Ingle JN, Bongartz T, Kalari KR, Goss PE, Shepherd LE, Mushiroda T, Kubo M, Wang L & Weinshilboum RM 2017 TCL1A Single-Nucleotide Polymorphisms and Estrogen-Mediated Toll-Like Receptor-MYD88-Dependent Nuclear Factor-kappaB Activation: Single-Nucleotide Polymorphism- and Selective Estrogen Receptor Modulator-Dependent Modification of Inflammation and Immune Response. Mol Pharmacol 92 175-184.https://doi.org/10.1124/mol.117.108340
Ho MF, Bongartz T, Liu M, Kalari KR, Goss PE, Shepherd LE, Goetz MP, Kubo M, Ingle JN, Wang L, et al. 2016 Estrogen, SNP-Dependent Chemokine Expression and Selective Estrogen Receptor Modulator Regulation. Mol Endocrinol 30 382-398.https://doi.org/10.1210/me.2015-1267
Hu Q, Zhang WJ, Liang L, Li LL, Yin W, Su QL & Lin FF 2022 Establishing a Predictive Nomogram for Cervical Lymph Node Metastasis in Patients With Papillary Thyroid Carcinoma. Frontiers in Oncology 11.https://doi.org/10.3389/fonc.2021.766650
Imai M, Ohta R, Varela JC, Song H & Tomlinson S 2007 Enhancement of antibody-dependent mechanisms of tumor cell lysis by a targeted activator of complement. Cancer Res 67 9535-9541.https://doi.org/10.1158/0008-5472.CAN-07-1690
Jiang X, Wang Y, Li X, He L, Yang Q, Wang W, Liu J & Zha B 2020 Microarray profile of B cells from Graves' disease patients reveals biomarkers of proliferation. Endocr Connect 9 405-417.https://doi.org/10.1530/EC-20-0045
Jonklaas J, Nogueras-Gonzalez G, Munsell M, Litofsky D, Ain KB, Bigos ST, Brierley JD, Cooper DS, Haugen BR, Ladenson PW, et al. 2012 The impact of age and gender on papillary thyroid cancer survival. J Clin Endocrinol Metab 97 E878-887.https://doi.org/10.1210/jc.2011-2864
Kang S, Kang J, Shen H & Wu N 2021 Advances in regulatory B cells in autoimmune thyroid diseases. Int Immunopharmacol 96 107770.https://doi.org/10.1016/j.intimp.2021.107770
Khan D & Ahmed SA 2016 The immune System Is a natural Target for Estrogen Action: Opposing Effects of Estrogen in Two Prototypical Autoimmune Diseases. Frontiers in Immunology 6.https://doi.org/10.3389/fimmu.2015.00635
Kilfoy BA, Devesa SS, Ward MH, Zhang Y, Rosenberg PS, Holford TR & Anderson WF 2009 Gender is an age-specific effect modifier for papillary cancers of the thyroid gland. Cancer Epidemiol Biomarkers Prev 18 1092-1100.https://doi.org/10.1158/1055-9965.EPI-08-0976
Kim SS, Lee BJ, Lee JC, Kim SJ, Jeon YK, Kim MR, Huh JE, Mok JY, Kim BH, Kim YK, et al. 2011 COEXISTENCE OF HASHIMOTO'S THYROIDITIS WITH PAPILLARY THYROID CARCINOMA: THE INFLUENCE OF LYMPH NODE METASTASIS. Head and Neck-Journal for the Sciences and Specialties of the Head and Neck 33 1272-1277.https://doi.org/10.1002/hed.21594
Kitahara CM & Sosa JA 2016 The changing incidence of thyroid cancer. Nat Rev Endocrinol 12 646-653.https://doi.org/10.1038/nrendo.2016.110
Kovacs KG, Macsik-Valent B, Matko J, Bajtay Z & Erdei A 2021 Revisiting the Coreceptor Function of Complement Receptor Type 2 (CR2, CD21); Coengagement With the B-Cell Receptor Inhibits the Activation, Proliferation, and Antibody Production of Human B Cells. Front Immunol 12 620427.https://doi.org/10.3389/fimmu.2021.620427
La Vecchia C, Malvezzi M, Bosetti C, Garavello W, Bertuccio P, Levi F & Negri E 2015 Thyroid cancer mortality and incidence: a global overview. Int J Cancer 136 2187-2195.https://doi.org/10.1002/ijc.29251
Lee HJ, Noh KH, Lee YH, Song KH, Oh SJ, Kim SY & Kim TW 2015 NANOG signaling promotes metastatic capability of immunoedited tumor cells. Clin Exp Metastasis 32 429-439.https://doi.org/10.1007/s10585-015-9717-2
Li H, Yan XB, Liu LG, Huang LS, Yin MM, Pan C, Zhang P & Qin HL 2017 T-cell leukemia/lymphoma-1A predicts the clinical outcome for patients with stage II/III colorectal cancer. Biomedicine & Pharmacotherapy 88 924-930.https://doi.org/10.1016/j.biopha.2017.01.128
Liu J, Chen G, Meng XY, Liu ZH & Dong S 2014 Serum levels of sex hormones and expression of their receptors in thyroid tissue in female patients with various types of thyroid neoplasms. Pathol Res Pract 210 830-835.https://doi.org/10.1016/j.prp.2014.09.002
Lun Y, Wu X, Xia Q, Han Y, Zhang X, Liu Z, Wang F, Duan Z, Xin S & Zhang J 2013 Hashimoto's thyroiditis as a risk factor of papillary thyroid cancer may improve cancer prognosis. Otolaryngol Head Neck Surg 148 396-402.https://doi.org/10.1177/0194599812472426
Luu VP, Vazquez MI & Zlotnik A 2014 B cells participate in tolerance and autoimmunity through cytokine production. Autoimmunity 47 1-12.https://doi.org/10.3109/08916934.2013.856006
Moulton VR 2018 Sex Hormones in Acquired Immunity and Autoimmune Disease. Frontiers in Immunology 9.https://doi.org/10.3389/fimmu.2018.02279
Noh KH, Kim BW, Song KH, Cho H, Lee YH, Kim JH, Chung JY, Kim JH, Hewitt SM, Seong SY, et al. 2012 Nanog signaling in cancer promotes stem-like phenotype and immune evasion. Journal of Clinical Investigation 122 4077-4093.https://doi.org/10.1172/jci64057
Noureldine SI & Tufano RP 2015 Association of Hashimoto's thyroiditis and thyroid cancer. Current Opinion in Oncology 27 21-25.https://doi.org/10.1097/cco.0000000000000150
Pan J, Ye F, Yu C, Zhu Q, Li J, Zhang Y, Tian H, Yao Y, Zhu M, Shen Y, et al. 2021 Papillary Thyroid Carcinoma Landscape and Its Immunological Link With Hashimoto Thyroiditis at Single-Cell Resolution. Front Cell Dev Biol 9 758339.https://doi.org/10.3389/fcell.2021.758339
Prokopec KE, Rhodiner M, Matt P, Lindqvist U & Kleinau S 2010 Down regulation of Fc and complement receptors on B cells in rheumatoid arthritis. Clin Immunol 137 322-329.https://doi.org/10.1016/j.clim.2010.08.006
Pu W, Shi X, Yu P, Zhang M, Liu Z, Tan L, Han P, Wang Y, Ji D, Gan H, et al. 2021 Single-cell transcriptomic analysis of the tumor ecosystems underlying initiation and progression of papillary thyroid carcinoma. Nat Commun 12 6058.https://doi.org/10.1038/s41467-021-26343-3
Punt S, Corver WE, van der Zeeuw SAJ, Kielbasa SM, Osse EM, Buermans HPJ, de Kroon CD, Jordanova ES & Gorter A 2015 Whole-transcriptome analysis of flow-sorted cervical cancer samples reveals that B cell expressed TCL1A is correlated with improved survival. Oncotarget 6 38681-38694.https://doi.org/10.18632/oncotarget.4526
Rahbari R, Zhang L & Kebebew E 2010 Thyroid cancer gender disparity. Future Oncol 6 1771-1779.https://doi.org/10.2217/fon.10.127
Rajoria S, Suriano R, George AL, Kamat A, Schantz SP, Geliebter J & Tiwari RK 2012 Molecular target based combinational therapeutic approaches in thyroid cancer. Journal of Translational Medicine 10.https://doi.org/10.1186/1479-5876-10-81
Rubio GA, Catanuto P, Glassberg MK, Lew JI & Elliot SJ 2018 Estrogen receptor subtype expression and regulation is altered in papillary thyroid cancer after menopause. Surgery 163 143-149.https://doi.org/10.1016/j.surg.2017.04.031
Schlumberger M, Tahara M, Wirth LJ, Robinson B, Brose MS, Elisei R, Habra MA, Newbold K, Shah MH, Hoff AO, et al. 2015 Lenvatinib versus Placebo in Radioiodine-Refractory Thyroid Cancer. New England Journal of Medicine 372 621-630.https://doi.org/10.1056/NEJMoa1406470
Song KH, Oh SJ, Kim S, Cho H, Lee HJ, Song JS, Chung JY, Cho E, Lee J, Jeon S, et al. 2020 HSP90A inhibition promotes anti-tumor immunity by reversing multi-modal resistance and stem-like property of immune-refractory tumors. Nature Communications 11.https://doi.org/10.1038/s41467-019-14259-y
Srour MK, Gao BW, Dadmanesh F, Carlson K, Qu Y, Deng N, Cui XJ & Giuliano AE 2020 Gene expression comparison between primary triple-negative breast cancer and paired axillary and sentinel lymph node metastasis. Breast Journal 26 904-910.https://doi.org/10.1111/tbj.13684
Stachelscheid J, Jiang Q & Herling M 2021 The Modes of Dysregulation of the Proto-Oncogene T-Cell Leukemia/Lymphoma 1A. Cancers (Basel) 13.https://doi.org/10.3390/cancers13215455
Suteau V, Munier M, Briet C & Rodien P 2021 Sex Bias in Differentiated Thyroid Cancer. Int J Mol Sci 22.https://doi.org/10.3390/ijms222312992
Tan L, Ji JQ, Sharen G, Liu YW & Lv K 2022 Related factor analysis for predicting large-volume central cervical lymph node metastasis in papillary thyroid carcinoma. Frontiers in Endocrinology 13.https://doi.org/10.3389/fendo.2022.935559
Teitell MA 2005 The TCL1 family of oncoproteins: co-activators of transformation. Nat Rev Cancer 5 640-648.https://doi.org/10.1038/nrc1672
Wang LR, Chen JW, Yuan X, Wang J, Sun L, Jiang J, Zhang L, Liu M & Zhou Q 2022 Lymph node metastasis of papillary thyroid carcinoma in the context of Hashimoto's thyroiditis. Bmc Endocrine Disorders 22.https://doi.org/10.1186/s12902-021-00923-2
Yan C, He X, Chen Z & Wang Y 2022 Central Compartment Lymph Nodes Have Distinct Metastatic Patterns in Different Age Groups. Front Endocrinol (Lausanne) 13 807431.https://doi.org/10.3389/fendo.2022.807431
Zahedi A, Bondaz L, Rajaraman M, Leslie WD, Jefford C, Young JE, Pathak KA, Bureau Y, Rachinsky I, Badreddine M, et al. 2020 Risk for Thyroid Cancer Recurrence Is Higher in Men Than in Women Independent of Disease Stage at Presentation. Thyroid 30 871-877.https://doi.org/10.1089/thy.2018.0775
Zhang D, Tang JN, Kong DG, Cui QX, Wang K, Gong Y & Wu GS 2018 Impact of Gender and Age on the Prognosis of Differentiated Thyroid Carcinoma: a Retrospective Analysis Based on SEER. Hormones & Cancer 9 361-370.https://doi.org/10.1007/s12672-018-0340-y

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

Infiltration of B cell may underlie the contrary sex- and age-related biological behavior of papillary thyroid carcinoma

Status:

Version 1

Abstract

Figures

1 Introduction

2 Materials and Methods

2.1 Clinical data

2.2 Public data of gene expression

2.3 Statistical analysis and immune infiltration evaluation

3 Results

3.1 Clinical data and single-factor analysis of LNM

3.2 TCGA bulk gene expression and DEGs

3.3 TIMER and GENEMANIA

3.4 GEO database of single-cell RNA sequencing

3.5 Peripheral blood lymphocyte subpopulation

4 Discussion

5 Conclusions

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1