Abstract

Objectives

   To explore the potential influence of Sjogren’s syndrome (SS) on
   thyroid cancer (TC).

Methods

   First, a literature data mining (LDM) approach was used to reconstruct
   functional pathways connecting SS and TC. A meta-analysis was then
   performed to examine the expression changes of genes mediated by SS
   using 16 TC case/control expression datasets, with results validated
   through the TCGA/GTEx dataset. Finally, gene set enrichment analysis
   (GSEA) and survival analysis using GEPIA2 were conducted on the
   significant genes.

Results

   Our findings indicate that SS may increase the risk of TC by activating
   14 TC promoters (PDCD1, NTRK1, LGALS3, CD274, FOXP3, BCL2, CYP1A1,
   HMGB1, TGFB1, CCL2, PLA2G7, TFF3, LCN2, and CLDN1) and suppressing
   three TC inhibitors (MIR145, MIR30C1, and EP300). Four molecules
   (PLA2G7, TFF3, LCN2, and CLDN1) exhibited significant expression
   changes in TC patients (LFC > 1 or < -1; p < 2.07E-04), which were
   confirmed in TCGA/GTEx expression analysis. These results highlight
   three possible mechanisms—the SS-PLA2G7-CCL2-TC pathway, the
   SS-LCN2-LGALS3-TC pathway, and the SS-CLDN1-BCL2-TC pathway—that may
   explain how SS contributes to TC development. Enrichment analysis
   suggests that SS may affect TC prognosis by regulating leukocytes and
   tolerance induction. Survival analysis indicates that SS may enhance TC
   survival through the regulation of the CLDN1 and EGF pathways.

Conclusion

   LDM-based pathway analysis highlighted three genetic pathways through
   which SS may adversely affect TC progression, while SS may enhance TC
   survival via the CLDN1 and EGF pathways, highlighting the need for
   further research.

Introduction

   Sjögren’s syndrome (SS) is a chronic autoimmune disease that causes
   dryness of the mouth and eyes, as well as other symptoms such as dry
   skin, vaginal dryness, chronic cough, numbness in the arms and legs,
   fatigue, muscle and joint pain, and thyroid problems [[40]1]. SS can
   also seriously affect other organ systems, such as the lungs, kidneys,
   and nervous system [[41]2]. Furthermore, it increases the risk of
   lymphoma by 15% [[42]3]. SS is estimated to affect 0.1% to 4% of the
   general population, with a higher prevalence in middle-aged women
   (female-to-male ratio of 9:1) [[43]1, [44]4, [45]5].

   Thyroid cancer (TC) is a cancer that originates in the cells of the
   thyroid gland, a gland located in the front of the neck responsible for
   producing hormones that regulate the body’s metabolism [[46]6].
   Although TC is one of the least lethal types of cancer, with over
   56,000 new cases reported in the United States in 2017 and an estimated
   2,010 deaths from thyroid cancer were reported in the same year
   [[47]7]. The incidence has been increasing since the 1990s, rising from
   approximately 5.0 to 15.0 per 100,000 in 2014, with a higher incidence
   rate in women (22.2 new cases per 100,000) [[48]7].

   Although the exact cause of TC is unknown, certain risk factors have
   been identified, such as a family history of TC, exposure to radiation,
   and specific genetic syndromes [[49]8]. Several studies have suggested
   a potential association between SS and TC. For instance, one
   retrospective study reported a significantly higher incidence of TC in
   patients with SS than in the general population (pooled Standardized
   Infection Ratio (SIR) = 2.05, 95%CI 1.20–3.48) [[50]9], and several
   recent studies have also confirmed the increased risk of TC among
   patients with primary SS [[51]10–[52]12]. However, a definitive causal
   relationship between SS and TC has yet to be established, and the
   nature of the SS-TC relationship remains unclear and requires further
   investigation.

   In this study, we utilized extensive literature data mining to
   construct a molecular pathway driven by SS that potentially affects the
   development and progression of TC. In addition, we conducted a
   meta-analysis of RNA expression to examine the levels of SS-driven
   molecules in patients with TC. We also performed a pathway enrichment
   analysis to investigate the functions of the molecules linking SS and
   TC. Our findings provide novel insights into the role of SS as a risk
   factor for TC.

Materials and methods

SS-driven molecules influencing TC

   To investigate the potential influence of SS on TC, we performed
   literature data mining (LDM) to identify SS-driven molecules that also
   act as upstream regulators of TC. The LDM was carried out using Pathway
   Studio (version 12.3), which utilizes the natural language processing
   (NLP) tool MedScan [[53]13]. This process involved mining data from 24
   million PubMed abstracts and 3.5 million Elsevier and third-party
   full-text papers. Each relationship or edge was established based on
   facts extracted from the literature using NLP technology, supported by
   at least one reference. Key information extracted included relation
   type, relation polarity, reference title, PMID/DOI, and the key
   sentences where the relationship was identified. First, the downstream
   targets of SS with polarity (activated or inhibited in SS) were
   identified. Then TC upstream regulators with polarity (advancing or
   inhibiting the disease) were also identified. The overlapped entities
   were used to construct the molecular network connection between SS and
   TC. The relationship data within the molecular network was extracted
   from the Elsevier Knowledge graph database ([54]www.pathwaystudio.com),
   which covers the entire PubMed database, Elsevier publications, and
   third-party literature, updated as of February 2024. A manual check of
   the underlying references for each relationship was conducted for