Global knowledge mapping and emerging trends in research between spasmolytic polypeptide-expressing metaplasia and gastric carcinogenesis: A bibliometric analysis from 2002 to 2022

Abstract

Background
Spasmolytic polypeptide expression metaplasia (SPEM) occurs in the corpus of the stomach and is closely related to inflammations caused by H. pylori infection. Recently, SPEM was suggested as one of the dubious precancerous lesions of gastric cancer (GC). Thus, further research on SPEM cell transdifferentiation and its underlying mechanisms could facilitate the development of new molecular targets improving the therapeutics of GC. Using bibliometrics, we analyzed publications, summarized the research hotspots and provided references for scientific researchers engaged in related research fields.

Methods
We searched the Web of Science Core Collection (WoSCC) for publications related to SPEM-GC from 2002 to 2022. The VOSviewer, SCImago, CiteSpace and R software were used to visualize and analyze the data. Gene targets identified in the keyword list were analyzed for functional enrichment using the KEGG and GO databases.

Results
Of the 292 articles identified in the initial search, we observed a stable trend in SPEM-GC research but rapid growth in the number of citations. The United States was the leader in terms of quality publications and international cooperation among them. The total number of articles published by Chinese scholars was second to the United States. Additionally, despite its low centrality and average citation frequency, China has become one of the world’s most dynamic countries in academics. In terms of productivity, Vanderbilt University was identified as the most productive institution. Further, we also observed that Gastroenterology was the highest co-cited journal, and Goldenring Jr. was the most prolific author with the largest centrality.

Conclusion
SPEM could serve as an initial step in diagnosing gastric precancerous lesions. Current hotspots and frontiers of research include SPEM cell lineage differentiation, interaction with H. pylori, disturbances of the mucosal microenvironment, biomarkers, clinical diagnosis and outcomes of SPEM, as well as the development of proliferative SPEM animal models. However, further research and collaboration are still required. The findings presented in this study can be used as reference for the research status of SPEM-GC and determine new directions for future studies.

Full text

Global knowledge mapping and
emerging trends in research
between spasmolytic
polypeptide-expressing
metaplasia and gastric
carcinogenesis: A bibliometric
analysis from 2002 to 2022
Lin Liu
1
†
, Yang Wang
1
†
, Yukun Zhao
2
†
, Wei Zhang
3
†
, Jiong Liu
3
,
Fengyun Wang
1
, Ping Wang
1
and Xudong Tang
1
*
1
Institute of Digestive Diseases, Xiyuan Hospital of China Academy of Chinese Medical Sciences,
Beijing, China,
2
Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical
Sciences, Beijing, China,
3
Department of Pathology, Xiyuan Hospital of China Academy of Chinese
Medical Sciences, Beijing, China
Background: Spasmolytic polypeptide expression metaplasia (SPEM) occurs in
the corpus of the stomach and is closely related to inflammations caused by H.
pylori infection. Recently, SPEM was suggested as one of the dubious
precancerous lesions of gastric cancer (GC). Thus, further research on SPEM
cell transdifferentiation and its underlying mechanisms could facilitate the
development of new molecular targets improving the therapeutics of GC.
Using bibliometrics, we analyzed publications, summarized the research
hotspots and provided references for scientific researchers engaged in
related research fields.
Methods: We searched the Web of Science Core Collection (WoSCC) for
publications related to SPEM-GC from 2002 to 2022. The VOSviewer,
SCImago, CiteSpace and R software were used to visualize and analyze the
data. Gene targets identified in the keyword list were analyzed for functional
enrichment using the KEGG and GO databases.
Results: Of the 292 articles identified in the initial search, we observed a stable
trend in SPEM-GC research but rapid growth in the number of citations. The
United States was the leader in terms of quality publications and international
cooperation among them. The total number of articles published by Chinese
scholars was second to the United States. Additionally, despite its low centrality
and average citation frequency, China has become one of the world’s most
dynamic countries in academics. In terms of productivity, Vanderbilt University
was identified as the most productive institution. Further, we also observed that
Gastroenterology was the highest co-cited journal, and Goldenring Jr. was the
most prolific author with the largest centrality.
Frontiers in Cellular and Infection Microbiology frontiersin.org01
OPEN ACCESS
EDITED BY
Yifei Xu,
Guangzhou University of Chinese
Medicine, China
REVIEWED BY
Peter Kokol,
University of Maribor, Slovenia
Ling Hu,
Guangzhou University of Chinese
Medicine, China
*CORRESPONDENCE
Xudong Tang
txdly@sina.com
†
These authors share first authorship
SPECIALTY SECTION
This article was submitted to
Antibiotic Resistance and New
Antimicrobial drugs,
a section of the journal
Frontiers in Cellular and
Infection Microbiology
RECEIVED 26 November 2022
ACCEPTED 28 December 2022
PUBLISHED 27 January 2023
CITATION
Liu L, Wang Y, Zhao Y, Zhang W, Liu J,
Wang F, Wang P and Tang X (2023)
Global knowledge mapping and
emerging trends in research
between spasmolytic polypeptide-
expressing metaplasia and gastric
carcinogenesis: A bibliometric
analysis from 2002 to 2022.
Front. Cell. Infect. Microbiol.
12:1108378.
doi: 10.3389/fcimb.2022.1108378
COPYRIGHT
©2023Liu,Wang,Zhao,Zhang,Liu,
Wang, Wang and Tang. This is an open-
access article distributed under the
terms of the Creative Commons
Attribution License (CC BY). The use,
distribution or reproduction in other
forums is permitted, provided the
original author(s) and the copyright
owner(s) are credited and that the
original publication in this journal is
cited, in accordance with accepted
academic practice. No use,
distribution or reproduction is
permitted which does not comply with
these terms.
TYPE Original Research
PUBLISHED 27 January 2023
DOI 10.3389/fcimb.2022.1108378

Conclusion: SPEM could serve as an initial step in diagnosing gastric
precancerous lesions. Current hotspots and frontiers of research include
SPEM cell lineage differentiation, interaction with H. pylori, disturbances of
the mucosal microenvironment, biomarkers, clinical diagnosis and outcomes
of SPEM, as well as the development of proliferative SPEM animal models.
However, further research and collaboration are still required. The findings
presented in this study can be used as reference for the research status of
SPEM-GC and determine new directions for future studies.
KEYWORDS
spasmolytic polypeptide-expressing metaplasia (SPEM), gastric carcinogenesis (SGC-
7901), helicobacter pylori infection (H. pylori infection), gastric precancerous lesions,
bibliomeric analysis, visualization
1 Introduction
According to the World Health Organization, gastric cancer
(GC) was the third leading cause of cancer-related deaths
worldwide in 2020 (Smyth et al., 2020). Before developing into
GC, the gastric mucosa undergoes pathological changes such as
gastritis, atrophy, intestinal metaplasia (IM) and atypical
hyperplasia (Correa et al., 1975). However, there is a limited
understanding on the etiology and pathogenesis of GC, which
contributes to its poor prognosis (Ajani et al., 2017). Previous
studies showed that several factors, particularly Helicobacter
pylori (H. pylori) infection, can contribute to abnormal gastric
mucosal cell differentiation (Mills and Shivdasani, 2011). It is
often characterized by chronic inflammation followed by
parietal cell defects, which can accelerate the occurrence and
development of GC (Wroblewski et al., 2010). Two types of
metaplastic GC are related to parietal cell defects in the gastric
corpus: IM, characterized by intestinal-type cells, and antral
spasmolytic polypeptide metaplasia (SPEM), characterized by
trefoil factor 2 (TFF2) in deep antral glands (Saenz and Mills,
2018). Previous studies using animal models confirmed that
SPEM induced by H. pylori infection in mice progressed only to
dysplasia, not IM, suggesting that SPEM could be the beginning
of a precancerous process (Weis and Goldenring, 2009;Hibdon
and Samuelson, 2018;Goldenring and Mills, 2022). In contrast
to IM, the origin, regulatory mechanism and link to the
pathogenesis of GC for SPEM are still unknown (Nomura
et al., 2004;Yoshizawa et al., 2007;Nam et al., 2009;Nam
et al., 2010). In addition, endoscopic and pathological findings
on SPEM are relatively insidious, restricting related clinical
observation and treatment because it is hard to diagnose. As a
result, knowing the origin and progression mechanisms of
SPEM could help prevent it from progressing into dysplasia or
GC. Thus, comprehensive research on SPEM-GC is necessary to
assist scientists in obtaining deeper insights into the trends in
SPEM-GC related research.
Bibliometrics is a mathematical and statistical approach to
analyze research literature (Kokol et al., 2021) and was defined
by Prof Pritchard (1969) as aiming to discover the patterns of
scientific literature in a specificfield. Although various methods
can be used to perform a quantitative overview, from traditional
and systematic reviews to main path analyses and evidence
maps, only bibliometrics contribution and cooperation of
authors, institutions, countries, journals and keywords can
provide qualitative and quantitative forecasts of hotspots and
trends in certain research topics (van Eck et al., 2010;Chen,
2017;Liu et al., 2022). On the other hand, bibliometric mapping
can be used to visualize the structure and patterns of research
literature production in the form of science landscapes (Kokol
et al., 2018). In this regard, although SPEM has recently gained
the spotlight of the research community, a bibliometric analysis
of SPEM-GC has not yet been reported. Thus, this study aimed
to quantify the entire picture of SPEM research in the last 20
years using bibliometric software and R packages, which might
contribute to generating suggestions for future research about
SPEM and GC.
2 Methods
2.1 Database and study collection
According to previous bibliometric studies, the Web of
Science Core Collection (WoSCC) is the most widely used
database, with more than ten thousand high-quality journals
(Liu et al., 2022;Zhang et al., 2022a;Zhang et al., 2022b). A
database from the WoSCC, the Science Citation Index-
Expanded, was selected to conduct this study. The literature
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org02

searchfororiginalarticlesandreviewswasconducted
independently by two researchers on October 1, 2022, using
the search terms: #1: Topic (TS)= (spasmolytic polypeptide-
expressing metaplasia OR trefoil factor 2 OR TFF2); #2: TS=
(gastric cancer OR gastric carcinoma OR stomach cancer OR
stomach neoplasm*); Source of final search term: #1 AND #2.
The study period was from January 1, 2002, to October 1, 2022,
with English used as the only language. In total, 260 articles and
32 reviews were obtained (Figure 1). Supplementary File S1
displays the included studies.
2.2 Data compilation and purification
A range of key information was extracted from the WoSCC
database for further analysis in this study. This series contained
information such as the year of publication, the number of
citations, countries or regions, research organizations, authors,
sources, references and keywords. Then, several repetitive
keywords, such as nations, organizations, authors and
keywords, were combined into one word, spelling errors were
corrected, and irrelevant words were removed. Lastly, the
bibliometric analysis was completed by importing the cleaned
data into Microsoft Excel 365 and bibliometric
visualization platforms.
2.3 Analyses and visualizations
A nation’s productivity is generally measured by the number
of publications, and its impact is measured by the number of
average citations. In addition, screening procedure based on
Price’s Law (oI
m+1n(x)=
ffiffiffiffi
N
p), was employed in this study to
identify representative scholars and key research forces. In this
equation, x denoted the number of publications from each
author and n (x) denoted the number of authors who have
written x number of publications. Additionally, I equal to nmax
represented the number of documents produced by the highest-
producing author, N represented the total number of authors,
and m represented the minimum number of documents
produced by the core author. As a result, m=0:749 
ffiffiffiffiffiffiffiffiffiffi
Nmax
p≈
5:3 was used to define authors with ≥6 documents issued as the
core author (Knowlson et al., 2022).
Diagrams of visualizing network and knowledge structure
were conducted using VOSviewer, a widely used bibliometric
visualization software (van Eck and Waltman, 2010), which
provides three main visual maps: the network visualization map,
time-overlay visualization map and density visualization map.
This study used VOSviewer (Version 1.6.18) to analyze co-
authorship between countries, organizations, core authors,
influential journals and co-occurrence keywords (Kokol et al.,
2018). Furthermore, SCImago Graphica (Version 1.0.26) was
primarily used to assess the international geographic
collaborations and distribution among the top ten productive
countries (Hassan-Montero et al., 2022). Additionally, CiteSpace
(Version 6.1.R3), another visualization tool invented by Prof.
Chaomei Chen (Synnestvedt et al., 2005), was also used in this
study to visualize the co-citation analysis of references and authors
and identify the keywords and references with the strongest
citation bursts. CiteSpace was also used to create a dual map
overlay of journals using parameters: duration (2002–2022), years
sliced (3 years), the type of node (reference, cited author, and cited
journal), selection criteria (g-index = 25), and pruning methods
(Pathfinder and pruning sliced networks). An additional
Cytoscape plugin, CytoNCA, was used to conduct centrality
analyses among the productive countries, organizations and
authors of SPEM-GC.
2.4 GO and KEGG annotations
To further review the key pathways and targets related to the
regulation of SPEM transformation, GO classification and
KEGG pathway (http://www.omicsbean.cn/)methodswere
employed to identify genes’functional categories and predict
their biological functions. Figures were generated with R using
KEGG pathway enrichment analysis and GO enrichment
analysis with a corrected p-value < 0.05.
3 Results
3.1 Trend analysis of annual publications
and citations
A total of 292 SPEM-GC papers written by 1757 authors at
412 organizations from 41 countries were collected. They were
published in 131 journals, cited by 1395 journals and referenced
in 8431 articles. The total number of citations was 9345, and the
average number of citations per publication was 35.76. The H-
FIGURE 1
Literature search and screening flowchart.
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org03

index of all the documents was 53, indicating a high academic
value and social impact for papers in this field. Based on
Figure 2A, we observed that the number of documents issued
each year from 2002 to 2012 was relatively stable, except for two
small peaks in 2017 and 2020. In contrast, the annual citation
curve increased steadily since 2002 and peaked in 2021 when
11,816 citations were recorded.
3.2 Contribution of core-productive
countries and organizations
To determine which countries had the most prominent
contribution and cooperation in the field of SPEM-GC, we
made a visual analysis of the number of documents issued,
citations, and co-occurrence frequencies for 41 countries and
regions. The results showed that most SPEM-GC studies were
from North America, Europe and East Asia. The number of
publications of the top 10 productive countries/regions
continued to rise rapidly (Figure 2B). As shown in Table 1, the
top ten productive countries/regions had the highest number of
publications. The United States published 125 papers in this
field, accounting for 40.7% of all papers. Although China ranked
second in terms of publications, it had the lowest average
citation among the top 10 productive countries.
Co-authorship network maps of the top 10 productive
countries were generated using VOSviewer and SCImago
(Figure 2C). The results showed that the United States was
a leading cooperation center in this field, with close ties to
Japan, South Korea and China. According to Table 2,the
United States was the most central country (0.47), with
Germany and the United Kingdom ranking second (0.35)
and third (0.32), respectively. However, a visualization of the
number and the year of issuance using VOSviewer indicated
that despite European countries such as Finland and France
being the first countries to publish the first research in the
field, since 2014, Asian countries such as China, South Korea
and Singapore have gradually become the main research
centers in this field (Figure 2D).
3.3 Contribution of active authors
Based on Price’s Law, 69.7% of the total articles in this field
were published by 18 core authors. More than 50% of the
documents issued by core authors defined by Price’s law were
evaluated, and the results suggested that the SPEM-GC research
field was relatively stable in terms of authorship cooperatives.
Table 3 shows the top ten authors, organizations and countries
with the most recently published papers in this field. Among
them, seven of the top ten authors were from the United States,
two were from South Korea, and one was from Japan. In terms of
high productivity, the top three authors withthe most papers were
Americans. They are Goldenring, James R. Vanderbilt University
(N = 51, APC = 61.9), Mills, Jason C. Washington University (N =
21, APC = 49.7), and Wang, Tc, Columbia University (N = 19,
APC = 90.5). With a centrality of 0.18, Goldenring Jr. was the
most cited co-author. Figure 3A shows the authors with a
minimum of 6 publications. Based on overlay visualization of
co-authorships (Figure 3B), the blue cluster is considered a
pioneering group for SPEM-GC research. Comparatively, the
yellow and Laurel-green cluster authors have published papers
in recent years. Upon further visual analysis of the co-cited
network, Goldenring James R. authored most of the cited
articles along with Mills Jason C., Nam Ki Taek and Petersen
Cheritine P. (Figure 3C). In terms of burst monitoring of authors
(Figure 3D), Wang Tc, Lee Hyuk-Joon and Kaminishi M were the
top three ranked institutions between 2002 and 2009, followed by
Nam and Ki Taek bursting between 2010 and 2012. Presently, the
bursting of Choi Eunyoung from 2016 to 2022 and Mills Jason C.
indicates their dominance in this field.
3.4 Analysis of influential journals
We found that articles on SPEM-GC were published in 131
journals. As shown in Figure 4A, 135 documents were published
in the top 14 journals (>5 documents in counts), accounting for
44% of the articles included. A total of 31 articles were published
in Gastroenterology (IF 2021 = 33.9), followed by the American
Journal of Pathology (IF 2021 = 5.8) and Gut (IF 2021 = 31.8).
Figure 4B illustrates the number of citations, in which a deeper
orange color indicates more co-citations. As shown in Table 4,
most of the top ten JCI district journals with the highest average
citation rate in this field were renowned journals over the past 20
years, among which 9 had an H-index over 50. The top journals
in gastroenterology were Gastroenterology and Gut, Cancer
Research in oncology, and Journal of Pathology in pathology.
Among them, the United States and the United Kingdom had
four journals each, while Japan and Switzerland had one each.
Using a dual map overlay of relevant journals, we visualized
the journal’s citation relationships within related fields
(Figure 4C). In the map, the labels indicate the journal’sfield.
Its left side represents cited literature, and its right side
represents cited literature. We determined the causal
relationship between citations by determining the citation
path. Citations made up the applied research and the research
basis in this field. The colors signify different citation paths, with
orange representing one citation path and green representing
another. The orange line indicates that the included articles were
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org04

mostly associated with Molecular, Biology, and Immunology
disciplines. Based on the green path, the articles included in the
analysis were found to be mostly distributed in Medicine,
Medical and Clinical fields, while their cited papers were
mostly distributed in Molecular, Biology, and Genetics.
3.5 Analysis of highly citing and
co-cited references
Reference analysis was conducted, and VOSviewer and
CiteSpace were utilized to visualize the references that
D
A
B
C
FIGURE 2
SPEM-GC publications trends and co-occurrence map over the last two decades. (A) Global trend in publication outputs and total citations per
year on SPEM-GC from 2002 to 2022. (B) Core countries/regions of publications and average citations on SPEM-GC from 2002 to 2022.
(C) The global geographic collaborations and distribution visualization map ranked the top ten countries/regions in terms of the total number of
documents issued. The size of the map area represents the weight of the number of documents issued by the state accounting for the total
number of documents issued, with a larger area suggesting more documents issued. The color of the map represents the total citation of
articles published in each country, with a darker color representing a greater number of total citations. Yellow lines represent the intensity of
joint documents issued between different regions, with wider lines representing a greater number of cooperative documents issued by the two.
(D) Visualization of the citation overlay map for core countries/regions. In the node group, nodes represent countries and regions, and their size
shows the number of publications. The connections between nodes represent the interrelation between citations. The width of the links reveals
the citation strength.
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org05

supported the development of in-depth studies. We first
performed a coupled network analysis of 292 articles using the
VOSviewer software and generated a visual map based on the
top 50 citing references with the strongest association strength
(Figure 5A). Based on coupling strength, these references were
classified into four clusters: Cluster 1 (red dominates), consisting
of 16 highly citing references with the theme of “Cellular
Reprogramming and Regeneration of SPEM”; Cluster 2 (green
dominates), consisting of 13 highly citing references with the
theme of “The origin of SPEM”; Cluster 3 (blue dominates)
consisting of 11 highly citing references, with the theme of
“Oxyntic Atrophy, IM and SEPM”, and; Cluster 4 (yellow
dominates) comprising a total of 10 highly citing references,
with the theme of “Trefoil Factor Family Peptides”. According to
the time-overlay visualization map in Figure 5B, the references
in cluster 1 published by Goldenring (2022) (Goldenring and
Mills, 2022), Lee (2022) (Lee et al., 2021), Jeong (2021) (Jeong
et al., 2021), Bockerstett (2020) (Bockerstett et al., 2020) and
Burclaff (2020) (Burclaff et al., 2020), as well as references in
cluster 4 published by Hoffmann (2020 and 2022) (Hoffmann,
2012;Hoffmann, 2020), represent the current frontiers of
research. A complete list of the top ten citing references for
SPEM-GC is shown in Table 5.
Furthermore, a total of 8431 references were cited at least 23
times based on Price’s law. According to Table 6, the ten most
co-cited references were cited at least 124 times. One of the most
co-cited references was an article by Houghton J et al. published
in Science in 2004 (n=903). Nine of the top 10 articles were
research papers, and one was a Review. As shown in Figure 5C,
the reference timeline visualized the evolution of research
hotspots over time, and cluster labels were created based on
the terms associated with each cluster’s highest frequency. We
observed that: cluster #2 (Trefoil factor1), #4 (Gene regulation),
#5 (Spasmolytic polypeptide) and #12 (the TTF peptides) started
TABLE 1 The top 10 productive countries involved in SPEM-GC research.
Rank Country Publications Citations Average Citation Centrality
1 United States 125 5822 46.6 0.47
2 China 71 1174 16.5 0.29
3 Japan 69 3313 48.0 0.06
4 South Korea 29 789 27.2 0
5 Germany 24 696 29.0 0.35
6 United Kingdom 22 777 35.3 0.32
7 Australia 13 1217 93.6 0.03
8 Italy 9 156 17.3 0.19
9 Netherlands 9 612 68.0 0.06
10 Singapore 9 472 52.4 0.16
TABLE 2 The top 10 productive organizations involved in SPEM-GC research.
Rank Organization Publications Citations Average Citation Centrality
1 Vanderbilt Univ 52 3168 60.9 0.39
2 Tokyo Univ 25 1983 79.3 0.14
3 Washington Univ 21 1059 50.4 0.16
4 Michigan Univ 13 385 29.6 0.01
5 MIT 11 1449 131.7 0.05
9 Massachusetts Univ 10 1422 142.2 0.02
7 Natl Canc Ctr 10 613 61.3 0.08
8 Seoul Natl Univ 10 514 51.4 0.04
6 Columbia Univ 10 373 37.3 0.04
10 Harvard Univ 9 452 50.2 0.05
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org06

earlier, while cluster #0 (Stem cells), #8 (Differentiation) and #14
(progenitor) could be considered the frontier since they are
still ongoing.
Citation bursts are references with a significant increase in
citations over time. Figure 5D shows the top 25 citation bursts of
the 71 detected. The burst with the strongest strength
(strength=10.86) was entitled “A molecular signature of gastric
metaplasia arising in response to acute parietal cell loss”(Nozaki
et al., 2008), published in Gastroenterology by Koji Nozaki et al.
in 2008, with citation bursts between 2010 and 2013. Among the
25 references, 10 (40%) were published in 2017-2022, indicating
their importance in this field. Notably, 8 (32%) of these 25
papers were still experiencing citation bursts by the time of
writing this manuscript. In light of all these factors, we
hypothesized that SPEM-GC would continue to attract
attention in the future. Additionally, we also found that 5
papers dealt with the proliferation and lineage conversion of
SPEM cells (Engevik et al., 2016;Leushacke et al., 2017;Burclaff
TABLE 3 The top 10 productive authors involved in SPEM-GC research.
Rank Author Publications Average Citation H-Index Centrality Affiliation Country
1 Goldenring, Jr 51 61.9 76 0.18 Vanderbilt Univ United States
2 Mills, Jason C. 21 49.7 48 0.03 Baylor College of Medicine United States
3 Wang, Tc 19 90.5 79 0.02 Columbia Univ United States
4 Nam, Ki Taek 14 51.2 36 0 Yonsei Univ South Korea
5 Nomura, S 13 123.8 57 0 Tokyo Univ Japan
6 Fox, Jg 11 131.7 109 0.08 Massachusetts Univ United States
7 Choi, Eunyoung 9 23.6 13 0.04 Vanderbilt Univ United States
8 Petersen, Christine P. 8 34.0 17 0 Vanderbilt Univ United States
9 Kaminishi, M 8 39.9 51 0 Vanderbilt Univ United States
10 Lee, Hyuk-joon 8 55.1 54 0 Seoul Natl Univ South Korea
D
A
B
C
FIGURE 3
Co-occurrence analysis of active authors and their contributions. The network visualization map (A) and overlay visualization map (B) of the
core co-authorship analysis generated by VOSviewer. The minimum number of documents of an author is ≥6. (C) The visualization map of the
core author co-cited network carried on SCImago. (D) A list of the top 10 authors with the strongest citation bursts using SPEM-GC cells. Blue
bars indicate the authors’first article published, and red bars indicate the strength of the citation burst.
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org07

et al., 2017;Goldenring, 2018;Radyk et al., 2018;Willet et al.,
2018) and 3 dealt with mucosal immune regulation (Nozaki
et al., 2008;Petersen et al., 2017;Petersen et al., 2018), indicating
that SPEM might significantly influence the research field of
gastric carcinogenesis by affecting the above mechanisms.
3.6 Keywords analysis of trending topic
A total of 1,394 keywords were extracted from the titles and
abstracts of the included papers. Using VOSviewer, 65 keywords
appeared more than nine times and were used to generate the
visual map in Figure 6A. We conducted cluster analysis on high-
frequency keywords and divided them into three clusters:
Cluster 1 (red dominates), comprising 32 core keywords and
was the largest, with the most prevalent keywords being gastric
cancer (119 times), expression (79 times), and trefoil peptides
(72 times). Cluster 2 (green dominates), comprising 20 core
keywords, among which the most common were H. pylori (121
times), SPEM (113 times), and gastric (102 times). Cluster 3
(blue dominates), comprising 13 core keywords, with cancer (79
times), inflammation (34 times) and differentiation (30 times)
being the most common. Figure 6B shows the link strength
keywords displayed as a density map, in which the colors
indicate the total strength of the links. H. pylori (748), gastric
cancer (724) and SPEM (706) were the three keywords with the
strongest association. Figure 6C shows the top 11 high-
frequency keywords over time for each cluster. Six out of 11
clusters are still underway. The largest cluster was spasmolytic
polypeptide-expressing metaplasia (#0), followed by oxyntic
atrophy (#1), Mongolian gerbils (#4), cellular differentiation
(#6), activation (#7) and trefoil factor 1 (#11). As a next step,
we analyzed the relationship between keywords, the identified
themes and three clusters, which is detailed in Table 7 (Kokol
et al., 2022). There were three components to this: expression of
gastric cancer genes, H. pylori infection and SPEM, as well as cell
differentiation and proliferation.
According to the time-overlay visualization map in
Figure 6D,“chief cells”,“progenitor cells”,“progression”,
“biomarker”and “atrophy”were the recent keywords in
A
B
C
FIGURE 4
Visualization analysis of influential journals. (A) The publications output and average citation of the top 10 journals in SPEM-GC. (B) VOSviewer
was used to visualize the spectral density map of journals. A deeper color indicates a greater number of citations. (C) CiteSpace’sdual-mapoverlap
of SPEM-GC journals. The citing journals are on the left, and the cited journals are on the right. The colored paths indicate their citation relations.
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org08

addition to keyword trends. Essentially, these keywords seem to
outline the current frontiers of research. Additionally, CiteSpace
was used to identify the top 20 keywords with the strongest
citation bursts (Figure 6E). As indicated by the red part, the
keywords indicate a blowout at this stage. The keywords related
to “ps2”or “trefoil factor 1”bursts were the strongest (strength =
7.29), followed by intestinal “trefoil factor”(strength = 4.82) and
“epidermal growth factor”(strength = 3.46). We also found that the
keywords were still emerging in 2022. Thus, the research areas of
“chief cell”,“inflammation”,“stem cell”,“atrophy”and “biomarker”
might become hot spots in the future.
3.7 Annotations of SPEM-GC target
genes and pathways
To further clarify the focus of mechanistic studies in SPEM-
GC-related research fields, we extracted and analyzed the
keywords of all associated genes in literature, based on which
147 associated gene keywords were identified. Supplementary
File S2 lists the relevant statistical results. Among them, the most
frequently associated gene was TFF1 (54 times), followed by
TFF2 (Petersen et al., 2018) and PSEN2 (Nozaki et al., 2008).
Figure 7A lists the keywords having a frequency >5. KEGG
pathway enrichment analysis showed that PI3K-Akt, JAK-
STAT, HIF-1, MAPK, Hippo, Wnt, VEGF, cell cycle and Ras
signaling pathways were the hot research pathways in the field of
SPEM-GC. Figure 7B reveals that the immune regulation of
Th17 cell differentiation, cytokine-cytokine receptor interaction,
and differentiation of Th1 and Th2 cells were also major topics
in this field. Further analysis of GO functional annotation and
significant enrichment analysis in Figure 7C revealed that
Biological Process (BP) was predominantly represented in cell
proliferation, single-multicellular organism process, and
multicellular organismal process. We also found that Cellular
Component (CC) was mainly found in the extracellular region,
whereas Molecular Function (MF) was mainly found in identical
protein binding and receptor binding sites.
4 Discussion
4.1 General overview
Although SPEM was first reported in 1999 by Schmidts et al.
(Schmidt et al., 1999), it was not until 2002 that Halldorsdottir
et al. discovered a link between SPEM and GC (Halldorsdottir
et al., 2003). Analysis of the WoSCC database from 2002 to 2022
shows that 292 papers were published in 131 journals by 1757
authors in 412 organizations from 41 nations. Despite relatively
stable document volumes, the increasing number of citations
indicated that SPEM-GC is becoming increasingly popular.
TABLE 4 The top 10 JCR Q1 Journals involved in SPEM-GC research.
Rank Journals Country Average
Citation
2021
IF
H-
Index
Subdiscipline Publisher OA
1 Gastroenterology United
States
70.9 33.9 423 Gastroenterology & Hepatology W.B.
Saunders
Ltd
No
2 Cancer Research United
States
46.3 13.3 466 Oncology AACR No
3 American Journal of Pathology United
States
38.2 5.8 289 Pathology Elsevier No
4 Gut United
Kingdom
37.1 31.8 311 Gastroenterology & Hepatology BMJ No
5 Journal of Pathology United
Kingdom
35.9 9.9 193 Oncology/Pathology Wiley No
6 Laboratory Investigation United
Kingdom
33.0 5.5 155 Biochemistry, Genetics and
Molecular Biology/Medicine
Nature No
7 Gastric Cancer Japan 25.0 7.7 87 Gastroenterology & Hepatology/
Oncology
Springer No
8 Cellular and Molecular
Gastroenterology and Hepatology
United
States
21.6 8.8 48 Gastroenterology & Hepatology Elsevier No
9 International Journal of Molecular
Sciences
Switzerland 18.1 6.2 195 Biochemistry, Genetics and
Molecular Biology
MDPI Yes
10 Alimentary Pharmacology and
Therapeutics
United
Kingdom
18.0 9.5 186 Gastroenterology & Hepatology/
Pharmacology & Pharmacy
Wiley No
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org09

Additionally, SPEM-GC research has steadily grown in the last
two decades. According to Table 2, the United States contributed
to the most number of publications on SPEM-GC among the top
ten productive institutions, of which eight were from the United
States, one from Japan and one from South Korea. The United
States maintained its dominant position in SPEM-GC research
with a centrality of 0.47. We also found that Germany, the
United States, the United Kingdom and China played key roles
in the global collaboration of SPEM-GC research. China was
second to the United States as the largest issuer in this field, with
a total of 71 issues. Despite the low average citation rate of
Chinese scholars (van Eck et al., 2010), compared to the United
D
AB
C
FIGURE 5
Coupling and co-citation analysis of references. (A) Top 50 highly citing references cluster map. The node’ssizerepresentsthestrengthofthe
references, and the link indicates the correlation between them. Each node is colored according to the cluster in which the two papers cited the same
reference more frequently. (B) Time-overlay visualization map of the top 50 highly cited references. (C) The timeline shows all the co-cited references
related to SPEM-GC. Each horizontal line represents a cluster, and #0 represents the largest cluster. Co-cited frequencies are reflectedinnodesize,
and links indicate co-citation relationships. The color of the node and line represent different years. The nodes represent their first co-citation. (D) Graph
showing the top 25 references with the greatest citation bursts involved in SPEM-GC (sorted by beginning year). The blue bars indicate that the
reference has been published, and the red bars represent how citations have burst during the studies’publication.
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org10

States (Lei et al., 2013) and Japan (Katz et al., 2005), they have
gradually become a central region for research over the past few
years (Figure 2D).
Asoneofthetop10andco-citedauthors,JamesR.
Goldenring published the greatest number of SPEM-related
papers, indicating his prominent contribution to the field
(Table 3 and Figure 3A). The origin of precancerous lesions in
the stomach is the primary focus of Dr. Goldenring (Vanderbilt
University). Over the past decade, his team has produced
paradigm-shifting data proving that precancerous metaplasia
does not arise from altered stomach stem cells but develops from
the transdifferentiation of protein-secreting chief cells into
metaplastic mucous-producing cells (Goldenring et al;Nam
et al., 2010;Mills and Goldenring, 2017). They also studied
how immune cell populations (M2-macrophages and type II
innate lymphoid cells (ILC2s)) modulated the progression of
precancerous lesions from metaplasia to growth and
proliferative activity (Meyer et al., 2020). Mills Jason C., a
Baylor College of Medicine professor, was identified as one of
the most productive SPEM-GC authors and ranked in the top 10
and co-cited authors. His research focuses on multiple regulated
mechanisms involved in palingenesis during metaplasia and
cancer of the gastric lining. In 2022, James R. Goldenring and
Jason C. Mills (Goldenring and Mills, 2022). published an
important review summarizing SPEM cell regulation
mechanisms and pathophysiology in Gastroenterology.
According to their study, gastric glands with mixed incomplete
intestinal metaplasia and proliferative SPEM might be at greater
risk for cancer and dysplasia. In scenarios with chronic pyloric
and intestinal metaplasia, targeting early metaplastic lineages
could be an effective approach. According to the journal analysis
(Figure 4 and Table 4), Gastroenterology published the most
SPEM-GC studies, as well as the most cited ones, including 7 of
the top 10 highly cited articles (Judd et al., 2004;Katz et al., 2005;
Nozaki et al., 2008;Nam et al., 2010;Lei et al., 2013)(Table 6).
Among the top 3 published journals and top 5 co-cited journals,
TABLE 5 The top 10 citing references based on total link strength in SPEM-GC research.
Rank Title First
author Year Journal
Total
link
strength
Citations Cluster DOI
1Murine Models of Gastric Corpus
Preneoplasia
Christine
P. Petersen 2017
Cellular and
Molecular
Gastroenterology
and Hepatology
1468 47 1 10.1016/
j.jcmgh.2016.11.001
2
Cellular Plasticity, Reprogramming,
and Regeneration: Metaplasia in the
Stomach and Beyond
James R.
Goldenring 2022 Gastroenterology 1285 7 1 10.1053/
j.gastro.2021.10.036
3
Acid and the basis for cellular plasticity
and reprogramming in gastric repair
and cancer
JoseB.
Saenz 2018
Nature Reviews
Gastroenterology
& Hepatology
1226 54 1 10.1038/
nrgastro.2018.5
4Stem Cells, Self-Renewal and Cancer of
the Gastric Epithelium
Werner
Hoffmann 2012 Curr Med Chem 1086 20 2 10.2174/
0929867311209065975
5
Current understanding of SPEM and
its standing in the pre-neoplastic
process
Victoria G.
Weis 2009 Gastric Cancer 1008 87 3 10.1007/s10120-009-
0527-6
6Metaplasia in the Stomach—Precursor
of Gastric Cancer?
Hiroto
Kinoshita 2017 Int. J. Mol. Sci. 1006 40 1 10.3390/ijms18102063
7
Self-Renewal and Cancers of the
Gastric Epithelium: An Update and the
Role of the Lectin TFF1 as an Antral
Tumor Suppressor
Werner
Hoffmann 2022 Int. J. Mol. Sci. 974 0 4 10.3390/ijms23105377
8
Trefoil Factor Family (TFF) Peptides
and Their Diverse Molecular Functions
in Mucus Barrier Protection and More:
Changing the Paradigm
Werner
Hoffmann 2020 Int. J. Mol. Sci. 932 25 4 10.3390/ijms21124535
9Role of metaplasia during gastric
regeneration
Emma
Teal 2020
American Journal
of Physiology-
Cell Physiology
901 8 1 10.1152/
ajpcell.00415.2019
10 Trefoil factors: Gastrointestinal-specific
proteins associated with gastric cancer Ping Xiao 2015 Clinica Chimica
Acta 870 28 4 10.1016/
j.cca.2015.08.004
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org11

the American Journal of Pathology and Gut played an essential
role in research on SPEM-GC. These journals mainly focus on
studies from the Molecular, Biology and Genetics fields.
Altogether, these results were consistent with dual-map
analysis, which revealed that SPEM-GC research is currently
strongly focused on molecular biology and immunology.
In some instances, the knowledge base was represented
partly by co-cited references cited by scholars involved in
related research. There were four references in the top ten co-
cited references related to proliferation, differentiation and
precancerous changes within the stomach (Houghton et al.,
2004;Katz et al., 2005;Nozaki et al., 2008;Nam et al., 2010),
two that elaborated on trefoil factor1 or spasmolytic
polypeptides (Bossenmeyer-Pourie et al., 2002;Tebbutt et al.,
2002), two on gene regulations (Akiyama et al., 2003;Lei et al.,
2013), one on immunoregulation (Judd et al., 2004), and one on
the molecular mechanisms of gastric epithelial stem cells (Mills
and Shivdasani, 2011). Eight references were still in the burst
phase and deserve more attention, among which 5 papers
focused on SPEM cell proliferation and lineage transformation
(Burclaff et al., 2017;Engevik et al., 2016;Goldenring, 2018;
Leushacke et al., 2017;Radyk et al., 2018;Willet et al., 2018) and
3 were on mucosal immune regulation (Nozaki et al., 2008;
Petersen et al., 2017;Petersen et al., 2018), indicating that SPEM
had a significant impact on the research field of
gastric carcinogenesis.
4.2 The hotspots and frontiers
For researchers in this age of information explosion and
technology, it is essential to keep up with the latest trends in the
research field. In bibliometrics, keyword co-occurrences can
reflect the focus in specific areas, overlay and timeline views can
illustratethe evolution of new hotspots, and the emerging topics in
the discipline can be identified through reference clusters and
citation bursts (Liu et al., 2022;Li et al., 2022;Zhang et al., 2022a;
Yang et al., 2022). As part of this study, we examined reference
timeline and burst (Figures 5C,D), keyword overlay, co-
occurrence, timeline, burst (Figures 6A–C), KEGG (Figure 7B),
and GO annotations (Figure 7C) to evaluate the hotspots and
frontiers of SPEM-GC research. The 6 hotspots and frontiers of
SPEM-GC are discussed below.
TABLE 6 The top 10 globally cited documents based on total citations in SPEM-GC research.
Rank Title Document
Type
First
author Year Journal Citations DOI
1Gastric cancer originating from bone marrow-
derived cells In vivo study Houghton J 2004 Science 903 10.1126/
science.1099513
2
Reciprocal regulation of gastrointestinal
homeostasis by SHP2 and STAT-mediated trefoil
gene activation in gp130 mutant mice
In vivo study Tebbutt NC 2002 Nature medicine 382 10.1038/nm763
3
Identification of Molecular Subtypes of Gastric
Cancer With Different Responses to PI3-Kinase
Inhibitors and 5-Fluorouracil
Clinical
research Lei ZD 2013 Gastroenterology 284 10.1053/
j.gastro.2013.05.010
4
GATA-4 and GATA-5 transcription factor genes
and potential downstream antitumor target genes
are epigenetically silenced in colorectal and
gastric cancer
In vitro study
and clinical
research
Akiyama Y 2003 Mol Cell Biol 202
10.1128/
MCB.23.23.8429-
8439.2003
5
Loss of Klf4 in mice causes altered proliferation
and differentiation and precancerous changes in
the adult stomach
In vivo study Katz JP 2005 Gastroenterology 183 10.1053/
j.gastro.2005.02.022
6Mature chief cells are cryptic progenitors for
metaplasia in the stomach In vivo study Nam KT 2010 Gastroenterology 176 10.1053/
j.gastro.2010.09.005
7
The trefoil factor 1 participates in gastrointestinal
cell differentiation by delaying the G1-S phase
transition and reducing apoptosis
In vitro study Bossenmeyer-
Pourie C 2002 J Cell Biol 146 10.1083/
jcb200108056
8
Gastric cancer development in mice lacking the
SHP2 binding site on the IL-6 family co-receptor
gp130
In vivo study Judd LM 2004 Gastroenterology 141 10.1053/
j.gastro.2003.10.066
9 Gastric epithelial stem cells Review Mills JC 2011 Gastroenterology 131 10.1053/
j.gastro.2010.12.001
10 A molecular signature of gastric metaplasia
arising in response to acute parietal cell loss In vivo study Nozaki K 2008 Gastroenterology 124 10.1053/
j.gastro.2007.11.058
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org12

4.2.1 Lineage transformation of SPEM cells
A debated topic in SPEM cell development is the lineage
transformation of cells. Presently, there are three main
hypotheses: “Re-differentiation of chief cells”,“Proliferative of
stem cells”,and“Pre-metaplastic cells”. According to Nam et al.,
SPEM cells can express the chief cell marker Mist1 by cell lineage
tracing (Nam et al., 2010). A 2018 study by Radyk et al. reported
that tamoxifen induced SPEM cells despite that 5-FU inhibited
stem cell proliferation and their location overlapped with the
location of chief cells (Radyk et al., 2018). In acute and chronic
SPEM animal models, Goldenring et al. (Mills and Goldenring,
2017;Burclaff et al., 2020) found that chief cells in the deep part of
gastric mucosal glands could be reactivated for replication. It is
thought that mucosal inflammation induced mature differentiated
chief cells to convert into SPEM cells, which promoted the repair
of the gastric mucosa. However, this process changed the cell
structure and transcriptional profiles and increased the expression
of proliferative proteins like TFF2, MUC6 and CD44v9. This also
increased the possibility of cell carcinogenesis by entering the “cell
cycle hit mode”. However, most of the current research on chief
D
A
B
E
C
FIGURE 6
Analysis of trending topics and keywords. (A) The co-occurrence keywords with papers ≥9 (cluster map). The node’s size represents the
frequency of co-occurrence of the keywords, and the link indicates the correlation between keywords. Each node is colored according to the
cluster in which the two keywords occur most frequently, with the link thickness being proportional to that number. (B) The keywords’density
map drawn using VOSviewer. The word size, roundness and opacity of the orange color are positively correlated with frequency. (C) The SPEM-
GC timeline view of co-cited keywords. (D) Time-overlay visualization map of co-occurrence keywords. (E) SPEM-GC’s top 20 keywords with
the strongest citation bursts.
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org13

cell differentiation relies on animal models, and the hypothesis of
SPEM transdifferentiation is still controversial. Hayakawa et al.
(Kinoshita et al., 2017) reported in 2017 that the isthmus of the
gland might be a major location of acute SPEM proliferation. In
contrast, there was little proliferative activity at the gland’sbase,
which was contradictory to the “Re-differentiation of chief cells”
hypothesis. In addition to chief cell redifferentiation, stem cells
may also be a source of SPEM cells (Hayakawa et al., 2017). A new
hypothesis proposedby this study suggested that SPEM could be a
compensatory proliferative process following the loss of parietal
cells originating from the isthmus stem cells (Kinoshita et al.,
2018). Hata et al. (2020) determined that isthmic stem cells
transformed into “precursor SPEM cells”during chronic
inflammatory conditions using a G-protein-coupled form of
estrogen receptor protein (GPR30) labeling, thus refuting the
hypothesis of “Re-differentiation of chief cells”.In2020
Bockerstett et al. (Bockerstett et al., 2020;Bockerstett et al.,
2020) concluded that both stem cells and chief cells could
develop into SPEM under 10x single-cell detection. This pre-
metaplastic phenotype can be examined in patients with chronic
gastritis and SPEM model animals using a quasi-temporal analysis
of fundic glandular cells. In addition, SPEMs are hybrid stem/chief
cell phenotypes, that is, “Pre-metaplastic cells”.
4.2.2 H. pylori infection and SPEM
By analyzing the relevant literature in the past 20 years, we
found that H. pylori infection was the most important topic in
SPEM-GC research (Meyer and Goldenring, 2018;Yan et al.,
2022). A series of changes were reported following H. pylori
infection, including inflammatory cell infiltration, foveolar
hyperplasia, and loss of parietal cells in the gastric mucosa,
followed by the appearance of SPEM cells in the mucosa
(Yoshizawa et al., 2007). Sanchez et al. (Saenz et al., 2019)
research on the host epithelium showed that H. pylori could
bind to Lewis B (Leb) and Sialyl Lewis X (SLeX) receptors.
Tamoxifen combined with H. pylori infection induced chronic
SPEM in a mouse model by attaching to gastric epithelial cells
through blood group antigen-binding Adhesin (BabA) and Sialic
acid-binding Adhesion (SabA), respectively. Infection with H.
pylori promotes the proliferation and progression of SPEM cells,
resulting in a vicious cycle (Graham, 2014). Shimizu et al. (2016)
reported the development and morphological changes of
progressive SPEM glands expressing GSII in a Mongolian
gerbil model of H. pylori infection in 2016. They found that
multiple factors, including host and source of infection, played a
role in SPEM caused by H. pylori infection. Macrophages,
dendritic cells and T cells were induced to bind to H. pylori
through the p38/ERK1/2 pathway (Krueger et al., 2009;
Bernhardt et al., 2010). Studies with genetically engineered
mice found that Ctsz and CLDN18 could protect against
SPEM (Krueger et al., 2013;Hagen et al., 2018). Besides the
host factors discussed above, H. pylori virulence factors (e.g.,
CagA) might also contribute to SPEM development
(Wroblewski et al., 2010).
4.2.3 Mucosal microenvironmental
disturbances and SPEM
Aside from the above questions on the origin of proliferating
SPEM cells, their occurrence and progression are also hot topics
in this field. Petersen et al. (2018) illustrated in 2017 how IL-33
might act as an alarm signal to stimulate the type II
inflammatory response, thereby driving SPEM development.
Parietal cells produce key growth factors, such as dual
regulatory proteins, transforming growth factor alpha (TGFa),
TABLE 7 Clusters of co-cited keywords specialized in SPEM-GC research.
Cluster Color Theme Main frequent codes (total links > 50)
Prevailing
sub-categories
of clustering
analysis
1 Red
Expression of
gastric cancer
genes
gastric cancer (724), trefoil peptides (470), genes (344), ps2 (178), mucins (103), cancer cells
(100), prognosis (97), epidermal-growth-factor (86), invasion (86), methylation (83), activation
(79), tumor suppressor (70), messenger-rna (65), mutations (55)
#3 messenger-rna
#7 activation
#9 phospharylation
#10 dna methylation
#11 trefoil factor 1
2 Green
H. Pylori
Infection and
SPEM
h. pylori (748), spem (706), gastric (683), intestinal metaplasia (407), epithelial-cells (272), stem
cells (251), oxyntic atrophy (208), chief cells (202), parietal-cells (169), atrophic gastritis (114),
acid-secretion (93), infection (84), zymogenic cells (79), cdx2 (63), sonic hedgehog (62), nf-kappa-
b (59)
#0 spasmolytic
polypeptide-
expressing metaplasia
#1 oxyntic atrophy
#5 mucosa
#8 chief cell
3 Blue
Cell
differentiation
and
proliferation
cancer (476), carcinogenesis (215), inflammation (206), differentiation (200), identification (178),
biomarker (139), progenitor cells (88), progression (70), atrophy (68), proliferation (66)
#1 oxyntic atrophy
#5 mucosa
#6 cellular
differentiation
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org14

heparin-binding EGF-like growth factor (HB-EGF) and
hedgehog (Shh), which play a key role in SPE proliferation
and differentiation (Weis and Goldenring, 2009;Bernhardt et al.,
2010;Saenz and Mills, 2018). It was shown in a recent study that
the damaged gastric mucosa of SPEM mice and patients with
gastric precancerous lesions (GPL) exhibited type II
inflammatory reactions and increased the number of ILC2s
(Meyer et al., 2020). It was also demonstrated that the
suppression of A and B triggered the NF-B/MAPK signaling
pathway in GATA3+ ILC2s, inducing aggravating mucosal
immune damage and allowing SPEM to develop by
upregulating type II cytokines, including IL-13, IL-4, IL-5 and
IL-9 (Buzzelli et al., 2015;Liu et al., 2015;Bando and Colonna,
2020). Also, IL-13 released after acute parietal cell injury
activated macrophages into M2 macrophages and contributed
to SPEM production (De Salvo et al., 2021). It is crucial for
gastric mucosal cells to have M2 macrophages to upregulate
SPEM and IM-related genes, such as trefoil factor 3 (TFF3),
cystic fibrosis transmembrane regulator (CFTR) and deleted in
malignant brain tumors 1 (DMBT1), during metaplasia
progression (Choi et al., 2016;Meyer and Goldenring, 2018).
Thus, inhibiting the IL-33 or IL-13 cytokine pathway could
regulate macrophage polarization and be considered for
potentially treating GPL (Hayashi et al., 2012). In addition, it
has been found that the expression of structurally activated
Kirsten rat sarcoma viral oncogene (Kras) in chief cells could
promote M2 macrophage infiltration in the gastric mucosa,
aggravating the development of SPEM (Choi et al., 2016;
Goldenring and Mills, 2022). Previous studies have
demonstrated that chronic inflammation cytokines TLR9 and
A
B
C
FIGURE 7
Target genes and pathways annotated for SPEM-GC. (A) The 25 high-frequency genes. (B) KEGG pathway enrichment analysis results of 147
literature gene keywords. (C) GO functional annotation and enrichment analysis results of the literature gene keywords.
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org15

IFN-gdirectly induce apoptosis in gastric epithelial cells. They
also developed chronic atrophic gastritis and SPEM,
subsequently increasing their risk of SPEM-related
carcinogenesis (Osaki et al., 2019;Ding et al., 2022).
4.2.4 Progression and outcome of SPEM
The progression and outcome of SPEM lesions is also a
controversial topic. By clarifying the relationship between SPEM
and gastric cancer and precancerous lesions, the nature of SPEM
lesions can be accurately defined and then matched clinical
prevention and treatment. The accumulation of mutations in
long-lived mature cells can be viewed in basic research. Chief
cells found in areas of initial metaplasia foci were found to be the
most damaged. Upon accumulating a certain amount of
mutations, SPEM cells evolve into clonal forms of expansion,
becoming the cell of origin of dysplasia and even gastric cancer
(Saenz and Mills, 2018;Miao et al., 2021). Clinical study results
from Singapore showed that MUC5AC, KRAS, BRAF and EZH2
mistranslated mutations were more prevalent in SPEM, which
are more genetically similar to GC tissues (Srivastava et al.,
2020). Another retrospective cohort study from Iceland
(Halldorsdottir et al., 2003) reported 82% of preoperative
gastric mucosal biopsy specimens tested positive for SPEM,
which is significantly higher than IM (57%). Additionally,
SPEM models constructed from feline H. pylori-infected mice
were found to have more DNA mismatch repair gene defects
than normal gastric glands, consistent with genetic analyses of
precancerous tissues (Wang et al., 2014). During gastric
carcinogenesis, SPEM glands exhibit genetic instability because
the genetic properties of the source stem cells can accumulate
enough mutations to cause GC (Chen et al., 2020). The above
results provide indirect evidence that SPEM increases the risk of
carcinogenesis in precancerous tissues. Nevertheless, some
scholars, such as Graham et al. (Graham and Zou, 2018),
concluded that prior studies on SPEM’s progression to GC
were inconsistent, with limited clinical evidence based on
human tissues. Additionally, autoimmune gastritis can also
lead to SPEM with or without IM, whereas it rarely progresses
to GC.
4.2.5 Clinical diagnosis and biomarkers
for SPEM
SPEM is also known as pseudopyloric gland metaplasia,
mucinous metaplasia or corpus antrum metaplasia (Schmidt
et al., 1999;Saenz and Mills, 2018;Goldenring, 2018). SPEM
lesions usually occur in the deep part of the glandular duct in the
early stages of human gastric mucosa injury, making endoscopic
diagnosis difficult. Thus, discovering more sensitive, specific and
simple detection methods paves the way for subsequent clinical
interventions. Previous studies found that SPEM predominantly
co-expressed TFF2 and MUC6 (Bockerstett et al., 2020), and
since then, more relevant biomarkers have emerged over time. A
corpus-predominant gastritis index (CGI) was proposed by Tsai
et al. (2013) in 2013. According to relevant clinical studies, the
incidence of SPEM in CGI-positive patients was significantly
higher than in CGI-negative, suggesting that it can be used as an
early detection tool for precancerous lesions (Cheng et al., 2017).
As a follow-up to the above studies, Kuo et al. examined the
association between serum TFF2 levels and the expression of
miR-21, 155 and 223 in gastric mucosa for SPEM and reported
that the above molecules might have diagnostic values (Kuo
et al., 2017;Kuo et al., 2019). Subsequent studies successively
showed that GSII (Shimizu et al., 2016), CD44v9 (Bertaux-
Skeirik et al., 2017;Zavros, 2017), Clusterin (Vange et al.,
2017), SRY-related high mobility group box gene 9 (SOX9)
(Serizawa et al., 2016), human epididymis protein 4 (HE4)
(Nozaki et al., 2008;Jeong et al., 2021)andmyelinand
lymphocyte protein 2 (MAL2) (Weis et al., 2014)were
associated with the expression and proliferation of SPEM cells.
In recent studies, aquaporin 5 (AQP5), Trop2 and DDIT4 were
shown to reflect parietal cell loss and the severity of SPEM
development and could also predict a higher risk of GC (Riera
et al., 2020;Lee et al., 2021;Miao et al., 2021).
4.2.6 Construction of proliferative SPEM
model animals
Establishing a sustained and stable animal model of
proliferative SEPM is the basis for studying the pathogenesis
of SPEM. Since SPEM pathological evolution is a chronic
pathogenetic process, corresponding methods like H. pylori-
infected model take months to complete, which is not
conducive to studying gastritis and GC in humans (Li et al.,
2021). Animal models of acute SPEM induced by chemical drugs
are currently being used as an attempt to shorten modeling time,
including DMP-777 and L635, as well as the intraperitoneal
injection of tamoxifen, a selective estrogen receptor modulator at
high dose (Petersen et al., 2017). A loss of parietal cells can be
caused by any of the three methods, resulting in the formation of
SPEM at the stomach base of mice. DMP-777 is a cell-specific
inhibitor of neutrophil elastase that destroys parietal cells
without causing inflammatory reactions. Unlike DMP-777,
L635 exerts similar inflammatory effects to H. Felis infection
without elastase inhibitors, but it is expensive and difficult to
obtain. Similarly, reversible acute parietal cell injury was
observed in mice from high tamoxifen doses, but this model
did not cause gastric inflammation and recovered within three
weeks (Saenz et al., 2016;Lee et al., 2017;Meyer et al., 2020). It
must be noted that although the above drugs can induce SPEM,
the observed metaplasia is reversible and does not match the
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org16

chronic SPEM development in clinical situations. Hence, further
research is needed to explore a research model similar to chronic
SPEM in clinical settings.
4.3 Strengths and limitations
Overall, this present study represents the first bibliometric
analysis of SPEM-GC-related publications in the past two
decades. The presented type of analysis offers a fresh and
objective perspective on evolving research topics and trends,
which cannot be obtained through traditional reviews. As part of
the research, a multidimensional analysis was conducted using
various bibliometric software tools to provide more
comprehensive results for readers. As a comprehensive guide
for future developments in GC research, this study also provides
scholars with an overview on SPEM-GC research and an
objective guide for the public to understand the significance of
SPEM. However, there were some limitations in this study. First,
as only WoSCC data were used, it is possible that some relevant
studies in PubMed, Scopus and other databases were excluded,
resulting in incomplete data collection. However, it should be
noted that WoSCC indexes the largest number of articles,
ensuring source integrity. Additionally, high-quality articles
published in other languages were not considered due to the
focus on English-only articles. Lastly, due to methodological
limitations of the overall literature quality evaluation system,
some newly published high-quality documents might not have
been included in the bibliometrics analysis due to their low
citations and centrality.
4.4 Conclusion
We report the first bibliometric analysis summarizing the
knowledge map of research between SPEM and gastric cancer in
the last two decades and the potential future research hotspots.
We found that the United States had the most high-quality
publications and the greatest international cooperation and
communications. However, worldwide collaboration among
organizations needs to be improved. Additionally, although
SPEM could be identified through multiple biomolecular
markers as a possible source of GC, there is still a lack of
understanding on how SPEM contributes to the early detection
and treatment of cancer, indicating a potential research area and
discoveries in the future. The findings of this study can be used
as a guide for choosing research topics, defining the most
promising research frontiers, and selecting appropriate
journals for publication. Additionally, we provided
information to clinicians and practitioners on new approaches
and technologies that might enhance the treatment of H. pylori
infection-related gastric mucosal diseases and benefit
populations at high risk of developing GC.
Data availability statement
The original contributions presented in the study are
included in the article/Supplementary Material. Further
inquiries can be directed to the corresponding author.
Author contributions
XDT designed this study and revised the paper. LL, YW and YKZ
conducted data analysis and paper writing. LL and WZ performed the
bibliometric analyses. JL, PW and FYW made the figures and tables. All
authors contributed to the article and approved the submitted version.
Funding
The work was supported by the National Natural Science
Foundation of China (No. 82274511), China Academy of
Chinese Medical Sciences (CACMS) Innovation Fund (No.
CI2021A01004), and the Postdoctoral Research Foundation of
China (No. 2021M693541 and No. 2022T150731).
Acknowledgments
The authors thank Beijing Precise Health Biotechnology Co., Ltd
forprovidingtheRlanguagepack,whichwasusedinthispaper.The
company was not involved in the study design, collection, analysis,
interpretation of data, the writing of this article or the decision to submit
it for publication. All authors declare no other competing interests.
Conflict of interest
The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their affiliated organizations,
or those of the publisher, the editors and the reviewers. Any product
that may be evaluated in this article, or claim that may be made by its
manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/
fcimb.2022.1108378/full#supplementary-material
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org17

References
Ajani, J., Lee, J., Sano, T., Janjigian, Y., Fan, D., and Song, S. (2017). Gastric
adenocarcinoma. Nat. Rev. Dis. Primers. 3, 17036. doi: 10.1038/nrdp.2017.36
Akiyama, Y., Watkins, N., Suzuki, H., Jair, K. W., van Engeland, M., Esteller, M.,
et al. (2003). GATA-4 and GATA-5 transcription factor genes and potential
downstream antitumor target genes are epigenetically silenced in colorectal and
gastric cancer. Mol. Cell Biol. 23 (23), 8429–8439. doi: 10.1128/MCB.23.23.8429-
8439.2003
Bando, J. K., and Colonna, M. (2020). Group 2 innate lymphoid cells induce
antibody production in gastric tissue. Trends Immunol. 41 (8), 643–645. doi:
10.1016/j.it.2020.06.001
Bernhardt, A., Kuester, D., Roessner, A., Reinheckel, T., and Krueger, S. (2010).
Cathepsin X-deficient gastric epithelial cells in co-culture with macrophages:
characterization of cytokine response and migration capability after helicobacter
pylori infection. J. Biol. Chem. 285 (44), 33691–33700. doi: 10.1074/
jbc.M110.146183
Bertaux-Skeirik, N., Wunderlich, M., Teal, E., Chakrabarti, J., Biesiada, J., Mahe,
M., et al. (2017). CD44 variant isoform 9 emerges in response to injury and
contributes to the regeneration of the gastric epithelium. J. Pathol. 242 (4), 463–
475. doi: 10.1002/path.4918
Bockerstett, K. A., Lewis, S. A., Noto, C. N., Ford, E. L., Saenz, J. B., Jackson,
N. M., et al. (2020). Single-cell transcriptional analyses identify lineage-
specific epithelial responses to inflammation and metaplastic development
in the gastric corpus. Gastroenterology 159 (6), 2116–29.e4. doi: 10.1053/
j.gastro.2020.08.027
Bockerstett, K. A., Lewis, S. A., Wolf, K. J., Noto, C. N., Jackson, N. M., Ford, E.
L., et al. (2020). Single-cell transcriptional analyses of spasmolytic polypeptide-
expressing metaplasia arising from acute drug injury and chronic inflammation in
the stomach. Gut 69 (6), 1027–1038. doi: 10.1136/gutjnl-2019-318930
Bossenmeyer-Pourie, C., Kannan, R., Ribieras, S., Wendling, C., Stoll, I., Thim,
L., et al. (2002). The trefoil factor 1 participates in gastrointestinal cell
differentiation by delaying G1-s phase transition and reducing apoptosis. J. Cell
Biol. 157 (5), 761–770. doi: 10.1083/jcb200108056
Burclaff, J., Osaki, L. H., Liu, D., Goldenring, J. R., and Mills, J. C. (2017).
Targeted apoptosis of parietal cells is insufficient to induce metaplasia in stomach.
Gastroenterology 152 (4), 762–6.e7. doi: 10.1053/j.gastro.2016.12.001
Burclaff, J., Willet, S. G., Saenz, J. B., and Mills, J. C. (2020). Proliferation and
differentiation of gastric mucous neck and Chief cells during homeostasis and
injury-induced metaplasia. Gastroenterology 158 (3), 598–609.e5. doi: 10.1053/
j.gastro.2019.09.037
Buzzelli, J. N., Chalinor, H. V., Pavlic, D. I., Sutton, P., Menheniott, T. R., Giraud,
A. S., et al. (2015). IL33 is a stomach alarmin that initiates a skewed Th2 response to
injury and infection. Cell Mol. Gastroenterol. Hepatol. 1 (2), 203–21.e3. doi:
10.1016/j.jcmgh.2014.12.003
Chen, C. (2017). Science mapping: A systematic review of the literature. J. Data
Inf. Science 2 (2), 1–40. doi: 10.1515/jdis-2017-0006
Cheng, H. C., Tsai, Y. C., Yang, H. B., Yeh, Y. C., Chang, W. L., Kuo, H. Y., et al.
(2017). The corpus-predominant gastritis index can be an early and reversible
marker to identify the gastric cancer risk of helicobacter pylori-infected nonulcer
dyspepsia. Helicobacter. 22 (4), 1–8. doi: 10.1111/hel.12385
Chen, J., Zhu, C., Wang, C., Hu, C., Czajkowsky, D., Guo, Y., et al. (2020).
Evidence for heightened genetic instability in precancerous spasmolytic
polypeptide expressing gastric glands. J. Med. Genet 57 (6), 385–388. doi:
10.1136/jmedgenet-2018-105752
Choi, E., Hendley, A. M., Bailey, J. M., Leach, S. D., and Goldenring, J. R. (2016).
Expression of activated ras in gastric Chief cells of mice leads to the full spectrum of
metaplastic lineage transitions. Gastroenterology 150 (4), 918–30.e13. doi: 10.1053/
j.gastro.2015.11.049
Correa, P., Haenszel, W., Cuello, C., Tannenbaum, S., and Archer, M. (1975). A
model for gastric cancer epidemiology. Lancet 2 (7924), 58–60. doi: 10.1016/s0140-
6736(75)90498-5
De Salvo, C., Pastorelli, L., Petersen, C. P., Butto, L. F., Buela, K. A., Omenetti, S.,
et al. (2021). Interleukin 33 triggers early eosinophil-dependent events leading to
metaplasia in a chronic model of gastritis-prone mice. Gastroenterology 160 (1),
302–316.e7. doi: 10.1053/j.gastro.2020.09.040
Ding, L., Chakrabarti, J., Sheriff, S., Li, Q., Hong, H. N. T., Sontz, R. A., et al.
(2022). Toll like receptor 9 pathway mediates schlafen(+)-MDSC polarization
during helicobacter-induced gastric metaplasias. Gastroenterology 163 (2), 411–
425. doi: 10.1053/j.gastro.2022.04.031
Engevik, A. C., Feng, R., Choi, E., White, S., Bertaux-Skeirik, N., Li, J., et al.
(2016). The development of spasmolytic Polypeptide/TFF2-expressing metaplasia
(SPEM) during gastric repair is absent in the aged stomach. Cell Mol. Gastroenterol.
Hepatol. 2 (5), 605–624. doi: 10.1016/j.jcmgh.2016.05.004
Goldenring, J. R. (2018). Pyloric metaplasia, pseudopyloric metaplasia,
ulcerassociated cell lineage and spasmolytic polypeptide-expressing metaplasia:
Reparative lineages in the gastrointestinal mucosa J. Pathol. 245 (2), 132–137. doi:
10.1002/path.5066
Goldenring, J. R., Nam, K.T., and Mills, J. C. (2011). The origin of pre-neoplastic
metaplasia in the stomach: Chief cells emerge from the Mist. Exp. Cell Res. 317 (19),
2759–2764. doi: 10.1016/j.yexcr.2011.08.017
Goldenring, J., and Mills, J. (2022). Cellular plasticity, reprogramming, and
regeneration: Metaplasia in the stomach and beyond. Gastroenterology 162 (2),
415–430. doi: 10.1053/j.gastro.2021.10.036
Graham, D. (2014). History of helicobacter pylori, duodenal ulcer, gastric ulcer
and gastric cancer. World J. Gastroenterology 20 (18), 5191–5204. doi: 10.3748/
wjg.v20.i18.5191
Graham, D., and Zou, W. (2018). Guilt by association: intestinal metaplasia does
not progress to gastric cancer. Curr. Opin. Gastroenterology 34 (6), 458–464. doi:
10.1097/MOG.0000000000000472
Hagen, S. J., Ang, L. H., Zheng, Y., Karahan, S. N., Wu, J., Wang, Y. E., et al.
(2018). Loss of tight junction protein claudin 18 promotes progressive neoplasia
development in mouse stomach. Gastroenterology 155 (6), 1852–1867. doi:
10.1053/j.gastro.2018.08.041
Halldorsdottir, A. E., Sigurdardottir, M., Jonasson, J. G., Oddsdottir, M.,
Magnusson, J., Lee, J. R., et al. (2003). Spasmolytic polypeptide-expressing
Metaplasia(SPEM) associated with gastric cancerin Iceland. Digestive Dis. Sci. 48
(3), 431–441. doi: 10.1023/A:1022564027468
Hassan-Montero, Y., De-Moya-Anegon, F., and Guerrero-Bote, V. P. (2022).
SCImago graphica: A new tool for exploring and visually communicating data.
Profesional la informacion. 31 (5), e310502. doi: 10.3145/epi.2022.sep.02
Hata, M., Kinoshita, H., Hayakawa, Y., Konishi, M., Tsuboi, M., Oya, Y., et al.
(2020). GPR30-expressing gastric Chief cells do not dedifferentiate but are
eliminated via PDK-dependent cell competition during development of
metaplasia. Gastroenterology 158 (6), 1650–1666.e15. doi: 10.1053/
j.gastro.2020.01.046
Hayakawa, Y., Fox, J. G., and Wang, T. C. (2017). The origins of gastric cancer
from gastric stem cells: Lessons from mouse models. Cell Mol. Gastroenterol.
Hepatol. 3 (3), 331–338. doi: 10.1016/j.jcmgh.2017.01.013
Hayashi, D., Tamura, A., Tanaka, H., Yamazaki, Y., Watanabe, S., Suzuki, K.,
et al. (2012). Deficiency of claudin-18 causes paracellular h+ leakage, up-regulation
of interleukin-1beta, and atrophic gastritis in mice. Gastroenterology 142 (2), 292–
304. doi: 10.1053/j.gastro.2011.10.040
Hibdon, E. S., and Samuelson, L. C. (2018). Cellular plasticity in the stomach:
Insights into the cellular origin of gastric metaplasia. Gastroenterology 154 (4), 801–
803. doi: 10.1053/j.gastro.2018.02.001
Hoffmann, W. (2012). Self-renewal of the gastric epithelium from stem and
progenitor cells. Curr. Medicinal Chem. 19 (35), 5975–5983. doi: 10.2174/
0929867311209065975
Hoffmann, W. (2020). Trefoil factor family (TFF) peptides and their diverse
molecular functions in mucus barrier protection and more: Changing the
paradigm. Int. J. Mol. Sci. 21 (12), 1–20. doi: 10.3390/ijms21124535
Houghton, J., Stoicov, C., Nomura, S., Rogers, A. B., Carlson, J., Li, H., et al.
(2004). Gastric cancer originating from bone marrow-derived cells. Science 306
(5701), 1568–1571. doi: 10.1126/science.1099513
Jeong, H., Lee, B., Kim, K. H., Cho, S. Y., Cho, Y., Park, J., et al. (2021). WFDC2
promotes spasmolytic polypeptide-expressing metaplasia through the upregulation
of IL33 in response to injury. Gastroenterology 161 (3), 953–967. doi: 10.1053/
j.gastro.2021.05.058
Judd, L. M., Alderman, B. M., Howlett, M., Shulkes, A., Dow, C., Moverley, J.,
et al. (2004). Gastric cancer development in mice lacking the SHP2 binding site on
the IL-6 family co-receptor gp130. Gastroenterology 126 (1), 196–207. doi: 10.1053/
j.gastro.2003.10.066
Katz, J. P., Perreault, N., Goldstein, B. G., Actman, L., McNally, S. R., Silberg, D.
G., et al. (2005). Loss of Klf4 in mice causes altered proliferation and differentiation
and precancerous changes in the adult stomach. Gastroenterology 128 (4), 935–945.
doi: 10.1053/j.gastro.2005.02.022
Kinoshita, H., Hayakawa, Y., and Koike, K. (2017). Metaplasia in the stomach-
precursor of gastric cancer? Int. J. Mol. Sci. 18 (10), 1–6. doi: 10.3390/ijms18102063
Kinoshita, H., Hayakawa, Y., Niu, Z., Konishi, M., Hata, M., Tsuboi, M., et al.
(2018). Mature gastric chief cells are not required for the development of
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org18

metaplasia. Am. J. Physiol. Gastrointest Liver Physiol. 314 (5), G583–GG96. doi:
10.1152/ajpgi.00351.2017
Knowlson, C., Dean, A., Doherty, L., Fairhurst, C., Brealey, S., and Torgerson, D.
(2022). Recruitment patterns in multicentre randomised trials fit more closely to
price’s law than the pareto principle: A review of trials funded and published by the
united kingdom health technology assessment programme. Contemp. Clin. trials.
113, 106665. doi: 10.1016/j.cct.2021.106665
Kokol,P.,BlazunVosner,H.,andZavrsnik,J.(2021).Applicationof
bibliometrics in medicine: a historical bibliometrics analysis. Health Info Libr J.
38 (2), 125–138. doi: 10.1111/hir.12295
Kokol, P., Kokol, M., and Zagoranski, S. (2022). Machine learning on small size
samples: A synthetic knowledge synthesis. Sci. Prog. 105 (1), 368504211029777.
doi: 10.1177/036850421102977
Kokol, P., Zavrsnik, J., and Vosner, H. B. (2018). Bibliographic-based
identification of hot future research topics: An opportunity for hospital
librarianship. J. Hosp. Librarianship. 18 (4), 315–322. doi: 10.1080/
15323269.2018.1509193
Krueger, S., Bernhardt, A., Kalinski, T., Baldensperger, M., Zeh, M., Teller, A.,
et al. (2013). Induction of premalignant host responses by cathepsin x/z-deficiency
in helicobacter pylori-infected mice. PLoS One 8 (7), e70242. doi: 10.1371/
journal.pone.0070242
Krueger, S., Kuester, D., Bernhardt, A., Wex, T., and Roessner, A. (2009).
Regulation of cathepsin X overexpression in h. pylori-infected gastric epithelial
cells and macrophages. J. pathology. 217 (4), 581–588. doi: 10.1002/path.2485
Kuo, H., Chang, W., Yeh, Y., Cheng, H., Tsai, Y., Wu, C., et al. (2019).
Spasmolytic polypeptide-expressing metaplasia associated with higher
expressions of miR-21, 155, and 223 can be regressed by helicobacter pylori
eradication in the gastric cancer familial relatives. Helicobacter. 24 (3), e12578.
doi: 10.1111/hel.12578
Kuo, H. Y., Chang, W. L., Yeh, Y. C., Tsai, Y. C., Wu, C. T., Cheng, H. C., et al.
(2017). Serum level of trefoil factor 2 can predict the extent of gastric spasmolytic
polypeptide-expressing metaplasia in the h. pylori-infected gastric cancer relatives.
Helicobacter. 22 (1), 1–8. doi: 10.1111/hel.12320
Lee, S. H., Jang, B., Min, J., Contreras-Panta, E. W., Presentation, K. S., Delgado,
A. G., et al. (2021). Up-regulation of aquaporin 5 defines spasmolytic polypeptide-
expressing metaplasia and progression to incomplete intestinal metaplasia. Cell
Mol. Gastroenterol. Hepatol 13 (1), 199–217. doi: 10.1016/j.jcmgh.2021.08.017
Lee, C., Lee, H., Hwang, S. Y., Moon, C. M., and Hong, S. N. (2017). IL-10 plays a
pivotal role in tamoxifen-induced spasmolytic polypeptide-expressing metaplasia
in gastric mucosa. Gut Liver. 11 (6), 789–797. doi: 10.5009/gnl16454
Lei, Z., Tan, I. B., Das, K., Deng, N., Zouridis, H., Pattison, S., et al. (2013).
Identification of molecular subtypes of gastric cancer with different responses to
PI3-kinase inhibitors and 5-fluorouracil. Gastroenterology 145 (3), 554–565. doi:
10.1053/j.gastro.2013.05.010
Leushacke, M., Tan, S. H., Wong, A., Swathi, Y., Hajamohideen, A., Tan, L. T.,
et al. (2017). Lgr5-expressing chief cells drive epithelial regeneration and cancer in
the oxyntic stomach. Nat. Cell Biol. 19 (7), 774–786. doi: 10.1038/ncb3541
Liu, X., Cao, K., Xu, C., Hu, T., Zhou, L., Cao, D., et al. (2015). GATA-3
augmentation down-regulates Connexin43 in helicobacter pylori associated gastric
carcinogenesis. Cancer Biol. Ther. 16 (6), 987–996. doi: 10.1080/
15384047.2015.1030552
Liu, K., Zhao, S., Li, J., Zheng, Y., Wu, H., Kong, J., et al. (2022). Knowledge
mapping and research hotspots of immunotherapy in renal cell carcinoma: A text-
mining study from 2002 to 2021. Front. Immunol. 13, 969217. doi: 10.3389/
fimmu.2022.969217
Li, K., Wang, A., Liu, H., and Li, B. (2021). Protocol for chemically induced
murine gastric tumor model. STAR Protoc. 2 (4), 100814. doi: 10.1016/
j.xpro.2021.100814
Li, Q., Yang, W., Li, J., and Shan, Z. (2022). Emerging trends and hot spots in
autoimmune thyroiditis research from 2000 to 2022: A bibliometric analysis. Front.
Immunol. 13, 953465. doi: 10.3389/fimmu.2022.953465
Meyer, A. R., Engevik, A. C., Madorsky, T., Belmont, E., Stier, M. T., Norlander,
A. E., et al. (2020). Group 2 innate lymphoid cells coordinate damage response in
the stomach. Gastroenterology 159 (6), 2077–91.e8. doi: 10.1053/
j.gastro.2020.08.051
Meyer, A. R., and Goldenring, J. R. (2018). Injury, repair, inflammation and
metaplasia in the stomach. J. Physiol. 596 (17), 3861–3867. doi: 10.1113/JP275512
Miao, Z. F., Sun, J. X., Adkins-Threats, M., Pang, M. J., Zhao, J. H., Wang, X.,
et al. (2021). DDIT4 licenses only healthy cells to proliferate during injury-induced
metaplasia. Gastroenterology 160 (1), 260–71.e10. doi: 10.1053/j.gastro.2020.09.016
Mills, J. C., and Goldenring, J. R. (2017). Metaplasia in the stomach arises from
gastric Chief cells. Cell Mol. Gastroenterol. Hepatol. 4 (1), 85–88. doi: 10.1016/
j.jcmgh.2017.03.006
Mills,J.C.,andShivdasani,R.A.(2011).Gastricepithelialstemcells.
Gastroenterology 140 (2), 412–424. doi: 10.1053/j.gastro.2010.12.001
Nam, K. T., Lee, H. J., Mok, H., Romero-Gallo, J., Crowe, J. E.Jr., Peek, R. M.Jr.,
et al. (2009). Amphiregulin-deficient mice develop spasmolytic polypeptide
expressing metaplasia and intestinal metaplasia. Gastroenterology 136 (4), 1288–
1296. doi: 10.1053/j.gastro.2008.12.037
Nam, K. T., Lee, H. J., Sousa, J. F., Weis, V. G., O’Neal, R. L., Finke, P. E., et al.
(2010). Mature chief cells are cryptic progenitors for metaplasia in the stomach.
Gastroenterology 139 (6), 2028–37.e9. doi: 10.1053/j.gastro.2010.09.005
Nomura, S., Baxter, T., Yamaguchi, H., Leys, C., Vartapetian, A. B., Fox, J. G.,
et al. (2004). Spasmolytic polypeptide expressing metaplasia to preneoplasia in h.
felis-infected mice. Gastroenterology 127 (2), 582–594. doi: 10.1053/
j.gastro.2004.05.029
Nozaki, K., Ogawa, M., Williams, J. A., Lafleur, B. J., Ng, V., Drapkin, R. I., et al.
(2008). A molecular signature of gastric metaplasia arising in response to acute
parietal cell loss. Gastroenterology 134 (2), 511–522. doi: 10.1053/
j.gastro.2007.11.058
Osaki, L. H., Bockerstett, K. A., Wong, C. F., Ford, E. L., Madison, B. B., DiPaolo,
R. J., et al. (2019). Interferon-gamma directly induces gastric epithelial cell death
and is required for progression to metaplasia. J. Pathol. 247 (4), 513–523. doi:
10.1002/path.5214
Petersen, C. P., Meyer, A. R., De Salvo, C., Choi, E., Schlegel, C., Petersen, A.,
et al. (2018). A signalling cascade of IL-33 to IL-13 regulates metaplasia in the
mouse stomach. Gut 67 (5), 805–817. doi: 10.1136/gutjnl-2016-312779
Petersen, C. P., Mills, J. C., and Goldenring, J. R. (2017). Murine models of
gastric corpus preneoplasia. Cell Mol. Gastroenterol. Hepatol. 3 (1), 11–26. doi:
10.1016/j.jcmgh.2016.11.001
Pritchard, J. (1969). Statistical bibliography or bibliometrics? J. Documentation
25, 348–349.
Radyk, M. D., Burclaff, J., Willet, S. G., and Mills, J. C. (2018). Metaplastic cells in
the stomach arise, independently of stem cells, via dedifferentiation or
transdifferentiation of Chief cells . Gastroenterology 154 (4), 839–43.e2. doi:
10.1053/j.gastro.2017.11.278
Riera, K. M., Jang, B., Min, J., Roland, J. T., Yang, Q., Fesmire, W. T., et al.
(2020). Trop2 is upregulated in the transition to dysplasia in the metaplastic gastric
mucosa. J. Pathol. 251 (3), 336–347. doi: 10.1002/path.5469
Saenz, J. B., Burclaff, J., and Mills, J. C. (2016). Modeling murine gastric
metaplasia through tamoxifen-induced acute parietal cell loss. Methods Mol.
Biol. 1422, 329–339. doi: 10.1007/978-1-4939-3603-8_28
Saenz, J. B., and Mills, J. C. (2018). Acid and the basis for cellular plasticity and
reprogramming in gastric repair and cancer. Nat. Rev. Gastroenterol. Hepatol. 15
(5), 257–273. doi: 10.1038/nrgastro.2018.5
Saenz, J. B., Vargas, N., and Mills, J. C. (2019). Tropism for spasmolytic
polypeptide-expressing metaplasia allows helicobacter pylori to expand its
intragastric niche. Gastroenterology 156 (1), 160–74.e7. doi: 10.1053/
j.gastro.2018.09.050
Schmidt, P., Lee, J., Joshi, V., Playford, R., Poulsom, R., Wright, N., et al. (1999).
Identification of a metaplastic cell lineage associated with human gastric
adenocarcinoma. Lab. investigation; J. Tech. Methods pathology. 79 (6), 639–646.
Serizawa, T., Hirata, Y., Hayakawa, Y., Suzuki, N., Sakitani, K., Hikiba, Y., et al.
(2016). Gastric metaplasia induced by helicobacter pylori is associated with
enhanced SOX9 expression via interleukin-1 signaling. Infect. Immun. 84 (2),
562–572. doi: 10.1128/IAI.01437-15
Shimizu, T., Choi, E., Petersen, C. P., Noto, J. M., Romero-Gallo, J., Piazuelo, M.
B., et al. (2016). Characterization of progressive metaplasia in the gastric corpus
mucosa of Mongolian gerbils infected with helicobacter pylori. J. Pathol. 239 (4),
399–410. doi: 10.1002/path.4735
Smyth, E., Nilsson, M., Grabsch, H., van Grieken, N., and Lordick, F. (2020).
Gastric cancer. Lancet (London England). 396 (10251), 635–648. doi: 10.1016/
S0140-6736(20)31288-5
Srivastava, S., Huang, K. K., Rebbani, K., Das, K., Fazreen, Z., Yeoh, K. G., et al.
(2020). An LCM-based genomic analysis of SPEM, gastric cancer and pyloric gland
adenoma in an Asian cohort. Mod Pathol. 33 (10), 2075–2086. doi: 10.1038/
s41379-020-0520-5
Synnestvedt, M., Chen, C., and Holmes, J. (2005). CiteSpace II: visualization and
knowledge discovery in bibliographic databases. AMIA Annu. Symposium Proc.
AMIA Symposium. 724–728.
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org19

Tebbutt, N. C., Giraud, A. S., Inglese, M., Jenkins, B., Waring, P., Clay, F. J., et al.
(2002). Reciprocal regulation of gastrointestinal homeostasis by SHP2 and STAT-
mediated trefoil gene activation in gp130 mutant mice. Nat. Med. 8 (10), 1089–
1097. doi: 10.1038/nm763
Tsai, Y., Hsiao, W., Yang, H., Cheng, H., Chang, W., Lu, C., et al. (2013). The
corpus-predominant gastritis index may serve as an early marker of helicobacter
pylori-infected patients at risk of gastric cancer. Alimentary Pharmacol. Ther. 37
(10), 969–978. doi: 10.1111/apt.12291
van Eck, N., and Waltman, L. (2010). Software survey: VOSviewer, a computer
program for bibliometric mapping. Scientometrics. 84 (2), 523–538. doi: 10.1007/
s11192-009-0146-3
van Eck, N. J., Waltman, L., Dekker, R., and van den Berg, J. (2010). A comparison
of two techniques for bibliometric mapping: Multidimensional scaling and VOS. J.
Am. Soc. Inf. Sci. Technol. 61 (12), 2405–2416. doi: 10.1002/asi.21421
Vange, P., Bruland, T., Doseth, B., Fossmark, R., Sousa, M. M. L., Beisvag, V.,
et al. (2017). The cytoprotective protein clusterin is overexpressed in
hypergastrinemic rodent models of oxyntic preneoplasia and promotes gastric
cancer cell survival. PLoS One 12 (9), e0184514. doi: 10.1371/journal.pone.0184514
Wang, K., Yuen, S., Xu, J., Lee, S., Yan, H., Shi, S., et al. (2014). Whole-genome
sequencing and comprehensive molecular profiling identify new driver mutations
in gastric cancer. Nat. Genet 46 (6), 573–582. doi: 10.1038/ng.2983
Weis, V. G., and Goldenring, J. R. (2009). Current understanding of SPEM and
its standing in the pre-neoplastic process. Gastric Cancer. 12 (4), 189–197. doi:
10.1007/s10120-009-0527-6
Weis, V., Petersen, C., Mills, J., Tuma, P., Whitehead, R., and Goldenring, J.
(2014). Establishment of novel in vitro mouse chief cell and SPEM cultures
identifies MAL2 as a marker of metaplasia in the stomach. Am.J.Physiol.
Gastrointestinal liver Physiol. 307 (8), G777–G792. doi: 10.1152/ajpgi.00169.2014
Willet, S. G., Lewis, M. A., Miao, Z. F., Liu, D., Radyk, M. D., Cunningham, R. L.,
et al. (2018). Regenerative proliferation of differentiated cells by mTORC1-
dependent paligenosis. EMBO J. 37 (7), 1–17. doi: 10.15252/embj.201798311
Wroblewski, L. E., Peek, R. M.Jr., and Wilson, K. T. (2010). Helicobacter pylori
and gastric cancer: factors that modulate disease risk. Clin. Microbiol. Rev. 23 (4),
713–739. doi: 10.1128/CMR.00011-10
Yan, L., Chen, Y., Chen, F., Tao, T., Hu, Z., Wang, J., et al. (2022). Effect of
helicobacter pylori eradication on gastric cancer prevention: Updated report from a
randomized controlled trial with 26. 5 Years Follow-up. Gastroenterol. 163 (1), 154–
62.e3. doi: 10.1053/j.gastro.2022.03.039
Yang, S., Zhao, S., Ye, Y., Jia, L., and Lou, Y. (2022). Global research trends on
the links between gut microbiota and cancer immunotherapy: A bibliometric
analysis (2012-2021). Front. Immunol. 13, 952546. doi: 10.3389/
fimmu.2022.952546
Yoshizawa, N., Takenaka, Y., Yamaguchi, H., Tetsuya, T., Tanaka, H.,
Tatematsu, M., et al. (2007). Emergence of spasmolytic polypeptide-expressing
metaplasia in Mongolian gerbils infected with helicobacter pylori. Lab. Invest. 87
(12), 1265–1276. doi: 10.1038/labinvest.3700682
Zavros, Y. (2017). Initiation and maintenance of gastric cancer: A focus on
CD44 variant isoforms and cancer stem cells. Cell Mol. Gastroenterol. Hepatol. 4
(1), 55–63. doi: 10.1016/j.jcmgh.2017.03.003
Zhang,J.,Chen,P.,andMiao,L.(2022a).Abibliometricandscientific
knowledge-map study of the chimeric antigen receptor (CAR) natural killer
(NK) cell-related research from 2010 to 2022. Front. Immunol. 13, 969196. doi:
10.3389/fimmu.2022.69196
Zhang, J., Song, L., Jia, J., Tian, W., Lai, R., Zhang, Z., et al. (2022b). Knowledge
mapping of necroptosis from 2012 to 2021: A bibliometric analysis . Front.
Immunol. 13, 917155. doi: 10.3389/fimmu.2022.917155
Liu et al. 10.3389/fcimb.2022.1108378
Frontiers in Cellular and Infection Microbiology frontiersin.org20