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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Oncol.</journal-id>
<journal-title>Frontiers in Oncology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Oncol.</abbrev-journal-title>
<issn pub-type="epub">2234-943X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fonc.2021.745209</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Oncology</subject>
<subj-group>
<subject>Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Metabolic Reprogramming in Gastric Cancer: Trojan Horse Effect</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Bin</surname>
<given-names>Yu-Ling</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1410229"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hu</surname>
<given-names>Hong-Sai</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Tian</surname>
<given-names>Feng</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1429015"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wen</surname>
<given-names>Zhen-Hua</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1429020"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yang</surname>
<given-names>Mei-Feng</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wu</surname>
<given-names>Ben-Hua</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1475655"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Li-Sheng</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yao</surname>
<given-names>Jun</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Li</surname>
<given-names>De-Feng</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1169039"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Gastroenterology, Shenzhen People&#x2019;s Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology)</institution>, <addr-line>Shenzhen</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Rheumatology and Immunology, ZhuZhou Central Hospital</institution>, <addr-line>Zhuzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Gastroenterology, ZhuZhou Central Hospital</institution>, <addr-line>Zhuzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Hematology, Yantian District People&#x2019;s Hospital</institution>, <addr-line>Shenzhen</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Elisa Giommoni, Careggi University Hospital, Italy</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Tania Fiaschi, Universit&#xe0; degli Studi di Firenze, Italy; Arun Upadhyay, Northwestern University, United States</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: De-Feng Li, <email xlink:href="mailto:ldf830712@163.com">ldf830712@163.com</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Gastrointestinal Cancers: Gastric Esophageal Cancers, a section of the journal Frontiers in Oncology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>12</day>
<month>01</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>11</volume>
<elocation-id>745209</elocation-id>
<history>
<date date-type="received">
<day>21</day>
<month>07</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>12</day>
<month>11</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Bin, Hu, Tian, Wen, Yang, Wu, Wang, Yao and Li</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Bin, Hu, Tian, Wen, Yang, Wu, Wang, Yao and Li</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>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.</p>
</license>
</permissions>
<abstract>
<p>Worldwide, gastric cancer (GC) represents the fifth most common cancer for incidence and the third leading cause of death in developed countries. Despite the development of combination chemotherapies, the survival rates of GC patients remain unsatisfactory. The reprogramming of energy metabolism is a hallmark of cancer, especially increased dependence on aerobic glycolysis. In the present review, we summarized current evidence on how metabolic reprogramming in GC targets the tumor microenvironment, modulates metabolic networks and overcomes drug resistance. Preclinical and clinical studies on the combination of metabolic reprogramming targeted agents and conventional chemotherapeutics or molecularly targeted treatments [including vascular endothelial growth factor receptor (VEGFR) and HER2] and the value of biomarkers are examined. This deeper understanding of the molecular mechanisms underlying successful pharmacological combinations is crucial in finding the best-personalized treatment regimens for cancer patients.</p>
</abstract>
<kwd-group>
<kwd>gastric cancer</kwd>
<kwd>glycolysis</kwd>
<kwd>metabolic reprogramming</kwd>
<kwd>tumor microenvironment</kwd>
<kwd>drug resistance</kwd>
</kwd-group>
<counts>
<fig-count count="3"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="171"/>
<page-count count="14"/>
<word-count count="5696"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Gastric cancer (GC) is currently the third leading cause of cancer-related death globally and varies significantly among different geographical areas, despite the overall morbidity and mortality are declining (<xref ref-type="bibr" rid="B1">1</xref>). Surgery is an effective option for the treatment of GC, while patients with advanced GC lose the best opportunity of surgery due to multiple metastasis (<xref ref-type="bibr" rid="B2">2</xref>). Compared with other primary tumors, GC with multiple metastases has higher tissue heterogeneity, which is caused by multiple specific gene clusters or gene mutations (<xref ref-type="bibr" rid="B3">3</xref>). Therefore, GC displays aggressive behavior and treatment resistance, bringing great difficulties for the development of molecular targeted drugs and individualized precise treatment. Moreover, based on the molecular classification of The Cancer Genome Atlas (TCGA), GC encompasses different molecular subtypes, such as Epstein&#x2013;Barr virus (EBV 9%), microsatellite instability (MSI 22%), genomic stable (20%), and chromosomal instability (50%), and often exhibits a poor and unfavorable prognosis (<xref ref-type="bibr" rid="B4">4</xref>).</p>
<p>It has become clear enough that a single cancer hallmark (e.g., self-sufficiency in growth signals, insensitivity to antigrowth signals, evading apoptosis, limitless replicative potential, sustained angiogenesis, and tissue invasion and metastasis) cannot be used to globally define tumor alteration (<xref ref-type="bibr" rid="B5">5</xref>). As early as last century, Warburg found that owing to uninterrupted growth, tumor cells would reprogram their metabolism production network by circumventing mitochondrial oxidative phosphorylation and facilitating aerobic glycolysis to maintain the normal levels of ATP and NADH (<xref ref-type="bibr" rid="B6">6</xref>). Metabolic reprogramming, including the remodeling of glucose, lipid, glutamine, oxidative phosphorylation, and mitochondrial respiration (<xref ref-type="bibr" rid="B7">7</xref>), plays a pivotal role in the regulation of gene transcription, DNA damage repair, and metabolic enzymes, to transmit or release cytokines through signaling pathways in the tumor microenvironment (TME). Accumulating evidence indicates that cancer cells may transfer biologically functional molecules to their surrounding stromal cells by reprogramming metabolism, which facilitates cancer metastasis, drug resistance, and immunosuppression (<xref ref-type="bibr" rid="B8">8</xref>&#x2013;<xref ref-type="bibr" rid="B10">10</xref>). If this series of cancer cells disorders are regarded as energy metabolism alteration, limiting energy currency ATP and redox currency NADH can be achieved by using small molecule drugs targeting energy metabolism or cutting off the metabolic pathway of energy supply. Similar to the Trojan horse effect, by targeting metabolic changes, we can identify potential new targets for accurate cancer treatment and design antitumor strategies to improve the concentration of drugs into cells. Therefore, metabolic reprogramming has become a promising target in cancer therapy, including refractory cancers such as GC.</p>
<p>Alterations in amino acid synthesis and catabolism, lipid biogenesis, and other pathways such as polyamine processing, are commonly seen in GC (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>). However, the development of GC and TME forms a complex loop, and the specific mechanism underlying its metabolic reprogramming remains largely unexplored. The present review outlines recent updates, addressing how bioenergetic metabolism reprogramming is involved in GC, aiming to better understand their role in the GC progression, which might help develop new therapeutic approaches by targeting GC metabolism.</p>
</sec>
<sec id="s2">
<title>Characteristics of Metabolic Reprogramming in GC</title>
<p>Malignant tumors have the common characteristics of high metabolism. However, epigenetic changes, tissue origin, differentiation status, and other internal and external factors such as oxygen and nutrients in tumor microcirculation result in a unique metabolic profile that distinguishes cancer cells from normal cells (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Reprogramming of the tumor metabolism includes upregulation of aerobic glycolysis, a strongly enhanced glutaminyl, and lipid accumulation in tumor cells, potentially providing energy and structural requirements for the development of cancer cells (<xref ref-type="fig" rid="f1">
<bold>Figures&#xa0;1A, B</bold>
</xref>
<bold>) (</bold>
<xref ref-type="bibr" rid="B23">23</xref>). However, effective stratification strategies and selection of predictive biomarkers for personalized medicine are currently limited. GC, as a heterogeneous disease, lacks specific symptoms in its early stages, leading to a delayed diagnosis with three-quarters of patients presenting with non-curable advanced disease (<xref ref-type="bibr" rid="B24">24</xref>). Moreover, the energy metabolism reprogramming of GC has its own characteristics due to the heterogeneity. For instance, six metabolites (alanine, &#x3b1;-ketoisocaproic acid, proline, glycerin acid, pantothenic acid, and adenosine) show varying expression levels between GC cell lines and a normal gastric epithelial cell line (<xref ref-type="bibr" rid="B25">25</xref>). In particular, genome-wide expression profiles have found that an intestinal subtype of gastric tumors is involved in glucose metabolism and glutamine metabolism-related gene, and glucose transport and glucan related to metabolic genes are enriched in the diffuse subtype of GC (<xref ref-type="bibr" rid="B26">26</xref>). Therefore, it is urgently necessary to integrate clinical, morphological, and molecular data by identifying key metabolic processes of GC for the patient stratification for personalized therapy.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Biomarker of metabolic reprogramming in GC.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left"/>
<th valign="top" align="center">Biomarker</th>
<th valign="top" align="center">Function</th>
<th valign="top" align="center">Locations</th>
<th valign="top" align="center">Impactions in GC</th>
<th valign="top" align="center">Clinical Significance in GC</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="3" align="left">
<bold>Aerobic glycolysis</bold>
</td>
<td valign="top" align="left">GLUT 3 (<xref ref-type="bibr" rid="B12">12</xref>)</td>
<td valign="top" align="left">Rate-limiting glucose transport</td>
<td valign="top" align="left">Cytoplasm</td>
<td valign="top" align="left">Infiltration and polarization in GC TAM</td>
<td valign="top" align="left">TNM stage, DFS, OS</td>
</tr>
<tr>
<td valign="top" align="left">ENO1 (<xref ref-type="bibr" rid="B13">13</xref>)</td>
<td valign="top" align="left">Catalyzing the conversion of 2-PG to PEP</td>
<td valign="top" align="left">Cytoplasm, Cell membrane</td>
<td valign="top" align="left">Regulation the stem cell-like characteristics</td>
<td valign="top" align="left">Infiltration depth, Stage, OS</td>
</tr>
<tr>
<td valign="top" align="left">GRINA (<xref ref-type="bibr" rid="B14">14</xref>)</td>
<td valign="top" align="left">Glutamate Receptor</td>
<td valign="top" align="left">Membrane</td>
<td valign="top" align="left">Enhancing the glycolytic metabolism</td>
<td valign="top" align="left">Histological differentiation, TNM stage, Metastasis, Vessel invasion, perineuronal invasion</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="left">
<bold>Glutamine consumption</bold>
</td>
<td valign="top" align="left">SLC1A3 (<xref ref-type="bibr" rid="B15">15</xref>)</td>
<td valign="top" align="left">Glutamate transporter</td>
<td valign="top" align="left">Mitochondria, Nuclear</td>
<td valign="top" align="left">Increasing aspartate import in hypoxia</td>
<td valign="top" align="left">Histological differentiation, TNM stage</td>
</tr>
<tr>
<td valign="top" align="left">GGCT (<xref ref-type="bibr" rid="B16">16</xref>)</td>
<td valign="top" align="left">Catalyzing the &#x3b3;-glutamyl peptides to generates 5-oxoproline and free AAs</td>
<td valign="top" align="left">Cytosol, Extracellular exosome</td>
<td valign="top" align="left">Inhibition cell proliferation and inducing apoptosis (<xref ref-type="bibr" rid="B17">17</xref>)</td>
<td valign="top" align="left">Histological grade, LNM, TNM stage</td>
</tr>
<tr>
<td valign="top" align="left">SLC1A5 (<xref ref-type="bibr" rid="B18">18</xref>)</td>
<td valign="top" align="left">Glutamine transporter</td>
<td valign="top" align="left">Plasma membrane</td>
<td valign="top" align="left">Inhibition of glutamine synthetase to reduce GC cell proliferation and resistance</td>
<td valign="top" align="left">Local invasion, LNM, TNM stages, Ki-67 expression</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="left">
<bold>Lipid biosynthesis</bold>
</td>
<td valign="top" align="left">SCD-1 (<xref ref-type="bibr" rid="B19">19</xref>)</td>
<td valign="top" align="left">Conversion of saturated FAs to monounsaturated FA</td>
<td valign="top" align="left">Endoplasmic reticulum membrane</td>
<td valign="top" align="left">Enhancing the tumor growth, migration, anti-ferroptosis</td>
<td valign="top" align="left">TNM stage, LNM, OS,</td>
</tr>
<tr>
<td valign="top" align="left">LPCAT1 (<xref ref-type="bibr" rid="B20">20</xref>)</td>
<td valign="top" align="left">Composition of plasma membrane<break/>(<xref ref-type="bibr" rid="B21">21</xref>)</td>
<td valign="top" align="left">Endoplasmic reticulum membrane.</td>
<td valign="top" align="left">The conversion of LPC to PC</td>
<td valign="top" align="left">Tumor depth, LNM, TNM stage</td>
</tr>
<tr>
<td valign="top" align="left">Rev-erb&#x3b1; (<xref ref-type="bibr" rid="B22">22</xref>)</td>
<td valign="top" align="left">Lipid metabolism nuclear receptor</td>
<td valign="top" align="left">Nucleus, Cytoplasm</td>
<td valign="top" align="left">The inhibition of proliferation by reducing glycolytic flux and PPP</td>
<td valign="top" align="left">TMN stage</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>2-PG, 2-phosphoglycerate; PEP, phosphoenolpyruvate; FAs, Fatty acids; AAs, amino acids; LNM, lymph node metastasis; PPP, pentose phosphate pathway.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Schematic showing a comparative account of normal <italic>vs.</italic> cancer cell metabolic reprogramming <bold>(A)</bold>. The association between aerobic glycolysis (Warburg effect) and the glutamine metabolism and fatty acids metabolism. Biomarkers in GC (indicated in green boxes) along with signaling molecules (orange circles). Next, the mitochondrial dysfunction or phenotypic alteration <bold>(B)</bold>. AA, amino acid; CoA, coenzyme A; ENO1, enolase 1; F-6-P, fructose 6-phosphate; FA, fatty acids; G-6-P, glucose-6-phosphate; GGCT, glutamylcyclo transferase; GLUT3, glucose transporter3; GRINA, glutamate receptor; GLS, glutaminase1; HK2, hexokinase2; LDHA, lactate dehydrogenase; LPC, lysophosphatidylcholine; LPCAT1, lysophosphatidylcholine acyltransferase; MUFA, multiunsaturated fatty acid; PEP, phosphoenolpyruvate; PFK1, phosphofructokinase1; PC, phosphatidylcholine; PFKFB3, phosphofructokinase-2/fructose-2,6 bisphosphatase 3; PKM2, pyruvate kinase2; SFA, saturated fatty acids; SCD-1, stearoyl-CoA desaturase 1; TCA, tricarboxylic acid cycle. Dotted lines indicate the feed-back inhibition/regulation of some of the glycolytic enzymes by corresponding metabolites.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-745209-g001.tif"/>
</fig>
<sec id="s2_1">
<title>Aerobic Glycolysis</title>
<p>Aerobic glycolysis is the process of oxidation of glucose into pyruvate, followed by lactate production under normoxic conditions, which promotes glutaminolysis to satisfy the precursor requirements of nucleic acids (<xref ref-type="bibr" rid="B27">27</xref>). The upregulation of glycolysis is mostly due to the increased expressions of enzymes and transporters involved in glucose uptake, lactate production, and lactate secretion (<xref ref-type="bibr" rid="B28">28</xref>). <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref> outlines the stepwise process of glycolysis, including the substrates and enzymes of the pathway. The glucose uptake of cells largely depends on the concentration of membrane transport proteins collectively known as the glucose transporter (GLUT) family. Significantly, GLUT 3, acting as a biomarker to determine prognosis and immune infiltration in GC, not only potentially contributes to M2 subtype transition of macrophages in the TME by mediating glucose influx (<xref ref-type="bibr" rid="B12">12</xref>) but also is correlated with higher tumor&#x2013;node&#x2013;metastasis (TNM) stage and negative survival (<xref ref-type="bibr" rid="B29">29</xref>). Moreover, glycolytic enzyme Enolase 1 (ENO1), as a poor prognosis biomarker in GC (<xref ref-type="bibr" rid="B13">13</xref>), which is involved in hypoxia, increases glucose uptake and metabolism <italic>via</italic> upregulating GLUT3 and promoting the lactate production (<xref ref-type="bibr" rid="B30">30</xref>). The molecular mechanisms of metabolic reprogramming in GC have been applied in clinical practice. For example, a study consisting of 279 patients routinely staged in the absence of metastases on CT has identified previously unsuspected metastases in 7% of patients using F-18 fluorodeoxyglucose, which would likely not have been identified by conventional staging without PET-CT in 5% (<xref ref-type="bibr" rid="B31">31</xref>).</p>
</sec>
<sec id="s2_2">
<title>Glutamine</title>
<p>Glutamine, a new energy source for tumor cells, provides nitrogen and carbon sources that replenish tricarboxylic acid (TCA) cycle intermediates for the sake of nucleic acids. Glutamine is first converted to glutamate and ammonium by glutaminase (GLS). Subsequently, it is catalyzed by glutamate dehydrogenase (GDH) and converted to &#x3b1;- ketoglutarate (<xref ref-type="bibr" rid="B32">32</xref>). Then, &#x3b1;-ketoglutarate enters the TCA cycle, which provides energy and macromolecular intermediates, as seen in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>. The combination of GLS1 and glutamyl cyclotransferase (GGCT) is highly sensitive and specific for detecting GC, which is strongly associated with histological grade, lymph node metastasis, and TNM stage (<xref ref-type="bibr" rid="B16">16</xref>). The SLC1 family (glutamate transporters) plays important roles in providing cells throughout the body with glutamate for metabolic purposes (<xref ref-type="bibr" rid="B33">33</xref>). For example, the loss of function of SLC1A3 (GLAST) and SLC1A5 (also known as ASCT2 or Na-dependent transmembrane transporter) has been implicated in the pathogenesis of GC. SLC1A3 is positively associated with the poor prognosis, and it provides a competitive advantage to GC, increasing aspartate import under the hypoxic condition (<xref ref-type="bibr" rid="B15">15</xref>). SLC1A5 is correlated with malignant features, such as deeper local invasion, higher lymph node metastasis, advanced TNM stages, and higher Ki-67 expression (<xref ref-type="bibr" rid="B18">18</xref>). However, the inhibition of glutamine synthetase remarkably reduces the proliferation and resistance of GC cells, suggesting that glutamine mediates GC growth and the therapeutic efficacy of targeted treatment (<xref ref-type="bibr" rid="B34">34</xref>). Interestingly, as a glutamate receptor, the N-methyl D-aspartate-associated protein 1 (GRINA) is involved in lipid and sterol synthesis (<xref ref-type="bibr" rid="B35">35</xref>), and it also modulates aerobic glycolysis and promotes tumor progression in GC (<xref ref-type="bibr" rid="B14">14</xref>).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>TME comprising the tumor cells and various stromal cells in GC. They evade immune surveillance during GC progression by balancing energy requirements and in TME. Finally, the metabolites of TME impacts cancer-specific or related phenotypes. Apo E, apolipoprotein E; Ado, adenosine; Oxd, oxidation; PPP, pentose phosphate pathway; ROS, reactive oxygen species; TAM, tumor-associated macrophages.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-745209-g002.tif"/>
</fig>
</sec>
<sec id="s2_3">
<title>Fatty Acids</title>
<p>Fatty acids (FAs, as molecule signals and energy sources, are important as the basic backbone of many lipids and generally recognized as part of the metabolic landscape of cancer (<xref ref-type="bibr" rid="B36">36</xref>). The <italic>de novo</italic> FA synthesis pathway is enhanced to glucose and glutamine metabolism in tumor cells (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>) <bold>(</bold>
<xref ref-type="bibr" rid="B11">11</xref>). Strikingly, FA metabolisms, FA transport, and fat differentiation-related signatures are also highly activated in GC (<xref ref-type="bibr" rid="B26">26</xref>). Stearoyl-CoA desaturase 1 (SCD-1), which converts saturated FAs into monounsaturated FAs, is overexpressed and exhibits the ability to promote tumor growth, migration, and anti-ferroptosis in GC (<xref ref-type="bibr" rid="B19">19</xref>). Lysophosphatidylcholine acyltransferase 1 (LPCAT1) is involved in the metastasis and recurrence of GC (<xref ref-type="bibr" rid="B20">20</xref>), especially in converting lysophosphatidylcholine (LPC) to phosphatidylcholine (PC), which is positively correlated with tumor differentiation but negatively correlated with tumor depth, lymph node metastasis, and tumor stage in GC (<xref ref-type="bibr" rid="B37">37</xref>). interestingly, Rev-erb&#x3b1; (nuclear receptor subfamily 1 group D member 1) regulates lipid metabolism nuclear receptor, and it is not only associated with TMN stages but also its reduction causes GC progression by augmenting the glycolysis (<xref ref-type="bibr" rid="B22">22</xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Shift in metabolic networks in GC. The metabolic intermediates of metabolic reprogramming are associated with diverse pathways in the cells inside and outside. HP, <italic>H. pylori</italic>; MCT, monocarboxylate channel transporter.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-745209-g003.tif"/>
</fig>
<p>Based on the TCGA dataset, a signature consisting of seven&#xa0;glycolysis genes (STC1, CLDN9, EFNA3, ZBTB7A, NT5E, NUP50, and CXCR4) is established, demonstrating that an immunosuppressive TME can lead to poor prognosis in GC (<xref ref-type="bibr" rid="B38">38</xref>). All the above evidence displays different metabolic traits compared&#xa0;with the tumors from which they originate, enabling&#xa0;survival and growth in the new TME, and it selectively and dynamically adapts their metabolism at every step during&#xa0;the&#xa0;metastatic cascade, which creates a nutrient-rich microenvironment. These alterations are pivotal to the development and maintenance of the malignant phenotype of cancer cells in unfavorable TME or metastatic sites.</p>
</sec>
</sec>
<sec id="s3">
<title>Metabolic Alteration in the GC Immune Microenvironment</title>
<p>TME (composed of the tumor cells, immune cells, and fibroblasts) releases various molecules or activates the metabolic reprogramming signaling in cancer cells to remodel surrounding areas (<xref ref-type="bibr" rid="B39">39</xref>), contributing to immune escape mechanisms and drug resistance with GC development (<xref ref-type="bibr" rid="B40">40</xref>). However, altered metabolism is not limited to cellular energetic pathways. For example, the metabolic programming of immune cells can affect antigen presentation, ultimately leading to the alteration of tumor immunity (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>) <bold>(</bold>
<xref ref-type="bibr" rid="B41">41</xref>). Especially, immune-infiltrating cells in the TME can play dual roles, either promoting or inhibiting tumor growth, in response to metabolic stresses and external signals.</p>
<sec id="s3_1">
<title>T Cells</title>
<p>T cells have a natural ability to fight cancer cells in the TME. Yet, these cancer-fighting T cells are gradually exhausted and lose immunological memory potential (<xref ref-type="bibr" rid="B42">42</xref>). CD4<sup>+</sup> T cells (helper T cells) and CD8<sup>+</sup>T cells (cytotoxic T cells) are the two broad functional groups of mature T cells (<xref ref-type="bibr" rid="B43">43</xref>). First, regulatory T (Treg) cells, the subsets of CD4<sup>+</sup> T cells, are rapidly expanded upon encountering self-antigens expressed by cancer cells, and its accumulation in GC can decompose ATP to adenosine, then induce apoptosis, and inhibit the proliferation of CD8<sup>+</sup> T cells, leading to immune inactivation and evasion (<xref ref-type="bibr" rid="B44">44</xref>). In addition, Treg cells can regulate transcription factor Foxp3 to restrain PIK3/Akt/mTOR signaling, which diminished glycolysis metabolism (<xref ref-type="bibr" rid="B45">45</xref>). Further research has demonstrated that Treg cells activate their lipid metabolism to support the survival (<xref ref-type="bibr" rid="B46">46</xref>). In addition, the accumulation of Treg cells in GC also activates the PI3K/Akt/mTOR pathway, which increases free fatty acids (FFAs) and generates an immunosuppressive TME, resulting in resistance to immunotherapy (<xref ref-type="bibr" rid="B47">47</xref>). The glycolysis and antitumor functions of CD8<sup>+</sup> T cells can be inhibited by activating STAT3 to drive the FA oxidation (FAO) (<xref ref-type="bibr" rid="B48">48</xref>). These findings explain that the ratio of CD8<sup>+</sup> T cells to Treg cells in the GC TME is an important factor for prognosis and clinical efficacies (<xref ref-type="bibr" rid="B49">49</xref>).</p>
</sec>
<sec id="s3_2">
<title>Neutrophils</title>
<p>Neutrophils, as an important component of the tumor-infiltrating immune cells, can release several cytokines [such as interleukin-1&#x3b2; (IL-1&#x3b2;), tumor necrosis factor alpha (TNF-&#x3b1;), and interferon gamma (IFN-&#x3b3;)], which is mediated by multiple&#xa0;mediators, including cytokines, chemokines, lipids, and growth factors in TME (<xref ref-type="bibr" rid="B50">50</xref>). In GC, high-infiltration neutrophils have been associated with poor prognosis (<xref ref-type="bibr" rid="B51">51</xref>). Especially, neutrophils in GC inhibit the proliferation of CD4<sup>+</sup> T cells and form a local immunosuppressive environment through the programmed cell death 1 (PD-1)/programmed cell death protein-L1 (PDL&#x2212;1) pathway (<xref ref-type="bibr" rid="B52">52</xref>). They secrete a wide spectrum of factors, including matrix metalloproteinases and proinflammatory cytokines, to initiate carcinogenesis (<xref ref-type="bibr" rid="B53">53</xref>) (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). Neutrophils effectively suppress normal T-cell immunity and prolong their lifespan, contributing to the migration of GC (<xref ref-type="bibr" rid="B54">54</xref>). In GC, neutrophils are polarized to an N2 phenotype to promote tumor migration (<xref ref-type="bibr" rid="B53">53</xref>). Neutrophil is often discounted as purely glycolytic (<xref ref-type="bibr" rid="B55">55</xref>), while oxidative neutrophils use mitochondrial FAO to produce and suppress T cells in glucose-restricted TME (<xref ref-type="bibr" rid="B56">56</xref>). Evidently, these results show that targeting the lipid metabolic mechanism of neutrophils and T cells can synergize with antitumor immunity.</p>
</sec>
<sec id="s3_3">
<title>Tumor-Associated Macrophages</title>
<p>Tumor-associated macrophages (TAMs) include antitumor M1-like (M1-TAMs) or protumor M2-like (M2-TAMs) TAMs (<xref ref-type="bibr" rid="B57">57</xref>). Upon stimulation by IFN-&#x3b3; or lipopolysaccharide (LPS), macrophages are polarized in the M1 phenotype, whereas M2 polarization can be achieved <italic>via</italic> incubation with IL-4 and IL-13 (<xref ref-type="bibr" rid="B58">58</xref>&#x2013;<xref ref-type="bibr" rid="B60">60</xref>). The metabolic alterations of macrophage polarization can determine the phenotype and function of TAMs in promoting the cancer progression. Conversely, cancer cells can also utilize metabolic byproducts to manipulate TAMs to their benefits (<xref ref-type="bibr" rid="B61">61</xref>). For example, M2 macrophages are triggered by GC-derived mesenchymal stromal cells, promoting metastasis and EMT (<xref ref-type="bibr" rid="B62">62</xref>). Further research has found that M2 macrophage polarization from GC, involving the JAK2/STAT3 signaling pathway, is attenuated by blockading the secretion of IL-6/IL-8 (<xref ref-type="bibr" rid="B63">63</xref>). Most likely, M2 macrophages modulate lipid metabolism by deriving apolipoprotein E and then remodel the cytoskeleton to support migration in GC (<xref ref-type="bibr" rid="B64">64</xref>, <xref ref-type="bibr" rid="B65">65</xref>). Especially, M2 macrophage can exacerbate the FA &#x3b2;-oxidation and promote the 5-fluorouracil (5-FU) chemoresistance in GC (<xref ref-type="bibr" rid="B66">66</xref>). The lipid restores the activity and substantially enhances the phagocytosis of TAMs, leading to promoted cytotoxic T-cell-mediated tumor regression in GC (<xref ref-type="bibr" rid="B67">67</xref>). In addition, miR-130b, the correspondent of the M2-TAMs in GC (<xref ref-type="bibr" rid="B68">68</xref>), is associated with lipid metabolism and 5-FU resistance and even can activate PI3K (<xref ref-type="bibr" rid="B69">69</xref>&#x2013;<xref ref-type="bibr" rid="B71">71</xref>), which is potentially a new chemotherapeutic target by interfering immune cell metabolism in TAMs. Since TAMs have a high degree of plasticity, M2 macrophages can be repolarized to M1-TAMs. Therefore, reprogramming TAMs into antitumor activity is a new cancer treatment strategy.</p>
</sec>
<sec id="s3_4">
<title>Cancer-Associated Fibroblasts</title>
<p>Cancer-associated fibroblasts (CAFs), a protective barrier of the tumor, activate metabolically reprogrammed TAMs (<xref ref-type="bibr" rid="B72">72</xref>, <xref ref-type="bibr" rid="B73">73</xref>) and block T-cell penetration into tumor nests by secreting transforming growth factor beta 1 (TGF-&#x3b2;1) (<xref ref-type="bibr" rid="B74">74</xref>). It is nourished by TGF-&#x3b2;1, which then strongly promotes the metabolic switch from oxidative phosphorylation to aerobic glycolysis in highly metastatic GC (<xref ref-type="bibr" rid="B75">75</xref>, <xref ref-type="bibr" rid="B76">76</xref>). Further studies show that the CAFs facilitate vasculogenic mimicry formation <italic>via</italic> metabolic pathways PI3K (<xref ref-type="bibr" rid="B77">77</xref>), which exacerbates the chemotherapeutical efficacy and prognosis of GC (<xref ref-type="bibr" rid="B78">78</xref>). MiR-149 links IL-6 to mediate the crosstalk between tumor cells and CAFs, leading to the enhanced epithelial-to-mesenchymal transition and stem-like properties, which alters the metabolism and allows GC cells to spread throughout the body (<xref ref-type="bibr" rid="B79">79</xref>, <xref ref-type="bibr" rid="B80">80</xref>).</p>
</sec>
<sec id="s3_5">
<title>
<italic>Helicobacter pylori</italic> Infection</title>
<p>Persistent <italic>Helicobacter pylori</italic> infection is well-known to affect the inflammatory TME and promote GC carcinogenesis (<xref ref-type="bibr" rid="B81">81</xref>). In addition to involving inflammatory activation, <italic>H. pylori</italic> participates in various cell types, including immune cells, gastric epithelium, glands, and stem cells (<xref ref-type="bibr" rid="B82">82</xref>). <italic>H. pylori</italic> activates, polarizes, and recruits macrophages to sustain a continuous supply of proinflammatory and protumorigenic cytokines [such as IL-1, IL-6, IL-1&#x3b2;, TNF-&#x3b1;, macrophage inflammatory protein-2 (MIP-2), and inducible nitric oxide synthase (iNOS)] (<xref ref-type="bibr" rid="B83">83</xref>), and inevitably, they alter the metabolism as key contributors to immune evasion. The above-mentioned studies involved harnessing metabolic byproducts and hijacking the functions of tumor-infiltrating immune cells, favoring an immunosuppressive phenotype (<xref ref-type="bibr" rid="B84">84</xref>), which impacts many malignancy features, including the expansion and survival of tumor cells, metastasis, and angiogenesis (<xref ref-type="bibr" rid="B85">85</xref>). These findings provide a rationale for metabolically targeting the TME, which may assist in improving tumor responsiveness to immune checkpoint blockade (ICB) therapies. Therefore, whether the dysregulated metabolism of TME is a cell-intrinsic program or competition with GC cells for limited nutrients needs to be further discussed.</p>
</sec>
</sec>
<sec id="s4">
<title>Metabolic Networks in GC</title>
<p>The progression of GC involves a shared set of metabolic reprogramming pathways, which produce excess lactic acid to reduce the pH value in TME and acquire metabolic adaptations (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>) <bold>(</bold>
<xref ref-type="bibr" rid="B86">86</xref>, <xref ref-type="bibr" rid="B87">87</xref>). This metabolic alteration in GC switches from oxidative phosphorylation to glycolysis concerned promoting EMT, tumor angiogenesis, and the metastatic colonization of distant organs, resulting in regulation of the invasion-metastasis cascade (<xref ref-type="bibr" rid="B80">80</xref>). In addition, some pathogens, such as <italic>H. pylori</italic>, further mediate an inflammatory environment and trigger the oncogenic pathway, leading to DNA damage in gastric mucosal epithelial cells, continuous accumulation of intracellular abnormal metabolites, and eventually malignant transformation (<xref ref-type="bibr" rid="B88">88</xref>, <xref ref-type="bibr" rid="B89">89</xref>).</p>
<sec id="s4_1">
<title>HIF-1&#x3b1;/ROS</title>
<p>The physiological gastrointestinal luminal epithelium is hypoxic (<xref ref-type="bibr" rid="B90">90</xref>), and tissue hypoxia induces metabolic reprogramming and may result in malignant transformation of gastric mucosal epithelial cells (<xref ref-type="bibr" rid="B91">91</xref>). Moreover, it even induces resistance to chemoradiotherapy, leading to therapeutic failure (<xref ref-type="bibr" rid="B92">92</xref>). Hypoxia-inducible factor-1 alpha (HIF-1&#x3b1;) controls the production of reactive oxygen species (ROS) in oxygen concentration, which supports the adaptation of tumor cells and mediates lactic acid efflux by the monocarboxylate channel transporter (MCT) to promote macrophage polarization in a hypoxic TME (<xref ref-type="bibr" rid="B93">93</xref>). In addition, insulin treatment induces glucose uptake and enhances the expression of GLUT1, which is accompanied by the apoptotic effect due to HIF-1&#x3b1; inhibition (<xref ref-type="bibr" rid="B94">94</xref>). MiR-186 is involved in the CAF formation (<xref ref-type="bibr" rid="B95">95</xref>), which regulates glucose uptake and lactate production <italic>via</italic> HIF-1&#x3b1; (<xref ref-type="bibr" rid="B96">96</xref>, <xref ref-type="bibr" rid="B97">97</xref>). Approximately 70% of cases of <italic>H.&#xa0;pylori</italic> infection are involved in GC progression, which is responsible for persistent oxidative stress and DNA damage. Ultimately, HIF-1&#x3b1; promotes metabolic adaptation in a hypoxic environment (<xref ref-type="bibr" rid="B98">98</xref>). The cytotoxin-associated protein A (CagA) protein, one of the most important virulence factors of <italic>H. pylori</italic>, is&#xa0;localized in the mitochondria, where it subsequently results in a hypoxic condition in gastric epithelial cells and increases the HIF-1&#x3b1; activity (<xref ref-type="bibr" rid="B99">99</xref>). Then, the crosstalk between ROS and HIF-1&#x3b1; induces macrophage polarization <italic>via</italic> the Akt/mTOR pathway, which affects the progression of gastric lesions and state of infection (<xref ref-type="bibr" rid="B100">100</xref>).</p>
</sec>
<sec id="s4_2">
<title>PI3K/Akt/mTOR</title>
<p>The PI3K/Akt/mTOR pathway is frequently activated in promoting GC aggressiveness (<xref ref-type="bibr" rid="B101">101</xref>). It involves enhanced aerobic glycolysis (<xref ref-type="bibr" rid="B102">102</xref>) and then reshapes the immunosuppressive TAMs (<xref ref-type="bibr" rid="B103">103</xref>). Akt, as downstream of PI3K, is an important driver of the tumor glycolytic phenotype, which stimulates ATP production to increase GLUT expression and membrane translocation, phosphorylates key glycolytic enzymes, and thereby stimulates the signal transduction of the mTOR pathway (<xref ref-type="bibr" rid="B104">104</xref>). Especially, the PI3K/Akt pathway is significantly activated after <italic>H. pylori</italic> infection in tumor cells (<xref ref-type="bibr" rid="B105">105</xref>). Further studies indicate that CagA protein reduces cellular amino acids, and bolstering amino acid pools prevents mTOR inhibition (<xref ref-type="bibr" rid="B106">106</xref>). Moreover, CagA protein activates the PI3K/Akt pathway, induces glucose metabolism, and promotes GC cell proliferation (<xref ref-type="bibr" rid="B107">107</xref>). It has been reported that miR-133a blocks the autophagy to ruin the abnormal glutaminolysis <italic>via</italic> the Akt/mTOR pathway, further inhibiting the growth and metastasis of GC (<xref ref-type="bibr" rid="B80">80</xref>, <xref ref-type="bibr" rid="B108">108</xref>). Moreover, the A2a adenosine receptor promotes the GC Warburg effect by enhancing PI3K/Akt/mTOR pathway in hypoxic TAMs (<xref ref-type="bibr" rid="B109">109</xref>, <xref ref-type="bibr" rid="B110">110</xref>).</p>
</sec>
<sec id="s4_3">
<title>JAK/STAT</title>
<p>Janus kinase-signal transducer and activator of transcription (JAK/STAT) signaling, as the upstream of HIF-1&#x3b1; (<xref ref-type="bibr" rid="B111">111</xref>, <xref ref-type="bibr" rid="B112">112</xref>), regulates survival and immunosuppression of GC cells and sustains inflammation in TAMs, including tumor cell recognition and tumor-driven immune escape (<xref ref-type="bibr" rid="B113">113</xref>&#x2013;<xref ref-type="bibr" rid="B115">115</xref>), and it is essential in the activation of macrophages, natural killer (NK) cells, and T cells (<xref ref-type="bibr" rid="B116">116</xref>, <xref ref-type="bibr" rid="B117">117</xref>). However, efforts to develop therapeutic STAT3 inhibitors have thus far been unsuccessful (<xref ref-type="bibr" rid="B118">118</xref>). Activated STAT3 upregulates energy metabolism by translocating mitochondria, which is critical for glutamate-induced cell proliferation (<xref ref-type="bibr" rid="B119">119</xref>). Under hypoxic conditions, STAT3 physically interacts with programmed cell death protein-L1 (PD-L1) and facilitates its nuclear translocation, enhancing the macrophage-derived TNF&#x3b1;-induced tumor necrosis <italic>in vivo</italic>, and correlates with chemotherapeutic drugs (<xref ref-type="bibr" rid="B120">120</xref>). Especially, <italic>H. pylori</italic> disrupts lipid rafts <italic>via</italic> JAK/STAT and thereby reduces cholesterol levels in infected gastric epithelial cells, allowing the bacteria to escape from the host inflammatory response (<xref ref-type="bibr" rid="B121">121</xref>). Infiltrated macrophages can release STAT3 to induce PD-L1 expression in GC, which helps tumor cells escape from cytotoxic T-cell killing and promotes the proliferation of tumor cells (<xref ref-type="bibr" rid="B122">122</xref>). Given that interference with STAT3 activity is an amplified signaling cascade by targeting these cytokines; it curbs the growth of GC and augments antitumor immunity (<xref ref-type="bibr" rid="B123">123</xref>).</p>
<p>Although these studies have proven many substantial crosstalks and numerous links in metabolic activities, how to allow cells to maximize growth and proliferation and activate chronically in cancer remains unknown. Beyond doubt, the precancerous lesions of gastric epithelial cells have abnormal metabolic energy, and there is a cross-relationship with the pathways mentioned above. Therefore, it seems to be more valuable to trace the heterogeneity of primary lesions and the changes in metabolic enzymes in the tumor progression. In addition, drugging a specific metabolic circuitry associated with malignancy may ultimately be efficient only on a fraction of GC cells, operating as selective pressure and favoring the rapid emergence of resistant cells.</p>
</sec>
</sec>
<sec id="s5">
<title>The Strategies of Metabolic Reprogramming in GC</title>
<p>Nowadays, systemic chemotherapy is still the mainstay of treatment for advanced GC. A majority of patients do not benefit from monotherapy, such as 5-FU, due to frequent relapses caused by chemotherapy-resistant cancer clones. Therefore, the 5-year overall survival rate is only 20%&#x2013;35% (<xref ref-type="bibr" rid="B124">124</xref>&#x2013;<xref ref-type="bibr" rid="B126">126</xref>). Accumulating evidence showed that tumor cells, in order to adapt various toxic stimuli in the TME, are involved in the mechanism of self-defense or drug resistance, including enhancing DNA damage repair capacity, increasing efflux of drugs <italic>via</italic> upregulated resistance-associated proteins, and upregulating antiapoptotic proteins. However, this&#xa0;series of activities require a large amount of ATP supply (<xref ref-type="bibr" rid="B127">127</xref>). Therefore, metabolic reprogramming contributes to chemoresistance. The proposed metabolic mechanisms of drug resistance involve mainly in the increase in glucose and glutamine demand, glutaminolysis and glycolysis pathways activity, promotion of reduced nicotinamide adenine dinucleotide phosphate (NADPH) from the pentose phosphate pathway, activation of FAO, and upregulation of ornithine decarboxylase for polyamine production (<xref ref-type="bibr" rid="B128">128</xref>). Moreover, several genes are associated with metabolic reprogramming and drug resistance, such as GLUT1, LDHA, GAPDH, MCAM, and FAO (<xref ref-type="bibr" rid="B129">129</xref>&#x2013;<xref ref-type="bibr" rid="B132">132</xref>).</p>
<p>Currently, recurrent therapeutic resistance presents revolutionary claims, and targeting the metabolic reprogramming, such as glycolytic inhibitor, could be a strategy of Trojan Horse, which highlights the novel combinational trials and their preclinical rationale. A combination of glycolysis inhibitor and 5-FU can synergistically enhance the cytotoxicity of resistant GC cells (<xref ref-type="bibr" rid="B133">133</xref>). Glycolysis negatively affects survival outcomes of metastatic GC patients treated with paclitaxel-ramucirumab therapy (<xref ref-type="bibr" rid="B134">134</xref>).</p>
<sec id="s5_1">
<title>Molecularly Targeted Drugs</title>
<p>Human epidermal growth factor receptor 2 (HER2), an oncogenic tyrosine kinase, is overexpressed or amplified in 12%&#x2013;20% of GC (<xref ref-type="bibr" rid="B135">135</xref>). Several strategies have been developed directly against HER2. However, drug resistance remains a major unresolved clinical problem (<xref ref-type="bibr" rid="B136">136</xref>). KU004, a HER2 inhibitor, inhibits the Warburg effect by the PI3K/Akt signaling pathway and suppresses hexokinase II (HK2), which mediates antitumor effect (<xref ref-type="bibr" rid="B137">137</xref>). Especially, the PI3K/Akt pathway induces targeted HER2 drug resistance in GC (<xref ref-type="bibr" rid="B138">138</xref>, <xref ref-type="bibr" rid="B139">139</xref>). A glycolysis inhibitor MK2206 diminishes the trastuzumab resistance in HER2(+) GCs by attenuating the Warburg effect (<xref ref-type="bibr" rid="B139">139</xref>). Moreover, GATA6, the downstream of STAT3 (<xref ref-type="bibr" rid="B140">140</xref>), is involved in GC metabolic reprogramming, which may contribute to trastuzumab resistance (<xref ref-type="bibr" rid="B141">141</xref>). Further results indicate that Rhodium (III) complex 6, an effective STAT3 inhibitor (<xref ref-type="bibr" rid="B142">142</xref>), may be beneficial for targeting HER2 treatment of GC.</p>
<p>Aerobic glycolysis leads to the accumulation of lactate, which induces angiogenesis, an important process underlying tumor growth and metastasis (<xref ref-type="bibr" rid="B143">143</xref>). Ramucirumab, a vascular endothelial growth factor receptor (VEGFR) inhibitor, has shown limited benefits to GC due to metabolism activity (<xref ref-type="bibr" rid="B144">144</xref>). A further study suggested that glycolysis can negatively affect survival outcomes of metastatic GC patients treated with ramucirumab systemic therapy (<xref ref-type="bibr" rid="B134">134</xref>). Apatinib, another competitive inhibitor of VEGFR2, effectively suppresses glycolysis (<xref ref-type="bibr" rid="B145">145</xref>) and even induces the lipid metabolism in GC (<xref ref-type="bibr" rid="B146">146</xref>). The 2-deoxy-D-glucose, an inhibitor of glycolysis, can significantly reduce its angiogenic sprouting in tumor (<xref ref-type="bibr" rid="B147">147</xref>). PFKFB3 (glycolytic enzyme) not only regulates abnormal glycolytic metabolism in GC (<xref ref-type="bibr" rid="B148">148</xref>), and its inhibitors, PA-1 and PA-2, are potential antiangiogenic properties (<xref ref-type="bibr" rid="B149">149</xref>). Therefore, VEGFR inhibitor can be one of the cornerstones against angiogenesis therapies in GC subtypes, which represents an attractive therapeutic strategy to improve the efficacy of anti-GC treatments.</p>
</sec>
<sec id="s5_2">
<title>Immunotherapy</title>
<p>The cancer-immunity cycle (CIC) comprises a series of events that are required for immune-mediated control of tumor growth. Interruption of one or more steps of the CIC enables tumors to evade immunosurveillance. However, attempts to restore antitumor immunity by reactivating the CIC have had limited success thus far. The suppressive activity of Treg cells is mediated by several proteins present on the cell surface, such as the cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), and PD-1 (<xref ref-type="bibr" rid="B150">150</xref>), which induces cellular senescence and suppresses responder T cells through mediating accelerated glucose consumption (<xref ref-type="bibr" rid="B43">43</xref>). Immunotherapy, targeting the PD-1/PD-L1 and anticytotoxic lymphocyte antigen 4 (CTLA4) pathway, collectively named immune checkpoint inhibitor (ICI), by blocking Treg-mediated immunosuppression, derives durable remission and survival benefits for GC (<xref ref-type="bibr" rid="B151">151</xref>, <xref ref-type="bibr" rid="B152">152</xref>). However, 50% of MSI-high GC are intrinsically resistant to PD-1 therapies (<xref ref-type="bibr" rid="B153">153</xref>). It is likely that continuous exposure to PD-1 antigen, which induces metabolic reprogramming of the T cell, induces T-cell exhaustion (<xref ref-type="bibr" rid="B154">154</xref>, <xref ref-type="bibr" rid="B155">155</xref>). Diclofenac, a non-steroidal drug, turns out to inhibit the lactate transporters MCTs and improve T-cell killing, which improves the efficacy of anti-PD1 therapy (<xref ref-type="bibr" rid="B156">156</xref>). 6-Diazo-5-oxo-l-norleucine, a small molecule glutamine analog, increases infiltration of CD8+ T cells and sensitizes tumors to anti-PD1 therapy (<xref ref-type="bibr" rid="B157">157</xref>). Moreover, EBV-associated GC cells are treated with JAK2 inhibitor, PI3K inhibitor, and mTOR inhibitor, which arrests G0/G1, promotes the proliferation of T cells, and reduces the PD-L1 expression (<xref ref-type="bibr" rid="B158">158</xref>).</p>
<p>CTLA-4 represents a crucial immune checkpoint, the blockade of which can potentiate antitumor immunity. Limiting Treg cell metabolic competition in the TME may increase the effectiveness of immunotherapy (<xref ref-type="bibr" rid="B159">159</xref>). Especially, the effect of CTLA-4 blockade on the destabilization of T cells is dependent on T-cell glycolysis. Metformin is associated with decreased expression CTLA-4 of Treg cells, which induces glycolysis (<xref ref-type="bibr" rid="B160">160</xref>). Telaglenastat (CB-839), a potent GLS inhibitor, comminates with anti-PD1 or anti-CTLA4 antibodies, then increases tumor infiltration by effector T cells and improves the antitumor activity of these ICIs (<xref ref-type="bibr" rid="B161">161</xref>). Therefore, the combinational use of ICIs together with metabolic treatments to alleviate metabolic stress may improve the efficacy of immunotherapy.</p>
</sec>
<sec id="s5_3">
<title>Natural Compounds</title>
<p>Natural compounds, targeting the components of mitochondria, modulate metabolic abnormalities that are a consequence of&#xa0;immune cell dysfunction (<xref ref-type="bibr" rid="B162">162</xref>, <xref ref-type="bibr" rid="B163">163</xref>). For example, salazosulfapyridine blocks cystine/glutamate exchange activity and mitigates the supply of cysteine to increase intracellular ROS production, thereby increasing the effect of anticancer drugs, such as cisplatin. Especially, its combination with 2-deoxyglucose significantly inhibits cell proliferation (<xref ref-type="bibr" rid="B164">164</xref>). Crocin, one of the main bioactive compounds of saffron, not only inhibits the EMT, migration, and invasion of GC cells through HIF-1&#x3b1; signaling (<xref ref-type="bibr" rid="B165">165</xref>) but also protects against malignant transformation by altering mitochondrial function (<xref ref-type="bibr" rid="B166">166</xref>, <xref ref-type="bibr" rid="B167">167</xref>). The above-mentioned results show that natural compounds have great potential in regulating metabolic reprogramming. However, there are many kinds of natural compounds and different molecular pathways, and it is still necessary to establish a huge database and screen GC cell lines with metabolic phenotype for further studies.</p>
<p>To sum up, several metabolic inhibitors designed to target these pathways have been advanced into preclinical trials (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). Anticancer effect or resistance can be revered by innovative anticancer treatments targeting metabolism. Depending on tumor type, not all patients benefit from metabolic reprogramming treatment and clinical responses, and the outcome on GC progression can be either positive or negative. Therefore, understanding the mechanisms of metabolic reprogramming can be a necessary tool to identify combinations of drugs that elude resistance and allow a better response for the patients.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Metabolic reprogramming drugs in GC.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left"/>
<th valign="top" align="center">Agent</th>
<th valign="top" align="center">Type of metabolic reprogramming</th>
<th valign="top" align="center">Target pathway and protein</th>
<th valign="top" align="center">Observation</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="5" align="left">
<bold>Molecular targeted drugs</bold>
</td>
<td valign="top" align="left">MK2206</td>
<td valign="top" align="left">Glycolysis</td>
<td valign="top" align="left">PI3K/Akt</td>
<td valign="top" align="left">Reversion the trastuzumab resistance (<xref ref-type="bibr" rid="B139">139</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">Rhodium (III) complex 6</td>
<td valign="top" align="left">TCA cycle, glycolysis, and AA pathways</td>
<td valign="top" align="left">STAT3</td>
<td valign="top" align="left">Reversion the trastuzumab resistance (<xref ref-type="bibr" rid="B141">141</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">Apatinib</td>
<td valign="top" align="left">Glycolysis</td>
<td valign="top" align="left">VEGFR2/AKT1/SOX5/GLUT4</td>
<td valign="top" align="left">Inhibition the viability and proliferation (<xref ref-type="bibr" rid="B145">145</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">2-deoxy glucose</td>
<td valign="top" align="left">Glycolysis</td>
<td valign="top" align="left">JNK (<xref ref-type="bibr" rid="B168">168</xref>)</td>
<td valign="top" align="left">Inhibition the angiogenesis (<xref ref-type="bibr" rid="B147">147</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">PA-1, PA-2</td>
<td valign="top" align="left">Glycolysis</td>
<td valign="top" align="left">PFKFB3</td>
<td valign="top" align="left">Inhibition the angiogenesis (<xref ref-type="bibr" rid="B149">149</xref>)</td>
</tr>
<tr>
<td valign="top" rowspan="5" align="left">
<bold>Immunotherapy</bold>
</td>
<td valign="top" align="left">Diclofenac</td>
<td valign="top" align="left">Glycolysis</td>
<td valign="top" align="left">MCT1, MCT4</td>
<td valign="top" align="left">Improvement of the anti-PD1-induced T cell killing (<xref ref-type="bibr" rid="B156">156</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">6-diazo-5-oxo-l-norleucine</td>
<td valign="top" align="left">Glycolysis</td>
<td valign="top" align="left">Glutamine-utilizing enzymes</td>
<td valign="top" align="left">Increasing infiltration of CD8+ T cells and sensitized tumors to anti-PD1 therapy (<xref ref-type="bibr" rid="B157">157</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">AZD1480, LY294002, rapamycin</td>
<td valign="top" align="left">Glycolysis</td>
<td valign="top" align="left">JAK2, PI3K, mTOR</td>
<td valign="top" align="left">Arresting the G0/G1, promoting the T-cell proliferation, reducing the PD-L1 (<xref ref-type="bibr" rid="B158">158</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">Metformin</td>
<td valign="top" align="left">Glycolysis</td>
<td valign="top" align="left">mTOR/AKT (<xref ref-type="bibr" rid="B169">169</xref>)</td>
<td valign="top" align="left">Decreasing expression CTLA-4 of Treg cell (<xref ref-type="bibr" rid="B160">160</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">Telaglenastat</td>
<td valign="top" align="left">Glutamine</td>
<td valign="top" align="left">Glutamine enzymes</td>
<td valign="top" align="left">Increasing effector T cells (<xref ref-type="bibr" rid="B161">161</xref>)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Natural compounds</bold>
</td>
<td valign="top" align="left">Salazosulfapyridine</td>
<td valign="top" align="left">Glycolysis</td>
<td valign="top" align="left">Cystine/glutamate</td>
<td valign="top" align="left">Increasing ROS, inhibition cell proliferation (<xref ref-type="bibr" rid="B164">164</xref>)</td>
</tr>
<tr>
<td valign="top" align="left">Crocin</td>
<td valign="top" align="left">Mitochondrial Dysfunction (<xref ref-type="bibr" rid="B170">170</xref>).</td>
<td valign="top" align="left">HIF-1&#x3b1;</td>
<td valign="top" align="left">Inhibition the EMT, migration, invasion in GC (<xref ref-type="bibr" rid="B165">165</xref>)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>TCA, tricarboxylic acid; AA, amino acid.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s6">
<title>Conclusion</title>
<p>Historically, the numerous metabolic reprogramming advances in distinguishing tumors from adjacent, non-malignant tissues and targeting these phenotypes indicate potential clinical applications. However, most cancer metabolism research has focused on phenotypes of clinically detectable tumors or experimental models derived from them, and the metabolic reprogramming of cancer cells is much more complex than first observed. Moreover, most metabolic changes are neutral or only slightly modify cancer cell fitness under stress (<xref ref-type="bibr" rid="B171">171</xref>). Certain pathways are essential for the progression of selected cancers and can be exploited therapeutically, and understanding GC metabolism and identifying liabilities require a sophisticated view of how metabolic phenotypes evolve.</p>
<p>The development of anticancer drugs in GC presents some challenges. First is the identification of accurate biomarkers that can predict the response to anticancer therapy. The second challenge is that metabolic reprogramming has emerged as a druggable target across GC, and the clinical development of combinatorial approaches should focus on how to maximize the efficacy. Third, most of the previous metabolic reprogramming studies to this point have been focused on alterations in the metabolism of glucose, glutamine, and lipid, while metabolic reprogramming also utilizes a great variety of other microelements (<xref ref-type="bibr" rid="B126">126</xref>). Taken together, understanding gene alterations in metabolic reprogramming is extremely important not only for GC diagnosis and prognosis but also for the development of potential targeted therapy. We should expand the research direction from the perspective of energy metabolism reprogramming.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author Contributions</title>
<p>D-FL and Y-LB drafted the work or revised it critically for important intellectual content. H-SH, FT, ZHW, M-FY, B-HW, L-SW and JY contributed significantly to analysis and manuscript preparation. D-FL approved the final version to be published. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>This work was supported by the Natural Science Foundation of Guangdong Province (No. 2018A0303100024), Three Engineering Training Funds in Shenzhen (No. SYLY201718, No. SYJY201714, and No. SYLY201801), Technical Research and Development Project of Shenzhen (No. JCYJ20150403101028164, No. JCYC20170307100911479, and No. JCYJ20190807145617113), National Natural Science Foundation of China (No. 81800489), and the Natural Science Foundation of Hunan Province (No. 2021JJ70076), Technical Research and Development Project of Shenzhen (JCYJ20210324113802006).</p>
</sec>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of Interest</title>
<p>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.</p>
</sec>
<sec id="s10" sec-type="disclaimer">
<title>Publisher&#x2019;s Note</title>
<p>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.</p>
</sec>
</body>
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