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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">JRENHEP</journal-id>
<journal-title-group>
<journal-title>Journal of Renal and Hepatic Disorders</journal-title>
<abbrev-journal-title>JRENHEP</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2207-3744</issn>
<publisher>
<publisher-name>Troika Publisher</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.63268/jrenhp.v10i1.252</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Review</subject>
</subj-group>
</article-categories>
      <title-group>
        <article-title>The oncogenic implications of metabolic dysfunction-associated steatotic liver disease</article-title>
      </title-group>
    <contrib-group content-type="authors">
	  
        <contrib contrib-type="author">
          <name>
            <surname>Kamboj</surname>
            <given-names>Aditya</given-names>
          </name>
		  <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Singh</surname>
            <given-names>Amit Kumar</given-names>
          </name>
		  <xref ref-type="aff" rid="aff1">1</xref>
		  <xref ref-type="corresp" rid="cor1"/>
        </contrib>
		
		<aff id="aff1"><label>1</label>Department of Medical Lab Technology, UIAHS, Chandigarh University, 140301 Mohali, India</aff>
		
      </contrib-group>
	  
	  
<author-notes>
<corresp id="cor1"><italic>Author for correspondence:</italic> <email>amit.e15899@cumail.in</email></corresp>

</author-notes>


<pub-date pub-type="epub">
<day>20</day>
<month>06</month>
<year>2026</year>
</pub-date>
<pub-date pub-type="collection"><year>2026</year></pub-date>
<volume>10</volume>
<issue>1</issue>
<fpage>14</fpage>
<lpage>23</lpage>
<history>
<date date-type="received">
<day>09</day>
<month>10</month>
<year>2025</year></date> 
<date date-type="accepted">
<day>24</day>
<month>12</month>
<year>2025</year></date> 
</history>
<permissions>
<copyright-statement><italic>Copyright:</italic> The Author(s). Published by Troika Publisher.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/">
<license-p><italic>License:</italic> This open access article is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0">http://creativecommons.org/licenses/by/4.0</ext-link></license-p>
</license>%%%
</permissions>

    

<abstract>
<p>Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly 
termed non-alcoholic fatty liver disease (NAFLD), is receiving growing attention 
as a major public health issue globally, primarily because of its association 
with the development of hepatocellular carcinoma (HCC). MASLD is predominantly 
caused by obesity, type 2 diabetes mellitus, and lack of exercise, and has a 
broad clinical spectrum ranging from benign hepatic steatosis to non-alcoholic 
steatohepatitis (NASH), fibrosis, cirrhosis, and ultimately HCC. The pertinent 
problem is that HCC due to MASLD typically develops in patients without 
cirrhosis, making diagnosis and follow-up exceedingly challenging. MASLD is 
described as a multi-faceted condition involving insulin resistance, lipid 
deposition, oxidative stress, and chronic inflammation. Recent molecular studies 
related to lipid metabolism, mitochondrial dysfunction, and oncogenic pathways 
have identified candidate molecules, including microRNA-33 (<italic>miR-33</italic>), and 
Interferon Gamma Inducible Protein 16 (<italic>IFI16</italic>) variants. Emerging 
non-invasive diagnostic technologies, including liquid biopsies, next-generation 
sequencing (NGS), and machine learning-based models, are becoming important for 
early detection and individualized risk assessment. Currently, therapeutic 
interventions target oxidative stress, inflammatory responses, fibrosis, and 
lipid dysregulation. Some of the potentially useful interventions include 
bioactive flavonoids, repurposed medications (metformin and statins), and a novel 
nanotechnology-based drug delivery system that could slow disease progression and 
reduce cancer risk. Treating MASLD while addressing the risk of malignancy will 
require a precision medicine approach with a focus on lifestyle intervention, 
directed pharmacotherapy, and advanced diagnostic approaches implemented in a 
multidisciplinary fashion.</p>
</abstract>
<kwd-group>
<kwd>Non-alcoholic fatty liver disease (NAFLD)</kwd>
<kwd>Non-alcoholic steatohepatitis (NASH)</kwd>
<kwd>Metabolic dysfunction-associated steatotic liver disease (MASLD)</kwd>
<kwd>Metabolic dysfunction-associated steatohepatitis (MASH)</kwd>
<kwd>Hepatocellular carcinoma (HCC)</kwd>
</kwd-group>
</article-meta>
</front>
<body>


   <sec id="S1" sec-type="intro">
     <title>Introduction</title>  
     <p>Metabolic dysfunction-associated fatty liver disease (MAFLD), earlier known as 
non-alcoholic fatty liver disease (NAFLD), is now a critical global health 
concern because of its robust association with cancer etiology. Increasing 
evidence has placed the spotlight on MASLD as a primary causative factor not only 
for liver cancer but also for extrahepatic cancers. Most importantly, it has been 
strongly established as a leading risk factor for hepatocellular carcinoma (HCC), 
the increasing prevalence of which is closely associated with the global increase 
in metabolic disorders [<xref ref-type="bibr" rid="ref1">1</xref>]. Its prevalent nature is owed mainly to increasingly 
sedentary lifestyles, low levels of physical activity, and the chronic intake of 
high-calorie diets that tend to exceed the body&#x2019;s energy requirements, especially 
when linked with poor dietary quality and food imbalance [<xref ref-type="bibr" rid="ref2">2</xref>]. The defining 
feature of this condition is the accumulation of fat in the liver in the absence 
of other contributing factors, such as significant alcohol consumption. Obesity, 
type 2 diabetes mellitus, and metabolic syndrome have consistently been 
identified as its primary risk factors [<xref ref-type="bibr" rid="ref3">3</xref>]. The global surge in obesity and type 
2 diabetes has paralleled a sharp rise in the prevalence of MASLD. Recent data 
indicate that approximately 38% of the adult population is affected, while rates 
among children and adolescents range between 7% and 14%. Projections suggest 
that by 2040, nearly 55% of the world&#x2019;s population could be living with MASLD. 
Although not every individual with the condition will progress to advanced liver disease, MASLD has nonetheless emerged as the leading indication for liver transplantation in the United States, particularly among women and those diagnosed with hepatocellular carcinoma (HCC) [<xref ref-type="bibr" rid="ref4">4</xref>]. Although the genetic determinants of hepatic fat accumulation, such as allelic variants of lipid metabolism genes, may also play a role, these are less common and more frequent risk factors such as obesity and components of metabolic syndrome are more frequent. The prevalence of nonalcoholic fatty liver disease (NAFLD) without obesity widely ranges, suggesting that exogenous factors (such as high cholesterol, consumption of sugars such as fructose) and genetic risk factors both contribute to the development of NAFLD, but the latter is not a primary cause [<xref ref-type="bibr" rid="ref5">5</xref>]. Histologically, NAFLD may be classified into two primary 
groups: nonalcoholic steatohepatitis (NASH) and nonalcoholic fatty liver (NAFL). 
Lack of hepatic damage, notably ballooning degeneration in hepatocytes, and the 
buildup of fat in the liver are characteristics of NAFL. NASH, on the other hand, 
is characterized by hepatic steatosis, inflammation, and visible hepatocyte 
damage, including ballooning and may occur with or without fibrosis [<xref ref-type="bibr" rid="ref6">6</xref>].</p>  
     <p>Even though there is increasing evidence of the association between MAFLD and 
both hepatic and extrahepatic cancers, several important questions remain 
unanswered. The majority of the literature remains highly 
concentrated on HCC, and the potential mechanisms linking MAFLD to cancers beyond 
the liver are not yet fully understood. It is also challenging to determine 
causal relationships and patterns of cumulative risk progression, especially in 
diverse global populations, because large-scale longitudinal studies are seldom 
available [<xref ref-type="bibr" rid="ref7">7</xref>]. Unresolved questions include the extend to which disease severity, 
particularly fibrosis stage, directly impacts cancer incidence, whether MAFLD is 
an independent driver of carcinogenesis or merely a reflection of underlying 
metabolic dysfunction, and whether early targeted interventions could potentially 
significantly reduce future cancer risk in this patient population [<xref ref-type="bibr" rid="ref8">8</xref>]. The role of MAFLD in clinical response to cancer therapy, and treatment efficacy and outcomes, remain poorly defined, and further mechanistic and clinical research is needed to understand its role [<xref ref-type="bibr" rid="ref9">9</xref>]. Thus, this review provides a 
comprehensive summary of the literature on MAFLD and liver-related or 
extra-hepatic cancers with primary focus on recent knowledge gaps between MAFLD 
and cancer development, identifies major scientific hurdles as well as clinical 
needs based on current understanding, and proposes future research directions 
ranging from molecular mechanisms to advanced risk-stratification models and 
population-specific longitudinal studies, aimed to developing effective cancer 
prevention strategies secondary to MAFLD.</p>  
   </sec>  
   <sec id="S2">  
  
     <title>Metabolically driven steatotic liver disorder</title>  
 
   <sec id="S2_1">
       <title><italic>Perspective and terminology</italic></title>  
       <p>Fatty liver associated with is well known to cause liver damage and, in more 
extreme cases, to progress to cirrhosis. NASH was first identified as an 
independent liver-damaging condition in the 1980&#x2019;s, and was subsequently named by 
researchers [<xref ref-type="bibr" rid="ref10">10</xref>]. The term NAFLD covers a spectrum of chronic liver diseases, 
ranging from simple hepatic steatosis (NAFL) to non-alcoholic steatohepatitis 
(NASH), which involves inflammatory and injurious changes of the liver, with or 
without fibrosis [<xref ref-type="bibr" rid="ref11">11</xref>]. This condition was reclassified as MAFLD in 2020 after 
decades of research on MAFLD and its mechanisms underwent thorough investigation, 
showing evidence that implicates MAFLD in affecting systems outside of the liver. 
MAFLD is diagnosed when there is evidence for excess liver fat (which can be 
quantified via biopsy, imaging, or biomarker) in conjunction with at least one of 
the following overweight or obesity, type 2 diabetes mellitus, or displaying 
symptoms of metabolic dysfunction [<xref ref-type="bibr" rid="ref2">2</xref>]. With the change in naming conventions, 
MASLD is now a diagnosis based on inclusion and not necessarily exclusion of 
other causes. In 2023, the terminology was revised again to MASLD, which 
represents the disease with its connection to cardiometabolic disorders and 
shared underlying biological mechanisms [<xref ref-type="bibr" rid="ref12">12</xref>].</p>  
     </sec>  

 <sec id="S2_2">
<title><italic>Etiopathogenesis</italic></title>  
       <p>It is important to fully understand the epidemiology of MASLD, as its increasing 
global prevalence and significant metabolic associations have made it one of the 
most common causes of chronic liver disease worldwide [<xref ref-type="bibr" rid="ref13">13</xref>]. Studies have 
repeatedly found a clear link between metabolic syndrome and MASLD. However, the 
causes and how the disease develops in MASLD are not well understood. The 
&#x201C;two-hit&#x201D; hypothesis (first proposed in NAFLD) states that the first hit 
(mostly hepatic steatosis due to insulin resistance and other contributing 
factors) sensitizes the liver, while a second hit (including oxidative stress, 
inflammatory cytokines, mitochondrial dysfunction) leads to inflammation, cell 
death, and fibrosis [<xref ref-type="bibr" rid="ref14">14</xref>]. In contrast, the &#x201C;multiple-hit&#x201D; (or multi-hit) 
hypothesis argues that this model is too simplistic. Rather than just two 
sequential hits, many insults act in parallel on a liver that is genetically 
predisposed to injury, such as insulin resistance, adipokines that act from 
adipose tissue, gut microbiota, dietary/nutritional factors, genetic and 
epigenetic predispositions, endoplasmic reticulum (ER) stress, lipotoxicity [<xref ref-type="bibr" rid="ref15">15</xref>]. 
The &#x201C;multiple hits&#x201D; model suggests that MASLD develops in people who have a 
genetic tendency to develop it and are also exposed to several environmental 
factors, such as lifestyle behaviors, dietary patterns, and the bacteria in their 
gut (Fig. <xref ref-type="fig" rid="F1">1</xref>, Ref. [<xref ref-type="bibr" rid="ref16">16</xref>]). Importantly, hypotheses apply to mechanisms that involve 
carbohydrate and fat metabolism, and insulin resistance, such as the increased 
production of fat in the liver (de novo lipogenesis), reduced regulation of the 
breakdown of fat in adipose tissue (<italic>e.g.</italic>, increased fatty acid release 
and reduced breakdown of fatty acids), all of which contribute to lipotoxicity 
[<xref ref-type="bibr" rid="ref17">17</xref>].</p>  
      
<fig id="F1" orientation="portrait" position="float">
<label>Figure 1:</label>
<caption><p><bold>Schematic representation of the pathways progression of MASLD to 
hepatocellular carcinoma, involving genetic susceptibility, oxidative stress, 
insulin resistance, gut microbiome disturbances, and activation of stellate cells 
leading to fibrosis [<xref ref-type="bibr" rid="ref16">16</xref>].</bold> <ext-link ext-link-type="uri" xlink:href="https://www.mdpi.com/2077-0383/13/16/4657">https://www.mdpi.com/2077-0383/13/16/4657</ext-link>. 
PNPLA3: Patatin-like phospholipase domain-containing protein 3; hTERT: telomerase 
reverse transcriptase (in human); MASLD: Metabolic dysfunction-associated 
steatotic liver disease; TNF: Tumor necrosis factor; IGF: insulin-like growth 
factors.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://jrenhep.com/article/download/252/version/225/389/2799/fig1.jpg"/>
</fig>

 
     </sec>  
   </sec>  
   <sec id="S3">  
   
     <title>Pathophysiology of MASLD-HCC</title>  
     <p>The pathogenesis of MASLD is intricate and multifaceted, encompassing 
fibrogenesis, lipotoxicity, and inflammatory pathways. Following food intake, 
elevated blood glucose levels stimulate pancreatic insulin secretion; this is an 
important phase of operation. Then, insulin travels via the portal vein to the 
liver, where it directs metabolic pathways such as increasing de novo 
lipogenesis, which converts acetyl-coenzyme A (CoA) into fatty acids, and 
stimulates glycogenesis, storing excess glucose as glycogen. Activated by 
insulin, several intracellular signaling pathways mediate these anabolic actions. 
By managing oxidative metabolism, adenosine triphosphate (ATP) synthesis, and 
reactive oxygen species production, mitochondria play a crucial part in metabolic 
regulation. Increased hepatic lipogenesis, decreased insulin signaling in adipose 
tissue, and increased free fatty acid levels are all consequences of dysregulated 
anabolic signaling in the setting of hepatic insulin resistance. The development 
of MASLD is primarily dependent on the accumulation of fatty acids in the liver, 
which is largely caused by increased lipogenesis triggered by specific 
transcription factors. Fatty acid &#x3B2;-oxidation, which occurs in the 
mitochondria of the liver, transforms fatty acids into triglycerides, which are 
then encapsulated in very-low-density lipoproteins (VLDL) and secreted into the 
bloodstream. Hepatic steatosis results from triglycerides building up as lipid 
droplets inside hepatocytes when the capacity for either lipid export or 
oxidation is surpassed [<xref ref-type="bibr" rid="ref18">18</xref>]. The development of HCC in MASLD is complicated. Fig. <xref ref-type="fig" rid="F2">2</xref> (Ref. [<xref ref-type="bibr" rid="ref19">19</xref>]) illustrates possible pathways. In liver cells, the accumulation of 
fat with an underlying lipotoxicity produces a persistent state of inflammation 
that, over time, leads to fibrosis [<xref ref-type="bibr" rid="ref19">19</xref>].</p>  
   
<fig id="F2" orientation="portrait" position="float">
<label>Figure 2:</label>
<caption><p><bold>Pathogenic mechanisms linking obesity, genetics, insulin 
resistance, and inflammation to Metabolic dysfunction-associated steatotic liver 
disease (MASLD) progression, fibrosis, cirrhosis, and hepatocellular carcinoma 
[<xref ref-type="bibr" rid="ref19">19</xref>].</bold> <ext-link ext-link-type="uri" xlink:href="https://www.mdpi.com/2072-6694/16/2/259">https://www.mdpi.com/2072-6694/16/2/259</ext-link>. 
LPS: Lipopolysaccharides; FFAs: Free fatty acids; PNPLA3: Patatin-like phospholipase domain-containing protein 3; MBOAT7: 
membrane-bound O-acyltransferase domain-containing 7; Myc: myelocytoma; Wnt: 
Wingless/Integrated; PI3K: Phosphoinositide 3-Kinase; Akt: Protein Kinase B; 
mTOR: mechanistic Target of Rapamycin; ER: Endoplasmic reticulum.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://jrenhep.com/article/download/252/version/225/389/2800/fig2.jpg"/>
</fig>


   </sec>  
   <sec id="S4">  
   
     <title>MASLD as a spectrum: from steatosis to NASH and fibrosis</title>  
     <p>Lipid accumulation within hepatocytes characterize both disorders, however, 
their histological features, propensity for disease development, and clinical 
prognosis differ significantly. When fat is present in over 5% of hepatocytes 
without significant inflammation or hepatocellular damage, NAFL is recognized. It 
has always been thought to be a non-progressive, mostly benign illness. Emerging 
data, however, casts doubt on this presumption, suggesting that this 
oversimplified viewpoint could ignore the danger in some subgroups. Particularly 
in the presence of metabolic comorbidities such as obesity and type 2 diabetes 
mellitus, between 25&#x2013;30% of individuals with NAFL may progress to fibrosis and 
a subgroup to NASH. However, in addition to steatosis, NASH is typified by 
lobular inflammation and hepatocyte damage, including ballooning degeneration. 
This kind of illness has a much higher chance of developing cirrhosis, severe 
fibrosis, and HCC. It has been determined that the degree of fibrosis is the most 
accurate indicator of liver-related morbidity and overall mortality among several 
histological characteristics. Since a liver biopsy is now required for a definite 
diagnosis, distinguishing between NAFL and NASH is still clinically difficult. 
Disease monitoring and risk assessment are made more difficult by the fact that 
non-invasive diagnostic techniques still lack the sensitivity and specificity to 
reliably differentiate between the two. Advancing research identifies the wider 
systemic effect of NAFLD, which indicates that even individuals with 
uncomplicated steatosis are susceptible to drug-induced liver damage, alcoholic 
liver injury, and cardiovascular disturbances likely due to underlying 
hepatocellular dysfunction [<xref ref-type="bibr" rid="ref20">20</xref>].</p>  
   </sec>  
   <sec id="S5">  
  
     <title>Epidemiological link between MASLD and cancer</title>  
     <p>MASLD has been the fastest-increasing cause of HCC globally. A Swedish 
population-based study is presented as recent evidence that MASLD has surpassed 
conventional causes of hepatitis C virus (HCV) infection as the leading cause of 
HCC in Sweden. Between 2012 and 2018, the incidence of MASLD-related HCC 
increased markedly, rising by 50% from 1.0 to 1.5 cases per 100,000 
person-years. By 2017, MASLD accounted for 22% of all diagnosed cases of HCC in 
Sweden, overtaking HCV as the most common underlying cause. The declining 
prevalence of viral hepatitis due to successful antiviral therapy and the rising 
global prevalence of obesity, type 2 diabetes, and metabolic syndrome are two of 
the large burden diseases with a high risk of MASLD, and are only two 
illustrations of the broader shifts in disease epidemiology underlined by this 
trend. The study found that 39% of MASLD related HCC did not have cirrhosis, 
which is particularly clinically relevant. The exclusion of non-cirrhotic people 
from existing monitoring techniques usually results in delayed diagnosis, a 
higher tumor burden, and limited access to curative treatment choices, which 
makes this study noteworthy. Although early-stage detection rates (Barcelona 
Clinic Liver Cancer (BCLC) stage 0&#x2013;A) were similar, individuals with MASLD-HCC 
were often older (median age of 75), had bigger tumors, and had a greater risk of 
extrahepatic metastases than patients with HCC from other sources. Relative to 
their non-MASLD counterparts, a lower percentage of MASLD-HCC patients received 
curative therapy; however, after controlling for confounding factors, adjusted 
multivariable analysis showed no statistically significant differences in 
outcomes. The need to develop more comprehensive monitoring systems and improve 
HCC risk classification is highlighted by these findings, especially for MASLD, 
those who have no evidence of cirrhosis but are nonetheless at high risk for 
liver cancer [<xref ref-type="bibr" rid="ref21">21</xref>].</p>  
   </sec>  
   <sec id="S6">  
    
     <title>Molecular and genetic mechanisms linking MASLD to cancer</title>  
     <p>The research, &#x201C;<italic>miR-33</italic> deletion in hepatocytes attenuates 
MASLD-MASH-HCC progression&#x201D;, examines the molecular and genetic pathways 
responsible for the progression of hepatocellular carcinoma (HCC) from MASLD. 
This study examines the role of microRNA-33 (<italic>miR-33</italic>) because it has been 
identified as a key regulator of liver disease development from metabolism. 
Hepatocellular carcinoma (HCC) and liver fibrosis are serious outcomes of the 
most common liver disease, known as MASLD. Researchers reported that 
<italic>miR-33</italic> levels were demonstrably elevated in the livers of MASLD patients 
and in animals used in experiments. The authors made a <italic>miR-33</italic> knockout 
mouse model in hepatocytes available for a deeper understanding as well. The 
<italic>miR-33</italic> knockout mice exhibited some significant metabolic disruptions, 
such as inhibiting liver fat condensation, promoting reduced inflammation, and 
limiting fibrotic developments. The cellular consequences of the knockdown of 
<italic>miR-33</italic> included inhibition of lipogenesis, stimulation of mitochondrial 
biogenesis, and stimulation of fatty acid oxidation. It also upregulated genes 
involved in cholesterol regulation and antioxidant defense, and downregulated 
pathways of liver damage and injury. It is interesting to note that deletion of 
<italic>miR-33</italic> downregulates the yes-associated protein/transcriptional 
co-activator with PDZ-binding motif (YAP/TAZ) signaling pathway, which is a major 
driver of liver cancer development. Long-term experiments demonstrated a 
significant reduction in liver tumors in miR-33-deficient mice, in addition to 
inhibition of tumor growth and cell proliferation. Overall, <italic>miR-33</italic> is a 
molecular link between metabolic liver disease and cancer and represents a 
potential therapeutic target for preventing MASLD-associated HCC [<xref ref-type="bibr" rid="ref22">22</xref>]. The 
majority of existing data on <italic>miR-33</italic> in NAFLD comes from preclinical 
models. For example, in fructose-fed mice, hepatic <italic>miR-33</italic> is altered, 
and functional studies are performed using <italic>in vitro</italic> [<xref ref-type="bibr" rid="ref23">23</xref>].</p>  
   </sec>  
   <sec id="S7">  
   
     <title>Diagnostic and biomarker strategies</title>  
     <p>Through an integrated analysis of RNA sequencing states and whole-exome 
sequencing of liver tissues from patients with MASLD, three distinct 
transcriptomic subtypes (G1&#x2013;G3) have been identified, which reflect differences 
in the stage of disease progression. The <italic>IFI16</italic> gene variant (rs6940, 
A&gt;T, portending a missense mutation T779S), represents an important factor 
associated with worsening disease severity. This variant enhances inflammatory 
responses through DNA-sensing, specially via the interferon gamma inducible 
protein 16 IFI16-PYCARD (adaptor protein that is composed of two protein-protein 
interaction domains: a N-terminal PYRIN-PAAD-DAPIN domain (PYD) and a C-terminal 
caspase-recruitment domain (CARD))-protease enzyme Caspase-1 (CASP1) signaling 
pathway, which can act as a biomarker of disease progression for MASLD [<xref ref-type="bibr" rid="ref24">24</xref>]. In 
relation to <italic>IFI16</italic>, the data is more in the early stages. A very recent 
integrative genomic/transcriptomic study in MASLD liver tissue reported that 
genetic variants for <italic>IFI16</italic> (rs6940) had associations with disease 
progression, and that <italic>in vitro</italic> binding assessments indicated the variant 
had stronger dsDNA binding and increased inflammatory signaling through the 
IFI16-PYCARD-caspase-1 pathway [<xref ref-type="bibr" rid="ref24">24</xref>]. Next-generation sequencing (NGS) and 
artificial intelligence (AI) advancements are revolutionizing the diagnosis and 
management of HCC. Alpha-fetoprotein (AFP) testing and ultrasound imaging are 
traditional methods that have been undervalued, as they are not sensitive, 
particularly at the earlier stages of disease detectable by the testing 
modalities. NGS allows for the capacity of identifying a genetic mutation in 
somatic blood or tissue to allow early diagnosis. In particular, non-invasive 
liquid biopsies (specifically those making the distinction between circulating 
tumor DNA and cfDNA) are being increasingly recognized for their reliable 
potential for the early, accurate diagnosis as technologists increasingly trust 
the sufficiency of the data. Commercially available platforms such as Foundation 
One Liquid CDx and Guardant360 CDx, now provide timely, safe, and more precise 
alphanumeric characterization results. In addition to diagnosis, NGS also 
identifies molecular biomarkers, which are crucial for personalized treatment. 
NGS makes it possible to identify resistance-associated mutations in viral 
hepatitis, such as Hepatitis B Virus (HBV) and HCV (<italic>e.g.</italic>, G1896A in HBV; 
(Nonstructural protein 5A) NS5A and NS5B mutations in HCV), which helps choose 
antiviral treatments that work.</p>  
     <p>Furthermore, changes in Tumor Protein p53 (TP53), Telomerase Reverse 
Transcriptase (TERT), and Catenin Beta 1 (CTNNB1) are examples of recurrent 
somatic mutations in HCC that have therapeutic and prognostic consequences. For 
example, CTNNB1 mutations may indicate resistance to immunotherapy, especially 
immune checkpoint drugs, but TP53 mutations are frequently linked to poor 
clinical outcomes. Through the analysis of intricate genomic datasets, AI greatly 
enhances the usefulness of NGS by identifying molecular patterns and mutations 
that are clinically significant. Invasive treatments are frequently avoided 
because of AI-based diagnostic algorithms that improve early detection and make 
accurate variant calling possible. The integration of NGS with AI thus supports a 
precision oncology framework, allowing for more tailored treatment plans and 
better patient outcomes [<xref ref-type="bibr" rid="ref25">25</xref>].</p>  
   </sec>  
   <sec id="S8">  
    
     <title>Prognostic modeling for MASLD-related HCC</title>  
     <p>Several recent investigations have aimed to delineate the differences between 
patients with and without cirrhosis regarding the incidence and clinical outcomes 
of HCC developing in association with MASLD. Nearly 35% of cases of HCC 
associated with MASLD develop in non-cirrhotic livers, according to data from a 
multicenter registry. The non-cirrhotic MASLD-related HCC patients tend to have 
larger tumor sizes (as well as more advanced stages of disease) and were often 
older at diagnosis compared to cirrhotic patients, but also had better liver 
function, with the consideration that they may receive more aggressive and 
potentially curative therapies. Since HCC typically presents incidentally in 
non-cirrhotic patients, they are not routinely surveilled, and as such, their 
diagnosis is generally at a later stage of disease than their cirrhotic 
counterparts. As a result of their higher hepatic functional reserve, 
non-cirrhotic MASLD patients can achieve survival outcomes similar to patients 
with cirrhosis, even if they tend to have a greater burden of tumor [<xref ref-type="bibr" rid="ref23">23</xref>, <xref ref-type="bibr" rid="ref24">24</xref>]. In 
addition, research shows that while the overall incidence of HCC in MASLD 
patients without cirrhosis is low (&lt;1.5 cases per 1000 patient years), it is 
still clinically relevant, given how common MASLD is worldwide [<xref ref-type="bibr" rid="ref23">23</xref>]. Although the 
primary aim of present screening initiatives is aimed at cirrhotic patients, this 
distinction has significant consequences for surveillance approaches. Robust 
predictive models and extensive cost-benefit analyses are needed to adequately 
incorporate non-cirrhotic MASLD [<xref ref-type="bibr" rid="ref25">25</xref>]. <xref ref-type="table" rid="T1">Table 1</xref> (Ref. [<xref ref-type="bibr" rid="ref21">21</xref>, <xref ref-type="bibr" rid="ref26">26</xref>, <xref ref-type="bibr" rid="ref27">27</xref>, <xref ref-type="bibr" rid="ref28">28</xref>, <xref ref-type="bibr" rid="ref29">29</xref>]) summarizes key 
studies detailing the study type, country, duration, and major findings, 
providing an evidence-based overview of the oncogenic risk associated with MASLD.</p>  
   


<table-wrap id="T1" orientation="portrait" position="float">
<label>Table 1.</label>
<caption>
<p>Overview of key studies examining MASLD associated cancer 
risk.</p></caption>
<table frame="border" rules="all">
<thead valign="top">
<tr>
<th align="left">S/N</th> 
<th align="center">Methodology/study design/case details</th> 
<th align="center">Country</th> 
<th align="center">Duration/follow-up</th> 
<th align="center">Major findings &amp; notes</th> 
<th align="center">References</th></tr> 
</thead>
<tbody valign="top">
<tr>
<td align="left">1</td> 
<td align="center">Narrative + systematic synthesis of human studies on HCC arising in MASLD; analyzed epidemiology, surveillance issues, and non-cirrhotic HCC cases</td> 
<td align="center">USA/international literature</td> 
<td align="center">NA (review)</td> 
<td align="center">MASLD is an increasingly common cause of HCC; up to ~30% of MASLD-related HCC occurs in non-cirrhotic livers, with implications for surveillance strategies.</td> 
<td align="center">[<xref ref-type="bibr" rid="ref26">26</xref>]</td></tr> 
<tr>
<td align="left">2</td> 
<td align="center">Prospective cohort analysis using UK Biobank baseline data; SLD subtyping into MASLD, MetALD, and other categories; multivariable Cox models for 24 site-specific cancers</td> 
<td align="center">United Kingdom</td> 
<td align="center">283,238 participants; median follow-up reported in cohort (see paper)</td> 
<td align="center">MASLD was the most prevalent SLD and associated with increased risk of overall cancer, digestive system cancers (except gastric), breast cancer, renal and endometrial cancers and Hodgkin lymphoma; estimated PAR% higher for MASLD for many cancers.</td> 
<td align="center">[<xref ref-type="bibr" rid="ref27">27</xref>]</td></tr> 
<tr>
<td align="left">3</td> 
<td align="center">Large population cohort using national health records; fatty-liver indices to classify SLD subtypes; Fine&#x2013;Gray subdistribution hazards for cancer risk across millions of person-years</td> 
<td align="center">South Korea</td> 
<td align="center">Very large sample; multi-year follow-up (tens of millions of person-years)</td> 
<td align="center">MASLD, MetALD and other SLDs linked to higher liver and GI cancer risk; MetALD showed particularly high risk; MASLD linked to modest increases in some extrahepatic cancers.</td> 
<td align="center">[<xref ref-type="bibr" rid="ref26">26</xref>]</td></tr> 
<tr>
<td align="left">4</td> 
<td align="center">Nationwide registry analysis of HCC etiology trends; categorized HCC cases by underlying cause (MASLD, viruses, alcohol)</td> 
<td align="center">Sweden</td> 
<td align="center">National registry years (longitudinal)</td> 
<td align="center">MASLD became the most common cause of HCC in Sweden over the study period&#x2014;demonstrating a epidemiological shift from viral to metabolic drivers.</td> 
<td align="center">[<xref ref-type="bibr" rid="ref21">21</xref>]</td></tr> 
<tr>
<td align="left">5</td> 
<td align="center">Meta-analysis pooling longitudinal cohorts comparing NAFLD <italic>vs.</italic> non-NAFLD for HCC incidence and mortality; subgroup analyses by fibrosis/NASH</td> 
<td align="center">Multi-country (studies pooled internationally)</td> 
<td align="center">Varied follow-up across included cohorts</td> 
<td align="center">NAFLD (and especially NASH with fibrosis) was associated with increased HCC incidence and liver-cancer mortality&#x2014;supporting fibrosis stage as a key predictor.</td> 
<td align="center">[<xref ref-type="bibr" rid="ref28">28</xref>]</td></tr> 
<tr>
<td align="left">6</td> 
<td align="center">Longitudinal cohort assessing dynamic changes in MASLD/steatosis status and subsequent HCC risk; adjusted for metabolic factors and medications</td> 
<td align="center">Multi-cohort/pooled data</td> 
<td align="center">Several years per subject (cohort dependent)</td> 
<td align="center">Changes in MASLD status over time predicted differential HCC risk independent of static metabolic risk factors&#x2014;suggests importance of longitudinal phenotyping.</td> 
<td align="center">[<xref ref-type="bibr" rid="ref29">29</xref>]</td></tr> 
</tbody>
</table>

<table-wrap-foot>
<fn id="TF1-1"><p>HCC: hepatocellular carcinoma; MASLD: Metabolic dysfunction-associated steatotic 
liver disease; NAFLD: non-alcoholic fatty liver disease; NASH: non-alcoholic 
steatohepatitis; NA: Non-Alcoholic; MetALD: Metabolic dysfunction-Associated 
Alcohol-related Liver Disease; PAR: Population Attributable Risk.</p></fn></table-wrap-foot>
</table-wrap>



     <p>Median survival is often less than 12 months, underscoring the importantce to 
monitor people, especially those at higher risk, such as those with cirrhosis or 
chronic HBV infection. Because of this, the latest guidelines from the American 
Association for the Study of Liver Diseases and the European Association for the 
Study of the Liver recommend getting liver ultrasounds every six months, 
sometimes combined with alpha-fetoprotein tests. Even though there is no level I 
evidence supporting this approach, many observational studies have shown that 
regular monitoring works well for people with cirrhosis. Also, randomized 
controlled trials have confirmed that surveillance is helpful for those with HBV 
[<xref ref-type="bibr" rid="ref30">30</xref>].</p>  
   </sec>  
   <sec id="S9">  
    
     <title>Clinical implications for cancer</title>  
     <p>One of the biggest causes of cancer-related death around the world is still HCC, 
particularly among individuals with cirrhosis. Improving clinical outcomes 
requires routine surveillance because it makes early tumor diagnosis possible, 
which is necessary for access to potentially curative treatments such as 
radiofrequency ablation, liver transplantation, and surgical resection. An 
extensive meta-analysis that included 47 studies and more than 15,000 patients 
showed that surveillance greatly raises the chances of finding HCC early (odds 
ratio (OR) = 2.08) and getting treatment for it (OR = 2.24). Crucially, even 
after correcting for lead-time bias, patients who received routine surveillance 
also had improved overall survival (OR = 1.90). The difference in prognosis is 
remarkable: 5-year survival rates for early-stage HCC treated with curative 
intent can reach 70%, while advanced-stage disease usually has a median.</p>  
   </sec>  
   <sec id="S10">  
   
     <title>Therapeutic approaches</title>  
     <p>Therapeutic approaches for MASLD are evolving rapidly, with some of the current 
approaches involving modification of metabolic risk factors, new pharmacotherapy 
approaches, and intervention studies targeting risk factors implicated in the 
progression of disease [<xref ref-type="bibr" rid="ref31">31</xref>]. As research progresses into the MASLD metabolic, 
inflammatory, and fibrotic mechanisms, the therapeutic options available to 
manage MASLD continue to evolve. Current strategies include lifestyle 
modification, metabolic options, and most current work in pharmacological, 
molecular, and/or nano-technology therapeutics. The goal of these interventions 
is to reduce steatosis and inflammation, and halt the fibrosis and progression of 
long-term disease.</p>  

      <sec id="S10_1">
<title><italic>Anti-inflammatory drugs</italic></title>  
       <p>Inflammation represents a critical driver of MASLD-related hepatocarcinogenesis; 
thus, anti-inflammatory drugs may act as promising agents to block the 
development of HCC. Saroglitazar, a dual (Peroxisome proliferator-activated 
receptors) PPAR-&#x3B1;/&#x3B3; agonist, has been shown to inhibit tumor 
development in a NASH-driven HCC mouse model via the reduction of markers of 
liver injury and pro-inflammatory cytokines such as TNF-&#x3B1; [<xref ref-type="bibr" rid="ref32">32</xref>]. 
Similarly, scoparone, a naturally-occurring coumarin derivative, inhibited HCC 
development in NAFLD mice by inhibiting inflammation-related (p38 
Mitogen-Activated Protein Kinase/Also known as Protein Kinase B/Nuclear Factor 
kappa-light-chain-enhancer of activated B cells) p38-MAPK/Akt/NF-&#x3BA;B 
signaling pathways. Metformin, the famous licensed antidiabetic drug, has also 
chemopreventive impacts, as it decreases the incidence of HCC in preclinical 
models by regulating the immune cell populations and inhibiting 
inflammatory&#x2013;metabolic pathways [<xref ref-type="bibr" rid="ref33">33</xref>].</p>  
     </sec>  

       <sec id="S10_2">
<title><italic>Antioxidants</italic></title>  
       <p>Oxidative stress heightens the risk of liver injury and hastens progression from 
NASH to HCC. Antioxidants are capable of suppressing oxidative stress. Curcumin 
has been shown to reduce hepatic steatosis and fibrosis in a NASH-HCC mouse 
model, while downregulating pro-inflammatory cytokines and blocking the (high 
mobility group box 1 protein) HMGB1/NF-&#x3BA;B translocation, thus 
suppressing the carcinogenesis process [<xref ref-type="bibr" rid="ref34">34</xref>]. Additionally, meta-analyses of 
animal models have further demonstrated that curcumin downregulates Interleukin-6 
(IL-6), TNF-&#x3B1;, and other inflammatory markers through multiple signaling 
pathways (<italic>e.g.</italic>, (Toll-like receptor 4) TLR4/NF-&#x3BA;B, (Kelch-like 
ECH-associated protein 1 nuclear factor erythroid 2) Keap1/Nrf2), thereby 
attenuating the progression of NAFLD to HCC [<xref ref-type="bibr" rid="ref35">35</xref>]. Lycopene, a natural carotenoid 
of tomatoes, also protects against NASH by attenuating inflammasome activation 
(NLRP3), NF-&#x3BA;B activation, and by restoring the antioxidant defenses, 
potentially lowering the risk of HCC [<xref ref-type="bibr" rid="ref36">36</xref>].</p>  
     </sec>  
 
    <sec id="S10_3">
<title><italic>Anti-fibrotic</italic></title>  
       <p>In MASLD, fibrosis creates an environment that promotes cancer, and 
anti-fibrotic agents may have the potential to mitigate cancer progression. 
Pioglitazone, a selective agonist of PPAR-&#x3B3;, is widely known for its 
anti-fibrotic properties demonstrated in NASH models, which may reduce fibrosis 
by modulating multiple signaling pathways such as AMP-activated protein kinase 
(AMPK) and Mitogen-activated protein kinases (MAPK) that are involved in 
fibrosis, thereby preventing the fibrotic substrate to HCC. The drug NV556 (a new 
anti-fibrotic being tested in phase 1 trials) is little studied in HCC, but its 
capacity to blunt fibrogenic signaling elevates its potential in chemoprevention 
in fibrotic livers [<xref ref-type="bibr" rid="ref37">37</xref>].</p>  
     </sec>  

     <sec id="S10_4">
<title><italic>Lipid metabolism</italic></title>  
       <p>Disordered lipid metabolism and lipotoxicity contribute to liver injury and 
carcinogenesis. Interventions with n-3 polyunsaturated fatty acids (PUFAs) can 
restore lipid homeostasis by decreasing lipotoxic intermediates, which, in turn, 
can limit hepatocyte stress and possibly promote tumor growth. Bioactive 
plant-derived supplements, such as mulberry leaf powder, can also modulate lipid 
metabolism, reduce fatty acid overload, and intervene in lipotoxicity which would 
lead to reduced inflammation and tumorigenesis [<xref ref-type="bibr" rid="ref38">38</xref>].</p>  
     </sec>  
    
      <sec id="S10_5">
<title><italic>Immunomodulatory</italic></title>  
       <p>Immune dysregulation in MASLD leads to a tumor-permissive microenvironment. 
Therapies such as losartan may enhance anti-tumor immunity through reductions in 
fibrosis. Additionally, beneficial microbes, including Akkermansia muciniphila, 
have been shown to enhance T-cell mediated responses and improve immunotherapy 
responses in preclinical models, and thereby re-establish immune monitoring and 
limit tumor growth [<xref ref-type="bibr" rid="ref39">39</xref>].</p>  
     </sec>  
   </sec>  
   <sec id="S11">  
  
     <title>Emerging research and future directions</title>  
     <p>Flavonoids have proven to be synergistic with traditional chemotherapeutic 
agents to improve drug effectiveness and to target drug resistance. For example, 
quercetin has been shown to improve the anticancer ability of 5-fluorouracil and 
docetaxel, and epigallocatechin gallate (EGCG) improves the cytotoxicity of 
doxorubicin and gemcitabine. These combinations can lead to improved treatment 
outcomes while allowing dose reduction to minimize side effects. Recent studies 
have verified that targeting the ferroptotic pathway may impede the advancement 
of MASLD. Drugs like the thiazolidinediones (pioglitazone), Glucagon-like 
peptide-1 (GLP-1) receptors agonists (liraglutide), and a myriad of 
nutraceuticals including vitamin E, curcumin, quercetin have been found to have 
examples of anti-ferroptotic activity. These agents have been utilized to target 
the ferroptotic process through different mechanisms, including inhibitors of 
acyl-CoA synthetase long-chain family member 4 (ACSL4), activators of glutathione 
peroxidase 4 (GPX4), and/or stimulators of the Nrf2 antioxidant system. Their 
ability to modify iron homeostasis, inhibit oxidative stress-related damage, and 
to inhibit lipid peroxidation validates their influence as broad-spectrum 
treatment options for target MASLD.</p>  
     <p>In the future, perhaps our treatment response exploration will include 
ferroptosis-related biomarkers as a part of clinical trials. It is also important 
to gain a better understanding of the molecular processes, especially surrounding 
Factory X Racewear (FXR), AMPK, and mitochondrial factors. It may be possible to 
find novel treatment targets by identifying ferroptosis modulators in hepatic and 
extrahepatic tissues (such as adipose tissue and pancreatic &#x3B2;-cells). 
Additional clinical benefits may be provided by combination treatments that 
target inflammation, lipid metabolic abnormalities, and iron dysregulation. The 
application of AI-driven drug discovery techniques and delivery methods based on 
nanotechnology has the potential to speed up the creation of optimal medicines 
that target ferroptosis [<xref ref-type="bibr" rid="ref40">40</xref>]. However, one of the main challenges with 
ferroptosis-based therapies is that most of the evidence comes from preclinical 
studies (animal or cell models), and the best options for precisely regulating 
ferroptosis across the different stages of NAFLD are not well understood, which 
limits the translation of preclinical studies to human studies [<xref ref-type="bibr" rid="ref41">41</xref>]. Similarly, 
in AI-based therapeutic (or prognostic) approaches to liver disease (including 
MASLD), the hurdles included small and not representative datasets, not 
externally validated, algorithm transparency, and data integration and privacy 
issues, all of which limit real-world clinical use [<xref ref-type="bibr" rid="ref42">42</xref>]. Nonetheless, predictive 
medicine is changing quickly due to AI and machine learning (ML), especially in 
detecting high-risk MASLD patients who could develop HCC. Early and precise risk 
stratification is crucial because MASLD can develop into HCC without obvious 
clinical symptoms, particularly when severe fibrosis or cirrhosis is not present. 
Conventional screening methods frequently fail to identify at-risk people in 
these early, asymptomatic phases. A solution is provided by ML-based models, 
which use a variety of clinical and laboratory factors to produce individualized 
risk assessments. A recent study utilizing data from UC Davis and UC San 
Francisco developed a predictive model for HCC in patients with MASLD, achieving 
remarkable accuracy of 92.06% and an AUC of 0.97. Among the various clinical 
variables, the Fibrosis-4 (FIB-4) score emerged as the most influential 
predictor, followed by bilirubin, alkaline phosphatase (ALP), total cholesterol, 
and the presence of hypertension. The research underscored the power of ensemble 
learning algorithms like random forests and gradient boosting to handle 
complicated, nonlinear medical data, superior to other methods.</p>  
     <p>Future enhancements will come from integrating predictive systems with 
heterogeneous data sets; for example, in the future, predictive systems will 
utilize genomic data, imaging studies, environmental exposures, and lifestyle 
variables to perform risk stratification. Robust validation in real-world 
clinical practices and in ethnically diverse populations will be needed. 
Incorporation of these AI-based models into electronic medical record (EMR) 
systems could provide real-time risk stratification and inform population-level 
screening as well as tailored recommendations for individual patients [<xref ref-type="bibr" rid="ref43">43</xref>].</p>  
   </sec>  
   
    <sec id="S12" sec-type="conclusions">
     <title>Conclusion</title>  
     <p>Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known 
as non-alcoholic fatty liver disease, has become recognized as an important 
global health problem because of its strong relationship with hepatocellular 
carcinoma (HCC). MASLD is mainly induced by the triad of obesity, type 2 
diabetes, and physical inactivity, ranging from simple steatosis to NASH 
continuing through to fibrosis, cirrhosis, and liver cancer. One of the important 
clinical obstacles is that MASLD-associated HCC often develops in non-cirrhotic 
livers, making early-stage detection particularly difficult. This disease is 
developed by multifactorial mechanisms, such as insulin resistance, lipid 
accumulation, oxidative stress, mitochondrial dysfunction, and chronic 
inflammatory response. Recent advances in transcriptional and 
post-transcriptional processes have strengthened current understanding of 
carcinogenic pathways, with the participation of <italic>miR-33</italic> and 
<italic>IFI16</italic> splice variants. Non-invasive diagnostic approaches, including 
liquid biopsies, next-generation sequencing (NGS), and AI-based risk prediction 
approaches, are becoming increasingly established tools for early detection as 
well as personalized surveillance. Therapeutic approaches are developing, with 
particular focus on ameliorating oxidative stress, fibrosis, inflammatory 
pathways, and lipid dysregulation, as well as targeting bioactive 
flavonoids, repurposed drugs (<italic>i.e.</italic>, metformin and statins), and delivery 
systems in the form of nanotechnology. In conclusion, the treatment of MASLD and 
its oncogenic risks needs a precision-medicine strategy combining dietary and 
lifestyle interventions, targeted anti-pharmacotherapy, as well as an innovative 
diagnostic tool.</p>  
   </sec>  
   
   
   </body>
<back>
<ack>

   <sec id="S13">  
    
     <title>Availability of data and materials</title>  
     <p>Not applicable. This review did not generate or analyze any novel data. All 
information addressed is obtained as a result of published literature referred to 
in the article in the past.</p>  
   </sec>  
   <sec id="S14">  
    
     <title>Author contributions</title>  
     <p>AK&#x2014;conceived and designed the review and developed the literature search, data 
extraction, and analysis. AKS&#x2014;offered critical advice and helped with 
literature analysis as well as interpretation of results; helped in editorial 
modifications, read and endorsed the final manuscript. AK and AKS&#x2014;initially 
wrote and edited the manuscript. Both authors read and approved the final manuscript.</p>  
   </sec>  
   <sec id="S15">  
   
     <title>Ethics approval and consent to participate</title>  
     <p>Not applicable.</p>  
   </sec>  
   <sec id="S16">  
  
     <title>Acknowledgment</title>  
     <p>We would like to acknowledge the Department of Medical Lab Technology, 
Chandigarh University, for providing the required facilities.</p>  
   </sec>  
   <sec id="S17">  
   
     <title>Funding</title>  
     <p>This research received no external funding.</p>  
   </sec>  
   <sec id="S18">  
    
     <title>Conflict of interest</title>  
     <p>The authors declare no conflict of interest.</p>  
   </sec>  
  
</ack>

<fn-group>
<fn id="fn1"><p><italic>How to cite:</italic> Aditya Kamboj, Amit Kumar Singh. The oncogenic implications of metabolic dysfunction-associated steatotic liver disease. Journal of Renal and Hepatic Disorders. 2026; 10(1): 14-23. doi: 10.63268/jrenhp.v10i1.252.</p></fn></fn-group>



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