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	<title>drug transporters &#8211; Science</title>
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	<title>drug transporters &#8211; Science</title>
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		<title>Genes May Decide How Well Your Diabetes Drugs Work, Review Finds</title>
		<link>https://scienmag.com/genes-may-decide-how-well-your-diabetes-drugs-work-review-finds/</link>
		
		<dc:creator><![CDATA[Juliet Wilcox]]></dc:creator>
		<pubDate>Sat, 17 Oct 2026 03:05:11 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[clinical response to diabetes medication]]></category>
		<category><![CDATA[diabetes drug response variability]]></category>
		<category><![CDATA[drug transporters]]></category>
		<category><![CDATA[gene-guided diabetes therapy]]></category>
		<category><![CDATA[genetic factors in diabetes medication efficacy]]></category>
		<category><![CDATA[genetic predictors of drug side effects in diabetes]]></category>
		<category><![CDATA[Health Science Reports]]></category>
		<category><![CDATA[impact of genome on diabetes medication outcomes]]></category>
		<category><![CDATA[integrative review of diabetes pharmacogenetics]]></category>
		<category><![CDATA[MATE1]]></category>
		<category><![CDATA[Metformin]]></category>
		<category><![CDATA[metformin pharmacogenomics]]></category>
		<category><![CDATA[OCT1]]></category>
		<category><![CDATA[personalized diabetes treatment]]></category>
		<category><![CDATA[Pharmacogenetics]]></category>
		<category><![CDATA[pharmacogenetics of type 2 diabetes]]></category>
		<category><![CDATA[pharmacokinetic studies on diabetes drugs]]></category>
		<category><![CDATA[polygenic risk scores]]></category>
		<category><![CDATA[Precision medicine]]></category>
		<category><![CDATA[SGLT2 inhibitor response factors]]></category>
		<category><![CDATA[SGLT2 inhibitors]]></category>
		<category><![CDATA[Slc5a2]]></category>
		<category><![CDATA[Type 2 diabetes]]></category>
		<category><![CDATA[UGT1A9]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=292962</guid>

					<description><![CDATA[A new integrative review synthesizes 31 human studies showing how transporter, enzyme and target gene variants shape individual responses to metformin and SGLT2 inhibitors in type 2 diabetes.]]></description>
										<content:encoded><![CDATA[<p>Two of the most widely prescribed drugs in modern medicine, metformin and the sodium-glucose cotransporter-2 (SGLT2) inhibitors, work remarkably well for most people with type 2 diabetes, yet they fail or cause side effects in a substantial minority of patients. A new integrative review published in Health Science Reports argues that a large part of this unexplained variability may be written in the genome, and that the era of gene-guided diabetes therapy is approaching, even if it has not yet arrived.</p>
<p>The review, led by researchers synthesizing evidence from PubMed, Scopus and EBSCO up to July 2026, screened the literature according to PRISMA 2020 guidelines and ultimately included 31 original human studies: 18 on metformin and 13 on SGLT2 inhibitors. The authors deliberately chose an integrative framework, allowing them to combine pharmacogenetic association studies, pharmacokinetic investigations and clinical response data into a single narrative synthesis. Because the included studies varied so widely in design, populations and outcome measures, the team did not perform a formal meta-analysis or a uniform risk-of-bias assessment, instead weighing evidence by consistency, biological plausibility and sample size.</p>
<p>The scale of the clinical problem is enormous. According to the latest International Diabetes Federation Atlas figures cited in the review, roughly 589 million adults worldwide are living with type 2 diabetes, about one in nine adults, and that number is projected to reach 853 million by 2050. More than 90 percent of all adults with diabetes have the type 2 form, and approximately 252 million people, some 43 percent of the diabetic population, remain undiagnosed. With lifestyle change alone insufficient for most patients, pharmacotherapy is the backbone of treatment, which makes predictable drug response a global public health priority.</p>
<p>Metformin, the biguanide that has anchored first-line diabetes therapy for more than six decades, lowers glucose primarily by suppressing hepatic gluconeogenesis. It downregulates key gluconeogenic enzymes such as phosphoenolpyruvate carboxykinase and glucose-6-phosphatase, dampens glucagon-driven cAMP and protein kinase A signalling, and blocks mitochondrial glycerophosphate dehydrogenase, limiting the conversion of lactate and glycerol into glucose. It also activates AMP-activated protein kinase by inhibiting mitochondrial complex I, which reduces ATP and raises AMP, thereby curbing glucose production and lipogenesis while improving insulin sensitivity and promoting GLUT4-mediated glucose uptake in muscle and fat. Beyond glycemia, the drug has attracted interest for potential roles in cancer, polycystic ovary syndrome, non-alcoholic fatty liver disease and aging, and recent work suggests it may modulate the gut microbiome and stimulate the appetite-related metabolite N-lactoyl-phenylalanine.</p>
<p>Because metformin is not meaningfully metabolized, its fate in the body depends almost entirely on membrane transporters. Organic cation transporters encoded by SLC22A1 (OCT1), SLC22A2 (OCT2) and SLC22A3 (OCT3) mediate hepatic uptake, renal uptake and tissue distribution, while the multidrug and toxin extrusion proteins MATE1 and MATE2, encoded by SLC47A1 and SLC47A2, handle efflux into bile and urine. Polymorphisms in these genes can alter intracellular drug concentrations, systemic exposure and clearance, and thereby shift both glycemic efficacy and tolerability. The review identifies SLC22A1 as the most consistent genetic marker of metformin response: reduced-function OCT1 alleles have been linked across Han Chinese, Danish, Jordanian, Mexican-Mestizo and South Indian cohorts to attenuated HbA1c reductions, lower plasma metformin concentrations and higher rates of gastrointestinal intolerance. Notably, Danish data showed that carriers of the rs72552763 deletion experienced roughly 1.1 percent less HbA1c lowering at six months than non-carriers.</p>
<p>The evidence for the other transporter genes is more modest and less reproducible. SLC22A2 variants, particularly rs316019, appear to influence renal clearance of metformin more than glucose-lowering effect, with some studies showing reduced clearance in carriers and others finding no significant interaction at all. SLC22A3 and SLC47A1 show moderate, population-dependent associations with glycemic response, while SLC47A2 findings are inconsistent across South Indian and Iraqi cohorts. Intriguingly, the ATM gene, which encodes a kinase functionally linked to AMPK signalling rather than drug transport, has been associated with variability in metformin efficacy in both Chinese and large European cohorts, demonstrating that pharmacodynamic pathways, not just pharmacokinetic ones, shape who responds. The review&#8217;s authors stress that none of these individual associations yet supports routine genotype-guided metformin prescribing.</p>
<p>SGLT2 inhibitors, by contrast, represent a younger and genetically less charted pharmacogenomic landscape. This drug class, including canagliflozin, dapagliflozin, empagliflozin, ertugliflozin and bexagliflozin, descends conceptually from phlorizin, a compound isolated from apple tree bark whose glucose-blocking properties in the kidney were recognized as early as the 1930s. Modern gliflozins selectively inhibit SGLT2, the transporter responsible for reabsorbing roughly 90 to 97 percent of filtered glucose in the proximal tubule, forcing the excess glucose out in urine through an entirely insulin-independent mechanism. In persistent hyperglycemia, renal SGLT2 expression is upregulated, so blocking it counteracts a maladaptive amplification loop. Although their glucose-lowering effect is modest, large trials have established robust cardiovascular and renoprotective benefits, making them a cornerstone of contemporary care.</p>
<p>Pharmacogenetically, SGLT2 inhibitors are metabolized mainly by glucuronidation through UGT1A9 and UGT2B4. Reduced-function variants such as UGT1A9*3 (p.Met33Thr) increase systemic exposure to canagliflozin and ertugliflozin by about 1.26 to 1.45-fold in pharmacokinetic studies, but these changes have not translated into clinically meaningful differences in efficacy or dose requirements, and pooled analyses of more than 1,600 participants concluded that no dose adjustment is warranted. Variants in the drug target gene SLC5A2, which encodes SGLT2 itself, show associations with glucose homeostasis, HbA1c and diabetes risk in some populations, and one Slovenian study linked the rs9934336 A allele to higher fasting glucose and increased risk of diabetic retinopathy. Emerging but preliminary data suggest SLC5A2 variants may even modulate cardiorenal outcomes, possibly reflecting a form of natural SGLT2 inhibition that limits additional drug benefit. Meanwhile, the PNPLA3 I148M variant, a major determinant of fatty liver disease, appears to modify how much liver fat patients lose on dapagliflozin, with risk-allele carriers responding less to monotherapy but more when the drug is combined with omega-3 carboxylic acids.</p>
<p>The review&#8217;s comparative analysis highlights how mechanistically distinct these two drug classes are, and why their pharmacogenetic profiles differ so sharply. Metformin acts on the liver and depends on a well-characterized transporter network, giving it the most mature pharmacogenetic evidence base of any oral glucose-lowering agent. SGLT2 inhibitors act on the kidney, are cleared by hepatic glucuronidation, and carry strong cardiorenal benefits with very low hypoglycemia risk, but their genetic determinants remain emerging and modest in effect. The authors grade SLC22A1 as the most promising biomarker for clinical use, while most other metformin genes and all SGLT2-related markers remain investigational or exploratory. A recurring theme is that drug response is inherently polygenic: no single variant explains enough variance to guide treatment alone, and genetic effects operate within a web of clinical and environmental modifiers including renal function, diet, concomitant medications and the gut microbiome, which is estimated to contribute alongside genetics to roughly a third of the individual variation in metformin response.</p>
<p>Looking forward, the review outlines several priorities for translating pharmacogenomics into practice. Polygenic risk scores tailored to metformin and SGLT2 inhibitors must be developed, but current discovery cohorts are heavily Eurocentric, limiting generalizability to South Asian, Latino and African populations where genetic architecture and drug response may differ. Multi-omics integration, combining genomics with proteomics, metabolomics, metagenomics and epigenomics, is proposed as the path to more accurate prediction, potentially accelerated by artificial intelligence. Implementation science matters too: clinicians have expressed frustration with commercial pharmacogenetic panels that lack actionable diabetes-specific information and are not embedded in electronic medical records. Ultimately, the authors conclude that large prospective, multicenter, ethnically diverse interventional studies, ideally piggybacking on ongoing cardiovascular and renal trials of SGLT2 inhibitors, are essential before gene-guided glycemic therapy can move from promising biology to routine clinical decision-making.</p>
<p><strong>Subject of Research:</strong> Pharmacogenetics of metformin and SGLT2 inhibitor response in type 2 diabetes</p>
<p><strong>Article Title:</strong> Gene‐Guided Therapy in Type 2 Diabetes Mellitus: An Integrative Review of the Pharmacogenetics of Metformin and Sodium‐Glucose Cotransporter‐2 Inhibitors</p>
<p><strong>Article References:</strong> Hossain, I., Haidar, M., Ratul, M. A., Sumona, J. F., Shabnaz, S., Nokib, A. F., &amp; Fatema‐Tuz‐Zohora (2026). Gene‐Guided Therapy in Type 2 Diabetes Mellitus: An Integrative Review of the Pharmacogenetics of Metformin and Sodium‐Glucose Cotransporter‐2 Inhibitors. <em>Endocrinology, Diabetes &amp; Metabolism, 9</em>(6), Article e70343. <a href="https://doi.org/10.1002/edm2.70343" rel="noopener noreferrer">https://doi.org/10.1002/edm2.70343</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1002/edm2.70343" rel="noopener noreferrer">10.1002/edm2.70343</a></p>
<p><strong>Keywords:</strong> type 2 diabetes, metformin, SGLT2 inhibitors, pharmacogenetics, OCT1, MATE1, UGT1A9, SLC5A2, precision medicine, polygenic risk scores, drug transporters, Health Science Reports</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">292962</post-id>	</item>
		<item>
		<title>Thyroid Cancer Protein Rewires Tumor Metabolism and Drives Drug Resistance</title>
		<link>https://scienmag.com/thyroid-cancer-protein-rewires-tumor-metabolism-and-drives-drug-resistance/</link>
		
		<dc:creator><![CDATA[Nathaniel Bowman]]></dc:creator>
		<pubDate>Sat, 12 Sep 2026 16:37:07 +0000</pubDate>
				<category><![CDATA[Cancer]]></category>
		<category><![CDATA[biomarker]]></category>
		<category><![CDATA[cancer cell signaling pathways]]></category>
		<category><![CDATA[cancer metabolism]]></category>
		<category><![CDATA[cancer treatment resistance]]></category>
		<category><![CDATA[chemoresistance]]></category>
		<category><![CDATA[drug transporters]]></category>
		<category><![CDATA[ECT2]]></category>
		<category><![CDATA[ECT2 protein in cancer]]></category>
		<category><![CDATA[glycolysis]]></category>
		<category><![CDATA[lipoic acid]]></category>
		<category><![CDATA[metabolic reprogramming in cancer]]></category>
		<category><![CDATA[molecular targets for thyroid cancer therapy]]></category>
		<category><![CDATA[MYC]]></category>
		<category><![CDATA[oncogenes and tumor suppressors]]></category>
		<category><![CDATA[papillary thyroid carcinoma]]></category>
		<category><![CDATA[PI3K/AKT pathway]]></category>
		<category><![CDATA[PI3K/AKT pathway in thyroid cancer]]></category>
		<category><![CDATA[RhoA]]></category>
		<category><![CDATA[role of lipoic acid in tumor growth]]></category>
		<category><![CDATA[Thyroid cancer]]></category>
		<category><![CDATA[Thyroid cancer metabolism]]></category>
		<category><![CDATA[tumor drug resistance mechanisms]]></category>
		<category><![CDATA[tumor microenvironment influence]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=196391</guid>

					<description><![CDATA[New research shows the protein ECT2 drives papillary thyroid carcinoma growth by suppressing lipoic acid metabolism, activating PI3K/AKT signaling and fueling glycolysis while simultaneously promoting chemotherapy resistance through altered drug transport.]]></description>
										<content:encoded><![CDATA[<p>A single protein may help explain why some papillary thyroid carcinomas grow more aggressively and shrug off chemotherapy, according to a new study published in Cancer Cell International. Researchers led by Zhishan Huang of Jiangnan University&#8217;s School of Medicine report that ECT2, a protein better known for its role in cell division, acts as a metabolic master switch in papillary thyroid carcinoma, or PTC, the most common form of thyroid cancer. The team found that ECT2 suppresses a cellular pathway involving lipoic acid while simultaneously activating the well-known PI3K/AKT signaling cascade, and that elevated ECT2 levels correlate with poorer outcomes in thyroid cancer patients.</p>
<p>ECT2, or epithelial cell transforming sequence 2, has long presented oncologists with a paradox. Across different cancer types it has been reported to behave sometimes as an oncogene that drives tumor growth and sometimes as a tumor suppressor that restrains it, with its effect apparently dictated by a mixture of intrinsic cellular factors and cues from the surrounding tumor microenvironment. What has been missing, the authors argue, is a clear picture of what ECT2 actually does in PTC, where its expression dynamics, clinical relevance and mechanism of action had remained poorly defined. The new work sets out to fill that gap with a combination of patient tissue analysis and mechanistic experiments in cell lines.</p>
<p>The team began by measuring ECT2 in surgical specimens from PTC patients using immunohistochemistry, a technique that reveals where proteins accumulate within tissue sections. They complemented this with quantitative real-time PCR and Western blotting to quantify messenger RNA and protein levels in PTC cell lines compared with normal thyroid epithelial cells. The results were consistent across methods: ECT2 was significantly upregulated in tumor cells, and high expression in patient tumors tracked closely with poor prognosis, marking the protein as a potential predictive biomarker for the disease.</p>
<p>To probe what ECT2 was actually doing, the researchers turned to loss-of-function experiments in two widely used PTC cell lines, TPC-1 and BCPAP. When they knocked down ECT2, the cells&#8217; capacity to proliferate dropped sharply, as measured by CCK-8 assays and colony formation tests, which gauge both short-term metabolic activity and the ability of individual cells to establish expanding colonies. Transwell migration and invasion assays showed that ECT2 depletion also hampered the cells&#8217; movement through artificial barriers, a laboratory proxy for the invasive behavior that makes cancers dangerous. Conversely, activating ECT2 signaling pushed proliferation in the opposite direction, confirming the protein&#8217;s role as a growth promoter in these cells.</p>
<p>The mechanistic heart of the study came from RNA sequencing, which allowed the team to survey the entire transcriptomic landscape of PTC cells with and without ECT2. That analysis revealed a dual regulatory scheme. On one side, ECT2 suppresses the lipoic acid pathway; on the other, it activates the PI3K/AKT pathway, a canonical growth-signaling route frequently hijacked in human cancers. Lipoic acid, a mitochondrial cofactor essential for energy-generating enzyme complexes, has emerged in recent years as a regulator of cellular metabolism, and its suppression by ECT2 suggests the protein is actively reshaping how thyroid tumor cells produce and spend energy.</p>
<p>The sequencing data pointed to a specific chain of events downstream of ECT2. The protein induces phosphorylation of RhoA, a small GTP-binding protein involved in cytoskeletal regulation, which in turn activates the transcription factor MYC, one of the most potent drivers of gene expression in proliferating cells. Activated MYC ramps up the expression of glycolysis-related genes, pushing the cells toward the fermentative glucose metabolism that characterizes the Warburg effect, the metabolic reprogramming that allows rapidly dividing tumors to generate biomass and signaling intermediates even in oxygen-rich conditions. In effect, ECT2 appears to rewire PTC cells&#8217; energy economy from the top down, through a signaling cascade that connects a cytoskeletal regulator to one of cancer biology&#8217;s most influential transcription factors.</p>
<p>Perhaps the most clinically provocative finding concerns drug resistance. The researchers found that ECT2 downregulates drug influx transporters, the molecular gatekeepers that carry chemotherapeutic agents into cells, while simultaneously upregulating efflux transporters that pump drugs back out. The net effect is that tumor cells take in less medication and expel more of what does get in, raising the IC50 value, the drug concentration required to kill half the cells, and thereby rendering them measurably more resistant to treatment. This transport-based resistance mechanism operates independently of the metabolic reprogramming, giving ECT2 a second, parallel route to worsening patient outcomes.</p>
<p>Taken together, the findings recast ECT2 as a hub where growth signaling, metabolic reprogramming and drug transport converge in papillary thyroid carcinoma. The authors conclude that the protein drives PTC cell proliferation through its dual suppression of the lipoic acid pathway and activation of PI3K/AKT, while its effects on RhoA phosphorylation, MYC activation and glycolysis gene expression provide the metabolic fuel for unchecked growth, and its manipulation of transporters undermines chemotherapy. They emphasize that these discoveries offer a novel entry point for targeting the ECT2 signaling axis therapeutically, potentially combining metabolic interventions with strategies to restore drug sensitivity.</p>
<p>The study, supported by the Wuxi Double Hundred Top-notch Talent Program, also carries important caveats that the authors themselves acknowledge. The core mechanistic work was performed in cell lines, and while the clinical correlation between ECT2 expression and prognosis was established in patient specimens, the full pathway from protein to patient outcome will require further validation in animal models and larger clinical cohorts. The researchers call explicitly for continued mechanistic and translational investigation, noting that turning a biomarker discovery into a therapeutic strategy is a long road involving drug development, delivery optimization and careful patient stratification.</p>
<p>For a cancer that is often described as highly curable, papillary thyroid carcinoma nonetheless poses real challenges in the subset of patients with aggressive, treatment-refractory disease, and the identification of ECT2 as a driver of both proliferation and chemoresistance offers a molecular handle on that problem. If subsequent studies confirm that blocking ECT2 activity, or restoring lipoic acid pathway function, can sensitize tumors to existing drugs, the protein could become both a prognostic marker guiding treatment intensity and a target for combination therapies aimed at the metabolic vulnerabilities of hard-to-treat thyroid cancers.</p>
<p><strong>Subject of Research:</strong> The role of ECT2 in regulating energy metabolism and chemoresistance in papillary thyroid carcinoma.</p>
<p><strong>Article Title:</strong> ECT2 antagonizes lipoic acid to modulate papillary thyroid carcinoma progression through energy metabolism pathways</p>
<p><strong>Article References:</strong> Huang, Z., Gao, Y., Wang, N., Cai, D., &amp; Bai, N. (2026). ECT2 antagonizes lipoic acid to modulate papillary thyroid carcinoma progression through energy metabolism pathways. <em>Cancer Cell International</em>. <a href="https://doi.org/10.1186/s12935-026-04459-0" rel="noopener noreferrer">https://doi.org/10.1186/s12935-026-04459-0</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12935-026-04459-0" rel="noopener noreferrer">10.1186/s12935-026-04459-0</a></p>
<p><strong>Keywords:</strong> ECT2, papillary thyroid carcinoma, lipoic acid, PI3K/AKT pathway, glycolysis, MYC, RhoA, chemoresistance, cancer metabolism, thyroid cancer, drug transporters, biomarker</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">196391</post-id>	</item>
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