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	<title>DNA mismatch repair &#8211; Science</title>
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	<title>DNA mismatch repair &#8211; Science</title>
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		<title>Three-Gene Signature Predicts Survival and Platinum Drug Response in Liver Cancer</title>
		<link>https://scienmag.com/three-gene-signature-predicts-survival-and-platinum-drug-response-in-liver-cancer/</link>
		
		<dc:creator><![CDATA[Nathaniel Bowman]]></dc:creator>
		<pubDate>Wed, 23 Sep 2026 00:16:11 +0000</pubDate>
				<category><![CDATA[Cancer]]></category>
		<category><![CDATA[apoptosis regulation in tumors]]></category>
		<category><![CDATA[BAK1]]></category>
		<category><![CDATA[BIRC5]]></category>
		<category><![CDATA[cell-cycle control genes]]></category>
		<category><![CDATA[chemotherapy response biomarkers]]></category>
		<category><![CDATA[DNA mismatch repair]]></category>
		<category><![CDATA[DNA repair mechanisms in cancer]]></category>
		<category><![CDATA[genomic predictors of treatment response]]></category>
		<category><![CDATA[hepatocellular carcinoma]]></category>
		<category><![CDATA[international cohorts liver cancer study]]></category>
		<category><![CDATA[LASSO-Cox regression]]></category>
		<category><![CDATA[liver cancer]]></category>
		<category><![CDATA[liver cancer survival prediction]]></category>
		<category><![CDATA[MSH2]]></category>
		<category><![CDATA[oxaliplatin]]></category>
		<category><![CDATA[personalized treatment in hepatocellular carcinoma]]></category>
		<category><![CDATA[platinum drug resistance]]></category>
		<category><![CDATA[platinum resistance]]></category>
		<category><![CDATA[prognostic signature]]></category>
		<category><![CDATA[systemic therapy for liver cancer]]></category>
		<category><![CDATA[TCGA]]></category>
		<category><![CDATA[three-gene prognostic signature]]></category>
		<category><![CDATA[tumor immune microenvironment]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=209033</guid>

					<description><![CDATA[Researchers at Sun Yat-Sen University have developed a three-gene signature based on platinum resistance biology that predicts overall survival and oxaliplatin sensitivity in hepatocellular carcinoma across multiple international cohorts.]]></description>
										<content:encoded><![CDATA[<p>Hepatocellular carcinoma, the most common form of primary liver cancer, remains one of the deadliest malignancies worldwide, and clinicians have long struggled with a deceptively simple question: which patients will live longer, and which treatments will actually work for them? A new study published in BMC Cancer offers a data-driven answer built from an unexpected angle — the biology of platinum drug resistance. A team of researchers at Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, in Guangzhou, China, has constructed a compact three-gene prognostic signature drawn from genes linked to resistance against platinum-based chemotherapy, and shown that it can stratify overall survival in patients with hepatocellular carcinoma across multiple independent international cohorts.</p>
<p>The logic behind the approach is rooted in a clinical reality. Platinum compounds such as oxaliplatin and cisplatin are mainstays of systemic therapy for many cancers and are used in hepatocellular carcinoma, particularly in hepatic arterial infusion chemotherapy regimens. Yet responses vary dramatically between patients, and tumors that initially respond often acquire resistance. That variability implies that the molecular machinery governing platinum sensitivity — DNA repair, apoptosis, and cell-cycle control — is not merely a side note in treatment biology but may be woven into the fundamental behavior of the tumor itself. If so, the genes that determine whether a cell survives platinum damage might also carry prognostic information that transcends any single drug.</p>
<p>To test that hypothesis, the researchers assembled transcriptomic and clinical data from three large public repositories: The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), and the Gene Expression Omnibus (GEO). This multi-cohort design matters because a signature that only works in one dataset is often an artifact of overfitting rather than a genuine biological signal. By training in one cohort and validating in others, the team could ask whether their model generalized to patients whose tumors were sequenced in different laboratories, on different platforms, under different protocols.</p>
<p>The starting point was a curated panel of 70 platinum resistance-related genes, or PRRGs, drawn from the pathway literature. The researchers systematically evaluated the prognostic relevance of each gene in hepatocellular carcinoma, looking for consistent associations between expression levels and patient outcomes. From this screening process, three genes emerged with the strongest and most robust signal: BIRC5, BAK1, and MSH2. Each of these genes occupies a distinct and well-characterized position in cellular biology. BIRC5, better known in the literature as survivin, is an inhibitor of apoptosis protein that is barely detectable in most adult tissues but abundantly expressed in many tumors, where it helps cancer cells evade programmed cell death. BAK1 encodes a pro-apoptotic effector that sits at the mitochondrial gateway of the intrinsic apoptosis pathway, acting as a molecular trigger for self-destruction when cellular damage becomes irreparable. MSH2 is a core component of the DNA mismatch repair system, the cellular proofreading apparatus that corrects replication errors and recognizes certain types of DNA damage, including the lesions inflicted by platinum drugs.</p>
<p>With these three candidate genes in hand, the team built their Platinum Resistance-Related Prognostic Signature, abbreviated PRPS, using least absolute shrinkage and selection operator Cox regression, commonly known as LASSO. This statistical technique is a workhorse of modern genomics because it performs variable selection and regularization simultaneously, shrinking the coefficients of less informative genes toward zero and thereby producing models that are both parsimonious and less prone to overfitting. The resulting risk score assigns each patient a continuous value based on the weighted expression of BIRC5, BAK1, and MSH2, and patients are then classified into high-risk and low-risk groups by a threshold determined in the training data.</p>
<p>The performance of the signature was evaluated with a battery of standard survival-analysis tools. Kaplan-Meier curves showed a clear separation in overall survival between high- and low-risk patients in the TCGA training cohort, and — critically — the same separation held up in the ICGC validation cohort and in the independent GSE14520 dataset. Time-dependent receiver operating characteristic analysis quantified the signature&#8217;s discriminatory accuracy at multiple time points, while multivariable Cox regression addressed the essential question of clinical independence: does the PRPS predict survival beyond what is already captured by established factors such as tumor stage, alpha-fetoprotein levels, and age? The answer, according to the study, was yes, positioning the three-gene score as an independent prognostic factor rather than a redundant echo of conventional staging.</p>
<p>What do the three genes actually tell us about tumor biology? Functional enrichment and protein-protein interaction analyses, the latter performed using the STRING database, pointed to three interconnected biological themes: cell-cycle regulation, apoptosis, and DNA repair. This triad makes intuitive sense. Platinum drugs kill cells by cross-linking DNA; whether a tumor cell dies depends on how efficiently it repairs the damage, how readily it triggers apoptosis in response to unrepaired lesions, and how its cell-cycle checkpoints respond to genomic stress. A signature built from one gene in each of these arms — MSH2 in repair, BAK1 in apoptotic execution, and BIRC5 in apoptotic inhibition and mitotic regulation — effectively samples the tumor&#8217;s entire decision-making apparatus when confronted with platinum-induced injury.</p>
<p>Perhaps the most intriguing findings concern the tumor immune microenvironment. Using single-sample gene set enrichment analysis (ssGSEA) and the CIBERSORT computational deconvolution method, the researchers estimated the relative abundance of different immune cell populations within tumors from high-PRPS and low-PRPS patients. The two groups displayed distinct immune infiltration patterns, including differences in regulatory T cells, supporting the idea that the platinum resistance axis is entangled with immunological context. This observation carries practical weight, because the immune landscape of a tumor increasingly determines its response to immunotherapy, and a prognostic score that also tracks immune features could eventually help clinicians weigh combined treatment strategies. The study also examined total mutation burden and genomic alterations associated with the signature, adding a genomic dimension to the risk stratification.</p>
<p>Crucially, the team did not stop at computational analysis. In laboratory experiments using the PLC/PRF/5 hepatocellular carcinoma cell line, they knocked down each of the three genes individually and measured the consequences. Silencing MSH2, BAK1, or BIRC5 inhibited cell proliferation, and — more strikingly — increased the cells&#8217; sensitivity to oxaliplatin, reflected in reduced half-maximal inhibitory concentrations. These wet-lab results transform the signature from a purely statistical construct into a set of experimentally testable hypotheses: each gene is not merely correlated with outcome but appears functionally involved in the proliferative capacity and drug responsiveness of liver cancer cells. The authors are careful to frame this appropriately, noting that the findings support further prospective and mechanistic validation rather than immediate clinical deployment.</p>
<p>The study, led by Qiaohong Lin, Weidong Wang, and Kai Wen as co-first authors, with Haohan Liu, Yongcong Yan, and Zhiyu Xiao as corresponding authors, was conducted in accordance with the Declaration of Helsinki and approved by the institutional ethics committee of Sun Yat-Sen Memorial Hospital. It was funded by the National Natural Science Foundation of China, the Guangdong Basic and Applied Basic Research Foundation, the China Postdoctoral Science Foundation, and the Beijing Xisike Clinical Oncology Research Foundation, with the funders having no role in study design or analysis. For a disease that claims hundreds of thousands of lives each year, the appeal of a three-gene bloodless risk score is obvious: it is simple enough to be measured by routine quantitative PCR in a pathology laboratory, yet grounded in a biological axis — platinum sensitivity — that directly informs treatment decisions. If prospective validation confirms these results, the boundary between predicting prognosis and predicting drug response may begin to blur, and the humble mismatch repair gene, the mitochondrial apoptotic trigger, and the fetal survival factor survivin may find a new role at the bedside of liver cancer patients.</p>
<p><strong>Subject of Research:</strong> A platinum resistance-related three-gene prognostic signature for overall survival in hepatocellular carcinoma</p>
<p><strong>Article Title:</strong> Integrated analysis identifies a platinum resistance-related prognostic signature for overall survival in hepatocellular carcinoma</p>
<p><strong>Article References:</strong> Lin, Q., Wang, W., Wen, K., Tao, M., Wen, J., Li, H., Liang, K., Liu, H., Yan, Y., &amp; Xiao, Z. (2026). Integrated analysis identifies a platinum resistance-related prognostic signature for overall survival in hepatocellular carcinoma. <em>BMC Cancer</em>. <a href="https://doi.org/10.1186/s12885-026-17000-3" rel="noopener noreferrer">https://doi.org/10.1186/s12885-026-17000-3</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12885-026-17000-3" rel="noopener noreferrer">10.1186/s12885-026-17000-3</a></p>
<p><strong>Keywords:</strong> hepatocellular carcinoma, platinum resistance, prognostic signature, BIRC5, BAK1, MSH2, oxaliplatin, LASSO Cox regression, tumor immune microenvironment, TCGA, DNA mismatch repair, liver cancer</p>
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