Gliomas are primary brain tumors that arise from glial cells and range from slow-growing to highly aggressive. The World Health Organization grades them from 1 to 4; in practice, many studies contrast low-grade (grades 1–2) with high-grade (grades 3–4) disease because prognosis and treatment differ. Molecular features also matter. Mutations in IDH1/2 and codeletion of 1p/19q refine diagnosis and often track with outcome.
A major reason gliomas are difficult to treat is their invasive behavior. That trait connects to epithelial-to-mesenchymal transition (EMT), a cellular program in which cells loosen junctions and gain migratory capacity. EMT in glioma is better seen as a spectrum: tumor cells can display both epithelial markers (such as CDH1 and TJP1/ZO-1) and mesenchymal markers or regulators (including CDH2, VIM, CTNNB1, LEF1, NOTCH1, SOX2, SNAI1/2, ZEB1/2, and TWIST1). Mapping how these genes vary across glioma types and grades can clarify biology and point to practical targets for research.
A pooled look at 3,497 tumors
The study assembled eight cBioPortal cohorts totaling 3,497 samples from 3,143 patients. The team surveyed mutations, copy-number changes, and mRNA for 13 EMT-related genes, then layered on expression analyses from GlioVis, subtype patterns within glioblastoma (GBM), survival associations, methylation–expression links, and qRT-PCR validation in patient tissues (18 grade-2, 5 grade-3, 16 GBM; 12 controls).
NOTCH1 and SOX2 dominate the alteration map
Across low- and high-grade gliomas, NOTCH1 and SOX2 emerged as the most frequently altered genes. NOTCH1 changes were mainly mutations (with a substantial subset labeled oncogenic), while SOX2 tended to show amplification. When compared to other EMT markers such as CDH1, CTNNB1, or ZEB1, NOTCH1 alterations were more common. At the transcript level, both NOTCH1 and SOX2 were lower in GBM than in lower grades, and the team’s qRT-PCR echoed this decline with increasing grade.
Grade shapes the EMT profile
Alterations did not distribute evenly across disease stages. In the pooled analysis, NOTCH1 and LEF1 changes were associated with low-grade glioma, whereas shifts in CDH1, CTNNB1, TJP1/ZO-1, TWIST1, SOX2, VIM, ZEB1, and ZEB2 were linked to high-grade disease. Only GBM and diffuse glioma showed alterations across all 13 genes under study, underscoring broad EMT involvement in the most advanced tumors.
IDH1 status and GBM subtype refine the picture
Stratifying by IDH1 sharpened contrasts. IDH1-mutant GBM displayed lower expression of CDH2, LEF1, and SNAI1 and higher ZEB1 than IDH1-wild-type GBM. Subtype analysis within GBM added another layer: TJP1/ZO-1 aligned with the classical subtype, while ZEB2 aligned with the proneural subtype. These patterns highlight that EMT readouts depend on molecular context, not just histologic grade.
TWIST1 flags poorer survival
Among the 13 genes, higher TWIST1 expression was linked to shorter overall survival in GBM in Kaplan–Meier analysis. After age adjustment and IDH1 stratification, no single gene reached conventional significance, but TWIST1 continued to trend in the same direction. Taken together, the survival data position TWIST1 as a candidate marker worth deeper evaluation rather than a definitive prognostic test.
Bench validation supports key trends
The authors tested tumor and control tissues by qRT-PCR. Epithelial transcripts CDH1 and TJP1/ZO-1 were lower in tumors, consistent with reduced junctional features in higher-grade disease. CTNNB1, VIM, and TWIST1 rose with grade, while SOX2 and NOTCH1 declined—patterns generally consistent with the in-silico findings. Some targets (such as ZEB1/2 and LEF1) showed partial discordance, a reminder that cohort composition and technical choices can influence measurements.
DNA methylation links to expression
For several genes—including CDH1, TJP1/ZO-1, SNAI1/2, and VIM—mRNA levels correlated with DNA methylation, with a borderline signal for NOTCH1. These associations point to epigenetic regulation as one mechanism shaping EMT marker profiles in glioma.
What’s new—and why it matters
Novel findings
-
A cross-cohort map shows NOTCH1 and SOX2 are the most frequently altered EMT-related genes across glioma grades.
-
Grade-linked shifts separate low- from high-grade disease, while IDH1 status and GBM subtype further refine EMT expression patterns.
-
TWIST1 expression associates with poorer survival in GBM in unadjusted analysis.
-
Independent qRT-PCR in patient tissue largely mirrors the computational trends.
Practical implications for researchers
-
The alteration and expression landscape provides a data-driven shortlist—NOTCH1, SOX2, TWIST1, CTNNB1, VIM, ZEB1/2—for functional follow-up in models that capture IDH1 status and GBM subtype.
-
The methylation–expression relationships suggest pairing gene perturbation with epigenetic assays to understand regulatory control.
-
Because signals shift with grade, IDH1, and subtype, future experimental designs should stratify accordingly to avoid averaging away real effects.
Suggested next steps noted by the authors
-
Functional validation of NOTCH1 and SOX2 (e.g., knockdown in GBM cell lines) to test effects on proliferation, migration, and invasion.
-
Broader experimental work to link specific alterations to EMT phenotypes and to clarify which changes are drivers versus passengers.
Bottom line
This study assembles a large, coherent view of EMT-related genes across glioma. The most frequent alterations center on NOTCH1 and SOX2, multiple EMT markers track with grade and molecular subtype, and TWIST1 emerges as a survival-linked signal that warrants deeper study. For labs working on glioma biology, the dataset offers clear priorities and a framework for targeted experiments—while reminding us that EMT in the brain is not a switch but a spectrum influenced by both tumor grade and genotype.
The translation of the preceding English text in Croatian:
Gliomi su primarni tumori mozga koji nastaju iz glijalnih stanica i mogu varirati od spororastućih do vrlo agresivnih. Svjetska zdravstvena organizacija razvrstava ih u stupnjeve od 1 do 4; u praksi mnoge studije uspoređuju niskostupanjske (stupnjevi 1–2) i visokostupanjske (stupnjevi 3–4) oblike bolesti jer se prognoza i liječenje razlikuju. Važne su i molekularne značajke. Mutacije u IDH1/2 i kodelecija 1p/19q dodatno preciziraju dijagnozu i često su povezane s ishodom bolesti.
Glavni razlog zašto je gliome teško liječiti njihovo je invazivno ponašanje. Taj se fenomen povezuje s epitelno-mezenhimalnom tranzicijom (EMT), staničnim programom u kojem stanice gube međustanične spojeve i stječu migracijsku sposobnost. EMT u gliomu bolje je promatrati kao spektar: tumorske stanice mogu istodobno iskazivati epitelne markere (poput CDH1 i TJP1/ZO-1) te mezenhimalne markere ili regulatore (uključujući CDH2, VIM, CTNNB1, LEF1, NOTCH1, SOX2, SNAI1/2, ZEB1/2 i TWIST1). Mapiranje varijacija ekspresije ovih gena među različitim tipovima i stupnjevima glioma može razjasniti biološke procese i ukazati na praktične ciljeve istraživanja.
Zajednička analiza 3.497 tumora
Studija je obuhvatila osam kohorti s platforme cBioPortal, ukupno 3.497 uzoraka od 3.143 pacijenta. Tim je analizirao mutacije, promjene broja kopija gena i mRNA za 13 gena povezanih s EMT-om, a zatim dodao analize ekspresije iz baze GlioVis, obrasce podtipova unutar glioblastoma (GBM), povezanost sa preživljenjem, veze između metilacije i ekspresije te qRT-PCR validaciju u tkivima pacijenata (18 stupanj-2, 5 stupanj-3, 16 GBM; 12 kontrola).
NOTCH1 i SOX2 dominiraju kartom genetskih promjena
Kroz nisko- i visokostupanjske gliome, NOTCH1 i SOX2 pokazali su se kao najčešće promijenjeni geni. Promjene NOTCH1 bile su uglavnom mutacije (s velikim udjelom označenih kao onkogene), dok je SOX2 najčešće pokazivao amplifikaciju. U usporedbi s drugim EMT markerima poput CDH1, CTNNB1 ili ZEB1, promjene NOTCH1 bile su češće. Na razini transkripta, i NOTCH1 i SOX2 imali su nižu ekspresiju u GBM-u nego u nižim stupnjevima, a qRT-PCR analiza potvrdila je taj pad s porastom stupnja bolesti.
Stupanj bolesti oblikuje EMT profil
Promjene nisu bile jednoliko raspoređene među stadijima bolesti. U objednjenoj analizi, promjene NOTCH1 i LEF1 bile su povezane s niskostupanjskim gliomom, dok su promjene u CDH1, CTNNB1, TJP1/ZO-1, TWIST1, SOX2, VIM, ZEB1 i ZEB2 bile češće u visokostupanjskim tumorima. Samo GBM i difuzni gliom pokazali su promjene u svih 13 analiziranih gena, što naglašava široku uključenost EMT-a u najnaprednijim tumorima.
Status IDH1 i GBM podtip dodatno pojašnjavaju sliku
Stratifikacija prema IDH1 statusu dodatno je naglasila razlike. IDH1-mutantni GBM pokazao je nižu ekspresiju CDH2, LEF1 i SNAI1 te višu razinu ZEB1 u usporedbi s IDH1-wild-type GBM. Analiza podtipova unutar GBM-a dodala je još jedan sloj: TJP1/ZO-1 bio je povezan s klasičnim podtipom, dok je ZEB2 bio povezan s proneuralnim podtipom. Ovi obrasci pokazuju da EMT pokazatelji ovise o molekularnom kontekstu, a ne samo o histološkom stupnju.
TWIST1 označava lošije preživljenje
Među 13 gena, viša ekspresija TWIST1 povezana je s kraćim ukupnim preživljenjem u GBM-u prema Kaplan–Meier analizi. Nakon prilagodbe za dob i IDH1 status, nijedan gen nije dosegao konvencionalnu statističku značajnost, no TWIST1 je i dalje pokazivao isti trend. U cjelini, podaci o preživljenju pozicioniraju TWIST1 kao kandidatni marker vrijedan daljnje evaluacije, ali ne i kao konačni prognostički test.
Potvrda na razini eksperimentalnog stola
Autori su testirali tumorske i kontrolne uzorke pomoću qRT-PCR metode. Epitelni transkripti CDH1 i TJP1/ZO-1 bili su niži u tumorima, što je u skladu sa smanjenim međustaničnim spojevima u višim stupnjevima bolesti. CTNNB1, VIM i TWIST1 rasli su s porastom stupnja, dok su SOX2 i NOTCH1 padali – uzorci uglavnom u skladu s in-silico nalazima. Neki ciljevi (poput ZEB1/2 i LEF1) pokazali su djelomična odstupanja, što podsjeća da sastav kohorte i tehnički pristupi mogu utjecati na rezultate mjerenja.
Veze između DNA metilacije i ekspresije
Za nekoliko gena – uključujući CDH1, TJP1/ZO-1, SNAI1/2 i VIM – razine mRNA korelirale su s DNA metilacijom, s graničnim signalom za NOTCH1. Ove povezanosti ukazuju na epigenetsku regulaciju kao jedan od mehanizama koji oblikuju EMT profile u gliomu.
Što je novo — i zašto je važno
Nova saznanja
-
Karta više kohorti pokazuje da su NOTCH1 i SOX2 najčešće promijenjeni EMT-povezani geni kroz sve stupnjeve glioma.
-
Promjene povezane sa stupnjem razlikuju niskostupanjske od visokostupanjskih tumora, dok IDH1 status i GBM podtip dodatno preciziraju obrasce ekspresije EMT-a.
-
Ekspresija TWIST1 povezana je s lošijim preživljenjem u GBM-u u neovisnoj analizi.
-
Neovisna qRT-PCR analiza u tkivima pacijenata uglavnom potvrđuje računalne nalaze.
Praktične implikacije za istraživače
-
Krajolik promjena i ekspresije daje podatkovno utemeljen uži izbor gena — NOTCH1, SOX2, TWIST1, CTNNB1, VIM, ZEB1/2 — za funkcionalna istraživanja u modelima koji uključuju IDH1 status i GBM podtip.
-
Odnosi između metilacije i ekspresije sugeriraju da bi istraživanja trebala kombinirati genetske perturbacije s epigenetskim analizama radi razumijevanja regulatornih mehanizama.
-
Budući da se signali mijenjaju s tumorskim stupnjem, IDH1 statusom i podtipom, budući eksperimenti trebali bi biti stratificirani kako bi se izbjeglo “prosječno” gubljenje stvarnih učinaka.
Predloženi sljedeći koraci prema autorima
-
Funkcionalna validacija gena NOTCH1 i SOX2 (npr. knockdown u GBM staničnim linijama) radi testiranja učinaka na proliferaciju, migraciju i invaziju.
-
Šira eksperimentalna istraživanja za povezivanje specifičnih genetskih promjena s EMT fenotipovima i razjašnjenje koje su promjene pokretači, a koje samo prate bolest.
Zaključak
Ova studija nudi opsežan i koherentan pregled EMT-povezanih gena u gliomima. Najčešće promjene koncentrirane su oko NOTCH1 i SOX2, brojni EMT markeri koreliraju sa stupnjem i molekularnim podtipom, a TWIST1 se ističe kao signal povezan s preživljenjem koji zaslužuje dublje istraživanje. Za laboratorije koji proučavaju biologiju glioma, ovaj skup podataka nudi jasne prioritete i okvir za ciljane eksperimente — uz podsjetnik da EMT u mozgu nije prekidač, već spektar koji ovisi o stupnju tumora i genotipu.
Reference:
Nives Pećina-Šlaus, Alja Zottel, Željko Škripek, Borna Puljko, Fran Dumančić, Anja Bukovac, Ivana Jovčevska, Anja Kafka
In silico analysis reveals distinct changes in markers of epithelial to mesenchymal transition in glioma subtypes.
Biomol Biomed [Internet]. 2025 Jul. 17 [cited 2025 Nov. 7];25(12):2712–2736.
Available from: https://www.bjbms.org/ojs/index.php/bjbms/article/view/12598
Additional information:
We invite submissions for our upcoming thematic issues, including:
- Immune Prediction and Prognostic Biomarkers in Immuno-Oncology
- Artificial Intelligence and Machine Learning in disease diagnosis and treatment target identification
More news: Blog
Editor: Merima Hadžić
Leave a Reply