bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.09.18.752756

Passenger co-deletion confounds glutaminolysis signatures anchored on PTEN loss: a cautionary case for location-aware signature design

Abstract

PTEN-deficient tumors are widely assumed to be glutamine-dependent, a view that has helped motivate the clinical development of glutaminase inhibitors. Whether glutaminolytic transcription scales with PTEN copy-number loss in human tumors, and by what mechanism, has not been established. We classified TCGA PanCancer Atlas tumors by GISTIC copy number as PTEN intact, hemizygous, or homozygous deletion, and scored a five-gene glutaminolysis signature (GLS, SLC1A5, GOT1, GLUD1, GPT2) against loss severity across fourteen tumor types, testing MYC mediation and chromosome-10 co-deletion as alternative mechanisms, with GLS dependence assessed in DepMap CRISPR data. The signature decreased with PTEN loss in all fourteen types, significantly in twelve, but was not MYC-mediated. The decline tracked chromosomal position rather than pathway membership: GLUD1 and GOT1 flank PTEN on 10q, and thirty-seven neighboring genes carrying no glutaminolysis annotation tracked PTEN copy number just as closely (mean rho 0.843 compared with 0.842), with co-deletion fidelity falling monotonically with distance from PTEN (rho = -0.993). Adjustment for genome-wide aneuploidy left the association intact, whereas conditioning on each gene's own copy number abolished it for the chromosome-10 genes and left the others unchanged. In a natural experiment contrasting PTEN point-mutant, copy-neutral tumors with copy-neutral wild-type tumors, GLUD1 was lower in the mutant group when all cohorts were pooled (P = 1.0 x 10^-8), an effect attributable to endometrial carcinoma, the one lineage in which mutation alone lowered GLUD1; excluding that lineage in a post hoc sensitivity analysis left no detectable difference (P = 0.22, equivalence P = 0.015), whereas hemizygous and homozygous deletion lowered GLUD1 dose-dependently in every analysis. GLS dependence did not differ across dosage tiers. Prostate carcinoma was the sole departure in the negative direction, its off-chromosome-10 decline surviving adjustment for tumor purity, stage, ERG status and proliferation, opposite in direction to the signaling prediction; breast and stomach showed small positive associations. The inverse PTEN-glutaminolysis relationship in this transcript signature is therefore explained predominantly by passenger co-deletion rather than by a PTEN-linked metabolic program, making PTEN copy number unreliable as a stand-alone glutaminolysis biomarker and illustrating a general hazard: any signature scored against a frequently co-deleted locus can be confounded by where its genes sit. We provide a four-step screening procedure: decompose the signature by chromosomal position relative to the driver; test each constituent gene's own copy number against the driver's; compare driver-mutant copy-neutral tumors with copy-neutral wild-type tumors; and check the inferred pathway activity against an independent functional readout.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Abusneina, A. M., Elwirfli, S. M.. 2026-09-22. Passenger co-deletion confounds glutaminolysis signatures anchored on PTEN loss: a cautionary case for location-aware signature design. https://doi.org/10.64898/2026.09.18.752756

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

m6A-Driven Intratumoral Cholesterol Biosynthesis Fuels Castration-Resistant Prostate Cancer Progression

Both nuclear pore complexes (NPCs) and RNA N6-methyladenosine (m6A) machinery are indispensable for proper cellular function. Although their collaborative roles in the nuclear export of messenger RNAs (mRNAs) have been reported, it remains ambiguous whether and how this collaboration may contribute to cancer progression. Here we identify a functional cooperation between NPCs and m6A signaling that promotes the development of castration-resistant prostate cancer (CRPC). We showed that nuclear export of m6A-modified mRNAs, mediated by the interaction between RNA methyltransferase METTL3 and the nucleoporin NUP93, is functionally coupled to cholesterol biosynthesis. Given that cholesterol-fueled intratumoral androgen production is one of the mechanisms driving CRPC, we demonstrated that overexpression of the wild-type METTL3 or NUP93, but neither the enzymatically dead METTL3 nor the mutant NUP93 that loses METTL3-interacting capability, elevates intracellular levels of androgens, activates AR signaling under castrate condition, and promotes androgen-independent growth of prostate cancer cells both in vitro and in vivo. Importantly, pharmacological inhibition of METTL3 or targeted demethylation on mRNAs encoding key cholesterol biosynthesis enzymes effectively suppressed CRPC malignancy. Together, these findings uncover a therapeutically targetable m6A-METTL3-NUP93 axis that links nuclear mRNA export and metabolic reprogramming to fuel CRPC progression, providing a conceptually new strategy for the treatment of this lethal disease.

cancer biology↗

ST6Gal2 promotes α2,6-sialylation and aggressive phenotypes in neuroblastoma cells

Neuroblastoma is the most common extracranial solid tumor of childhood. Its clinical behavior ranges from spontaneous regression to lethal, treatment-refractory disease. Aberrant 2,6-sialylation contributes to aggressive phenotypes in many cancers, but the role of ST6Gal2, a neural-enriched 2,6-sialyltransferase, in neuroblastoma is largely unexplored. Here, we examine the clinical and functional significance of ST6Gal2 in neuroblastoma. In two independent public cohorts (SEQC, n=498; Kocak, n=649), high ST6GAL2 expression was associated with significantly worse overall and event-free survival. In the SEQC cohort, ST6GAL2 expression was higher in high-risk and MYCN-amplified tumors, varied across International Neuroblastoma Staging System stages, and correlated positively with a mesenchymal transcriptional signature (Spearman {rho}=0.181). The mesenchymal correlation was reproduced in the Kocak cohort ({rho}=0.204). Stable shRNA-mediated knockdown of ST6GAL2 in SK-N-AS and SK-N-BE(2) cells reduced proliferation and viability, impaired wound closure, and decreased migration and invasion. In preliminary experiments in SK-N-AS cells, ST6GAL2 knockdown reduced binding of Sambucus nigra agglutinin, consistent with a role for ST6Gal2 in 2,6-sialylation. Together, these findings link ST6Gal2 expression to aggressive clinical and transcriptional features and pro-tumorigenic phenotypes in neuroblastoma and nominate ST6Gal2-mediated sialylation as a candidate pathway for mechanistic study.

cancer biology↗

Unsupervised transcriptomic analysis of paired pre- and post-treatment specimens reveals divergent chemoimmunomodulatory induction trajectories in breast cancer

The immunomodulatory effects of chemotherapy (chemoimmunomodulation; CIM) are clinically consequential and heterogeneous, yet no systematic framework exists for classifying the immunomodulatory trajectory a tumor follows in response to treatment (CIM trajectory). Here, we present the CIM Induction Classifier (CIMIC), an unsupervised clustering pipeline leveraging delta gene expression across 3,189 CIM-related genes to classify specimens chemoimmunomodulatory trajectory. Applied to two pre- and post-chemotherapy breast cancer (BC) datasets (NKI/SMC, N = 36; NEO, N = 19) and nine epirubicin-perturbed triple-negative BC (TNBC) cell lines, CIMIC identified two divergent CIM trajectories: a functional CIM (Fun-CIM) trajectory, broadly conserved across tumors and cell lines and characterized by induction of inflammatory cell death, antigen presentation, viral mimicry, and adaptive immune activation programs, and a dysfunctional CIM (Dys-CIM) trajectory, characterized by induction of proteostatic and metabolic stress-adaptation programs, reduced immune cell abundances and cytotoxic activity, and enrichment of aggressive BC subtypes. Using survival and longitudinal transcriptomic data in NKI/SMC (N = 20), treatment-induced increases in Fun-CIM-associated genes and ssGSEA scores were associated with reduced recurrence, whereas Dys-CIM-associated genes and scores were associated with increased recurrence. In multivariable analyses within independent chemotherapy-treated BC cohorts (METABRIC, N = 412; SCAN-B, N = 2,462), higher baseline Fun-CIM ssGSEA scores were associated with better outcomes, whereas higher baseline Dys-CIM ssGSEA scores were associated with worse outcomes. These findings establish CIM as a dynamic, trajectory-level process and position CIMIC as a framework for defining CIM trajectories and supporting future efforts to identify predictors, mechanisms, and therapeutic strategies that maximize beneficial CIM.

cancer biology↗