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A high-risk retinoblastoma subtype with stemness features, dedifferentiated cone states and neuronal/ganglion cell gene expression.

ABSTRACT: Retinoblastoma is the most frequent intraocular malignancy in children, originating from a maturing cone precursor in the developing retina. Little is known on the molecular basis underlying the biological and clinical behavior of this cancer. Here, using multi-omics data, we demonstrate the existence of two retinoblastoma subtypes. Subtype 1, of earlier onset, includes most of the heritable forms. It harbors few genetic alterations other than the initiating RB1 inactivation and corresponds to differentiated tumors expressing mature cone markers. By contrast, subtype 2 tumors harbor frequent recurrent genetic alterations including MYCN-amplification. They express markers of less differentiated cone together with neuronal/ganglion cell markers with marked inter- and intra-tumor heterogeneity. The cone dedifferentiation in subtype 2 is associated with stemness features including low immune and interferon response, E2F and MYC/MYCN activation and a higher propensity for metastasis. The recognition of these two subtypes, one maintaining a cone-differentiated state, and the other, more aggressive, associated with cone dedifferentiation and expression of neuronal markers, opens up important biological and clinical perspectives for retinoblastomas.

SUBMITTER: Liu J

PROVIDER: S-EPMC8458383 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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A high-risk retinoblastoma subtype with stemness features, dedifferentiated cone states and neuronal/ganglion cell gene expression.

Liu Jing J Ottaviani Daniela D Sefta Meriem M Desbrousses Céline C Chapeaublanc Elodie E Aschero Rosario R Sirab Nanor N Lubieniecki Fabiana F Lamas Gabriela G Tonon Laurie L Dehainault Catherine C Hua Clément C Fréneaux Paul P Reichman Sacha S Karboul Narjesse N Biton Anne A Mirabal-Ortega Liliana L Larcher Magalie M Brulard Céline C Arrufat Sandrine S Nicolas André A Elarouci Nabila N Popova Tatiana T Némati Fariba F Decaudin Didier D Gentien David D Baulande Sylvain S Mariani Odette O Dufour Florent F Guibert Sylvain S Vallot Céline C Rouic Livia Lumbroso-Le LL Matet Alexandre A Desjardins Laurence L Pascual-Pasto Guillem G Suñol Mariona M Catala-Mora Jaume J Llano Genoveva Correa GC Couturier Jérôme J Barillot Emmanuel E Schaiquevich Paula P Gauthier-Villars Marion M Stoppa-Lyonnet Dominique D Golmard Lisa L Houdayer Claude C Brisse Hervé H Bernard-Pierrot Isabelle I Letouzé Eric E Viari Alain A Saule Simon S Sastre-Garau Xavier X Doz François F Carcaboso Angel M AM Cassoux Nathalie N Pouponnot Celio C Goureau Olivier O Chantada Guillermo G de Reyniès Aurélien A Aerts Isabelle I Radvanyi François F

Nature communications 20210922 1

Retinoblastoma is the most frequent intraocular malignancy in children, originating from a maturing cone precursor in the developing retina. Little is known on the molecular basis underlying the biological and clinical behavior of this cancer. Here, using multi-omics data, we demonstrate the existence of two retinoblastoma subtypes. Subtype 1, of earlier onset, includes most of the heritable forms. It harbors few genetic alterations other than the initiating RB1 inactivation and corresponds to d ...[more]

PMID: 34552068

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Project description:BackgroundCancer stemness has been proven to affect tumorigenesis, metastasis, and drug resistance in various cancers, including lung squamous cell carcinoma (LUSC). We intended to develop a clinically applicable stemness subtype classifier that could assist physicians in predicting patient prognosis and treatment response.MethodsThis study collected RNA-seq data from TCGA and GEO databases to calculate transcriptional stemness indices (mRNAsi) using the one-class logistic regression machine learning algorithm. Unsupervised consensus clustering was conducted to identify a stemness-based classification. Immune infiltration analysis (ESTIMATE and ssGSEA algorithms) methods were used to investigate the immune infiltration status of different subtypes. Tumor Immune Dysfunction and Exclusion (TIDE) and Immunophenotype Score (IPS) were used to evaluate the immunotherapy response. The pRRophetic algorithm was used to estimate the efficiency of chemotherapeutic and targeted agents. Two machine learning algorithms (LASSO and RF) and multivariate logistic regression analysis were performed to construct a novel stemness-related classifier.ResultsWe observed that patients in the high-mRNAsi group had a better prognosis than those in the low-mRNAsi group. Next, we identified 190 stemness-related differentially expressed genes (DEGs) that could categorize LUSC patients into two stemness subtypes. Patients in the stemness subtype B group with higher mRNAsi scores exhibited better overall survival (OS) than those in the stemness subtype A group. Immunotherapy prediction demonstrated that stemness subtype A has a better response to immune checkpoint inhibitors (ICIs). Furthermore, the drug response prediction indicated that stemness subtype A had a better response to chemotherapy but was more resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Finally, we constructed a nine-gene-based classifier to predict patients' stemness subtype and validated it in independent GEO validation sets. The expression levels of these genes were also validated in clinical tumor specimens.ConclusionThe stemness-related classifier could serve as a potential prognostic and treatment predictor and assist physicians in selecting effective treatment strategies for patients with LUSC in clinical practice.

Project description:We sought to characterize the regenerated cells, if any, when photoreceptor ablation was mostly limited to a particular cone subtype. This allowed us to uniquely assess whether the remaining cells influence specification of regenerating photoreceptors. The ability to replace lost photoreceptors via stem cell therapy holds promise for treating many retinal degenerative diseases. Zebrafish are potent for modelling this because they have robust regenerative capacity emanating from endogenous stem cells, and abundant cone photoreceptors including multiple spectral subtypes similar to human fovea. We ablated the homolog of the human S-cones, the ultraviolet-sensitive (UV) cones, and tested the hypothesis that the photoreceptors regenerating in their place take on identities matching those expected from normal cone mosaic development. We created transgenic fish wherein UV cones can be ablated by addition of a prodrug. Thus photoreceptors developed normally and only the UV cones expressed nitroreductase; the latter converts the prodrug metronidazole to a cell-autonomous neurotoxin. A significant increase in proliferation of progenitor cell populations (p<0.01) was observed when cell ablation was primarily limited to UV cones. In control fish, we found that BrdU primarily incorporated into rod photoreceptors, as expected. However the majority of regenerating photoreceptors became cones when retinal cell ablation was predominantly restricted to UV cones: a 2-fold increase in the relative abundance of cones (p?=?0.008) was mirrored by a 35% decrease in rods. By primarily ablating only a single photoreceptor type, we show that the subsequent regeneration is biased towards restoring the cognate photoreceptor type. We discuss the hypothesis that, after cone death, the microenvironment formed by the remaining retinal cells may be influential in determining the identity of regenerating photoreceptors, though other interpretations are plausible. Our novel animal model provides control of ablation that will assist in identifying mechanisms required to replace cone photoreceptors clinically to restore daytime vision.

Dataset Information

A high-risk retinoblastoma subtype with stemness features, dedifferentiated cone states and neuronal/ganglion cell gene expression.

Publications

A high-risk retinoblastoma subtype with stemness features, dedifferentiated cone states and neuronal/ganglion cell gene expression.

Similar Datasets

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