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Deciphering the Genomic Landscape and Pharmacological Profile of Uncommon Entities of Adult Rhabdomyosarcomas.

ABSTRACT: Adult rhabdomyosarcoma (RMS) represents an uncommon entity with an incidence of less than 3% of all soft tissue sarcomas (STS). Consequently, the natural history and the clinical management of this disease are infrequently reported. In order to fill this gap, we investigated the molecular biology of an adult RMS case series. The expression of epithelial mesenchymal transition-related gene and chemoresistance-related gene panels were evaluated. Moreover, taking advantage of our STS translational model combining patient-derived primary culture and 3D-scaffold, the pharmacological profile of an adult head and neck sclerosing RMS was assessed. Furthermore, NGS, microsatellite instability, and in silico analyses were carried out. RT-PCR identified the upregulation of CDH1, SLUG, MMP9, RAB22a, S100P, and LAPTM4b, representing promising biomarkers for this disease. Pharmacological profiling showed the highest sensitivity with anthracycline-based regimen in both 2D and 3D culture systems. NGS analysis detected RAB3IP-HMGA2 in frame gene rearrangement and FGFR4 mutation; microsatellite instability analysis did not detect any alteration. In silico analysis confirmed the mutation of FGFR4 as a promising marker for poor prognosis and a potential therapeutic target. We report for the first time the molecular and pharmacological characterization of rare entities of adult head and neck and posterior trunk RMS. These preliminary data could shed light on this poorly understood disease.

SUBMITTER: De Vita A

PROVIDER: S-EPMC8584142 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:With the exception of trastuzumab, therapies directed at receptor tyrosine kinases (RTKs) in gastroesophageal adenocarcinomas (GEA) have had limited success. Recurrent fibroblast growth factor receptor 2 (FGFR2) alterations exist in GEA; however, little is known about the genomic landscape of FGFR2-altered GEA. We examined FGFR2 alteration frequency and frequency of co-occurring alterations in GEA. SUBJECTS, MATERIALS, AND METHODS:A total of 6,667 tissue specimens from patients with advanced GEA were assayed using hybrid capture-based genomic profiling. Tumor mutational burden (TMB) was determined on up to 1.1 Mb of sequenced DNA, and microsatellite instability was determined on 95 or 114 loci. Descriptive statistics were used to compare subgroups. RESULTS:We identified a total of 269 (4.0%) FGFR2-altered cases consisting of FGFR2-amplified (amp; 193, 72% of FGFR2-altered), FGFR2-mutated (36, 13%), FGFR2-rearranged (re; 23, 8.6%), and cases with multiple FGFR2 alterations (17, 6.3%). Co-occurring alterations in other GEA RTK targets including ERBB2 (10%), EGFR (8%), and MET (3%) were observed across all classes of FGFR2-altered GEA. Co-occurring alterations in MYC (17%), KRAS (10%), and PIK3CA (5.6%) were also observed frequently. Cases with FGFR2amp and FGFR2re were exclusively microsatellite stable. The median TMB for FGFR2-altered GEA was 3.6 mut/mb, not significantly different from a median of 4.3 mut/mb seen in FGFR2 wild-type samples. CONCLUSION:FGFR2-altered GEA is a heterogenous subgroup with approximately 20% of FGFR2-altered samples harboring concurrent RTK alterations. Putative co-occurring modifiers of FGFR2-directed therapy including oncogenic MYC, KRAS, and PIK3CA alterations were also frequent, suggesting that pretreatment molecular analyses may be needed to facilitate rational combination therapies and optimize patient selection for clinical trials. IMPLICATIONS FOR PRACTICE:Actionable receptor tyrosine kinase alterations assayed within a genomic context with therapeutic implications remain limited to HER2 amplification in gastroesophageal adenocarcinomas (GEA). Composite biomarkers and heterogeneity assessment are critical in optimizing patients selected for targeted therapies in GEA. Comprehensive genomic profiling in FGFR2-altered GEA parallels the heterogeneity findings in HER2-amplified GEA and adds support to the utility of genomic profiling in advanced gastroesophageal adenocarcinomas.

Project description:IntroductionTo develop effective therapies and identify novel early biomarkers for chronic kidney disease, an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in chronic kidney disease (CKD) origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for 9 kidney disease entities that account for most of CKD worldwide. Our primary goal was to demonstrate the possibilities and potential on data analysis and integration to the nephrology community.MethodsWe integrated data from 5 publicly available studies and compared glomerular gene expression profiles of disease with that of controls from nontumor parts of kidney cancer nephrectomy tissues. A major challenge was the integration of the data from different sources, platforms, and conditions that we mitigated with a bespoke stringent procedure.ResultsWe performed a global transcriptome-based delineation of different kidney disease entities, obtaining a transcriptomic diffusion map of their similarities and differences based on the genes that acquire a consistent differential expression between each kidney disease entity and nephrectomy tissue. We derived functional insights by inferring the activity of signaling pathways and transcription factors from the collected gene expression data and identified potential drug candidates based on expression signature matching. We validated representative findings by immunostaining in human kidney biopsies indicating, for example, that the transcription factor FOXM1 is significantly and specifically expressed in parietal epithelial cells in rapidly progressive glomerulonephritis (RPGN) whereas not expressed in control kidney tissue. Furthermore, we found drug candidates by matching the signature on expression of drugs to that of the CKD entities, in particular, the Food and Drug Administration-approved drug nilotinib.ConclusionThese results provide a foundation to comprehend the specific molecular mechanisms underlying different kidney disease entities that can pave the way to identify biomarkers and potential therapeutic targets. To facilitate further use, we provide our results as a free interactive Web application: https://saezlab.shinyapps.io/ckd_landscape/. However, because of the limitations of the data and the difficulties in its integration, any specific result should be considered with caution. Indeed, we consider this study rather an illustration of the value of functional genomics and integration of existing data.

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Deciphering the Genomic Landscape and Pharmacological Profile of Uncommon Entities of Adult Rhabdomyosarcomas.

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