Image-based deep learning model using DNA methylation data predicts the origin of cancer of unknown primary.

Cancer of unknown primary (CUP) is a rare type of metastatic cancer in which the origin of the tumor is unknown. Since the treatment strategy for patients with metastatic tumors depends on knowing the primary site, accurate identification of the origin site is important. Here, we developed an image-based deep-learning model that utilizes a vision transformer algorithm for predicting the origin of CUP. Using DNA methylation dataset of 8,233 primary tumors from The Cancer Genome Atlas (TCGA), we categorized 29 cancer types into 18 organ classes and extracted 2,312 differentially methylated CpG sites (DMCs) from non-squamous cancer group and 420 DMCs from squamous cell cancer group. Using these DMCs, we created organ-specific DNA methylation images and used them for model training and testing. Model performance was evaluated using 394 metastatic cancer samples from TCGA (TCGA-meta) and 995 samples (693 primary and 302 metastatic cancers) obtained from 20 independent external studies. We identified that the DNA methylation image reveals a distinct pattern based on the origin of cancer. Our model achieved an overall accuracy of 96.95 % in the TCGA-meta dataset. In the external validation datasets, our classifier achieved overall accuracies of 96.39 % and 94.37 % in primary and metastatic tumors, respectively. Especially, the overall accuracies for both primary and metastatic samples of non-squamous cell cancer were exceptionally high, with 96.79 % and 96.85 %, respectively.

Central neurocytoma exhibits radial glial cell signatures with FGFR3 hypomethylation and overexpression.

We explored the genomic events underlying central neurocytoma (CN), a rare neoplasm of the central nervous system, via multiomics approaches, including whole-exome sequencing, bulk and single-nuclei RNA sequencing, and methylation sequencing. We identified FGFR3 hypomethylation leading to FGFR3 overexpression as a major event in the ontogeny of CN that affects crucial downstream events, such as aberrant PI3K-AKT activity and neuronal development pathways. Furthermore, we found similarities between CN and radial glial cells based on analyses of gene markers and CN tumor cells and postulate that CN tumorigenesis is due to dysregulation of radial glial cell differentiation into neurons. Our data demonstrate the potential role of FGFR3 as one of the leading drivers of tumorigenesis in CN.

Genomic analysis as a tool to infer disparate phylogenetic origins of dysembryoplastic neuroepithelial tumors and their satellite lesions.

Dysembryoplastic neuroepithelial tumor (DNET) is a low-grade brain tumor commonly associated with drug-resistant epilepsy. About half of DNETs are accompanied by tiny nodular lesions separated from the main mass. The existence of these satellite lesions (SLs) has shown a strong association with tumor recurrence, suggesting that they are true tumors. However, it is not known whether SLs represent multiple foci of progenitor tumor cell extension and migration or a multifocal development of the main DNET. This study was designed to elucidate the histopathology and pathogenesis of SLs in DNETs. Separate biopsies from the main masses and SLs with DNET were analyzed. We performed comparative lesion sequencing and phylogenetic analysis. FGFR1 K656E and K655I mutations or duplication of the tyrosine kinase domain was found in all 3 DNET patients and the main masses and their SLs shared the same FGFR1 alterations. The phylogenic analysis revealed that the SLs developed independently from their main masses. It is possible that the main mass and its SLs were separated at an early stage in oncogenesis with shared FGFR1 alterations, and then they further expanded in different places. SLs of DNET are true tumors sharing pathogenic mutations with the main masses. It is plausible that multifocal tumor development takes place in the dysplastic cortex containing cells with a pathogenic genetic alteration.

A glioneuronal tumor with CLIP2-MET fusion.

We report a case of glioneuronal tumor (GNT) with a discovery of novel gene fusion of CLIP2-MET resulting from aberrant chromosome 7 abnormalities. We executed an elaborate genomic study on this case including whole-exome sequencing and RNA sequencing. Genomic analysis of the tumor revealed aberrations in chromosomes 1 and 7 and a CLIP2-MET fusion. Further analysis of the upregulated genes revealed substantial connections with MAPK pathway activation. We concluded that the chromosome 7 abnormalities prompted CLIP2-MET gene fusion which successively leads to MAPK pathway activation. We deliberated that MAPK pathway activation is one of the driver pathways responsible for the oncogenesis of GNT.