Letter to the editor

ONGene: A literature-based database for human oncogenes

Molecular entities showing dysregulation in multiple cancers may hold great biomarker or therapeutic potential. There is accumulating evidence that highlights the dysregulation of a long non-coding RNA, MIR210HG, in various cancers and its oncogenic role. However, a comprehensive analysis of MIR210HG expression pattern, molecular mechanisms, diagnostic or prognostic significance or evaluation of its interaction with tumor microenvironment across various cancers remains unstudied.

A systematic pan-cancer analysis was done using multiple public databases and bioinformatic tools to study the molecular role and clinical significance of MIR210HG. We have analyzed expression patterns, genome alteration, transcriptional and epigenetic regulation, correlation with patient survival, immune infiltrates, co-expressed genes, interacting proteins, and pathways associated with MIR210HG.

The Pan cancer expression analysis of MIR210HG through various tumor datasets demonstrated that MIR210HG is significantly upregulated in most cancers and increased with the tumor stage in a subset of them. Furthermore, prognostic analysis revealed high MIR210HG expression is associated with poor overall and disease-free survival in specific cancer types. Genetic alteration analysis showed minimal alterations in the MIR210HG locus, indicating that overexpression in cancers is not due to gene amplification. The exploration of SNPs on MIR210HG suggested possible structural changes that may affect its interactions with the miRNAs. The correlation of MIR210HG with promoter methylation was found to be significantly negative in nature in majority of cancers depicting the possible epigenetic regulation of expression of MIR210HG. Additionally, MIR210HG showed negative correlations with immune cells and thus may have strong impact on the tumor microenvironment. Functional analysis indicates its association with hypoxia, angiogenesis, metastasis, and DNA damage repair processes. MIR210HG was found to interact with several proteins and potentially regulate chromatin modifications and transcriptional regulation.

A first pan-can cancer analysis of MIR210HG highlights its transcriptional and epigenetic deregulation and oncogenic role in the majority of cancers, its correlation with tumor microenvironment factors such as hypoxia and immune infiltration, and its potential as a prognostic biomarker and therapeutic target in several cancers.

Plasma cell leukemia (PCL) is one of the rare cancer which is characterized by the uncontrolled proliferation of plasma cells in peripheral blood and bone marrow. The aggressive behavior of the disease and high mortality rate among PCL patients makes it a thirst area to be explored.

The dataset for PCL was obtained from the GEO database and was analyzed using GEO2R for differentially expressed genes. Further, the functional enrichment analysis was carried out for DEGs using DAVID. The protein-protein interactions (PPI) for DEGs were obtained using STRING 11.5 and were analyzed in Cytoscape 3.7.2. to obtain the key hub genes. These key hub genes were investigated for their interaction with suitable drug candidates using DGIdb, DrugMAP, and Schrodinger's version 2022–1.

Out of the total of 104 DEGs, 39 genes were up-regulated whereas 65 genes were down-regulated. A total of 11 biological processes, 2 cellular components, and 5 molecular functions were enriched along with the 7 KEGG pathways for the DEGs. Further, a total of 11 hub genes were obtained from the PPI of DEGs of which TP53, MAPK1, SOCS1, MBD3, and YES1 were the key hub genes. Oxaliplatin, mitoxantrone, and ponatinib were found to have the highest binding affinity towards the p53, MAPK1, and YES1 proteins respectively.

TP53, MAPK1, SOCS1, MBD3, and YES1 are the signature hub genes that might be responsible for the aggressive prognosis of PCL leading to poor survival rate. However, p53, MAPK1, and YES1 can be targeted with oxaliplatin, mitoxantrone, and ponatinib.

The gene expression networks of a single cell can be used to reveal cell type- and condition-specific patterns that account for cell states, cell identity, and its responses to environmental changes. We applied single cell sequencing datasets to define mRNA patterns and visualized potential cellular capacities among hepatocellular cancer cells. The expressing numbers and levels of genes were highly heterogenous among the cancer cells. The cellular characteristics were dependent strongly on the expressing numbers and levels of genes, especially oncogenes and anti-oncogenes, in an individual cancer cell. The transcriptional activations of oncogenes and anti-oncogenes were strongly linked to inherent multiple cellular programs, some of which oppose and contend against other processes, in a cancer cell. The gene expression networks of multiple cellular programs proliferation, differentiation, apoptosis, autophagy, epithelial-mesenchymal transition, ATP production, and neurogenesis coexisted in an individual cancer cell. The findings give rise a hypothesis that a cancer cell expresses balanced combinations of genes and undergoes a given biological process by rapidly transmuting gene expressing networks.

Acute myeloid leukemia (AML) with mixed-lineage leukemia (MLL) gene rearrangement (MLLr) comprises a cellular hierarchy in which a subpopulation of cells serves as functional leukemia stem cells (LSCs). They are maintained by a unique gene expression program and chromatin states, which are thought to reflect the actions of enhancers. Here, we delineate the active enhancer landscape and observe pervasive enhancer malfunction in LSCs. Reconstruction of regulatory networks revealed a master set of hematopoietic transcription factors. We show that EP300 is an essential transcriptional coregulator for maintaining LSC oncogenic potential because it controls essential gene expression through modulation of H3K27 acetylation and assessments of transcription factor dependencies. Moreover, the EP300 inhibitor A-485 affects LSC growth by targeting enhancer activity via histone acetyltransferase domain inhibition. Together, these data implicate a perturbed MLLr-specific enhancer accessibility landscape, suggesting the possibility for disruption of the LSC enhancer regulatory axis as a promising therapeutic strategy in AML.

Somatic mutations occur as random genetic changes in genes through protein-affecting mutations (PAMs), gene fusions, or copy number alterations (CNAs). Mutations of different types can have a similar phenotypic effect (i.e., allelic heterogeneity) and should be integrated into a unified gene mutation profile. We developed OncoMerge to fill this niche of integrating somatic mutations to capture allelic heterogeneity, assign a function to mutations, and overcome known obstacles in cancer genetics. Application of OncoMerge to TCGA Pan-Cancer Atlas increased detection of somatically mutated genes and improved the prediction of the somatic mutation role as either activating or loss of function. Using integrated somatic mutation matrices increased the power to infer gene regulatory networks and uncovered the enrichment of switch-like feedback motifs and delay-inducing feedforward loops. These studies demonstrate that OncoMerge efficiently integrates PAMs, fusions, and CNAs and strengthens downstream analyses linking somatic mutations to cancer phenotypes.