Pan-Cancer Molecular Patterns and Biological Implications Associated with a Tumor-Specific Molecular Signature

Expression and function of NF-Y subunits in cancer

NF-Y is a Transcription Factor (TF) targeting the CCAAT box regulatory element. It consists of the NF-YB/NF-YC heterodimer, each containing an Histone Fold Domain (HFD), and the sequence-specific subunit NF-YA. NF-YA expression is associated with cell proliferation and absent in some post-mitotic cells. The review summarizes recent findings impacting on cancer development. The logic of the NF-Y regulome points to pro-growth, oncogenic genes in the cell-cycle, metabolism and transcriptional regulation routes. NF-YA is involved in growth/differentiation decisions upon cell-cycle re-entry after mitosis and it is widely overexpressed in tumors, the HFD subunits in some tumor types or subtypes. Overexpression of NF-Y -mostly NF-YA- is oncogenic and decreases sensitivity to anti-neoplastic drugs. The specific roles of NF-YA and NF-YC isoforms generated by alternative splicing -AS- are discussed, including the prognostic value of their levels, although the specific molecular mechanisms of activity are still to be deciphered.

Poor-prognosis molecular subtypes in adenocarcinomas of pancreato-biliary and gynecological origin: A systematic review

Pancreato-biliary and gynecological adenocarcinomas need better tools to predict clinical outcome. Potential prognostic mesenchymal(-like) transcriptome-based subtypes have been identified in these cancers. In this systematic review, we include studies into molecular subtyping and summarize biological and clinical features of the subtypes within and across sites of origin, searching for suggestions to improve classification and prognostication. PubMed and Embase were searched for original research articles describing potential mesenchymal(-like) mRNA-based subtypes in pancreato-biliary or gynecological adenocarcinomas. Studies limited to supervised clustering were excluded. Fourty-four studies, discussing cholangiocarcinomas, gallbladder, ampullary, pancreatic, ovarian, and endometrial adenocarcinomas were included. There was overlap in molecular and clinical features in mesenchymal(-like) subtypes across all adenocarcinomas. Approaches including microdissection were more likely to identify prognosis-associating subtypes. To conclude, molecular subtypes in pancreato-biliary and gynecological adenocarcinomas share biological and clinical characteristics. Furthermore, separation of stromal and epithelial signals should be applied in future studies into biliary and gynecological adenocarcinomas.

NF-YAl drives EMT in Claudinlow tumours

NF-Y is a trimeric transcription factor whose binding site -the CCAAT box- is enriched in cancer-promoting genes. The regulatory subunit, the sequence-specificity conferring NF-YA, comes in two major isoforms, NF-YA long (NF-YAl) and short (NF-YAs). Extensive expression analysis in epithelial cancers determined two features: widespread overexpression and changes in NF-YAl/NF-YAs ratios (NF-YAr) in tumours with EMT features. We performed wet and in silico experiments to explore the role of the isoforms in breast -BRCA- and gastric -STAD- cancers. We generated clones of two Claudin^low BRCA lines SUM159PT and BT549 ablated of exon-3, thus shifting expression from NF-YAl to NF-YAs. Edited clones show normal growth but reduced migratory capacities in vitro and ability to metastatize in vivo. Using TCGA, including upon deconvolution of scRNA-seq data, we formalize the clinical importance of high NF-YAr, associated to EMT genes and cell populations. We derive a novel, prognostic 158 genes signature common to BRCA and STAD Claudin^low tumours. Finally, we identify splicing factors associated to high NF-YAr, validating RBFOX2 as promoting expression of NF-YAl. These data bring three relevant results: (i) the definition and clinical implications of NF-YAr and the 158 genes signature in Claudin^low tumours; (ii) genetic evidence of 28 amino acids in NF-YAl with EMT-promoting capacity; (iii) the definition of selected splicing factors associated to NF-YA isoforms.

Comprehensive analysis of tumor immune microenvironment and prognosis of m6A-related lncRNAs in gastric cancer

Background

N6-methyladenosine (m6A) modification and long non-coding RNAs (lncRNAs) play pivotal roles in gastric cancer (GC) progression. The emergence of immunotherapy in GC has created a paradigm shift in the approaches of treatment, whereas there is significant heterogeneity with regard to degree of treatment responses, which results from the variability of tumor immune microenvironment (TIME). How the interplay between m6A and lncRNAs enrolling in the shaping of TIME remains unclear.

Methods

The RNA sequencing and clinical data of GC patients were collected from TCGA database. Pearson correlation test and univariate Cox analysis were used to screen out m6A-related lncRNAs. Consensus clustering method was implemented to classify GC patients into two clusters. Survival analysis, the infiltration level of immune cells, Gene set enrichment analysis (GSEA) and the mutation profiles were analyzed and compared between two clusters. A competing endogenous RNA (ceRNA) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of pathways in which m6A-related lncRNAs enriched. Then least absolute shrinkage and selection operator (LASSO) COX regression was implemented to select pivotal lncRNAs, and risk model was constructed accordingly. The prognosis value of the risk model was explored. In addition, the response to immune checkpoint inhibitors (ICIs) therapy were compared between different risk groups. Finally, we performed qRT-PCR to detect expression patterns of the selected lncRNAs in the 35 tumor tissues and their paired adjacent normal tissues, and validated the prognostic value of risk model in our cohort (N = 35).

Results

The expression profiles of 15 lncRNAs were included to cluster patients into 2 subtypes. Cluster1 with worse prognosis harbored higher immune score, stromal score, ESTIMATE score and lower mutation rates of the genes. Different immune cell infiltration patterns were also displayed between the two clusters. GSEA showed that cluster1 preferentially enriched in tumor hallmarks and tumor-related biological pathways. KEGG pathway analysis found that the target mRNAs which m6A-related lncRNAs regulated by sponging miRNAs mainly enriched in vascular smooth muscle contraction, cAMP signaling pathway and cGMP-PKG signaling pathway. Next, eight lncRNAs were selected by LASSO regression algorithm to construct risk model. Patients in the high-risk group had poor prognoses, which were consistent in our cohort. As for predicting responses to ICIs therapy, patients from high-risk group were found to have lower tumor mutation burden (TMB) scores and account for large proportion in the Microsatellite Instability-Low (MSI-L) subtype. Moreover, patients had distinct immunophenoscores in different risk groups.

Conclusion

Our study revealed that the interplay between m6A modification and lncRNAs might have critical role in predicting GC prognosis, sculpting TIME landscape and predicting the responses to ICIs therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09377-8.

Multi-Omics Model Applied to Cancer Genetics

In this review, we focus on bioinformatic oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical understanding of cancer. Before providing a deeper insight into the bioinformatics approach and utilities involved in oncology, we must understand what is a system biology framework and the genetic connection, because of the high heterogenicity of the backgrounds of people approaching precision medicine. In fact, it is essential to providing general theoretical information on genomics, epigenomics, and transcriptomics to understand the phases of multi-omics approach. We consider how to create a multi-omics model. In the last section, we describe the new frontiers and future perspectives of this field.