A Precisely Regulated Gene Expression Cassette Potently Modulates Metastasis and Survival in Multiple Solid Cancers

Successful tumor development and progression involves the complex interplay of both pro- and anti-oncogenic signaling pathways. Genetic components balancing these opposing activities are likely to require tight regulation, because even subtle alterations in their expression may disrupt this balance with major consequences for various cancer-associated phenotypes. Here, we describe a cassette of cancer-specific genes exhibiting precise transcriptional control in solid tumors. Mining a database of tumor gene expression profiles from six different tissues, we identified 48 genes exhibiting highly restricted levels of gene expression variation in tumors (n = 270) compared to nonmalignant tissues (n = 71). Comprising genes linked to multiple cancer-related pathways, the restricted expression of this “Poised Gene Cassette” (PGC) was robustly validated across 11 independent cohorts of ∼1,300 samples from multiple cancer types. In three separate experimental models, subtle alterations in PGC expression were consistently associated with significant differences in metastatic and invasive potential. We functionally confirmed this association in siRNA knockdown experiments of five PGC genes (p53CSV, MAP3K11, MTCH2, CPSF6, and SKIP), which either directly enhanced the invasive capacities or inhibited the proliferation of AGS cancer cells. In primary tumors, similar subtle alterations in PGC expression were also repeatedly associated with clinical outcome in multiple cohorts. Taken collectively, these findings support the existence of a common set of precisely controlled genes in solid tumors. Since inducing small activity changes in these genes may prove sufficient to potently influence various tumor phenotypes such as metastasis, targeting such precisely regulated genes may represent a promising avenue for novel anti-cancer therapies

A Densely Interconnected Genome-Wide Network of MicroRNAs and Oncogenic Pathways Revealed Using Gene Expression Signatures

MicroRNAs (miRNAs) are important components of cellular signaling pathways, acting either as pathway regulators or pathway targets. Currently, only a limited number of miRNAs have been functionally linked to specific signaling pathways. Here, we explored if gene expression signatures could be used to represent miRNA activities and integrated with genomic signatures of oncogenic pathway activity to identify connections between miRNAs and oncogenic pathways on a high-throughput, genome-wide scale. Mapping >300 gene expression signatures to >700 primary tumor profiles, we constructed a genome-wide miRNA–pathway network predicting the associations of 276 human miRNAs to 26 oncogenic pathways. The miRNA–pathway network confirmed a host of previously reported miRNA/pathway associations and uncovered several novel associations that were subsequently experimentally validated. Globally, the miRNA–pathway network demonstrates a small-world, but not scale-free, organization characterized by multiple distinct, tightly knit modules each exhibiting a high density of connections. However, unlike genetic or metabolic networks typified by only a few highly connected nodes (“hubs”), most nodes in the miRNA–pathway network are highly connected. Sequence-based computational analysis confirmed that highly-interconnected miRNAs are likely to be regulated by common pathways to target similar sets of downstream genes, suggesting a pervasive and high level of functional redundancy among coexpressed miRNAs. We conclude that gene expression signatures can be used as surrogates of miRNA activity. Our strategy facilitates the task of discovering novel miRNA–pathway connections, since gene expression data for multiple normal and disease conditions are abundantly available

Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer

Many solid cancers are known to exhibit a high degree of heterogeneity in their deregulation of different oncogenic pathways. We sought to identify major oncogenic pathways in gastric cancer (GC) with significant relationships to patient survival. Using gene expression signatures, we devised an in silico strategy to map patterns of oncogenic pathway activation in 301 primary gastric cancers, the second highest cause of global cancer mortality. We identified three oncogenic pathways (proliferation/stem cell, NF-κB, and Wnt/β-catenin) deregulated in the majority (>70%) of gastric cancers. We functionally validated these pathway predictions in a panel of gastric cancer cell lines. Patient stratification by oncogenic pathway combinations showed reproducible and significant survival differences in multiple cohorts, suggesting that pathway interactions may play an important role in influencing disease behavior. Individual GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Predicting pathway activity by expression signatures thus permits the study of multiple cancer-related pathways interacting simultaneously in primary cancers, at a scale not currently achievable by other platforms

The unconventional resistance protein PTR recognizes the Magnaporthe oryzae effector AVR-Pita in an allele-specific manner

International audienceBlast disease caused by the fungus Magnaporthe oryzae is one of the most devastating rice diseases. Disease resistance genes such as Pi-ta or Pi-ta2 are critical in protecting rice production from blast. Published work reports that Pi-ta codes for a nucleotide-binding and leucine-rich repeat domain protein (NLR) that recognizes the fungal protease-like effector AVR-Pita by direct binding. However, this model was challenged by the recent discovery that Pi-ta2 resistance, which also relies on AVR-Pita detection, is conferred by the unconventional resistance gene Ptr, which codes for a membrane protein with a cytoplasmic armadillo repeat domain. Here, using NLR Pi-ta and Ptr RNAi knockdown and CRISPR/Cas9 knockout mutant rice lines, we found that AVR-Pita recognition relies solely on Ptr and that the NLR Pi-ta has no role in it, indicating that it is not the Pi-ta resistance gene. Different alleles of Ptr confer different recognition specificities. The A allele of Ptr (PtrA) detects all natural sequence variants of the effector and confers Pi-ta2 resistance, while the B allele of Ptr (PtrB) recognizes a restricted set of AVR-Pita alleles and, thereby, confers Pi-ta resistance. Analysis of the natural diversity in AVR-Pita and of mutant and transgenic strains identified one specific polymorphism in the effector sequence that controls escape from PtrB-mediated resistance. Taken together, our work establishes that the M. oryzae effector AVR-Pita is detected in an allele-specific manner by the unconventional rice resistance protein Ptr and that the NLR Pi-ta has no function in Pi-ta resistance and the recognition of AVR-Pita

Long-read transcriptome sequencing reveals abundant promoter diversity in distinct molecular subtypes of gastric cancer

10.1186/s13059-021-02261-xGenome Biology2214