Integrative omics analysis reveals relationships of genes with synthetic lethal interactions through a pan-cancer analysis

Predicting host-based, synthetic lethal antiviral targets from omics data

Traditional antiviral therapies often have limited effectiveness due to toxicity and the emergence of drug resistance. Host-based antivirals are an alternative, but can cause nonspecific effects. Recent evidence shows that virus-infected cells can be selectively eliminated by targeting synthetic lethal (SL) partners of proteins disrupted by viral infection. Thus, we hypothesized that genes depleted in CRISPR knockout (KO) screens of virus-infected cells may be enriched in SL partners of proteins altered by infection. To investigate this, we established a computational pipeline predicting antiviral SL drug targets. First, we identified SARS-CoV-2-induced changes in gene products via a large compendium of omics data. Second, we identified SL partners for each altered gene product. Last, we screened CRISPR KO data for SL partners required for cell viability in infected cells. Despite differences in virus-induced alterations detected by various omics data, they share many predicted SL targets, with significant enrichment in CRISPR KO-depleted datasets. Our comparison of SARS-CoV-2 and influenza infection data revealed potential broad-spectrum, host-based antiviral SL targets. This suggests that CRISPR KO data are replete with common antiviral targets due to their SL relationship with virus-altered states and that such targets can be revealed from analysis of omics datasets and SL predictions.

Predicting host-based, synthetic lethal antiviral targets from omics data

Traditional antiviral therapies often have limited effectiveness due to toxicity and development of drug resistance. Host-based antivirals, while an alternative, may lead to non-specific effects. Recent evidence shows that virus-infected cells can be selectively eliminated by targeting synthetic lethal (SL) partners of proteins disrupted by viral infection. Thus, we hypothesized that genes depleted in CRISPR KO screens of virus-infected cells may be enriched in SL partners of proteins altered by infection. To investigate this, we established a computational pipeline predicting SL drug targets of viral infections. First, we identified SARS-CoV-2-induced changes in gene products via a large compendium of omics data. Second, we identified SL partners for each altered gene product. Last, we screened CRISPR KO data for SL partners required for cell viability in infected cells. Despite differences in virus-induced alterations detected by various omics data, they share many predicted SL targets, with significant enrichment in CRISPR KO-depleted datasets. Comparing data from SARS-CoV-2 and influenza infections, we found possible broad-spectrum, host-based antiviral SL targets. This suggests that CRISPR KO data are replete with common antiviral targets due to their SL relationship with virus-altered states and that such targets can be revealed from analysis of omics datasets and SL predictions.

Omics Overview of the SPARC Gene in Mesothelioma

The SPARC gene plays multiple roles in extracellular matrix synthesis and cell shaping, associated with tumor cell migration, invasion, and metastasis. The SPARC gene is also involved in the epithelial-mesenchymal transition (EMT) process, which is a critical phenomenon leading to a more aggressive cancer cell phenotype. SPARC gene overexpression has shown to be associated with poor survival in the mesothelioma (MESO) cohort from the TCGA database, indicating that this gene may be a powerful prognostic factor in MESO. Its overexpression is correlated with the immunosuppressive tumor microenvironment. Here, we summarize the omics advances of the SPARC gene, including the summary of SPARC gene expression associated with prognosis in pancancer and MESO, the immunosuppressive microenvironment, and cancer cell stemness. In addition, SPARC might be targeted by microRNAs. Notably, despite the controversial functions on angiogenesis, SPARC may directly or indirectly contribute to tumor angiogenesis in MESO. In conclusion, SPARC is involved in tumor invasion, metastasis, immunosuppression, cancer cell stemness, and tumor angiogenesis, eventually impacting patient survival. Strategies targeting this gene may provide novel therapeutic approaches to the treatment of MESO.

The Role of Biomarkers in Adrenocortical Carcinoma: A Review of Current Evidence and Future Perspectives

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy arising from the adrenal cortex often with unexpected biological behavior. It can occur at any age, with two peaks of incidence: in the first and between fifth and seventh decades of life. Although ACC are mostly hormonally active, precursors and metabolites, rather than end products of steroidogenesis are produced by dedifferentiated and immature malignant cells. Distinguishing the etiology of adrenal mass, between benign adenomas, which are quite frequent in general population, and malignant carcinomas with dismal prognosis is often unfeasible. Even after pathohistological analysis, diagnosis of adrenocortical carcinomas is not always straightforward and represents a great challenge for experienced and multidisciplinary expert teams. No single imaging method, hormonal work-up or immunohistochemical labelling can definitively prove the diagnosis of ACC. Over several decades' great efforts have been made in finding novel reliable and available diagnostic and prognostic factors including steroid metabolome profiling or target gene identification. Despite these achievements, the 5-year mortality rate still accounts for approximately 75% to 90%, ACC is frequently diagnosed in advanced stages and therapeutic options are unfortunately limited. Therefore, imperative is to identify new biological markers that can predict patient prognosis and provide new therapeutic options.