Genomic Profiling on an Unselected Solid Tumor Population Reveals a Highly Mutated Wnt/β-Catenin Pathway Associated with Oncogenic EGFR Mutations

DETECTION OF DISEASE‐CAUSING MUTATIONS IN PROSTATE CANCER BY NGS SEQUENCING

Gene mutations may affect the fate of many tumors including prostate cancer (PCa); therefore, the research of specific mutations associated with tumor outcomes might help the urologist to identify the best therapy for PCa patients such as surgical resection, adjuvant therapy or active surveillance. Genomic DNA (gDNA) was extracted from 48 paraffin‐embedded PCa samples and normal paired tissues. Next, gDNA was amplified and analyzed by next‐generation sequencing (NGS) using a specific gene panel for PCa. Raw data were refined to exclude false‐positive mutations; thus, variants with coverage and frequency lower than 100× and 5%, respectively were removed. Mutation significance was processed by Genomic Evolutionary Rate Profiling, ClinVar, and Varsome tools. Most of 3000 mutations (80%) were single nucleotide variants and the remaining 20% indels. After raw data elaboration, 312 variants were selected. Most mutated genes were KMT2D (26.45%), FOXA1 (16.13%), ATM (15.81%), ZFHX3 (9.35%), TP53 (8.06%), and APC (5.48%). Hot spot mutations in FOXA1, ATM, ZFHX3, SPOP, and MED12 were also found. Truncating mutations of ATM, lesions lying in hot spot regions of SPOP and FOXA1 as well as mutations of TP53 correlated with poor prognosis. Importantly, we have also found some germline mutations associated with hereditary cancer‐predisposing syndrome. gDNA sequencing of 48 cancer tissues by NGS allowed to detect new tumor variants as well as confirmed lesions in genes linked to prostate cancer. Overall, somatic and germline mutations linked to good/poor prognosis could represent new prognostic tools to improve the management of PCa patients.

The expression of circulating miR-504 in plasma is associated with EGFR mutation status in non-small-cell lung carcinoma patients

MicroRNAs (miRNAs), key regulators of gene expression at the post-transcriptional level, are grossly misregulated in some human cancers, including non-small-cell lung carcinoma (NSCLC). The aberrant expression of specific miRNAs results in the abnormal regulation of key components of signalling pathways in tumour cells. MiRNA levels and the activity of the gene targets, including oncogenes and tumour suppressors, produce feedback that changes miRNA expression levels and indicates the cell's genetic activity. In this study, we measured the expression of five circulating miRNAs (miR-195, miR-504, miR-122, miR-10b and miR-21) and evaluated their association with EPIDERMAL GROWTH FACTOR RECEPTOR (EGFR) mutation status in 66 NSCLC patients. Moreover, we examined the discriminative power of circulating miRNAs for EGFR mutant-positive and -negative NSCLC patients using two different data normalisation approaches. We extracted total RNA from the plasma of 66 non-squamous NSCLC patients (31 of whom had tumours with EGFR mutations) and measured circulating miRNA levels using quantitative reverse transcription polymerase chain reaction (RT-qPCR). The miRNA expression levels were normalised using two endogenous controls: miR-191 and miR-16. We found significant associations between the expression of circulating miR-504 and EGFR-activating mutations in NSCLC patients regardless of the normalisation approach used (p = 0.0072 and 0.0236 for miR-16 and miR-191 normalisation, respectively). The greatest discriminative power of circulating miR-504 was observed in patients with EGFR exon 19 deletions versus wild-type EGFR normalised to miR-191 (area under the curve (AUC) = 0.81, p < 0.0001). Interestingly, circulating miR-504 levels were significantly reduced in the v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS)-mutated subgroup compared to EGFR-mutated patients (p < 0.0030) and those with EGFR/KRAS wild-type tumours (p < 0.0359). Our study demonstrated the feasibility and potential diagnostic value of plasma miR-504 expression analysis to distinguish between EGFR-mutated and wild-type NSCLC patients. However, quality control and normalisation strategies are very important and have a major impact on the outcomes of circulating miRNA analyses.

Lung cancer stem cells and their aggressive progeny, controlled by EGFR/MIG6 inverse expression, dictate a novel NSCLC treatment approach

The lung cancer stem cell (LuCSC) model comprises an attractive framework to explore acquired drug resistance in non-small cell lung cancer (NSCLC) treatment. Here, we used NSCLC cell line model to translate cellular heterogeneity into tractable populations to understand the origin of lung cancers and drug resistance. The epithelial LuCSCs, presumably arising from alveolar bipotent stem/progenitor cells, were lineage naïve, noninvasive, and prone to creating aggressive progeny expressing AT2/AT1 markers. LuCSC-holoclones were able to initiate rimmed niches, where their specialization created pseudo-alveoli structures. Mechanistically, LuCSC transitioning from self-renewal (β-catenin and Nanog signaling) to malignant lineage differentiation is regulated by EGFR activation and the inverse inhibition of tumor suppressor MIG6. We further identified the functional roles of endogenous EGFR signaling in mediating progeny invasiveness and their ligands in LuCSC differentiation. Importantly, drug screening demonstrated that EGFR driving progeny were strongly responsive to TKIs; however, the LuCSCs were exclusively resistant but sensitive to AMPK agonist Metformin, antibiotic Salinomycin and to a lesser degree Carboplatin. Our data reveals previously an unknown mechanism of NSCLC resistance to EGFR-TKIs, which is associated with LuCSCs bearing a silenced EGFR and inversely expressed MIG6 suppressor gene. Taken altogether, successful NSCLC treatment requires development of a novel combination of drugs, efficiently targeting both LuCSCs and heterogeneous progeny.

Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma

Cholangiocarcinoma (CCA) is one of the most common epithelial cell malignancies worldwide. However, its prognosis is poor. The aim of the present study was to examine the prognostic landscape and potential therapeutic targets for CCA. RNA sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) dataset and processed. A total of 172 genes that were significantly associated with overall survival of patients with CCA were identified using the univariate Cox regression method. Bioinformatics tools were applied using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO). It was identified that ‘Wnt signaling pathway’, ‘cytoplasm’ and ‘AT DNA binding’ were the three most significant GO categories of CCA survival-associated genes. ‘Transcriptional misregulation in cancer’ was the most significant pathway identified in the KEGG analysis. Using the Drug-Gene Interaction database, a drug-gene interaction network was constructed, and 31 identified genes were involved in it. The most meaningful potential therapeutic targets were selected via protein-protein and gene-drug interactions. Among these genes, polo-like kinase 1 (PLK1) was identified to be a potential target due to its significant upregulation in CCA. To rapidly find molecules that may affect these genes, the Connectivity Map was queried. A series of molecules were selected for their potential anti-CCA functions. 0297417-0002B and tribenoside exhibited the highest connection scores with PLK1 via molecular docking. These findings may offer novel insights into treatment and perspectives on the future innovative treatment of CCA.