Neural activity is increasingly recognized as a crucial regulator of cancer growth. In the brain, neuronal activity robustly influences glioma growth through paracrine mechanisms ¹ and by electrochemical integration of malignant cells into neural circuitry via neuron-to-glioma synapses ^2,3 . Outside of the central nervous system, innervation of tumours such as prostate, head and neck, breast, pancreatic, and gastrointestinal cancers by peripheral nerves similarly regulates cancer progression ^4–12 . However, the extent to which the nervous system regulates small cell lung cancer (SCLC) progression, either in the lung or when growing within the brain, is less well understood. SCLC is a lethal high-grade neuroendocrine tumour that exhibits a strong propensity to metastasize to the brain. Here we demonstrate that in the lung, vagus nerve transection markedly inhibits primary lung tumour development and progression, highlighting a critical role for innervation in SCLC growth. In the brain, SCLC cells co-opt neuronal activity-regulated mechanisms to stimulate growth and progression. Glutamatergic and GABAergic (γ-aminobutyric acid-producing) cortical neuronal activity each drive proliferation of SCLC in the brain through paracrine and synaptic neuron–cancer interactions. SCLC cells form bona fide neuron-to-SCLC synapses and exhibit depolarizing currents with consequent calcium transients in response to neuronal activity; such SCLC cell membrane depolarization is sufficient to promote the growth of intracranial tumours. Together, these findings illustrate that neuronal activity has a crucial role in dictating SCLC pathogenesis.

Mitochondria are central key players in cell metabolism, and mitochondrial DNA (mtDNA) instability has been linked to metabolic changes that contribute to tumorigenesis and to increased expression of pro-tumorigenic genes. Here, we use melanoma cell lines and metastatic melanoma tumors to evaluate the effect of mtDNA alterations and the expression of the mtDNA packaging factor, TFAM, on energetic metabolism and pro-tumorigenic nuclear gene expression changes. We report a positive correlation between mtDNA copy number, glucose consumption, and ATP production in melanoma cell lines. Gene expression analysis reveals a down-regulation of glycolytic enzymes in cell lines and an up-regulation of amino acid metabolism enzymes in melanoma tumors, suggesting that TFAM may shift melanoma fuel utilization from glycolysis towards amino acid metabolism, especially glutamine. Indeed, proliferation assays reveal that TFAM-down melanoma cell lines display a growth arrest in glutamine-free media, emphasizing that these cells rely more on glutamine metabolism than glycolysis. Finally, our data indicate that TFAM correlates to VEGF expression and may contribute to tumorigenesis by triggering a more invasive gene expression signature. Our findings contribute to the understanding of how TFAM affects melanoma cell metabolism, and they provide new insight into the mechanisms by which TFAM and mtDNA copy number influence melanoma tumorigenesis.

Melanoma is the deadliest form of skin cancer, and little is known about the impact of deregulated expression of long noncoding RNAs (lncRNAs) in the progression of this cancer. In this study, we explored RNA-Seq data to search for lncRNAs associated with melanoma progression. We found distinct lncRNA gene expression patterns across melanocytes, primary and metastatic melanoma cells. Also, we observed upregulation of the lncRNA ZEB1-AS1 (ZEB1 antisense RNA 1) in melanoma cell lines. Data analysis from The Cancer Genome Atlas (TCGA) confirmed higher ZEB1-AS1 expression in metastatic melanoma and its association with hotspot mutations in BRAF (B-Raf proto-oncogene, serine/threonine kinase) gene and RAS family genes. In addition, a positive correlation between ZEB1-AS1 and ZEB1 (zinc finger E-box binding homeobox 1) gene expression was verified in primary and metastatic melanomas. Using gene expression signatures indicative of invasive or proliferative phenotypes, we found an association between ZEB1-AS1 upregulation and a transcriptional profile for invasiveness. Enrichment analysis of correlated genes demonstrated cancer genes and pathways associated with ZEB1-AS1. We suggest that the lncRNA ZEB1-AS1 could function by activating ZEB1 gene expression, thereby influencing invasiveness and phenotype switching in melanoma, an epithelial-to-mesenchymal transition (EMT)-like process, which the ZEB1 gene has an essential role.

Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making.