LINE-1 ORF1p as a candidate biomarker in high grade serous ovarian carcinoma.

Long interspersed element 1 (LINE-1) open reading frame 1 protein (ORF1p) expression is a common feature of many cancer types, including high-grade serous ovarian carcinoma (HGSOC). Here, we report that ORF1p is not only expressed but also released by ovarian cancer and primary tumor cells. Immuno-multiple reaction monitoring-mass spectrometry assays showed that released ORF1p is confidently detectable in conditioned media, ascites, and patients' plasma, implicating ORF1p as a potential biomarker. Interestingly, ORF1p expression is detectable in fallopian tube (FT) epithelial precursors of HGSOC but not in benign FT, suggesting that ORF1p expression in an early event in HGSOC development. Finally, treatment of FT cells with DNA methyltransferase inhibitors led to robust expression and release of ORF1p, validating the regulatory role of DNA methylation in LINE-1 repression in non-tumorigenic tissue.

Total mutational load and clinical features as predictors of the metastatic status in lung adenocarcinoma and squamous cell carcinoma patients.

BACKGROUND: Recently, extensive cancer genomic studies have revealed mutational and clinical data of large cohorts of cancer patients. For example, the Pan-Lung Cancer 2016 dataset (part of The Cancer Genome Atlas project), summarises the mutational and clinical profiles of different subtypes of Lung Cancer (LC). Mutational and clinical signatures have been used independently for tumour typification and prediction of metastasis in LC patients. Is it then possible to achieve better typifications and predictions when combining both data streams? METHODS: In a cohort of 1144 Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LSCC) patients, we studied the number of missense mutations (hereafter, the Total Mutational Load TML) and distribution of clinical variables, for different classes of patients. Using the TML and different sets of clinical variables (tumour stage, age, sex, smoking status, and packs of cigarettes smoked per year), we built Random Forest classification models that calculate the likelihood of developing metastasis. RESULTS: We found that LC patients different in age, smoking status, and tumour type had significantly different mean TMLs. Although TML was an informative feature, its effect was secondary to the "tumour stage" feature. However, its contribution to the classification is not redundant with the latter; models trained using both TML and tumour stage performed better than models trained using only one of these variables. We found that models trained in the entire dataset (i.e., without using dimensionality reduction techniques) and without resampling achieved the highest performance, with an F1 score of 0.64 (95%CrI [0.62, 0.66]). CONCLUSIONS: Clinical variables and TML should be considered together when assessing the likelihood of LC patients progressing to metastatic states, as the information these encode is not redundant. Altogether, we provide new evidence of the need for comprehensive diagnostic tools for metastasis.

Immune-related IncRNA LINC00944 responds to variations in ADAR1 levels and it is associated with breast cancer prognosis.

AIMS: Breast cancer is one of the leading causes of woman deaths worldwide, being a major public health problem. It has been reported that the expression of the RNA-editing enzyme Adenosine Deaminase Acting on RNAs 1 (ADAR1) is upregulated in breast cancer, predicting poor prognosis in patients. A few reports in literature examine ADAR1 and long non-coding RNAs (lncRNAs) interplay in cancer and suggest key roles in cancer-related pathways. This study aimed to investigate whether ADAR1 could alter the expression levels of lncRNAs and explore how those changes are related to breast cancer biology. MAIN METHODS: ADAR1 overexpression and knockdown studies were performed in breast cancer cell lines to analyze the effects over lncRNAs expression. Guilt-by-Association correlation analysis of the TCGA-BRCA cohort was performed to predict the function of the lncRNA LINC00944. KEY FINDINGS: Here, we show that LINC00944 is responsive to ADAR1 up- and downregulation in breast cancer cells. We found that LINC00944 expression has a strong relationship with immune signaling pathways. Further assessment of the TCGA-BRCA cohort showed that LINC00944 expression was positively correlated to tumor-infiltrating T lymphocytes and pro-apoptotic markers. Moreover, we found that LINC00944 expression was correlated to the age at diagnosis, tumor size, and estrogen and progesterone receptor expression. Finally, we show that low expression of LINC00944 is correlated to poor prognosis in breast cancer patients. SIGNIFICANCE: Our study provides further evidence of the effect of ADAR1 over lncRNA expression levels, and on the participation of LINC00944 in breast cancer, suggesting to further investigate its potential role as prognostic biomarker.