Supplementary data are available at Bioinformatics online.

Ovarian cancer is one of the leading causes of death from gynecologic malignancy in women. High-grade serous carcinomas, low-grade serous carcinomas, endometrioid carcinomas, clear cell carcinomas, and mucinous carcinomas with distinct pathological and clinical characteristics are the main histological subtypes of ovarian cancer. The majority of ovarian cancer patients are diagnosed at an advanced stage due to a lack of suitable screening tests for early detection and specific early symptoms. Despite progress in therapy improvements in ovarian cancer, most patients develop a recurrence within months or years after initial treatment. Given that the presence of tumor infiltrating lymphocytes is associated with prognosis and ovarian cancer is among the first cancers with an established association of immune cell infiltration, identification of the immune microenvironment in ovarian cancer is thought to be promising. In this study, to increase the understanding of tumor immune cell interactions, we undertook a study of tumor infiltrating lymphocytes in a large group of ovarian cancer patients. Our results suggested that tumor immune infiltrates of ovarian cancer were quite cohort and subtype dependent, and activated CD4+ T and CD8+ T tumor infiltrating lymphocytes were associated with good overall survival in the high-grade serous tumors. We found that high expression levels of the immune-related genes were associated with good prognosis in high-grade serous carcinomas. In addition, two different groups of prognostic genes were found in the high-grade and low-grade serous carcinomas, indicating that these two subtypes of serous carcinomas were two biologically and clinically different cancer types.

Active telomerase is essential for stem cells and most cancers to maintain telomeres. The enzymatic activity of telomerase is related but not equivalent to the expression of TERT, the catalytic subunit of the complex. Here we show that telomerase enzymatic activity can be robustly estimated from the expression of a 13-gene signature. We demonstrate the validity of the expression-based approach, named EXTEND, using cell lines, cancer samples, and non-neoplastic samples. When applied to over 9,000 tumors and single cells, we find a strong correlation between telomerase activity and cancer stemness. This correlation is largely driven by a small population of proliferating cancer cells that exhibits both high telomerase activity and cancer stemness. This study establishes a computational framework for quantifying telomerase enzymatic activity and provides new insights into the relationships among telomerase, cancer proliferation, and stemness.

Accumulating evidence has demonstrated that long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) play important roles in initiation and development of human diseases. However, the mechanism of ceRNA regulated by lncRNA in myocardial infarction (MI) remained unclear. In this study, we performed a multi-step computational method to construct dysregulated lncRNA-mRNA networks for MI occurrence (DLMN_MI_OC) and recurrence (DLMN_MI_Re) based on “ceRNA hypothesis”. We systematically integrated lncRNA and mRNA expression profiles and miRNA-target regulatory interactions. The constructed DLMN_MI_OC and DLMN_MI_Re both exhibited biological network characteristics, and functional analysis demonstrated that the networks were specific for MI. Additionally, we identified some lncRNA-mRNA ceRNA modules involved in MI occurrence and recurrence. Finally, two new panel biomarkers defined by four lncRNAs (RP1-239B22.5, AC135048.13, RP11-4O1.2, RP11-285F7.2) from DLMN_MI_OC and three lncRNAs (RP11-363E7.4, CTA-29F11.1, RP5-894A10.6) from DLMN_MI_Re with high classification performance were, respectively, identified in distinguishing controls from patients, and patients with recurrent events from those without recurrent events. This study will provide us new insight into ceRNA-mediated regulatory mechanisms involved in MI occurrence and recurrence, and facilitate the discovery of candidate diagnostic and prognosis biomarkers for MI.