Given a passage, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the passage. Avoid creating questions that (i) can't be answered correctly without actually understanding the passage and (ii) uses the same words or phrases given in the passage.

Example Input: Endometrial cancers (ECs) are the most common form of gynecologic malignancy. Recent studies have reported that ECs reveal distinct markers for molecular pathogenesis, which in turn is linked to the various histological types of ECs. To understand further the molecular events contributing to ECs and endometrial tumorigenesis in general, a more precise identification of cancer-associated molecules and signaling networks would be useful for the detection and monitoring of malignancy, improving clinical cancer therapy, and personalization of treatments.', 'ECs-specific gene co-expression networks were constructed by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Important pathways and putative cancer hub genes contribution to tumorigenesis of ECs were identified. An elastic-net regularized classification model was built using the cancer hub gene signatures to predict the phenotypic characteristics of ECs. The 19 cancer hub gene signatures had high predictive power to distinguish among three key principal features of ECs: grade, type, and stage. Intriguingly, these hub gene networks seem to contribute to ECs progression and malignancy via cell-cycle regulation, antigen processing and the citric acid (TCA) cycle.
Example Output: Does visual gene-network analysis reveal the cancer gene co-expression in human endometrial cancer?

Example Input: Recent studies have suggested that the percent of positive cores in the prostate needle biopsy is a significant predictor of outcome among men undergoing radical prostatectomy or radiation therapy for prostate cancer. We evaluate whether either percent of cores with cancer or percent of cores positive from the most and least involved side of the prostate needle biopsy was associated with a worse outcome among men treated with radical prostatectomy.', 'A retrospective survey of 1,094 patients from the SEARCH Database treated with radical prostatectomy at 4 different equal access medical centers in California between 1988 and 2002 was undertaken. We used multivariate analysis to examine whether total percent of prostate needle biopsy cores with cancer, percent of cores positive from each side of the prostate and other clinical variables were significant predictors of adverse pathology and time to prostate specific antigen (PSA) recurrence following radical prostatectomy.', 'On multivariate analysis serum PSA and percent of positive cores were significant predictors of positive surgical margins, nonorgan confined disease and seminal vesicle invasion. Percent of positive cores (p <0.001), serum PSA (p = 0.008) and biopsy Gleason score (p = 0.014) were significant independent predictors of time to biochemical recurrence. On a separate multivariate analysis that included the variables of total percent of positive cores, percent of positive cores from the most involved side of the biopsy, percent of positive cores from the least involved side of the biopsy and whether the biopsy was positive unilaterally or bilaterally, only the percent of positive cores from the most involved side of the biopsy was a significant independent predictor of PSA failure following radical prostatectomy. Percent of positive cores was used to separate patients into a low risk (less than 34%), intermediate risk (34% to 50%) and high risk (greater than 50%) groups, which provided significant preoperative risk stratification for PSA recurrence following radical prostatectomy (p <0.001). Percent of positive cores cut points were able to further risk stratify men who were at low (p = 0.001) or intermediate (p = 0.036) but not high (p = 0.674) risk for biochemical failure based on serum PSA and biopsy Gleason score.
Example Output: Is percent of prostate needle biopsy cores with cancer significant independent predictor of prostate specific antigen recurrence following radical prostatectomy : results from SEARCH database?

Example Input: The receptor activator of NF-kB ligand (RANKL) has a critical role in osteoclast activation. Recently it has been demonstrated that human multiple myeloma (MM) cells do not express RANKL but up-regulate RANKL in bone marrow stromal cells (BMSC). To further investigate the role of RANKL in the pathophysiology of MM we evaluated the expression of its receptor RANK in MM cells and in the BM environment and the potential role of RANKL in the interaction of myeloma cells with the microenvironment.', 'RANK mRNA and protein expression were evaluated by reverse transcription polymerase chain reaction and Western blot analysis in human myeloma cell lines (HMCL), fresh purified MM cells, BMSC and endothelial cells. Moreover the effect and the role of RANKL on cytokine secretion were evaluated in BMSC, in endothelial cells and in co-culture conditions with myeloma cells.', 'We found that RANK is expressed in BMSC and endothelial cells but not in myeloma cells. Consistently, RANKL did not have a direct effect on myeloma cell survival, but RANKL treatment induced a significant increase of interleukin (IL)-6 and IL-11 secretion by both BMSC and endothelial cells. Moreover, in a co-culture system we found that myeloma cells up-regulated both IL-6 and IL-11 secretion by BMSC and endothelial cells through cell-to-cell contact. The presence of the RANK-Fc that blocks the RANK/RANKL interaction significantly inhibited HMCL-induced secretion of IL-6 and IL-11.
Example Output:
Is the RANK/RANK ligand system involved in interleukin-6 and interleukin-11 up-regulation by human myeloma cells in the bone marrow microenvironment?