Revisiting the Genomic and Transcriptomic Landscapes from Female Malignancies Could Provide Molecular Markers and Targets for Precision Medicine.

AIMS: Gynaecological malignancies such as breast, ovarian and cervical cancers have become an important public health problem. Detection of molecular alterations in cancer research is fundamental since it can reveal specific pathogenic patterns and genes that could serve as markers. Our aim was to characterize common genomic and transcriptomic signatures for the three gynaecologic malignancies with the highest incidence and mortality to try to identify new molecular markers, therapeutic targets and molecular signatures. METHODS: Here we analysed a total of 723 microarray libraries corresponding to equal number of breast, ovary and cervical cancer and non-cancer patient samples. Copy number variation (CNV) was carried out using 428 libraries and transcriptomic analysis using the 295 remaining samples. RESULTS: Our results showed that breast, ovary and cervical malignancies are characterized by gain of 1q chromosome. At transcriptomic level, they share 351 coding and non-coding genes, which could represent core transcriptome of gynaecological malignancies. Pathway analysis from the resulting gene lists from CNV and expression showed participation in cell cycle, metabolism, and cell adhesion molecules among others. CONCLUSIONS: Chromosome 1q characterize the gynaecological malignancies, which could harbour a richness of genetic repertoire to mine for molecular markers and targets, particular gynaecologic expression profile, containing FANCI, FH and MIR155HG among others, could represent part of the transcriptomic core for diagnostic test and attractive therapeutic targets. It may not be long before every human cancer sample is profiled for a detections test to ascertain a molecular diagnosis and prognosis and to define an optimal and precise treatment strategy.

Mid-arm muscle area is a better predictor of mortality than body mass index in COPD.

BACKGROUND: A low body mass index (BMI) has been shown to be an independent indicator of poor prognosis in patients with COPD. However, some studies suggest that muscle mass depletion (MD) is the main factor responsible for the negative effects attributable to malnutrition. STUDY OBJECTIVE: To evaluate the prognostic influence of MD estimated from anthropometric parameters. DESIGN AND MEASUREMENTS: Mortality was studied in a prospective cohort of 96 male patients with COPD (average age, 69 +/- 9 years; FEV1 percentage of predicted, 44 +/- 18% [ +/- SD]) followed up for 3 years, with an evaluation of the prognostic influence of the following anthropometric parameters: BMI, mid-arm muscle area (MAMA), and fat-free mass index. Other risk factors were also analyzed, such as age, comorbidity (Charlson index), basal dyspnea index, the St. George's Respiratory Questionnaire score, the number of hospital admissions in the year prior to nutritional evaluation, the number of hospital admissions in the year immediately after nutritional evaluation (Hpost), spirometry, and blood gases. RESULTS: In the multivariate study, Pa(CO2) (p = 0.003; hazard ratio, 1.08), Hpost (p = 0.005, hazard ratio, 4.63), and a MAMA value less than or equal to percentile 25 of the reference value (p25) [p = 0.025; hazard ratio, 3.78] were found to be independent indicators of poor prognosis. Respiratory mortality after 12, 24, and 36 months in the patients with MAMA < or = p25 was 12.1%, 31.4%, and 39.2%, respectively, vs 5.9%, 7.9%, and 13% in the group of patients without MD (p = 0.006). In normal-weight or overweight patients, MAMA < or = p25 increased the risk of mortality 3.4-fold (p = 0.032). CONCLUSIONS: MD is a better predictor of mortality than BMI in patients with COPD, fundamentally in normal-weight or overweight patients. The prognostic influence of MD can be estimated indirectly by determining the MAMA, an inexpensive, simple, and rapidly obtained anthropometric measure.