This cross-sectional study is aimed at assessing the quality of life in a cohort of breast cancer patients at the Oncology Department, King Abdulaziz University Hospital (KAUH), King Abdulaziz University (KAU), Jeddah, Saudi Arabia (SA), and to differentiate QoL among different groups. Mean time since diagnosis was 3.97±1.90 years. European Organization for Research and Treatment of Cancer Quality of Life Questionnaires—Core30 and BR23 (EORTC QLQ-C30 & BR23) were used to assess QoL in breast cancer survivors. ANOVA and independent t-test (parametric tests) were used for the categorical variables and Kruskal-Wallis and Mann-Whitney tests used for non-parametric tests. Linear regression analysis was done to measure predictors’ significance and to calculate the coefficient of determination. Two hundred and eighty-four patients completed the survey. Global health status and functional scales, in most of the domains, were high, while symptom scales were moderate-to-low for most items, showing better QoL. Insomnia and fatigue were the most disturbing symptoms. Patients exhibited higher scores for body image and future perspective, while the least score is for sexual functioning. Global health, physical functioning, and role functioning were better in the age group ≤50 years (p<0.05). Premenopausal and perimenopausal patients showed a better level of functioning as compared to postmenopausal patients (p = 0.001). Premenopausal patients scored higher for sexual enjoyment, as compared to peri- and post-menopausal patients (p = 0.04). Systemic therapy side effects were more evident in the breast conservative surgery group. Predictors explained 8% of the variation in Physical functioning (R-squared = 0.08). A predictor that had a remarkable influence on physical functioning, as compared to the other predictors in the model, was menopausal status (P = 0.02). So, it was concluded that the breast cancer patients visiting our institute had a better quality of life regarding overall global health status as well as functional and symptom scales. Some issues, for instance, fatigue, insomnia, hair loss, and others, warrant good supportive therapy.

BackgroundColorectal cancer (CRC) is a heterogeneous disease with different molecular characteristics associated with many variables such as the sites from which the tumors originate or the presence or absence of chromosomal instability. Identification of such variables, particularly mutational hotspots, often carries a significant diagnostic and/or prognostic value that could ultimately affect the therapeutic outcome.MethodsHigh-throughput mutational analysis of 99 CRC formalin-fixed and paraffin-embedded (FFPE) cases was performed using the Cancer Hotspots Panel (CHP) v2 on the Ion Torrent™ platform. Correlation with survival and other Clinicopathological parameters was performed using Fisher’s exact test and Kaplan–Meier curve analysis.ResultsTargeted sequencing lead to the identification of frequent mutations in TP53 (65 %), APC (36 %), KRAS (35 %), PIK3CA (19 %), PTEN (13 %), EGFR (11 %), SMAD4 (11 %), and FBXW7 (7 %). Other genes harbored mutations at lower frequency. EGFR mutations were relatively frequent and significantly associated with young age of onset (p = 0.028). Additionally, EGFR or PIK3CA mutations were a marker for poor disease-specific survival in our cohort (p = 0.009 and p = 0.032, respectively). Interestingly, KRAS or PIK3CA mutations were significantly associated with poor disease-specific survival in cases with wild-type TP53 (p = 0.001 and p = 0.02, respectively).ConclusionsFrequent EGFR mutations in this cohort as well as the differential prognostic potential of KRAS and PIK3CA in the presence or absence of detectable TP53 mutations may serve as novel prognostic tools for CRC in patients from the Kingdom of Saudi Arabia. Such findings could help in the clinical decision-making regarding therapeutic intervention for individual patients and provide better diagnosis or prognosis in this locality.

than in those who did not [15/235 (6.4%) vs. 137/436 (31.4%); p < 0.001; risk ratio: 0.20]. ConclusionsIn routine clinical practice, treatment with fec-d is associated with a higher-than-expected rate of febrile neutropenia, in light of which, primary prophylaxis with growth factor should be considered, per international guidelines. Adoption based on clinical trial reports of new therapies into mainstream practice must be done carefully and with scrutiny.

Introduction Fenofibrate is an agonist of peroxisome proliferator activated receptor alpha (PPAR-α), that possesses anti-inflammatory, antioxidant, and anti-thrombotic properties. Fenofibrate is effective against a variety of viral infections and different inflammatory disorders. Therefore, the aim of critical review was to overview the potential role of fenofibrate in the pathogenesis of SARS-CoV-2 and related complications. Results By destabilizing SARS-CoV-2 spike protein and preventing it from binding angiotensin-converting enzyme 2 (ACE2), a receptor for SARS-CoV-2 entry, fenofibrate can reduce SARS-CoV-2 entry in human cells Fenofibrate also suppresses inflammatory signaling pathways, which decreases SARS-CoV-2 infection-related inflammatory alterations. In conclusion, fenofibrate anti-inflammatory, antioxidant, and antithrombotic capabilities may help to minimize the inflammatory and thrombotic consequences associated with SARSCoV-2 infection. Through attenuating the interaction between SARS-CoV-2 and ACE2, fenofibrate can directly reduce the risk of SARS-CoV-2 infection. Conclusions As a result, fenofibrate could be a potential treatment approach for COVID-19 control.

Identifying and distinguishing cancer driver genes among thousands of candidate mutations remains a major challenge. Accurate identification of driver genes and driver mutations is critical for advancing cancer research and personalizing treatment based on accurate stratification of patients. Due to inter-tumor genetic heterogeneity many driver mutations within a gene occur at low frequencies, which make it challenging to distinguish them from non-driver mutations. We have developed a novel method for identifying cancer driver genes. Our approach utilizes multiple complementary types of information, specifically cellular phenotypes, cellular locations, functions, and whole body physiological phenotypes as features. We demonstrate that our method can accurately identify known cancer driver genes and distinguish between their role in different types of cancer. In addition to confirming known driver genes, we identify several novel candidate driver genes. We demonstrate the utility of our method by validating its predictions in nasopharyngeal cancer and colorectal cancer using whole exome and whole genome sequencing.