Cancer Informatics最新文献

Bisphenol-A (BPA) is a synthetic chemical that has widely been used in the production of polycarbonate plastic and epoxy resins in the manufacture of consumer products. The most common path of human exposure to BPA is by oral intake that involves genotoxicity, oxidative stress, endocrine disruption, mutagenicity, and carcinogenicity in both in vitro and in vivo models. Melatonin is known as a free-radical scavenger and a powerful antioxidant agent. This study aimed to investigate the effects of melatonin on viability and genetic disorders of normal Human Gingival Fibroblasts (HGF), colon cancer (MKN45), and bone marrow stem cell (MSC) lines exposed to BPA. For this purpose, MTT and Comet assays were performed to evaluate the cytotoxicity and genotoxicity properties of BPA and the role of melatonin. The results showed that BPA exposure resulted in increased oxidative stress parameters including MDA and ROS, and decreased GSH content. The current study demonstrated the cytotoxicity and genotoxicity effects of BPA and the protective role of melatonin in preventing cytotoxicity and DNA damage are induced by BPA.

Flavonoids contain pharmacological effects that help to protect cells from damage. However, the anticancer activity of flavonoids is related to their modulation of signal transduction pathways within cancer cells. Natural substances such as flavonoids have immune-stimulating anti-tumor effect that could lower breast cancer risk. However, various diseases included Alzheimer's and cancer disease are associated with flavonoids intake due to their ability as antioxidant agent to alter essential cellular enzyme's function. Therefore, through interaction between flavonoids and Cytochrome P450 (CYP) family enzymes led to make them chemopreventive agents for breast cancer. In this analysis, the chemo-informatics properties of 5 selective flavonoid derivatives and their efficiency as anti-breast cancer drugs were evaluated. Flavonoid ligands were docked with the predicted protein, which is human placental aromatase complexes with exemestane, a breast cancer drug (3S7S). Based on various docking energies, the molecular characteristics and bioactivity score of the following components, C₁₅H₁₂O₆ 2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-2,3-dihydro-4H-chromen-4-one and C₁₅H₁₂O₅ 5,8-dihydroxy-2-(4-hydroxyphenyl)-2,3-dihydro-4H-chromen-4-one showed greatest molecular properties and bioactivity docking scores of -8.633117 and -8.633117 kcal/mol respectively. Therefore, both compounds could be considered antitumor agent.

Background: The revolution in next-generation sequencing (NGS) technology has allowed easy access and sharing of high-throughput sequencing datasets of cancer cell lines and their integrative analyses. However, long-term passaging and culture conditions introduce high levels of genomic and phenotypic diversity in established cell lines resulting in strain differences. Thus, clonal variation in cultured cell lines with respect to the reference standard is a major barrier in systems biology data analyses. Therefore, there is a pressing need for a fast and entry-level assessment of clonal variations within cell lines using their high-throughput sequencing data.

Results: We developed a Python-based software, AStra, for de novo estimation of the genome-wide segmental aneuploidy to measure and visually interpret strain-level similarities or differences of cancer cell lines from whole-genome sequencing (WGS). We demonstrated that aneuploidy spectrum can capture the genetic variations in 27 strains of MCF7 breast cancer cell line collected from different laboratories. Performance evaluation of AStra using several cancer sequencing datasets revealed that cancer cell lines exhibit distinct aneuploidy spectra which reflect their previously-reported karyotypic observations. Similarly, AStra successfully identified large-scale DNA copy number variations (CNVs) artificially introduced in simulated WGS datasets.

Conclusions: AStra provides an analytical and visualization platform for rapid and easy comparison between different strains or between cell lines based on their aneuploidy spectra solely using the raw BAM files representing mapped reads. We recommend AStra for rapid first-pass quality assessment of cancer cell lines before integrating scientific datasets that employ deep sequencing. AStra is an open-source software and is available at https://github.com/AISKhalil/AStra.

Restricted mean survival time (RMST), recommended for reporting survival, lacks a tool to evaluate multilevel factors. The potential of the Gini's mean difference of RMSTs (Δ) is explored in a comparison of a lymph node ratio-based classification (LNRc) versus a number-based classification (ypN) applied to stage II/III breast cancer patients who received neoadjuvant chemotherapy and underwent axillary dissection. Number of positive nodes (npos) classified patients into ypN0, npos = 0, ypN1, npos = [1,3], ypN2, npos = [4,9], and ypN3, npos ⩾ 10. Ratio npos/(number of nodes examined) of 0, (0,0.20], (0.20,0.65], and >0.65, classified patients into Lnr0 to Lnr3, respectively. Unadjusted and Cox-adjusted RMSTs were computed for the ypN and LNRc's. At a follow-up time horizon of 72 months for 114 node-negative and 254 node-positive patients, unadjusted ypN0-ypN3 RMSTs were 62.4-41.4 months, Δ = 11.9 months (95%CI: 7.4-16.9), and Lnr0-Lnr3 62.4 to 36.3 months, Δ = 14.0 months (95%CI: 10.1-18.1). Cox models' ypN1-ypN3 hazard ratios were 1.81-3.30, and Lnr1-Lnr3 1.52-4.39. Δ from Cox-fitted survival were ypN 8.1 months (95%CI: 5.9-10.5), LNRc 10.5 months (95%CI: 8.4-12.8). In conclusion, Gini's mean difference is applicable to well established data in keeping with the literature on LNRc. It provides an alternative view on the improvement gained with a lymph node ratio-classification over using a number-classification.

Introduction: Epidermal growth factor receptor (EGFR) is a transmembrane protein that belongs to the ErbB/HER-family of tyrosine kinase receptors. Somatic mutations and overexpression of EGFR have been reported to play a vital role in cancer cell development and progression, including cell proliferation, differentiation, angiogenesis, apoptosis, and metastatic spread. Hence, EGFR is an important therapeutic target for the treatment of various types of epithelial cancers. Somatic mutations have led to resistance to clinically approved synthetic EGFR inhibitors. Furthermore, synthetic EGFR inhibitors have been associated with several side effects. Thus, there is a need to develop novel EGFR inhibitors with an acceptable biosafety profile and high efficacy.

Methods: Herein, we employed structural bioinformatics and theoretical chemistry techniques via molecular docking, molecular mechanics generalized Born surface area (MM-GBSA) calculation, density functional theory analysis (DFT), and pharmacokinetic study to identify novel EGFR inhibitors.

Results: The stringent molecular docking and MM-GBSA calculations identified MET 793, LYS 745, PHE 723, ASP 855, ARG 411, and THR 854 as principal amino acid residues for EGFR-ligands interactions. Furthermore, Colocasia affinis Schott compounds exhibited higher binding energy and more stable interactions than the reference compound (gefitinib). DFT analysis also ascertains better bioactivity and chemical reactivity of C. affinis Schott with favorable intramolecular charge transfer between electron-donor and electron acceptor groups. The pharmacokinetic profile of C. affinis Schott bioactive compounds satisfies Lipinski's rule of five assessment.

Conclusion: Collectively, C. affinis Schott compounds demonstrated higher inhibitory potentials against EGFR and better pharmacological properties when compared with gefitinib. C. affinis Schott compounds are therefore suggested as promising therapeutic EGFR inhibitors for cancer treatment.

Background: Due to the substantial increase in the number of glaucoma cases within the next several decades, glaucoma is a significant public health issue. The main objective of this study was to investigate the determinant factors of intraocular pressure and time to blindness of glaucoma patients under treatment at Felege Hiwot Referral Hospital, Bahir Dar, Ethiopia.

Methods: A retrospective study design was conducted on 328 randomly selected glaucoma patients using simple random sampling based on the identification number of patients in an ophthalmology clinic at the hospital under the follow-up period from January 2014 to December 2018. A linear mixed effects model for intraocular pressure data, a semi-parametric survival model for the time-to-blindness data and joint modeling of the 2 responses were used for data analysis. However, the primary outcome was survival time of glaucoma patients.

Results: The comparison of joint and separate models revealed that joint model was more adequate and efficient inferences because of its smaller standard errors in parameter estimations. This was also approved using AIC, BIC, and based on a significant likelihood ratio test as well. The estimated association parameter (α) in the joint model was .0160 and statistically significant (P-value = .0349). This indicated that there was strong evidence for positive association between the effects of intraocular pressure and the risk of blindness. The result indicated that the higher value of intraocular pressure was associated with the higher risk of blindness. Age, hypertension, type of medication, cup-disk ratio significantly affects both average intraocular pressure and survival time of glaucoma patients (P-value < .05).

Conclusion: The predictors; age, hypertension, type of medication, and cup-disk ratio were significantly associated with the 2 responses of glaucoma patients. Health professionals give more attention to patients who have blood pressure and cup-disk ratio greater than 0.7 during the follow-up time to reduce the risk of blindness of glaucoma patients.

Gastric cancer (GC) is one of the most frequent tumors in the world. Stomach adenocarcinoma is a heterogeneous tumor, turning the prognosis prediction and patients' clinical management difficult. Some diagnosis tests for GC are been development using knowledge based in polymorphisms, somatic copy number alteration (SCNA) and aberrant histone methylation. This last event, a posttranslational modification that occurs at the chromatin level, is an important epigenetic alteration seen in several tumors including stomach adenocarcinoma. Histone methyltransferases (HMT) are the proteins responsible for the methylation in specific amino acids residues of histones tails. Here, were presented several HMTs that could be relating to GC process. We use public data from 440 patients with stomach adenocarcinoma. We evaluated the alterations as SCNAs, mutations, and genes expression level of HMTs in these aforementioned samples. As results, it was identified the 10 HMTs most altered (up to 30%) in stomach adenocarcinoma samples, which are the PRDM14, PRDM9, SUV39H2, NSD2, SMYD5, SETDB1, PRDM12, SUV39H1, NSD3, and EHMT2 genes. The PRDM9 gene is among most mutated and amplified HMTs within the data set studied. PRDM14 is downregulated in 79% of the samples and the SUV39H2 gene is down expressed in patients with recurred/progressed disease. Several HMTs are altered in many cancers. It is important to generate a genetic atlas of alterations of cancer-related genes to improve the understanding of tumorigenesis events and to propose novel tools of diagnosis and prognosis for the cancer control.

Prognostication for patients with cancer is important for clinical planning and management, but remains challenging given the large number of factors that can influence outcomes. As such, there is a need to identify features that can robustly predict patient outcomes. We evaluated 8608 patient tumor samples across 16 cancer types from The Cancer Genome Atlas and generated distinct survival classifiers for each using clinical and histopathological data accessible to standard oncology workflows. For cancers that had poor model performance, we deployed a random-forest-embedded sequential forward selection approach that began with an initial subset of the 15 most predictive clinicopathological features before sequentially appending the next most informative gene as an additional feature. With classifiers derived from clinical and histopathological features alone, we observed cancer-type-dependent model performance and an area under the receiver operating curve (AUROC) range of 0.65 to 0.91 across all 16 cancer types for 1- and 3-year survival prediction, with some classifiers consistently outperforming those for others. As such, for cancers that had poor model performance, we posited that the addition of more complex biomolecular features could enhance our ability to prognose patients where clinicopathological features were insufficient. With the inclusion of gene expression data, model performance for 3 select cancers (glioblastoma, stomach/gastric adenocarcinoma, ovarian serous carcinoma) markedly increased from initial AUROC scores of 0.66, 0.69, and 0.67 to 0.76, 0.77, and 0.77, respectively. As a whole, this study provides a thorough examination of the relative contributions of clinical, pathological, and gene expression data in predicting overall survival and reveals cancer types for which clinical features are already strong predictors and those where additional biomolecular information is needed.

Background: The increasing cancer burden remains a public health challenge. Quality and accurate population data is important to improve cancer control, screening, and treatment programmes for the sub-Saharan Africa region.

Aim: The aim of this study was to establish hospital-based cancer surveillance system, thereby reporting the burden that cancer diagnosis and treatment place on 3 hospitals - an approach of health systems strengthening.

Methods: A hospital-based cancer surveillance was established in 3 public health facilities that provide oncology services in KwaZulu-Natal. An active method was used for finding cancer cases. The cancer surveillance database was evaluated according to the criteria recommended for cancer registries. Analyses of data included descriptive and crude incidence rates.

Results: A total of 2307 newly diagnosed cancer cases were reported in 2018, with a majority from Inkosi Albert Luthuli Central hospital (65.3%), followed by Greys hospital (30.8%) and then Addington hospital (3.94%). Most of the cancer cases were from the 2 major urban areas of the province (eThekwini and uMgungundlovu district). The most commonly diagnosed cancers from all combined 3 facilities for both sexes were breast, cervix, colorectal, Kaposi Sarcoma, and lung. Approximately half of the cancer cases had no staging, and 12.8% of the cases were diagnosed at stage 4. The mostly prescribed treatments for the patients were radiotherapy and chemotherapy.

Conclusions: Based on our hospital-based surveillance, cancer burden is high in the 3 facilities. Strengthening cancer screening and diagnostic policies and procedures that will allow expansion of accurate cancer surveillance system is essential in KwaZulu-Natal and South Africa as a whole.