Genome-wide association studies: how predictable is a person's cancer risk?

In Vitro and In Vivo Approaches for Screening the Potential of Anticancer Agents: A Review

BACKGROUND

Anticancer drug development is a tedious process, requiring several in vitro, in vivo, and clinical studies. In order to avoid chemical toxicity in animals during an experiment, it is necessary to envisage toxic doses of screened drugs in vivo at different concentrations. Several in vitro and in vivo studies have been reported to discover the management of cancer.

MATERIALS AND METHODS

This study focused on bringing together a wide range of in vivo and in vitro assay methods developed to evaluate each hallmark feature of cancer.

RESULT

This review provides detailed information on target-based and cell-based screening of new anticancer drugs in the molecular targeting period. This would help in inciting an alteration from the preclinical screening of pragmatic compound-orientated to target-orientated drug selection.

CONCLUSION

Selection methodologies for finding anticancer activity have importance for tumor- specific agents. In this study, advanced rationalization of the cell-based assay is explored along with broad applications of the cell-based methodologies considering other opportunities.

The association between XRCC3 rs1799794 polymorphism and cancer risk: a meta-analysis of 34 case-control studies

BACKGROUND

Studies on the XRCC3 rs1799794 polymorphism show that this polymorphism is involved in a variety of cancers, but its specific relationships or effects are not consistent. The purpose of this meta-analysis was to investigate the association between rs1799794 polymorphism and susceptibility to cancer.

METHODS

PubMed, Embase, the Cochrane Library, Web of Science, and Scopus were searched for eligible studies through June 11, 2019. All analyses were performed with Stata 14.0. Subgroup analyses were performed by cancer type, ethnicity, source of control, and detection method. A total of 37 studies with 23,537 cases and 30,649 controls were included in this meta-analysis.

RESULTS

XRCC3 rs1799794 increased cancer risk in the dominant model and heterozygous model (GG + AG vs. AA: odds ratio [OR] = 1.04, 95% confidence interval [CI] = 1.00-1.08, P = 0.051; AG vs. AA: OR = 1.05, 95% CI = 1.00-1.01, P = 0.015). The existence of rs1799794 increased the risk of breast cancer and thyroid cancer, but reduced the risk of ovarian cancer. In addition, rs1799794 increased the risk of cancer in the Caucasian population.

CONCLUSION

This meta-analysis confirms that XRCC3 rs1799794 is related to cancer risk, especially increased risk for breast cancer and thyroid cancer and reduced risk for ovarian cancer. However, well-designed large-scale studies are required to further evaluate the results.

Cancer cell detection by a heart-shaped dual-core photonic crystal fiber sensor

This paper contributes a novel design of sensor with a heart-shaped dual-core photonic crystal fiber (PCF) to detect cancerous cells in human cervical, blood, adrenal glands, and breast. Cancer-infected cells and their normal cells are considered in liquid form having their own refractive indices. In the designed PCF, the two heart-shaped cores separated by a large circular air hole serve as two independent waveguides. The large circular air hole is infiltrated by sample cells from different body parts. Detection of cancer-contaminated cells by the proposed PCF is based on the mode-coupling theory. According to the mode-coupling theory, the guided optical light transmits periodically from one core to another, throughout the PCF length. During this transmission, the optical light interacts with the cancerous cell, which is filled in the center air hole of the PCF. Due to this interaction, the dip wavelength of the transmission spectrum is sensitive to the corresponding cancerous cell filled in the center air hole of the PCF. The variation in the PCF transmission spectrum for cancerous cells and their normal cells is observed by using the finite element method. The dip wavelength shift of the cancer cell in reference to its normal cell has been measured from the transmission spectrum to determine the sensing performance of the proposed sensor. The sensitivity achieved of the proposed sensor for cervical cancer cell, blood cancer cell, adrenal gland cancer cell, and breast cancer cells are 7916.67 nm/RIU, 8571.43 nm/RIU, 9285.71 nm/RIU, and 10,000 nm/RIU, respectively, with a maximum detection limit of 0.024. Therefore, the proposed PCF sensor suggests high sensitivity with a rapid cancer detection mechanism.

Nonmalignant Formalin-Fixed Paraffin-Embedded Tissues as a Source to Study Germline Variants and Cancer Predisposition: A Systematic Review

Background: Archived formalin-fixed paraffin-embedded (FFPE) specimens from nonmalignant tissues derived from cancer patients are a vast and potentially valuable resource for high-quality genotyping analyses and could have a role in establishing inherited cancer risk. Methods: We systematically searched PubMed, Ovid MEDLINE, and Scopus databases for all articles that compared genotyping performance of DNA from nonmalignant FFPE tissue with blood DNA derived from cancer patients irrespective of tumor type. Two independent researchers screened the retrieved studies, removed duplicates, excluded irrelevant studies, and extracted genotyping data from the eligible studies. These studies included, but were not limited to, genotyping technique, reported call rate, and concordance. Results: Thirteen studies were reviewed, in which DNA from nonmalignant FFPE tissues derived from cancer patients was successfully purified and genotyped. All these studies used different approaches for genotyping of DNA from nonmalignant FFPE tissues to amplify single nucleotide polymorphisms (SNPs) and to estimate of loss of heterozygosity. The concordance between genotypes from nonmalignant FFPE tissues and blood derived from cancer patients was observed to be high, whereas the call rate of the tested SNPs was not reported in all included studies. Conclusion: This review illustrates that DNA from nonmalignant FFPE tissues derived from cancer patients can serve as an alternative and reliable source for assessment of germline DNA for various purposes, including assessment of cancer predisposition.

Protein-altering germline mutations implicate novel genes related to lung cancer development

Few germline mutations are known to affect lung cancer risk. We performed analyses of rare variants from 39,146 individuals of European ancestry and investigated gene expression levels in 7,773 samples. We find a large-effect association with an ATM L2307F (rs56009889) mutation in adenocarcinoma for discovery (adjusted Odds Ratio = 8.82, P = 1.18 × 10-15) and replication (adjusted OR = 2.93, P = 2.22 × 10-3) that is more pronounced in females (adjusted OR = 6.81 and 3.19 and for discovery and replication). We observe an excess loss of heterozygosity in lung tumors among ATM L2307F allele carriers. L2307F is more frequent (4%) among Ashkenazi Jewish populations. We also observe an association in discovery (adjusted OR = 2.61, P = 7.98 × 10-22) and replication datasets (adjusted OR = 1.55, P = 0.06) with a loss-of-function mutation, Q4X (rs150665432) of an uncharacterized gene, KIAA0930. Our findings implicate germline genetic variants in ATM with lung cancer susceptibility and suggest KIAA0930 as a novel candidate gene for lung cancer risk.

In-vivo antiproliferative activity of Morus latifolia leaf and bark extracts against Ehrlich's ascites carcinoma

Cancer is the second death causing disease all over the world and until today 100 different types of cancer have been identified whose treatment methods consist of serious side effects on human body. To reduce the frequency of adverse effects of cancer treatment, nowadays plant derived natural components are getting priority. The plant Morus latifolia is widely available in northern part of Bangladesh. The earlier researches suggested that popular varieties of some Morus sp. like Morus alba, Morus indica etc. have good anti-proliferative activity. Hence, this study was designed to evaluate the anti-proliferative activity of leaf and bark extracts of M. latifolia against Ehrlich's ascites carcinoma (EAC) in vivo. The leaf and bark extracts of M. latifolia were used in several bioassays including Brine shrimp lethality test, hemagglutination activity test, antioxidant activity test, and cell growth inhibition test. Besides, fluorescence microscopy was performed to study apoptotic features in EAC cells, and molecular analysis like real-time PCR were also conducted. The results of Brine shrimp lethality test, hemagglutination activity test, and antioxidant activity assay supported the cell growth inhibition capability of leaf and bark extracts which was confirmed by in vivo cell growth inhibition bioassay. Moreover, the experimental extracts were able to induce cell apoptotis through altering the expression pattern of Bcl-2 and Bax genes. All of the results of this study suggest that several noble compounds are present in M. latifolia plant extracts which are capable for healing cancer cells.

Fragmentation Spectra Prediction and DNA Adducts Structural Determination

In this work, chemical dynamics simulations were optimized and used to predict fragmentation mass spectra for DNA adduct structural determination. O⁶-methylguanine (O⁶-Me-G) was used as a simple model adduct to calculate theoretical spectra for comparison with measured high-resolution fragmentation data. An automatic protocol was established to consider the different tautomers accessible at a given energy and obtain final theoretical spectra by insertion of an initial tautomer. In the work reported here, the most stable tautomer was chosen as the initial structure, but in general, any structure could be considered. Allowing for the formation of the various possible tautomers during simulation calculations was found to be important to getting a more complete fragmentation spectrum. The calculated theoretical results reproduce the experimental peaks such that it was possible to determine reaction pathways and product structures. The calculated tautomerization network was crucial to correctly identifying all the observed ion peaks, showing that a mobile proton model holds not only for peptide fragmentation but also for nucleobases. Finally, first principles results were compared to simple machine learning fragmentation models.

Prerequisite of a Holistic Blend of Traditional and Modern Approaches of Cancer Management

Background:

With the advent of changes in lifestyle of people all around the world, cancer cases have been showing an exponential rise. Researchers from varied fields have been trying to solve this tricky issue.

Methods:

We undertook a systematic search of bibliographic databases of peer-reviewed research literature to evaluate the holistic blend of modern and traditional approaches, especially the Ayurvedic perspective of treatment of cancer along with the effect of our diet and lifestyle on the management (both prevention and cure) of cancer.

Results:

On the basis of extensive literature survey, it was found that Ayurveda as one of the ancient medicinal systems had been very well documented for utilizing its best practices for the treatment of various diseases including cancer, by utilization of several herbal plants and dietary interventions as therapeutics. Active components present in various herbs, which interfere with certain molecular targets to inhibit carcinogenesis are also summarized. Further, beneficial effects of yoga and exercise on psychological distress, cancer-related fatigue and global side-effects as well as their mechanism of action are also discussed. In addition, we recapitulate an upcoming field of Ayurgenomics to understand the possible correlation of Prakriti with genetics as well as epigenetics.

Conclusion:

Both genetic as well as environmental factors have shown their linkage with cancer. Substantial advancements in the field of targeted therapies have opened new horizons for the cancer patients. To fight with this grave situation, a combination of ancient and modern medicinal systems seems to be the need of the hour.

Cytochrome P450 and P-Glycoprotein-Mediated Interactions Involving African Herbs Indicated for Common Noncommunicable Diseases

Herbal remedies are regularly used to complement conventional therapies in the treatment of various illnesses in Africa. This may be because they are relatively cheap and easily accessible and are believed by many to be safe, cause fewer side effects, and are less likely to cause dependency. On the contrary, many herbs have been shown to alter the pharmacokinetics of coadministered allopathic medicines and can either synergize or antagonize therapeutic effects as well as altering the toxicity profiles of these drugs. Current disease burden data point towards epidemiological transitions characterised by increasing urbanization and changing lifestyles, risk factors for chronic diseases like hypertension, diabetes, and cancer which often present as multimorbidities. As a result, we highlight African herb-drug interactions (HDIs) modulated via cytochrome P450 enzyme family (CYP) and P-glycoprotein (P-gp) and the consequences thereof in relation to antihypertensive, antidiabetic, and anticancer drugs. CYPs are enzymes which account for to up to 70% of drug metabolism while P-gp is an efflux pump that extrudes drug substrates out of cells. Consequently, regulation of the relative activity of both CYP and P-gp by African herbs influences the effective drug concentration at the site of action and modifies therapeutic outcomes.

Exosomes for Immunoregulation and Therapeutic Intervention in Cancer

Exosomes, as a subset of extracellular vesicles, function as a mode of intercellular communication and molecular transfer, and facilitate the direct extracellular transfer of proteins, lipids, and miRNAs/mRNAs/DNAs between cells. Cancers have adapted exosomes and related microvesicles as a pathway that can suppress the immune system and establish a fertile local and distant environment to support neoplastic growth, invasion, and metastasis; these tumor-derived exosomes affect immunoregulation mechanisms, including immune activation and immune suppression. Immune cell-derived exosomes can modulate the immune response in cancer, which supports the belief that these membranous vesicles are immunotherapeutic reagents. In this review, we discuss the recent advances in the cancer immunotherapy, roles of exosomes in cancer, immunoregulation of tumor-derived exosomes, and immunomodulation by immune cell-derived exosomes. The topics covered here highlight novel insights into the development of efficient exosome-based cancer vaccines for cancer therapeutic intervention.

Joint detection of tumor markers with imaging ellipsometry biosensor

Tumor marker detection contributes to the early diagnosis of cancers. However, due to the lack of detection specificity, its results cannot act as a direct evidence to confirm cancer occurrence in clinic. Joint detection of tumor markers may improve the detection specificity. As a trial for clinical diagnosis of hepatocellular carcinoma, α-fetoprotein, α-l-fucosidase and ferritin have been combined and detected with a label-free, phase sensitive and high throughput imaging ellipsometry biosensor (IEB). Eighty-two sera have been quantitatively detected with IEB and the results are in agreement with the clinical standard approaches. Evaluated by receiver operating characteristic analysis, the specificity of joint detection improves remarkably with IEB for hepatocellular carcinoma. It can be foreseen that the joint detection of tumor markers with IEB has a potential for clinical cancer diagnosis.

Nipple-sparing mastectomy and immediate reconstruction in ductal carcinoma in situ: a critical assessment with 41 patients

BACKGROUND

Nipple-sparing mastectomy (NSM) is increasingly popular for the treatment of select breast cancers and prophylactic mastectomy. This study aimed to analyze the authors' 11-year experience with NSM and breast reconstruction in cases of ductal carcinoma in situ (DCIS) with an emphasis on indications, complications, and cancer recurrence rate.

METHODS

Between January 2000 and December 2010, 41 NSMs were performed in 41 women for DCIS. The mean age of the women was 49.7±8.7 years (range, 33-66 years). The indications for NSM were tumor size greater than 3 cm (18 cases), multifocal tumor (16 cases), and tumor recurrence (7 cases). In all cases, the tumor was located more than 2 cm from the nipple-areola complex (NAC), as shown by preoperative radiologic imaging. Histologic results, secondary NAC resection, complications, and cancer recurrence rates were recorded.

RESULTS

The NAC was lost in seven cases (17%) due to postoperative necrosis. In another 10 patients (25%), the NAC was secondarily removed due to proximity of the tumor to the resection margin. Five patients were lost to follow-up evaluation (12%). The authors report the long-term follow-up data for the remaining 19 patients (46%). In this group, they observed one local recurrence (5.3%) and one case of ovarian cancer.

CONCLUSION

Despite the low locoregional recurrence rate for DCIS, NSM remains controversial because of the nipple necrosis observed and the irradical tumor excisions. Given the ethical impossibility of conducting randomized controlled studies to compare NSM with conventional or skin-sparing mastectomy in DCIS, only long-term follow-up evaluations can demonstrate the safety of NSM.

LEVEL OF EVIDENCE IV

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Presence of S100A9-positive inflammatory cells in cancer tissues correlates with an early stage cancer and a better prognosis in patients with gastric cancer

Background

S100A9 was originally discovered as a factor secreted by inflammatory cells. Recently, S100A9 was found to be associated with several human malignancies. The purpose of this study is to investigate S100A9 expression in gastric cancer and explore its role in cancer progression.

Methods

S100A9 expression in gastric tissue samples from 177 gastric cancer patients was assessed by immunohistochemistry. The expression of its dimerization partner S100A8 and the S100A8/A9 heterodimer were also assessed by the same method. The effect of exogenous S100A9 on motility of gastric cancer cells AGS and BGC-823 was then investigated.

Results

S100A9 was specifically expressed by inflammatory cells such as macrophages and neutrophils in human gastric cancer and gastritis tissues. Statistical analysis showed that a high S100A9 cell count (> = 200) per 200x magnification microscopic field in cancer tissues was predictive of early stage gastric cancer. High S100A9-positive cell count was negatively correlated with lymph node metastasis (P = 0.009) and tumor invasion (P = 0.011). S100A9 was identified as an independent prognostic predictor of overall survival of patients with gastric cancer (P = 0.04). Patients with high S100A9 cell count were with favorable prognosis (P = 0.021). Further investigation found that S100A8 distribution in human gastric cancer tissues was similar to S100A9. However, the number of S100A8-positive cells did not positively correlate with patient survival. The inflammatory cells infiltrating cancer were S100A8/A9 negative, while those in gastritis were positive. Furthermore, exogenous S100A9 protein inhibited migration and invasion of gastric cancer cells.

Conclusions

Our results suggested S100A9-positive inflammatory cells in gastric cancer tissues are associated with early stage of gastric cancer and good prognosis.

Residual-QSAR. Implications for genotoxic carcinogenesis

INTRODUCTION

Both main types of carcinogenesis, genotoxic and epigenetic, were examined in the context of non-congenericity and similarity, respectively, for the structure of ligand molecules, emphasizing the role of quantitative structure-activity relationship ((Q)SAR) studies in accordance with OECD (Organization for Economic and Cooperation Development) regulations. The main purpose of this report involves electrophilic theory and the need for meaningful physicochemical parameters to describe genotoxicity by a general mechanism. RESIDUAL-QSAR METHOD: The double or looping multiple linear correlation was examined by comparing the direct and residual structural information against the observed activity. A self-consistent equation of observed-computed activity was assumed to give maximum correlation efficiency for those situations in which the direct correlations gave non-significant statistical information. Alternatively, it was also suited to describe slow and apparently non-noticeable cancer phenomenology, with special application to non-congeneric molecules involved in genotoxic carcinogenesis.

APPLICATION AND DISCUSSIONS

The QSAR principles were systematically applied to a given pool of molecules with genotoxic activity in rats to elucidate their carcinogenic mechanisms. Once defined, the endpoint associated with ligand-DNA interaction was used to select variables that retained the main Hansch physicochemical parameters of hydrophobicity, polarizability and stericity, computed by the custom PM3 semiempirical quantum method. The trial and test sets of working molecules were established by implementing the normal Gaussian principle of activities that applies when the applicability domain is not restrained to the congeneric compounds, as in the present study. The application of the residual, self-consistent QSAR method and the factor (or average) method yielded results characterized by extremely high and low correlations, respectively, with the latter resembling the direct activity to parameter QSARs. Nevertheless, such contrasted correlations were further incorporated into the advanced statistical minimum paths principle, which selects the minimum hierarchy from Euclidean distances between all considered QSAR models for all combinations and considered molecular sets (i.e., school and validation). This ultimately led to a mechanistic picture based on the identified alpha, beta and gamma paths connecting structural indicators (i.e., the causes) to the global endpoint, with all included causes. The molecular mechanism preserved the self-consistent feature of the residual QSAR, with each descriptor appearing twice in the course of one cycle of ligand-DNA interaction through inter-and intra-cellular stages.

CONCLUSIONS

Both basal features of the residual-QSAR principle of self-consistency and suitability for non-congeneric molecules make it appropriate for conceptually assessing the mechanistic description of genotoxic carcinogenesis. Additionally, it could be extended to enriched physicochemical structural indices by considering the molecular fragments or structural alerts (or other molecular residues), providing more detailed maps of chemical-biological interactions and pathways.

Trastuzumab and beyond: sequencing cancer genomes and predicting molecular networks

Life diversity can now be clearly explored with the next-generation DNA sequencing technology, allowing the discovery of genetic variants among individuals, patients and tumors. However, beyond causal mutations catalog completion, systems medicine is essential to link genotype to phenotypic cancer diversity towards personalized medicine. Despite advances with traditional single genes molecular research, including rare mutations in BRCA1/2 and CDH1 for primary prevention and trastuzumab for treating HER2-overexpressing breast and gastric tumors, overall, treatment failure and death rates are still alarmingly high. Revolution in sequencing reveals that, now both a huge number and widespread variability of driver mutations, including single-nucleotide polymorphisms, genomic rearrangements and copy-number changes involved in breast cancer development. All these genetic alterations result in a heterogeneous deregulation of signaling pathways, including EGFR, HER2, VEGF, Wnt/Notch, TGF and others.Cancer initiation, progression and metastases are driven by complex molecular networks rather than linear genotype-phenotype relationship. Therefore, clinical expectations by traditional molecular research strategies targeting single genes and single signaling pathways are likely minimal. This review discusses the necessity of molecular networks modeling to understand complex gene-gene, protein-protein and gene-environment interactions. Moreover, the potential of systems clinico-biological approaches to predict intracellular signaling pathways components networks and cancer heterogeneous cells within an individual tumor is described. A flowchart specific for three steps in cancer evolution separately tumorigenesis, early-stage and advanced-stage breast cancer is presented. Using reverse engineering starting with the integration of available established clinical, environmental, treatment and oncological outcomes (survival and death) data and then the still incomplete but progressively accumulating genotypic data into computational networks modeling may lead to bionetworks-based discovery of robust biomarkers and highly effective cancer drugs targets.

Novel clinico-genome network modeling for revolutionizing genotype-phenotype-based personalized cancer care

Although cancer heterogeneity, even within individual tumors with different treatment responses of subcloncal cells populations, suggests the need for personalized medicine, most funding and efforts go to conventional single gene-based research and comparative-effectiveness research. Cancer arises from changes in the DNA sequence in the genomes of cancer cells. These accelerating somatic mutations dysregulate signaling pathways, including EGFR, Wnt/Notch, Hedgehog and others, with a central role in cell growth, proliferation, survival, angiogenesis and metastasis. All of these genetic alterations can now be discovered using next-generation DNA sequencing technology. This high-throughput technology can achieve two major goals: first, to complete the catalogue of driver mutations, including point mutations, rearrangements and copy-number changes, by full and targeted sequencing; and second, to explore the functional role of cancer genes and their interactions by genome-wide RNA, serial analysis of gene expression, microRNAs, protein-DNA interactions, and comprehensive analyses of transcriptomes and interactomes. This review article discusses the challenges, including costs, in completing the catalogue of driver mutations for each cancer type and understanding how cancer genomes operate as whole biological systems. Now high-quality clinical treatment and outcomes (death or survival) data from biobanks, and extensive genetics and genomics data for some common tumors, including breast, colorectal and pancreatic cancer, are available. In this article, we will describe how all these clinical and genetics data could be integrated into reverse engineering-based network modeling to approach the extremely complex genotype-phenotype map. This clinico-genome systems model, published for the first time, opens the way for the discovery of new molecular innovations, both predictive markers and therapies, towards personalized treatment of cancer. Instead of the comparative-effectiveness research or personalized medicine debate, harmonization of both can revolutionize cancer management.