Genetic association with overall survival of taxane-treated lung cancer patients - a genome-wide association study in human lymphoblastoid cell lines followed by a clinical association study

Insight into the Role of the miR-584 Family in Human Cancers

Among the non-coding RNAs, the aberrant expression of microRNAs (miRNAs) is well described in the oncology field. It is clear that the altered expression of miRNAs is crucial for a variety of processes such as proliferation, apoptosis, motility, angiogenesis and metastasis insurgence. Considering these aspects, RNA-based therapies and the use of miRNAs as non-invasive biomarkers for early diagnosis are underlined as promising opportunities against cancer death. In the era of precision medicine, significant progress in next-generation sequencing (NGS) techniques has broadened knowledge regarding the miRNAs expression profile in cancer tissues and in the blood of cancer patients. In this scenario, pre-clinical and clinical studies suggested that the members of the miR-584 family, i.e., miR-584-5p and -3p, are prominent players in cancer development and progression. Under some conditions, these miRNAs are under-expressed in cancer tissues acting as tumor suppressors, while in other conditions, they are overexpressed, acting as oncogenes increasing the aggressive behavior of cancer cells. The aim of this review is to provide a comprehensive and up-to-date overview on the expression, upstream genes, molecular targets and signaling pathways influenced by the miR-584 family (i.e., miR-584-3p and -5p) in various human solid and hematological cancers. To achieve this goal, 64 articles on this topic are discussed. Among these articles, 55 are focused on miR-584-5p, and it is outlined how this miRNA could be used in future applications as a potential new therapeutic strategy and diagnostic tool.

Biomarker screening using integrated bioinformatics for the development of "normal-impaired glucose intolerance-type 2 diabetes mellitus"

Type 2 diabetes mellitus (T2DM) is a progressive disease. We utilized bioinformatics analysis and experimental research to identify biomarkers indicative of the progression of T2DM, aiming for early detection of the disease and timely clinical intervention. Integrating Mfuzz analysis with differential expression analysis, we identified 76 genes associated with the progression of T2DM, which were primarily enriched in signaling pathways such as apoptosis, p53 signaling, and necroptosis. Subsequently, using various analytical methods, including machine learning, we further narrowed down the hub genes to STK17A and CCT5. Based on the hub genes, we calculated the risk score for samples and interestingly found that the score correlated with multiple programmed cell death (PCD) pathways. Animal experiments revealed that the diabetes model exhibited higher levels of MDA and LDH, with lower expression of SOD, accompanied by islet cell apoptosis. In conclusion, our study suggests that during the progression of diabetes, STK17A and CCT5 may contribute to the advancement of the disease by regulating oxidative stress, programmed cell death pathways, and critical signaling pathways such as p53 and MAPK, thereby promoting the death of islet cells. This provides substantial evidence in support of further disease prevention and treatment strategies.

A Review of Medicinal Plants of the Himalayas with Anti-Proliferative Activity for the Treatment of Various Cancers

Simple Summary

Drugs are used to treat cancer. Most drugs available in the market are chemosynthetic drugs and have side effects on the patient during and after the treatment, in addition to cancer itself. For instance, hair loss, loss of skin color and texture, loss of energy, nausea, infertility, etc. To overcome these side effects, naturally obtained drugs from medicinal plants are preferred. Our review paper aims to encourage the study of anticancer medicinal plants by giving detailed information on thirty-three medicinal plants and parts that constitute the phytochemicals responsible for the treatment of cancer. The development of plant-based drugs could be a game changer in treating cancer as well as boosting the immune system.

Abstract

Cancer is a serious and significantly progressive disease. Next to cardiovascular disease, cancer has become the most common cause of mortality in the entire world. Several factors, such as environmental factors, habitual activities, genetic factors, etc., are responsible for cancer. Many cancer patients seek alternative and/or complementary treatments because of the high death rate linked with cancer and the adverse side effects of chemotherapy and radiation therapy. Traditional medicine has a long history that begins with the hunt for botanicals to heal various diseases, including cancer. In the traditional medicinal system, several plants used to treat diseases have many bioactive compounds with curative capability, thereby also helping in disease prevention. Plants also significantly contributed to the modern pharmaceutical industry throughout the world. In the present review, we have listed 33 medicinal plants with active and significant anticancer activity, as well as their anticancer compounds. This article will provide a basic set of information for researchers interested in developing a safe and nontoxic active medicinal plant-based treatment for cancer. The research will give a scientific foundation for the traditional usage of these medicinal herbs to treat cancer.

Molecular and Clinical Characterization of CCT2 Expression and Prognosis via Large-Scale Transcriptome Profile of Breast Cancer

Molecular chaperones play important roles in regulating various cellular processes and malignant transformation. Expression of some subunits of molecular chaperone CCT/TRiC complex have been reported to be correlated with cancer development and patient survival. However, little is known about the expression and prognostic significance of Chaperonin Containing TCP1 Subunit 2 (CCT2). CCT2 is a gene encoding a molecular chaperone that is a member of the chaperonin containing TCP1 complex (CCT), also known as the TCP1 ring complex (TRiC). Through the Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases, we systematically reviewed a total of 2,994 cases with transcriptome data and analyzed the functional annotation of CCT2 by Gene ontology and KEGG analysis. Univariate and multivariate survival analysis were performed to investigate the prognostic value of CCT2 in breast cancer. We found CCT2 was significantly upregulated in various tumors. In breast cancer, CCT2 expression was significantly upregulated in HER2-positive (HER2+) group, and more malignant group. In addition, we investigated correlations between CCT2 and other CCT members. Interestingly, almost all CCTs expression were positively correlated with each other, but not CCT6B. Survival analysis suggested that CCT2 overexpression was independently associated with worse prognosis of patients with breast cancer, especially in luminal A subtype. In summary, our results revealed that CCT2 might be involved in regulating cell cycle pathway, and independently predicted worse prognosis in breast cancer patients. These findings may expand understanding of potential anti-CCT2 treatments. To our knowledge, this is the largest and most comprehensive study characterizing the expression pattern of CCT2 together with its prognostic values in breast cancer.

PUMA: PANDA Using MicroRNA Associations

Motivation

Conventional methods to analyze genomic data do not make use of the interplay between multiple factors, such as between microRNAs (miRNAs) and the messenger RNA (mRNA) transcripts they regulate, and thereby often fail to identify the cellular processes that are unique to specific tissues. We developed PUMA (PANDA Using MicroRNA Associations), a computational tool that uses message passing to integrate a prior network of miRNA target predictions with target gene co-expression information to model genome-wide gene regulation by miRNAs. We applied PUMA to 38 tissues from the Genotype-Tissue Expression project, integrating RNA-Seq data with two different miRNA target predictions priors, built on predictions from TargetScan and miRanda, respectively. We found that while target predictions obtained from these two different resources are considerably different, PUMA captures similar tissue-specific miRNA–target regulatory interactions in the different network models. Furthermore, the tissue-specific functions of miRNAs we identified based on regulatory profiles (available at: https://kuijjer.shinyapps.io/puma_gtex/) are highly similar between networks modeled on the two target prediction resources. This indicates that PUMA consistently captures important tissue-specific miRNA regulatory processes. In addition, using PUMA we identified miRNAs regulating important tissue-specific processes that, when mutated, may result in disease development in the same tissue.

Availability and implementation

PUMA is available in C++, MATLAB and Python on GitHub (https://github.com/kuijjerlab and https://netzoo.github.io/).

Supplementary information

Supplementary data are available at Bioinformatics online.

Construction and validation of a novel prognostic signature of microRNAs in lung adenocarcinoma

MicroRNA (miRNA, miR) has been reported to be highly implicated in a wide range of biological processes in lung cancer (LC), and identification of differentially expressed miRNAs between normal and LC samples has been widely used in the discovery of prognostic factors for overall survival (OS) and response to therapy. The present study was designed to develop and evaluate a miRNA-based signature with prognostic value for the OS of lung adenocarcinoma (LUAD), a common histologic subtype of LC. In brief, the miRNA expression profiles and clinicopathological factors of 499 LUAD patients were collected from The Cancer Genome Atlas (TCGA) database. Kaplan-Meier (K-M) survival analysis showed significant correlations between differentially expressed miRNAs and LUAD survival outcomes. Afterward, 1,000 resample LUAD training matrices based on the training set was applied to identify the potential prognostic miRNAs. The least absolute shrinkage and selection operator (LASSO) cox regression analysis was used to constructed a six-miRNA based prognostic signature for LUAD patients. Samples with different risk scores displayed distinct OS in K-M analysis, indicating considerable predictive accuracy of this signature in both training and validation sets. Furthermore, time-dependent receiver operating characteristic (ROC) analysis demonstrated the nomogram achieved higher predictive accuracy than any other clinical variables after incorporating the clinical information (age, sex, stage, and recurrence). In the stratification analysis, the prognostic value of this classifier in LUAD patients was validated to be independent of other clinicopathological variables, such as age, gender, tumor recurrence, and early stage. Gene set annotation analyses were also conducted through the Hallmark gene set and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, indicating target genes of the six miRNAs were positively related to various molecular pathways of cancer, such as hallmark UV response, Wnt signaling pathway and mTOR signaling pathway. In addition, fresh cancer tissue samples and matched adjacent tissue samples from 12 LUAD patients were collected to verify the expression of miR-582's target genes in the model, further revealing the potential relationship between SOX9, RASA1, CEP55, MAP4K4 and LUAD tumorigenesis, and validating the predictive value of the model. Taken together, the present study identified a robust signature for the OS prediction of LUAD patients, which could potentially aid in the individualized selection of therapeutic approaches for LUAD patients.

Functional genomics based on germline genome-wide association studies of endocrine therapy for breast cancer

Breast cancer is the most common invasive cancer in women worldwide. Functional follow-up of breast cancer genome-wide association studies has led to the discovery of genes that regulate endocrine therapy response in a SNP- and drug-dependent manner. Here, we will present four examples in which functional genomic studies from breast cancer clinical trials led to novel pharmacogenomic insights and molecular mechanisms of selective estrogen receptor modulators and aromatase inhibitors. The approach utilized for studying genetic variability described in this review offers substantial potential for meaningful discoveries that move the field toward precision medicine for patients.

Estimation and inference for the indirect effect in high-dimensional linear mediation models

Mediation analysis is difficult when the number of potential mediators is larger than the sample size. In this paper we propose new inference procedures for the indirect effect in the presence of high-dimensional mediators for linear mediation models. We develop methods for both incomplete mediation, where a direct effect may exist, and complete mediation, where the direct effect is known to be absent. We prove consistency and asymptotic normality of our indirect effect estimators. Under complete mediation, where the indirect effect is equivalent to the total effect, we further prove that our approach gives a more powerful test compared to directly testing for the total effect. We confirm our theoretical results in simulations, as well as in an integrative analysis of gene expression and genotype data from a pharmacogenomic study of drug response. We present a novel analysis of gene sets to understand the molecular mechanisms of drug response, and also identify a genome-wide significant noncoding genetic variant that cannot be detected using standard analysis methods.

PRDM15 Is Associated with Risk of Chronic Obstructive Pulmonary Disease in a Rural Population in Chile

BACKGROUND

Genome-wide association studies (GWAS) have accelerated our understanding of the genetic underpinnings of chronic obstructive pulmonary disease (COPD); however, GWAS populations have typically consisted of European descent, with ∼1% of Latin American ancestry.

OBJECTIVE

To overcome this limitation, we conducted a GWAS in a rural Chilean population with increased COPD risk to investigate genetic variation of COPD risk in this understudied minority population.

METHOD

We carried out a case-control study of 214 COPD patients (defined by the GOLD criteria) and 193 healthy controls in Talca, Chile. DNA was extracted from venous blood and genotyped on the Illumina Global Screening Array (n = 754,159 markers). After exclusion based on Hardy-Weinberg equilibrium (p ≤ 0.001), call rates (<95%), and minor allele frequencies (<0.5%) in controls, 455,564 markers were available for logistic regression.

RESULTS

PRDM15 rs1054761 C allele (p = 2.22 × 10-7) was associated with decreased COPD risk. Three PRDM15 SNPs located on chromosome 21 were significantly associated with COPD risk (p < 10-6). Two of these SNPs, rs1054761 and rs4075967, were located on a noncoding transcript variant region of the gene.

CONCLUSION

PRDM15 overexpression may play a role in the B-cell dysregulation in COPD pathogenesis. To the best of our knowledge, the association between PRDM15 and COPD risk was not previously found in GWAS studies in largely European populations, highlighting the importance of investigating novel variants associated with COPD risk among ethnically diverse populations.

Regulatory Network and Prognostic Effect Investigation of PIP4K2A in Leukemia and Solid Cancers

Germline variants of PIP4K2A impact susceptibility of acute lymphoblastic leukemia (ALL) through inducing its overexpression. Although limited reports suggested the oncogenic role of PIP4K2A in cancers, regulatory network and prognostic effect of this gene remains poorly understood in tumorigenesis and leukemogenesis. In this study, we conducted genome-wide gene expression association analyses in pediatric B-ALL cohorts to discover expression associated genes and pathways, which is followed by the bioinformatics analyses to investigate the prognostic role of PIP4K2A and its related genes in multiple cancer types. 214 candidates were identified to be significantly associated with PIP4K2A expression in ALL patients, with known cancer-related genes rankings the top (e.g., RAC2, RBL2, and TFDP1). These candidates do not only tend to be clustered in the same types of leukemia, but can also separate the patients into novel molecular subtypes. PIP4K2A is noticed to be frequently overexpressed in multiple other types of leukemia and solid cancers from cancer cohorts including TCGA, and associated with its candidates in subtype-specific and cancer-specific manners. Interestingly, the association status varied in tumors compared to their matched normal tissues. Moreover, PIP4K2A and its related candidates exhibit stage-independent prognostic effects in multiple cancers, mostly with its lower expression significantly associated with longer overall survival (p < 0.05). Our findings reveal the transcriptional regulatory network of PIP4K2A in leukemia, and suggest its potentially important role on molecular subtypes of multiple cancers and subsequent treatment outcomes.

MicroRNA-1468 promotes tumor progression by activating PPAR-γ-mediated AKT signaling in human hepatocellular carcinoma

Background

Accumulating evidence confirm that aberrant microRNAs (miRNAs) expression contributes to hepatocellular carcinoma (HCC) development and progression. Previous study reported that miR-1468 showed an up-regulated tendency and might be a potential prognostic biomarker in HCC samples derived from TCGA database. However, the role of miR-1468 and its underlying mechanisms involved in the growth and metastasis of HCC remain poorly investigated.

Methods

CCK-8, EdU, colony formation and flow cytometry were used to determine proliferation, cell cycle progression and apoptosis of HCC cells in vitro. The subcutaneous tumor model in nude mice was established to detect tumor growth of HCC in vivo. The direct binding of miR-1468 to 3’UTR of Cbp/p300 interacting transactivator with Glu/Asp rich carboxy-terminal domain 2 (CITED2) and Up-frameshift protein 1 (UPF1) was confirmed by luciferase reporter assay.

Results

Here, we demonstrated that miR-1468 expression was up-regulated in HCC tissues and cell lines. Clinical analysis revealed that increased miR-1468 level was significantly correlated with malignant prognostic features and shorter survival. Gain- and loss-of-function experiments indicated that miR-1468 promoted cell proliferation, colony formation, cell cycle progression and induced apoptosis of HCC cells in vitro and in vivo. Moreover, CITED2 and UPF1 were identified as direct downstream targets of miR-1468 in HCC cells, and mediated the functional effects of miR-1468 in HCC, resulting in peroxisome proliferator-activated receptor-γ (PPAR-γ)/AKT signaling activation. In clinical samples of HCC, miR-1468 inversely correlated with the levels of CITED2 and UPF1, which were confirmed to be down-regulated in HCC. Restoration of CITED2 or UPF1 expression at least partially abolished the biological effects of miR-1468 on HCC cells. Moreover, alteration of PPAR-γ or AKT phosphorylation could reverse the function of miR-1468 in HCC.

Conclusions

Taken together, this research supports the first evidence that miR-1468 plays an oncogenic role in HCC via activating PPAR-γ/AKT pathway by targeting CITED2 and UPF1, and represents a promising therapeutic strategy for HCC patients.

Electronic supplementary material

The online version of this article (10.1186/s13046-018-0717-3) contains supplementary material, which is available to authorized users.

Large-scale prediction of microRNA-disease associations by combinatorial prioritization algorithm

Identification of the associations between microRNA molecules and human diseases from large-scale heterogeneous biological data is an important step for understanding the pathogenesis of diseases in microRNA level. However, experimental verification of microRNA-disease associations is expensive and time-consuming. To overcome the drawbacks of conventional experimental methods, we presented a combinatorial prioritization algorithm to predict the microRNA-disease associations. Importantly, our method can be used to predict microRNAs (diseases) associated with the diseases (microRNAs) without the known associated microRNAs (diseases). The predictive performance of our proposed approach was evaluated and verified by the internal cross-validations and external independent validations based on standard association datasets. The results demonstrate that our proposed method achieves the impressive performance for predicting the microRNA-disease association with the Area Under receiver operation characteristic Curve (AUC), 86.93%, which is indeed outperform the previous prediction methods. Particularly, we observed that the ensemble-based method by integrating the predictions of multiple algorithms can give more reliable and robust prediction than the single algorithm, with the AUC score improved to 92.26%. We applied our combinatorial prioritization algorithm to lung neoplasms and breast neoplasms, and revealed their top 30 microRNA candidates, which are in consistent with the published literatures and databases.

Genetic Variants Contributing to Colistin Cytotoxicity: Identification of TGIF1 and HOXD10 Using a Population Genomics Approach

Colistin sulfate (polymixin E) is an antibiotic prescribed with increasing frequency for severe Gram-negative bacterial infections. As nephrotoxicity is a common side effect, the discovery of pharmacogenomic markers associated with toxicity would benefit the utility of this drug. Our objective was to identify genetic markers of colistin cytotoxicity that were also associated with expression of key proteins using an unbiased, whole genome approach and further evaluate the functional significance in renal cell lines. To this end, we employed International HapMap lymphoblastoid cell lines (LCLs) of Yoruban ancestry with known genetic information to perform a genome-wide association study (GWAS) with cellular sensitivity to colistin. Further association studies revealed that single nucleotide polymorphisms (SNPs) associated with gene expression and protein expression were significantly enriched in SNPs associated with cytotoxicity (p ≤ 0.001 for gene and p = 0.015 for protein expression). The most highly associated SNP, chr18:3417240 (p = 6.49 × 10⁻⁸), was nominally a cis-expression quantitative trait locus (eQTL) of the gene TGIF1 (transforming growth factor β (TGFβ)-induced factor-1; p = 0.021) and was associated with expression of the protein HOXD10 (homeobox protein D10; p = 7.17 × 10⁻⁵). To demonstrate functional relevance in a murine colistin nephrotoxicity model, HOXD10 immunohistochemistry revealed upregulated protein expression independent of mRNA expression in response to colistin administration. Knockdown of TGIF1 resulted in decreased protein expression of HOXD10 and increased resistance to colistin cytotoxicity. Furthermore, knockdown of HOXD10 in renal cells also resulted in increased resistance to colistin cytotoxicity, supporting the physiological relevance of the initial genomic associations.

Integrative microRNA and gene profiling data analysis reveals novel biomarkers and mechanisms for lung cancer

BACKGROUND

Studies on the accuracy of microRNAs (miRNAs) in diagnosing non-small cell lung cancer (NSCLC) have still controversial. Therefore, we conduct to systematically identify miRNAs related to NSCLC, and their target genes expression changes using microarray data sets.

METHODS

We screened out five miRNAs and six genes microarray data sets that contained miRNAs and genes expression in NSCLC from Gene Expression Omnibus.

RESULTS

Our analysis results indicated that fourteen miRNAs were significantly dysregulated in NSCLC. Five of them were up-regulated (miR-9, miR-708, miR-296-3p, miR-892b, miR-140-5P) while nine were down-regulated (miR-584, miR-218, miR-30b, miR-522, miR486-5P, miR-34c-3p, miR-34b, miR-516b, miR-592). The integrating diagnosis sensitivity (SE) and specificity (SP) were 82.6% and 89.9%, respectively. We also found that 4 target genes (p < 0.05, fold change > 2.0) were significant correlation with the 14 discovered miRNAs, and the classifiers we built from one training set predicted the validation set with higher accuracy (SE = 0.987, SP = 0.824).

CONCLUSIONS

Our results demonstrate that integrating miRNAs and target genes are valuable for identifying promising biomarkers, and provided a new insight on underlying mechanism of NSCLC. Further, our well-designed validation studies surely warrant the investigation of the role of target genes related to these 14 miRNAs in the prediction and development of NSCLC.

Computational discovery of transcription factors associated with drug response

This study integrates gene expression, genotype and drug response data in lymphoblastoid cell lines with transcription factor (TF)-binding sites from ENCODE (Encyclopedia of Genomic Elements) in a novel methodology that elucidates regulatory contexts associated with cytotoxicity. The method, GENMi (Gene Expression iN the Middle), postulates that single-nucleotide polymorphisms within TF-binding sites putatively modulate its regulatory activity, and the resulting variation in gene expression leads to variation in drug response. Analysis of 161 TFs and 24 treatments revealed 334 significantly associated TF-treatment pairs. Investigation of 20 selected pairs yielded literature support for 13 of these associations, often from studies where perturbation of the TF expression changes drug response. Experimental validation of significant GENMi associations in taxanes and anthracyclines across two triple-negative breast cancer cell lines corroborates our findings. The method is shown to be more sensitive than an alternative, genome-wide association study-based approach that does not use gene expression. These results demonstrate the utility of GENMi in identifying TFs that influence drug response and provide a number of candidates for further testing.

Pharmacogenetic Discovery in CALGB (Alliance) 90401 and Mechanistic Validation of a VAC14 Polymorphism that Increases Risk of Docetaxel-Induced Neuropathy

PURPOSE

Discovery of SNPs that predict a patient's risk of docetaxel-induced neuropathy would enable treatment individualization to maximize efficacy and avoid unnecessary toxicity. The objectives of this analysis were to discover SNPs associated with docetaxel-induced neuropathy and mechanistically validate these associations in preclinical models of drug-induced neuropathy.

EXPERIMENTAL DESIGN

A genome-wide association study was conducted in metastatic castrate-resistant prostate cancer patients treated with docetaxel, prednisone and randomized to bevacizumab or placebo on CALGB 90401. SNPs were genotyped on the Illumina HumanHap610-Quad platform followed by rigorous quality control. The inference was conducted on the cumulative dose at occurrence of grade 3+ sensory neuropathy using a cause-specific hazard model that accounted for early treatment discontinuation. Genes with SNPs significantly associated with neuropathy were knocked down in cellular and mouse models of drug-induced neuropathy.

RESULTS

A total of 498,081 SNPs were analyzed in 623 Caucasian patients, 50 (8%) of whom experienced grade 3+ neuropathy. The 1,000 SNPs most associated with neuropathy clustered in relevant pathways including neuropathic pain and axonal guidance. An SNP in VAC14 (rs875858) surpassed genome-wide significance (P = 2.12 × 10^-8, adjusted P = 5.88 × 10^-7). siRNA knockdown of VAC14 in stem cell-derived peripheral neuronal cells increased docetaxel sensitivity as measured by decreased neurite processes (P = 0.0015) and branches (P < 0.0001). Prior to docetaxel treatment, VAC14 heterozygous mice had greater nociceptive sensitivity than wild-type litter mate controls (P = 0.001).

CONCLUSIONS

VAC14 should be prioritized for further validation of its potential role as a predictor of docetaxel-induced neuropathy and biomarker for treatment individualization. Clin Cancer Res; 22(19); 4890-900. ©2016 AACR.

Genome-Wide Study of Response to Platinum, Taxane, and Combination Therapy in Ovarian Cancer: In vitro Phenotypes, Inherited Variation, and Disease Recurrence

Background: The standard treatment for epithelial ovarian cancer (EOC) patients with advanced disease is carboplatin-paclitaxel combination therapy following initial debulking surgery, yet there is wide inter-patient variation in clinical response. We sought to identify pharmacogenomic markers related to carboplatin-paclitaxel therapy.

Methods: The lymphoblastoid cell lines, derived from 74 invasive EOC patients seen at the Mayo Clinic, were treated with increasing concentrations of carboplatin and/or paclitaxel and assessed for in vitro drug response using MTT viability and caspase3/7 apoptosis assays. Drug response phenotypes IC50 (effective dose at which 50% of cells are viable) and EC50 (dose resulting in 50% induction of caspase 3/7 activity) were estimated for each patient to paclitaxel and carboplatin (alone and in combination). For each of the six drug response phenotypes, a genome-wide association study was conducted.

Results: Statistical analysis found paclitaxel in vitro drug response phenotypes to be moderately associated with time to EOC recurrence (p = 0.008 IC50; p = 0.058 EC50). Although no pharmacogenomic associations were significant at p < 5 × 10⁻⁸, seven genomic loci were associated with drug response at p < 10⁻⁶, including at 4q21.21 for carboplatin, 4p16.1 and 5q23.2 for paclitaxel, and 3q24, 10q, 1q44, and 13q21 for combination therapy. Nearby genes of interest include FRAS1, MGC32805, SNCAIP, SLC9A9, TIAL1, ZNF731P, and PCDH20.

Conclusions: These results suggest the existence of genetic loci associated with response to platinum-taxane therapies. Further research is needed to understand the mechanism by which these loci may impact EOC clinical response to this commonly used regimen.

In vitro human cell line models to predict clinical response to anticancer drugs

In vitro human cell line models have been widely used for cancer pharmacogenomic studies to predict clinical response, to help generate pharmacogenomic hypothesis for further testing, and to help identify novel mechanisms associated with variation in drug response. Among cell line model systems, immortalized cell lines such as Epstein-Barr virus (EBV)-transformed lymphoblastoid cell lines (LCLs) have been used most often to test the effect of germline genetic variation on drug efficacy and toxicity. Another model, especially in cancer research, uses cancer cell lines such as the NCI-60 panel. These models have been used mainly to determine the effect of somatic alterations on response to anticancer therapy. Even though these cell line model systems are very useful for initial screening, results from integrated analyses of multiple omics data and drug response phenotypes using cell line model systems still need to be confirmed by functional validation and mechanistic studies, as well as validation studies using clinical samples. Future models might include the use of patient-specific inducible pluripotent stem cells and the incorporation of 3D culture which could further optimize in vitro cell line models to improve their predictive validity.

Evaluating the role of admixture in cancer therapy via in vitro drug response and multivariate genome-wide associations

AIM

We investigate the role of ethnicity and admixture in drug response across a broad group of chemotherapeutic drugs. Also, we generate hypotheses on the genetic variants driving differential drug response through multivariate genome-wide association studies.

METHODS

Immortalized lymphoblastoid cell lines from 589 individuals (Hispanic or non-Hispanic/Caucasian) were used to investigate dose-response for 28 chemotherapeutic compounds. Univariate and multivariate statistical models were used to elucidate associations between genetic variants and differential drug response as well as the role of ethnicity in drug potency and efficacy.

RESULTS & CONCLUSION

For many drugs, the variability in drug response appears to correlate with self-reported race and estimates of genetic ancestry. Additionally, multivariate genome-wide association analyses offered interesting hypotheses governing these differential responses.

Genetic risk of lung cancer associated with a single nucleotide polymorphism from EXO1: a meta analysis

BACKGROUND/AIM

Several reports have investigated the role of exonuclease 1 (EXO1) rs1047840 in lung cancer risk in different ethnic populations. Nevertheless, the results have been controversial. We aimed to assess the possible association between EXO1 rs1047840 and risk of lung cancer in a meta-analysis.

METHODS

Human hospital- or population-based studies released before December 16, 2013 were identified by systematic search of the PubMed and Embase databases. Data were extracted in duplicate from each study. An OR and 95% CI (odds ratio and 95% confidence interval) was calculated to evaluate the effects of EXO1 rs1047840 on lung carcinogenesis.

RESULTS

A total of 1,114 lung cancer patients and 1,166 well-matched controls were analyzed in this study. The fixed-effects meta-analysis revealed that carriage of a single A allele, compared to the carriage of single G allele, was associated with 1.18 times increased risk of lung cancer (A vs. G: OR =1.18; 95% CI: 1.03-1.35; PHeterogeneity, 0.121).

CONCLUSION

This first meta-analysis demonstrates that the A allele of EXO1 rs1047840 may confer modulating effects on the risk of lung cancer and could be used as a marker for early detection and primary prevention.

The SNP rs6500843 in 16p13.3 is associated with survival specifically among chemotherapy-treated breast cancer patients

We have utilized a two-stage study design to search for SNPs associated with the survival of breast cancer patients treated with adjuvant chemotherapy. Our initial GWS data set consisted of 805 Finnish breast cancer cases (360 treated with adjuvant chemotherapy). The top 39 SNPs from this stage were analyzed in three independent data sets: iCOGS (n=6720 chemotherapy-treated cases), SUCCESS-A (n=3596), and POSH (n=518). Two SNPs were successfully validated: rs6500843 (any chemotherapy; per-allele HR 1.16, 95% C.I. 1.08-1.26, p=0.0001, p(adjusted)=0.0091), and rs11155012 (anthracycline therapy; per-allele HR 1.21, 95% C.I. 1.08-1.35, p=0.0010, p(adjusted)=0.0270). The SNP rs6500843 was found to specifically interact with adjuvant chemotherapy, independently of standard prognostic markers (p(interaction)=0.0009), with the rs6500843-GG genotype corresponding to the highest hazard among chemotherapy-treated cases (HR 1.47, 95% C.I. 1.20-1.80). Upon trans-eQTL analysis of public microarray data, the rs6500843 locus was found to associate with the expression of a group of genes involved in cell cycle control, notably AURKA, the expression of which also exhibited differential prognostic value between chemotherapy-treated and untreated cases in our analysis of microarray data. Based on previously published information, we propose that the eQTL genes may be connected to the rs6500843 locus via a RBFOX1-FOXM1 -mediated regulatory pathway.

Pharmacokinetics, dynamics and toxicity of docetaxel: Why the Japanese dose differs from the Western dose

Docetaxel (Taxotere®) has been one of the most important chemotherapeutic drugs for cancer treatment since 1996. Although a large number of clinical studies have been conducted in various cancer fields, there is a discrepancy in the standard dose between Japan and Western countries. This article reviews the pharmacokinetic, pharmacodynamic and toxicological profiles of docetaxel, and explains why there exists an ethnic difference in dose, and further discusses which direction we should go forward to solve this problem. The original recommended dose was 100 mg/m² every 3 weeks in US and European populations, while a Japanese phase I study suggested the recommended dose as 60 mg/m² every 3 weeks. A prospective population pharmacokinetic analysis of docetaxel conducted in both the USA/Europe and Japan, indicated an absence of ethnic difference in the pharmacokinetics. Both analyses demonstrated that docetaxel clearance is related to α1-acid glycoprotein level, hepatic function, age and body surface area. The relationship was observed between increasing docetaxel dose and increased tumor response rates across the dose range of 60 to 100 mg/m². The area under the serum concentration time curve (AUC) of docetaxel at the first cycle was significantly related to time to progression. Hematological toxicities were well correlated with the AUC of docetaxel, and severe hematological toxicities were more frequently observed in Japanese patients treated with 60 mg/m², compared to the US/European patients treated with 75–100 mg/m² dose. The Japanese population seems more susceptible to the toxicity of docetaxel. A docetaxel dose of 75 mg/m² is now standard not only in global trials but also in recent Japanese trials. Although the optimal dose of docetaxel is still unclear, we need to continue to seek the appropriate dose of docetaxel depending on patient status and the goals of chemotherapy.

Genetic Variants of the MDM2 Gene Are Predictive of Treatment-Related Toxicities and Overall Survival in Patients With Advanced NSCLC

INTRODUCTION

Platinum agents can cause the formation of DNA adducts and induce apoptosis to eliminate tumor cells. The aim of the present study was to investigate the influence of genetic variants of MDM2 on chemotherapy-related toxicities and clinical outcomes in patients with advanced non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

We recruited 663 patients with advanced NSCLC who had been treated with first-line platinum-based chemotherapy. Five tagging single nucleotide polymorphisms (SNPs) in MDM2 were genotyped in these patients. The associations of these SNPs with clinical toxicities and outcomes were evaluated using logistic regression and Cox regression analyses.

RESULTS

Two SNPs (rs1470383 and rs1690924) showed significant associations with chemotherapy-related toxicities (ie, overall, hematologic, and gastrointestinal toxicity). Compared with the wild genotype AA carriers, patients with the GG genotype of rs1470383 had an increased risk of overall toxicity (odds ratio [OR], 3.28; 95% confidence interval [CI], 1.34-8.02; P = .009) and hematologic toxicity (OR, 4.10; 95% CI, 1.73-9.71; P = .001). Likewise, patients with the AG genotype of rs1690924 showed more sensitivity to gastrointestinal toxicity than did those with the wild-type homozygote GG (OR, 2.32; 95% CI, 1.30-4.14; P = .004). Stratified survival analysis revealed significant associations between rs1470383 genotypes and overall survival in patients without overall or hematologic toxicity (P = .007 and P = .0009, respectively).

CONCLUSION

The results of our study suggest that SNPs in MDM2 might be used to predict the toxicities of platinum-based chemotherapy and overall survival in patients with advanced NSCLC. Additional validations of the association are warranted.

Genome-wide association studies in Africans and African Americans: expanding the framework of the genomics of human traits and disease

Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.

Protein quantitative trait loci identify novel candidates modulating cellular response to chemotherapy

Annotating and interpreting the results of genome-wide association studies (GWAS) remains challenging. Assigning function to genetic variants as expression quantitative trait loci is an expanding and useful approach, but focuses exclusively on mRNA rather than protein levels. Many variants remain without annotation. To address this problem, we measured the steady state abundance of 441 human signaling and transcription factor proteins from 68 Yoruba HapMap lymphoblastoid cell lines to identify novel relationships between inter-individual protein levels, genetic variants, and sensitivity to chemotherapeutic agents. Proteins were measured using micro-western and reverse phase protein arrays from three independent cell line thaws to permit mixed effect modeling of protein biological replicates. We observed enrichment of protein quantitative trait loci (pQTLs) for cellular sensitivity to two commonly used chemotherapeutics: cisplatin and paclitaxel. We functionally validated the target protein of a genome-wide significant trans-pQTL for its relevance in paclitaxel-induced apoptosis. GWAS overlap results of drug-induced apoptosis and cytotoxicity for paclitaxel and cisplatin revealed unique SNPs associated with the pharmacologic traits (at p<0.001). Interestingly, GWAS SNPs from various regions of the genome implicated the same target protein (p<0.0001) that correlated with drug induced cytotoxicity or apoptosis (p≤0.05). Two genes were functionally validated for association with drug response using siRNA: SMC1A with cisplatin response and ZNF569 with paclitaxel response. This work allows pharmacogenomic discovery to progress from the transcriptome to the proteome and offers potential for identification of new therapeutic targets. This approach, linking targeted proteomic data to variation in pharmacologic response, can be generalized to other studies evaluating genotype-phenotype relationships and provide insight into chemotherapeutic mechanisms.

The central dogma of biology explains that DNA is transcribed to mRNA that is further translated into protein. Many genome-wide studies have implicated genetic variation that influences gene expression and that ultimately affect downstream complex traits including response to drugs. However, because of technical limitations, few studies have evaluated the contribution of genetic variation on protein expression and ensuing effects on downstream phenotypes. To overcome this challenge, we used a novel technology to simultaneously measure the baseline expression of 441 proteins in lymphoblastoid cell lines and compared them with publicly available genetic data. To further illustrate the utility of this approach, we compared protein-level measurements with chemotherapeutic induced apoptosis and cell-growth inhibition data. This study demonstrates the importance of using protein information to understand the functional consequences of genetic variants identified in genome-wide association studies. This protein data set will also have broad utility for understanding the relationship between other genome-wide studies of complex traits.

DNA repair pathways and their therapeutic potential in lung cancer

SUMMARY: 

Lung cancer is the leading cause of cancer-related mortality. According to WHO, 1.37 million deaths occur globally each year as a result of this disease. More than 70% of these cases are associated with prior tobacco consumption and/or cigarette smoking, suggesting a direct causal relationship. The development and progression of lung cancer and other malignancies involves the loss of genetic stability, resulting in acquisition of cumulative genetic changes; this affords the cell increased malignant potential. As such, an understanding of the mechanisms through which these events may occur will potentially allow for development of new anticancer therapies. This review will address the association between lung cancer and genetic instability, with a central focus on genetic mutations in the DNA damage repair pathways. In addition, we will discuss the potential clinical exploitation of these pathways, both in terms of biomarker staging, as well as through direct therapeutic targeting.

Effects of a functional variant c.353T>C in snai1 on risk of two contextual diseases. Chronic obstructive pulmonary disease and lung cancer

RATIONALE

Epithelial-mesenchymal transition (EMT) plays a key role in the development of chronic obstructive pulmonary disease (COPD) and lung cancer.

OBJECTIVES

There are five major EMT regulatory genes (Snai1, Slug, Zeb1, Zeb2, and Twist1) involved in EMT. We hypothesized that germline variants in these genes may influence the development of both diseases.

METHODS

Seven genetic variants were genotyped in two two-stage case-control studies with 2,072 lung cancer cases and 2,077 control subjects, and 1,791 patients with COPD and 1,940 control subjects to show their associations with development of both diseases.

MEASUREMENTS AND MAIN RESULTS

An exon variant c.353T>C(p.Val118Ala) of Snai1 harbored decreased risks of lung cancer (CT/CC vs. TT: odds ratio [OR], 0.76; 95% confidence interval [CI], 0.65-0.90) and COPD (CC vs. CT vs. TT: OR, 0.75; 95% CI, 0.63-0.89), and c.353T>C affected lung cancer risk indirectly through COPD (COPD accounted for 6.78% of effect that the variant had on lung cancer). Moreover, c.353T>C was correlated with lung cancer stages in smoking patients (P = 0.013), and those with the c.353C genotypes were less likely to have metastasis at diagnosis than those with the c.353TT genotype (OR, 0.60; 95% CI, 0.41-0.88). The c.353C allele encoding p.118Ala attenuated Snai1's ability to up-regulate mesenchymal biomarkers (i.e., fibronectin and vimentin) expression, and to promote EMT-like changes, including morphologic changes, cell migration, and invasion. However, these effects were not observed for the other variants.

CONCLUSIONS

The functional germline variant c.353T>C (p.Val118Ala) of Snai1 confers consistently decreased risks of lung cancer and COPD, and this variant affects lung cancer risk through a mediation effect of COPD.

Germline pharmacogenetics of paclitaxel for cancer treatment

Paclitaxel is a highly effective chemotherapeutic agent used in a variety of solid tumors. Some paclitaxel-treated patients experience the intended therapeutic response with manageable side effects, while others have minimal response and/or severe toxicity. This variability in treatment outcome is partially determined by variability in drug exposure (pharmacokinetics) and by patient and tumor sensitivity (pharmacodynamics). Both pharmacokinetics and pharmacodynamics are dictated in part by common variants in the germline genome, known as SNPs. This article reviews the published literature on paclitaxel pharmacogenetics in cancer, focusing primarily on polymorphisms in genes relevant to paclitaxel pharmacokinetics and discusses preliminary work on pharmacodynamic genes and genome-wide association studies.

Implications of genome-wide association studies in cancer therapeutics

Genome wide association studies (GWAS) provide an agnostic approach to identifying potential genetic variants associated with disease susceptibility, prognosis of survival and/or predictive of drug response. Although these techniques are costly and interpretation of study results is challenging, they do allow for a more unbiased interrogation of the entire genome, resulting in the discovery of novel genes and understanding of novel biological associations. This review will focus on the implications of GWAS in cancer therapy, in particular germ-line mutations, including findings from major GWAS which have identified predictive genetic loci for clinical outcome and/or toxicity. Lessons and challenges in cancer GWAS are also discussed, including the need for functional analysis and replication, as well as future perspectives for biological and clinical utility. Given the large heterogeneity in response to cancer therapeutics, novel methods of identifying mechanisms and biology of variable drug response and ultimately treatment individualization will be indispensable.

Genetic and epigenetic variants contributing to clofarabine cytotoxicity

2-chloro-2-fluoro-deoxy-9-D-arabinofuranosyladenine (Clofarabine), a purine nucleoside analog, is used in the treatment of hematologic malignancies and as induction therapy for stem cell transplantation. The discovery of pharmacogenomic markers associated with chemotherapeutic efficacy and toxicity would greatly benefit the utility of this drug. Our objective was to identify genetic and epigenetic variants associated with clofarabine toxicity using an unbiased, whole genome approach. To this end, we employed International HapMap lymphoblastoid cell lines (190 LCLs) of European (CEU) or African (YRI) ancestry with known genetic information to evaluate cellular sensitivity to clofarabine. We measured modified cytosine levels to ascertain the contribution of genetic and epigenetic factors influencing clofarabine-mediated cytotoxicity. Association studies revealed 182 single nucleotide polymorphisms (SNPs) and 143 modified cytosines associated with cytotoxicity in both populations at the threshold P ≤ 0.0001. Correlation between cytotoxicity and baseline gene expression revealed 234 genes at P ≤ 3.98 × 10(-6). Six genes were implicated as: (i) their expression was directly correlated to cytotoxicity, (ii) they had a targeting SNP associated with cytotoxicity, and (iii) they had local modified cytosines associated with gene expression and cytotoxicity. We identified a set of three SNPs and three CpG sites targeting these six genes explaining 43.1% of the observed variation in phenotype. siRNA knockdown of the top three genes (SETBP1, BAG3, KLHL6) in LCLs revealed altered susceptibility to clofarabine, confirming relevance. As clofarabine's toxicity profile includes acute kidney injury, we examined the effect of siRNA knockdown in HEK293 cells. siSETBP1 led to a significant change in HEK293 cell susceptibility to clofarabine.

MicroRNA-related genetic variants associated with clinical outcomes in early-stage non-small cell lung cancer patients

Given the density of single-nucleotide polymorphisms (SNP) in the human genome and the sensitivity of single-nucleotide changes in microRNA (miRNA) functionality and processing, we asked whether polymorphisms within miRNA processing pathways and binding sites may influence non-small cell lung cancer (NSCLC) patients' prognosis. We genotyped 240 miRNA-related SNPs in 535 patients with stage I and II NSCLCs to determine associations with overall recurrence and survival as well as effect in specific treatment subgroups. After correcting for multiple comparisons, the G allele of FZD4:rs713065 displayed a significant association with decreased risk of death in surgery-only patients [HR, 0.46; 95% confidence interval (CI), 0.32-0.65]. DROSHA:rs6886834 variant A allele (HR, 6.38; 95% CI, 2.49-16.31) remained significant for increased risk of recurrence in the overall and surgery-only populations, respectively. FAS:rs2234978 G allele remained significantly associated with survival in all patients (HR, 0.59; 95% CI, 0.44-0.77), whereas borderline significant in subgroups (surgery-only: HR, 0.59; 95% CI, 0.42-0.84; surgery plus chemo: HR, 0.19; 95% CI, 0.07-0.46). Luciferase assays showed that the FAS SNP created a miR-651 functional binding site. Survival tree analysis was conducted to classify patients into distinct risk subgroups based on their risk genotype combinations. These results indicate that miRNA-related polymorphisms may be associated with NSCLC patients' clinical outcomes through altered miRNA regulation of target genes.