Chemotherapeutic-induced apoptosis: a phenotype for pharmacogenomics studies

Usnic acid induced changes in biomolecules and their association with apoptosis in squamous carcinoma (A-431) cells: A flow cytometry, FTIR and DLS spectroscopic study

Many natural products induce apoptotic cell death in cancer cells, though studies on their interactions with macromolecules are limited. For the first time, this study demonstrated the cytotoxic potential of usnic acid (UA) against squamous carcinoma (A-431) cells and the associated changes in cell surface proteins, lipids and DNA by attenuated total reflection- fourier transform infrared spectroscopy (ATR-FTIR) and dynamic light scattering (DLS) spectroscopic studies. The IC₅₀ for UA was 98.9 µM after treatment of A-431 cells for 48 h, while the IC₅₀ reduced to 39.2 µM after 72 h of incubation time. UA induced oxidative stress in treated cells as confirmed by DCFHDA flow cytometry assay, depletion in reduced glutathione and increase in lipid peroxidation. The oxidative stress resulted in conformation change in amide I, amide II protein bands and DNA as observed by ATR-FTIR in UA treated A-431 cells. Shift in secondary structures of proteins from α helix to β sheets and structural changes in DNA was observed in UA treated A-431 cells. An increase in the band intensity of phospholipids, increased distribution of lipid and change in membrane potential was noted in UA treated cells, which was confirmed by externalization of phosphatidylserine to the outer membrane by annexin V-FITC/PI assay. Increase in mitochondrial membrane potential, cell cycle arrest at G0/G1 phase by flow cytometry and activation of caspase-3/7 dependent proteins confirmed the UA induced apoptosis in treated A-431 cells. FTIR and DLS spectroscopy confirmed the changes in biomolecules after UA treatment, which were associated with apoptosis, as observed by flow cytometry.

Integration of genetic and functional genomics data to uncover chemotherapeutic induced cytotoxicity

Identifying genetic variants associated with chemotherapeutic induced toxicity is an important step towards personalized treatment of cancer patients. However, annotating and interpreting the associated genetic variants remains challenging because each associated variant is a surrogate for many other variants in the same region. The issue is further complicated when investigating patterns of associated variants with multiple drugs. In this study, we used biological knowledge to annotate and compare genetic variants associated with cellular sensitivity to mechanistically distinct chemotherapeutic drugs, including platinating agents (cisplatin, carboplatin), capecitabine, cytarabine, and paclitaxel. The most significantly associated SNPs from genome wide association studies of cellular sensitivity to each drug in lymphoblastoid cell lines derived from populations of European (CEU) and African (YRI) descent were analyzed for their enrichment in biological pathways and processes. We annotated genetic variants using higher-level biological annotations in efforts to group variants into more interpretable biological modules. Using the higher-level annotations, we observed distinct biological modules associated with cell line populations as well as classes of chemotherapeutic drugs. We also integrated genetic variants and gene expression variables to build predictive models for chemotherapeutic drug cytotoxicity and prioritized the network models based on the enrichment of DNA regulatory data. Several biological annotations, often encompassing different SNPs, were replicated in independent datasets. By using biological knowledge and DNA regulatory information, we propose a novel approach for jointly analyzing genetic variants associated with multiple chemotherapeutic drugs.

Open source machine-learning algorithms for the prediction of optimal cancer drug therapies

Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM) algorithm combined with a standard recursive feature elimination (RFE) approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60). The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be “drivers” of cancer onset/progression. Application of our models to publically available ovarian cancer (OC) patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm “open source”, we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.

CXCL12 Mediates Aberrant Costimulation of B Lymphocytes in Warts, Hypogammaglobulinemia, Infections, Myelokathexis Immunodeficiency

The Warts, Hypogammaglobulinemia, Infections, Myelokathexis (WHIM) syndrome is an immunodeficiency caused by mutations in chemokine receptor CXCR4. WHIM patient adaptive immunity defects remain largely unexplained. We have previously shown that WHIM-mutant T cells form unstable immunological synapses, affecting T cell activation. Here, we show that, in WHIM patients and WHIM CXCR4 knock-in mice, B cells are more apoptosis prone. Intriguingly, WHIM-mutant B cells were also characterized by spontaneous activation. Searching for a mechanistic explanation for these observations, we uncovered a novel costimulatory effect of CXCL12, the CXCR4 ligand, on WHIM-mutant but not wild-type B cells. The WHIM CXCR4-mediated costimulation led to increased B-cell activation, possibly involving mTOR, albeit without concurrently promoting survival. A reduction in antigenic load during immunization in the mouse was able to circumvent the adaptive immunity defects. These results suggest that WHIM-mutant CXCR4 may lead to spontaneous aberrant B-cell activation, via CXCL12-mediated costimulation, impairing B-cell survival and thus possibly contributing to the WHIM syndrome defects in adaptive immunity.

Genetic variation is the major determinant of individual differences in leukocyte endothelial adhesion

Objective

To determine the genetic contribution to leukocyte endothelial adhesion.

Methods

Leukocyte endothelial adhesion was assessed through a novel cell-based assay using human lymphoblastoid cell lines. A high-throughput screening method was developed to evaluate the inter-individual variability in leukocyte endothelial adhesion using lymphoblastoid cell lines derived from different donors. To assess heritability, ninety-two lymphoblastoid cell lines derived from twenty-three monozygotic twin pairs and twenty-three sibling pairs were compared. These lymphoblastoid cell lines were plated with the endothelial cell line EA.hy926 and labeled with Calcein AM dye. Fluorescence was assessed to determine endothelial cell adhesion to each lymphoblastoid cell line. Intra-pair similarity was determined for monozygotic twins and siblings using Pearson pairwise correlation coefficients.

Results

A leukocyte endothelial adhesion assay for lymphoblastoid cell lines was developed and optimized (CV = 8.68, Z′-factor = 0.67, SNR = 18.41). A higher adhesion correlation was found between the twins than that between the siblings. Intra-pair similarity for leukocyte endothelial adhesion in monozygotic twins was 0.60 compared to 0.25 in the siblings. The extent to which these differences are attributable to underlying genetic factors was quantified and the heritability of leukocyte endothelial adhesion was calculated to be 69.66% (p-value<0.0001).

Conclusions

There is a heritable component to leukocyte endothelial adhesion. Underlying genetic predisposition plays a significant role in inter-individual variability of leukocyte endothelial adhesion.

EPS8 inhibition increases cisplatin sensitivity in lung cancer cells

Cisplatin, a commonly used chemotherapeutic, is associated with ototoxicity, renal toxicity and neurotoxicity, thus identifying means to increase the therapeutic index of cisplatin may allow for improved outcomes. A SNP (rs4343077) within EPS8, discovered through a genome wide association study of cisplatin-induced cytotoxicity and apoptosis in lymphoblastoid cell lines (LCLs), provided impetus to further study this gene. The purpose of this work was to evaluate the role of EPS8 in cellular susceptibility to cisplatin in cancerous and non-cancerous cells. We used EPS8 RNA interference to determine the effect of decreased EPS8 expression on LCL and A549 lung cancer cell sensitivity to cisplatin. EPS8 knockdown in LCLs resulted in a 7.9% increase in cisplatin-induced survival (P = 1.98 × 10(-7)) and an 8.7% decrease in apoptosis (P = 0.004) compared to control. In contrast, reduced EPS8 expression in lung cancer cells resulted in a 20.6% decrease in cisplatin-induced survival (P = 5.08 × 10(-5)). We then investigated an EPS8 inhibitor, mithramycin A, as a potential agent to increase the therapeutic index of cisplatin. Mithramycin A decreased EPS8 expression in LCLs resulting in decreased cellular sensitivity to cisplatin as evidenced by lower caspase 3/7 activation following cisplatin treatment (42.7% ± 6.8% relative to control P = 0.0002). In 5 non-small-cell lung carcinoma (NSCLC) cell lines, mithramycin A also resulted in decreased EPS8 expression. Adding mithramycin to 4 NSCLC cell lines and a bladder cancer cell line, resulted in increased sensitivity to cisplatin that was significantly more pronounced in tumor cell lines than in LCL lines (p<0.0001). An EGFR mutant NSCLC cell line (H1975) showed no significant change in sensitivity to cisplatin with the addition of mithramycin treatment. Therefore, an inhibitor of EPS8, such as mithramycin A, could improve cisplatin treatment by increasing sensitivity of tumor relative to normal cells.

The AKT1/NF-kappaB/Notch1/PTEN axis has an important role in chemoresistance of gastric cancer cells

The inherent resistance of tumors to DNA damage often limits the efficacy of chemotherapy. The aim of this work is to explore the potential mechanism for development of chemoresistance in gastric cancer. Our data revealed that AKT1 mRNA and protein expression were induced by doxorubicin (a chemotherapeutic agent); the doxorubicin-induced AKT1 expression and activation increased the binding of NF-kappaB on Notch1 DNA promoter and then promoted the Notch1 transcription and expression; enhanced expression of Notch1 further upregulated PTEN expression through CBF-1 binding to PTEN DNA promoter; and inhibition of AKT1 expression and activity sensitized the gastric cancer cell to doxorubicin treatment in cultured gastric cancer cell lines and xenograft nude mice gastric cancer model. Furthermore, our data demonstrated that both Notch1 and PTEN were absent or minimally expressed in gastric cancer tissue but abundant in paired normal gastric mucosa, and the expression of Notch1 correlated with that of PTEN. Together, these novel results suggested that a novel AKT1/NF-kappaB/Notch1/PTEN axis has an important role in the development of chemoresistance in gastric cancer. Notch1 has an anti-cancer role in gastric cancer.

Comprehensive genetic analysis of cytarabine sensitivity in a cell-based model identifies polymorphisms associated with outcome in AML patients

A whole-genome approach was used to investigate the genetic determinants of cytarabine-induced cytotoxicity. We performed a meta-analysis of genome-wide association studies involving 523 lymphoblastoid cell lines (LCLs) from individuals of European, African, Asian, and African American ancestry. Several of the highest-ranked single-nucleotide polymorphisms (SNPs) were within the mutated in colorectal cancers (MCC) gene. MCC expression was induced by cytarabine treatment from 1.7- to 26.6-fold in LCLs. A total of 33 SNPs ranked at the top of the meta-analysis (P < 10(-5)) were successfully tested in a clinical trial of patients randomized to receive low-dose or high-dose cytarabine plus daunorubicin and etoposide; of these, 18 showed association (P < .05) with either cytarabine 50% inhibitory concentration in leukemia cells or clinical response parameters (minimal residual disease, overall survival (OS), and treatment-related mortality). This count (n = 18) was significantly greater than expected by chance (P = .016). For rs1203633, LCLs with AA genotype were more sensitive to cytarabine-induced cytotoxicity (P = 1.31 × 10(-6)) and AA (vs GA or GG) genotype was associated with poorer OS (P = .015), likely as a result of greater treatment-related mortality (P = .0037) in patients with acute myeloid leukemia (AML). This multicenter AML02 study trial was registered at www.clinicaltrials.gov as #NCT00136084.

Pharmacogenomics of chemotherapeutic susceptibility and toxicity

The goal of personalized medicine is to tailor a patient's treatment strategy on the basis of his or her unique genetic make-up. The field of oncology is beginning to incorporate many of the strategies of personalized medicine, especially within the realm of pharmacogenomics, which is the study of how inter-individual genetic variation determines drug response or toxicity. A main objective of pharmacogenomics is to facilitate physician decision-making regarding optimal drug selection, dose and treatment duration on a patient-by-patient basis. Recent advances in genome-wide genotyping and sequencing technologies have supported the discoveries of a number of pharmacogenetic markers that predict response to chemotherapy. However, effectively implementing these pharmacogenetic markers in the clinic remains a major challenge. This review focuses on the contribution of germline genetic variation to chemotherapeutic toxicity and response, and discusses the utility of genome-wide association studies and use of lymphoblastoid cell lines (LCLs) in pharmacogenomic studies. Furthermore, we highlight several recent examples of genetic variants associated with chemotherapeutic toxicity or response in both patient cohorts and LCLs, and discuss the challenges and future directions of pharmacogenomic discovery for cancer treatment.

Whole-genome studies identify solute carrier transporters in cellular susceptibility to paclitaxel

OBJECTIVE

The clinical use of paclitaxel is limited by variable responses and the potential for significant toxicity. To date, studies of associations between variants in candidate genes and paclitaxel effects have yielded conflicting results. We aimed to evaluate the relationships between global gene expression and paclitaxel sensitivity.

METHODS

We utilized well-genotyped lymphoblastoid cell lines derived from the International HapMap Project to evaluate the relationships between cellular susceptibility to paclitaxel and global gene expression. Cells were exposed to varying concentrations of paclitaxel to evaluate paclitaxel-induced cytotoxicity and apoptosis. Among the top genes, we identified solute carrier (SLC) genes associated with paclitaxel sensitivity and narrowed down the list to those that had single nucleotide polymorphisms associated with both the expression level of the SLC gene and also with paclitaxel sensitivity. We performed an independent validation in an independent set of cell lines and also conducted functional studies using RNA interference.

RESULTS

Of all genes associated with paclitaxel-induced cytotoxicity at P less than 0.05 (1713 genes), there was a significant enrichment in SLC genes (31 genes). A subset of SLC genes, namely SLC31A2, SLC43A1, SLC35A5, and SLC41A2, was associated with paclitaxel sensitivity and had regulating single nucleotide polymorphisms that were also associated with paclitaxel-induced cytotoxicity. Multivariate modeling demonstrated that those four SLC genes together explained 20% of the observed variability in paclitaxel susceptibility. Using RNA interference, we demonstrated increased paclitaxel susceptibility with knockdown of three SLC genes, SLC31A2, SLC35A5, and SLC41A2.

CONCLUSION

Our findings are novel and lend further support to the role of transporters, specifically solute carriers, in mediating cellular susceptibility to paclitaxel.

Molecular signatures in response to Isoliquiritigenin in lymphoblastoid cell lines

Isoliquiritigenin (ISL) has been known to induce cell cycle arrest and apoptosis of various cancer cells. However, genetic factors regulating ISL effects remain unclear. The aim of this study was to identify the molecular signatures involved in ISL-induced cell death of EBV-transformed lymphoblastoid cell lines (LCLs) using microarray analyses. For gene expression and microRNA (miRNA) microarray experiments, each of 12 LCL strains was independently treated with ISL or DMSO as a vehicle control for a day prior to total RNA extraction. ISL treatment inhibited cell proliferation of LCLs in a dose-dependent manner. Microarray analysis showed that ISL-treated LCLs represented gene expression changes in cell cycle and p53 signaling pathway, having a potential as regulators in LCL survival and sensitivity to ISL-induced cytotoxicity. In addition, 36 miRNAs including five miRNAs with unknown functions were differentially expressed in ISL-treated LCLs. The integrative analysis of miRNA and gene expression profiles revealed 12 putative mRNA-miRNA functional pairs. Among them, miR-1207-5p and miR-575 were negatively correlated with p53 pathway- and cell cycle-associated genes, respectively. In conclusion, our study suggests that miRNAs play an important role in ISL-induced cytotoxicity in LCLs by targeting signaling pathways including p53 pathway and cell cycle.

Relating human genetic variation to variation in drug responses

Although sequencing a single human genome was a monumental effort a decade ago, more than 1000 genomes have now been sequenced. The task ahead lies in transforming this information into personalized treatment strategies that are tailored to the unique genetics of each individual. One important aspect of personalized medicine is patient-to-patient variation in drug response. Pharmacogenomics addresses this issue by seeking to identify genetic contributors to human variation in drug efficacy and toxicity. Here, we present a summary of the current status of this field, which has evolved from studies of single candidate genes to comprehensive genome-wide analyses. Additionally, we discuss the major challenges in translating this knowledge into a systems-level understanding of drug physiology, with the ultimate goal of developing more effective personalized clinical treatment strategies.

Functional consequences of PRPF39 on distant genes and cisplatin sensitivity

Variation in gene expression has been found to be important in disease susceptibility and pharmacogenomics. Local and distant expression quantitative trait loci (eQTLs) have been identified via genome-wide association study (GWAS); yet the functional analysis of these variants has been challenging. The aim of this study was to unravel the functional consequence of a gene with a local SNP with evidence for local and distant regulatory roles in cellular sensitivity to cisplatin, one of the most widely used chemotherapeutic drugs. To this end, we measured cellular susceptibility to cisplatin in 176 HapMap lymphoblastoid cell lines derived from Yoruba individuals from Ibadan, Nigeria. The 276 cytotoxicity-associated SNPs at the suggestive threshold of P ≤ 0.0001 were significantly enriched for eQTLs. Of these SNPs, we found one intronic SNP, rs17115814, that had a significant relationship with the expression level of its host gene, PRPF39 (P= 0.0007), and a significant correlation with the expression of over 100 distant transcripts (P ≤ 0.0001). Successful knockdown of PRPF39 expression using siRNA resulted in a significant increase in cisplatin resistance. We then measured the expression of 61 downstream targets after PRPF39 knockdown and found 53 gene targets had significant (P ≤ 0.05) expression changes. Included in the list of genes that significantly changed after PRPF39 knockdown were MAP3K4 and TFPD2, two important signaling genes previously shown to be relevant in cisplatin response. Thus, modulation of a local target gene identified through a GWAS was followed by a downstream cascade of gene expression changes resulting in greater resistance to cisplatin.

Genetic variation that predicts platinum sensitivity reveals the role of miR-193b* in chemotherapeutic susceptibility

Platinum agents are the backbone of cancer chemotherapy. Recently, we identified and replicated the role of a single nucleotide polymorphism (SNP, rs1649942) in predicting platinum sensitivity both in vitro and in vivo. Using the CEU samples from the International HapMap Project, we found the same SNP to be a master regulator of multiple gene expression phenotypes, prompting us to investigate whether rs1649942-mediated regulation of miRNAs may in part contribute to variation in platinum sensitivity. To these ends, 60 unrelated HapMap CEU I/II samples were used for our discovery-phase study using high-throughput genome-wide miRNA and gene expression profiling. Examining the relationships among rs1649942, its gene expression targets, genome-wide miRNA expression, and cellular sensitivity to carboplatin and cisplatin, we identified 2 platinum-associated miRNAs (miR-193b* and miR-320) that inhibit the expression of 5 platinum-associated genes (CRIM1, IFIT2, OAS1, KCNMA1, and GRAMD1B). We further replicated the relationship between the expression of miR-193b*, CRIM1, IFIT2, KCNMA1, and GRAMD1B, and platinum sensitivity in a separate HapMap CEU III dataset. We then showed that overexpression of miR-193b* in a randomly selected HapMap cell line results in resistance to both carboplatin and cisplatin. This relationship was also found in 7 ovarian cancer cell lines from NCI60 dataset and confirmed in an OVCAR-3 that overexpression of miR-193b* leads to increased resistance to carboplatin. Our findings highlight a potential mechanism of action for a previously observed genotype-survival outcome association. Further examination of miR-193b* in platinum sensitivity in ovarian cancer is warranted.

Regulatory polymorphisms in β-tubulin IIa are associated with paclitaxel-induced peripheral neuropathy

PURPOSE

Peripheral neuropathy is the dose-limiting toxicity of paclitaxel, a chemotherapeutic drug widely used to treat several solid tumors such as breast, lung, and ovary. The cytotoxic effect of paclitaxel is mediated through β-tubulin binding in the cellular microtubules. In this study, we investigated the association between paclitaxel neurotoxicity risk and regulatory genetic variants in β-tubulin genes.

EXPERIMENTAL DESIGN

We measured variation in gene expression of three β-tubulin isotypes (I, IVb, and IIa) in lymphocytes from 100 healthy volunteers, sequenced the promoter region to identify polymorphisms putatively influencing gene expression and assessed the transcription rate of the identified variants using luciferase assays. To determine whether the identified regulatory polymorphisms were associated with paclitaxel neurotoxicity, we genotyped them in 214 patients treated with paclitaxel. In addition, paclitaxel-induced cytotoxicity in lymphoblastoid cell lines was compared with β-tubulin expression as measured by Affymetrix exon array.

RESULTS

We found a 63-fold variation in β-tubulin IIa gene (TUBB2A) mRNA content and three polymorphisms located at -101, -112, and -157 in TUBB2A promoter correlated with increased mRNA levels. The -101 and -112 variants, in total linkage disequilibrium, conferred TUBB2A increased transcription rate. Furthermore, these variants protected from paclitaxel-induced peripheral neuropathy [HR, 0.62; 95% confidence interval (CI), 0.42-0.93; P = 0.021, multivariable analysis]. In addition, an inverse correlation between TUBB2A and paclitaxel-induced apoptosis (P = 0.001) in lymphoblastoid cell lines further supported that higher TUBB2A gene expression conferred lower paclitaxel sensitivity.

CONCLUSIONS

This is the first study showing that paclitaxel neuropathy risk is influenced by polymorphisms regulating the expression of a β-tubulin gene.

Lymphoblastoid cell lines in pharmacogenomic discovery and clinical translation

The ability to predict how an individual patient will respond to a particular treatment is the ambitious goal of personalized medicine. The genetic make up of an individual has been shown to play a role in drug response. For pharmacogenomic studies, human lymphoblastoid cell lines (LCLs) comprise a useful model system for identifying genetic variants associated with pharmacologic phenotypes. The availability of extensive genotype data for many panels of LCLs derived from individuals of diverse ancestry allows for the study of genetic variants contributing to interethnic and interindividual variation in susceptibility to drugs. Many genome-wide association studies for drug-induced phenotypes have been performed in LCLs, often incorporating gene-expression data. LCLs are also being used in follow-up studies to clinical findings to determine how an associated variant functions to affect phenotype. This review describes the most recent pharmacogenomic findings made in LCLs, including the translation of some findings to clinical cohorts.

Mixed effects modeling of proliferation rates in cell-based models: consequence for pharmacogenomics and cancer

The International HapMap project has made publicly available extensive genotypic data on a number of lymphoblastoid cell lines (LCLs). Building on this resource, many research groups have generated a large amount of phenotypic data on these cell lines to facilitate genetic studies of disease risk or drug response. However, one problem that may reduce the usefulness of these resources is the biological noise inherent to cellular phenotypes. We developed a novel method, termed Mixed Effects Model Averaging (MEM), which pools data from multiple sources and generates an intrinsic cellular growth rate phenotype. This intrinsic growth rate was estimated for each of over 500 HapMap cell lines. We then examined the association of this intrinsic growth rate with gene expression levels and found that almost 30% (2,967 out of 10,748) of the genes tested were significant with FDR less than 10%. We probed further to demonstrate evidence of a genetic effect on intrinsic growth rate by determining a significant enrichment in growth-associated genes among genes targeted by top growth-associated SNPs (as eQTLs). The estimated intrinsic growth rate as well as the strength of the association with genetic variants and gene expression traits are made publicly available through a cell-based pharmacogenomics database, PACdb. This resource should enable researchers to explore the mediating effects of proliferation rate on other phenotypes.

Cell-based models provide a convenient system to conduct studies that would be impossible to apply to human subjects, but the phenotypes measured on these models can be marred with biological noise. We propose a method (MEM) to address this issue by statistically combining data from various sources, and we apply it to the proliferation rates of cell lines collected as part of the International HapMap project. We show that the proliferation rate computed using our method is a better measure of the true proliferation rate of the cells and produces a much stronger association with gene expression phenotypes on the same cell lines: more than 30% of the genes tested were significantly associated with proliferation rate. We also demonstrate that genetic variants have an effect on growth rate. Finally, we make these intrinsic proliferation rates and the strength of the association with gene expression phenotypes public, which should allow other researchers to explore the mediating effects of proliferation on other phenotypes.