IntechOpen

Home > Books > Ovarian Cancer - From Pathogenesis to Treatment

Open access peer-reviewed chapter

Ethnic Differences in Susceptibility to the Effects of Platinum- Based Chemotherapy

Written By

Andrey Khrunin, Alexey Moisseev, Vera Gorbunova and Svetlana Limborska

Submitted: 30 November 2016 Reviewed: 11 January 2018 Published: 08 February 2018

DOI: 10.5772/intechopen.73798

Ovarian Cancer IntechOpen
Ovarian Cancer From Pathogenesis to Treatment Edited by Omer Devaja

From the Edited Volume

Ovarian Cancer - From Pathogenesis to Treatment

Edited by Omer Devaja and Andreas Papadopoulos

Book Details Order Print

Chapter metrics overview

1,240 Chapter Downloads

View Full Metrics
Advertisement

Abstract

There is substantial interindividual variability in the efficacy and tolerability of anticancer drugs. Such differences can be greater between individuals of different ethnicities. The clinical studies demonstrate that individuals from Asia (East Asia) are more susceptible to the effects of platinum-containing chemotherapies than their Western counterparts. To determine whether population-related genomics (i.e., frequencies of DNA polymorphisms) contribute to differences in patient outcomes, polymorphisms in 109 genes involved mainly in xenobiotic metabolism, DNA repair, the cell cycle, and apoptosis were tested in Russian (Caucasians) and Yakut (North Asians) ovarian cancer patients receiving cisplatin-based chemotherapy. Totally, 232 polymorphisms were genotyped in individual DNA samples using conventional PCR and arrayed primer extension technology. Single nucleotide polymorphisms (SNPs) in more than 30 genes were found to be associated with one or more of clinical end points (i.e., tumor response, progression-free survival, overall survival, and side effects). However, all associations between SNPs and clinical outcomes were specific for each of ethnic group studied. These findings let us to propose the existence of distinctive ethnic-related characteristics in molecular mechanisms determining the sensitivity of patients to platinum drug effects.

Keywords

  • cisplatin
  • DNA polymorphisms
  • ethnic diversity
  • chemotherapy
  • ovarian cancer

1. Introduction

There is substantial interindividual variability in the efficacy and tolerability of pharmaceuticals, including anticancer drugs. Such differences can be greater between individuals of different ethnicities [1]. Currently, pharmacoethnicity, or ethnic diversity in drug effectiveness and/or toxicity, is an increasingly recognized factor for accounting interindividual variations in drug response [2]. Although the reasons underlying ethnic diversity in drug response are likely multifactorial [3], the results of numerous population studies suggest that they may be attributed, at least in part, to the interpopulation differences in frequencies of DNA polymorphisms – inherited variations at the DNA sequence level [4, 5, 6]. In terms of FST, the most commonly used measure of population differentiation; the proportion of such differences is 5–13% of total genetic diversity depending on the type of polymorphic markers chosen [6]. The opponents of ethnic-/race-based explorations in pharmacogenomics often consider these portions of variation as non-essential in the context of considerably larger proportions of within population variation which represents the average difference between members of the same population and accounts for 87–95% of total variance [7, 8]. Nevertheless, significant differences in the population prevalence of functionally impaired allelic variants of genes may create a potential for ethnic differences in responses to drugs that are detoxified (transported or targeted) by the proteins that are encoded by those genes [9, 10, 11]. A prominent example how population-based genetic differences can affect the drug response is the significantly greater risk for Stevens-Johnson syndrome and toxic epidermal necrolysis among East/Southeast Asian carbamazepine users, particularly Han-Chinese, Thais, and Malaysians, that has been associated with HLA-B*1502 allele [12]. The relationship was not evident in non-Asian patients as well as in Japanese and Koreans due to infrequency of the allele in these populations. Another example is the lower average warfarin requirements of Asians linked to the higher frequency of AA genotype at SNP rs9923231 upstream of VKORC1 gene among them [13]. Finally, considering potential pharmacoethnicity of anticancer drugs, one of the most illustrative examples, although not associated with germline variations, is the higher response rate to EGFR inhibitors (e.g., gefitinib) of Asian (East Asian) lung cancer patients compared to Caucasians that correlates to higher frequencies of activating EGFR mutations in East Asians [14].

Keeping all that in mind, we carried out a comparative study aimed to explore the genetic bases of differences between Asian and Caucasian cancer patients in their sensitivity to the effects of platinum-containing chemotherapy. Platinum-based drugs are among the most widely used cytotoxic agents for the treatment of many types of cancer [15]. The first information about lesser tolerance of Asian patients to standard, approved for Europeans, doses of platinum-containing regimens came from Japanese physicians [16]. In both individual small studies and some common arm trials conducted in Japan and by Southwest Oncology Group, the higher frequency of toxicity, particularly hematologic toxicity, was registered in Asian patients than non-Asians (mostly Caucasians) [1, 17]. Moreover, it was also found that the incidence of toxicity was still higher among Asians even after appropriate dose reduction [1]. Although some comparative pharmacogenetic studies have been conducted, the reasons underlying the higher sensitivity/toxicity of Asians to the systemic platinum-containing therapy are not yet well understood [18, 19, 20]. To assess the effect of population genomics on difference in patient response, we comparatively explored the results of cisplatin-based chemotherapy in Russian (Caucasians) and Yakut (North Asians) ovarian cancer patients. Principal component analysis, performed by us using genotype data of a common set of 125,000 genome-wide SNPs, demonstrated significant differences between gene pools of Asian and non-Asian populations (Figure 1).

Figure 1.

Genetic structure of Eurasian populations (based on 125,000 autosomal SNPs). The first two PCs are shown. Each individual is represented by a sign and the label corresponding to their self-identified population origin.

The estimates, obtained using the same set of polymorphic markers, showed that a portion of variation accounted for population-related differences, FST, in allele frequency between Russians and Yakuts was as high as 0.08, creating the potential for searching a causative polymorphism(s) with corresponding prevalence in population frequency. In the current study such candidates were searched among 232 polymorphisms from 109 genes involved mainly in xenobiotic metabolism, DNA repair, the cell cycle, and apoptosis.

Advertisement

2. Materials and methods

2.1. Patients

Ovarian cancer patients were identified and treated between 2003 and 2007 years at the N. N. Blokhin Cancer Research Centre and the Yakutsk Republic Cancer Clinic. Once identified, patients were invited to participate and were enrolled after they signed an informed consent. Detailed procedures of patient enrolment and data collection have been described previously [21, 22]. Briefly, unrelated Russian and Yakut women with morphologically confirmed epithelial ovarian carcinoma, who had received no previous chemotherapy or radiation therapy, were recruited. The upper age limit was 65 years. Exclusion criteria were serious concomitant diseases (diabetes, uncontrolled hypertension, myocardial infarction within the last 6 months, etc.), and clinically significant hearing impairment (grade 2 or higher). To ascertain ethnicity, women completed a questionnaire about their ancestry; only self-described Russian and Yakut patients with no history of interethnic marriages in the past two generations were recruited. Before the initiation of chemotherapy, venous blood samples were obtained for genetic testing. The chemotherapy regimen was intravenous cisplatin (100 mg/m2) plus cyclophosphamide (600 mg/m2) on day 1, every 3 weeks, for a maximum of 6 cycles. Intraperitoneal chemotherapy and radiotherapy were not allowed. Toxicity of the treatment was described according to standard National Cancer Institute Common Toxicity Criteria version 2.0 [23]. All patients were assessed for the maximal grades of nephrotoxicity, ototoxicity, neurotoxicity, emesis, neutropenia, anemia, and thrombocytopenia.

The tumor response was assessed every 2 cycles. After the completion of chemotherapy, the patients were followed-up for disease relapse and survival. Patients with progressive disease were treated with second-line chemotherapy, mostly taxane based. The study protocol and informed consent form were approved by the Ethics Committee of the N. N. Blokhin Cancer Research Centre.

2.2. Genotyping

DNA was isolated from the venous blood samples (leukocytes) using a conventional approach including proteinase K treatment with subsequent phenol-chloroform extraction [24]. Some polymorphisms (Table 1) were genotyped using a polymerase chain reaction restriction fragment length polymorphism (RFLP)-based technique or determined directly through evaluation of their PCR product lengths.

Polymorphism #rs ID Genotypes (No. patients)* P
GSTA1 − 69 C/T rs3957357 CC (43/60) CT (49/22) TT (12/5) 0.0007
GSTM1 gene deletion 0/0 (47/28) +/0** (57/59) NA 0.0754
GSTM3 AGG deletion rs1799735 AGG/AGG (83/75) AGG/− (16/12) −/− (5/0) 0.1054
GSTM3 Val224Ile rs7483 Val/Val (39/30) Val/Ile (57/37) Ile/Ile (8/20) <0.0001
GSTP1 Ile105Val rs1695 Ile/Ile (41/67) Ile/Val (53/17) Val/Val (10/3) <0.0001
GSTP1 Ala114Val rs1138272 Ala/Ala (80/84) Ala/Val (24/3) ―*** 0.0001
GSTT1 gene deletion 0/0 (18/22) +/0** (86/65) NA 0.2123
ERCC1 19007 T/C rs11615 TT (43/53) TC (46/29) CC (15/5) 0.0146
ERCC1 8092 C/A rs3212986 CC (61/52) CA (37/31) AA (6/4) 0.9351
ERCC2 Asp312Asn rs1799793 Asp/Asp (34/66) Asp/Asn (50/19) Asn/Asn (20/2) <0.0001
ERCC2 Lys751Gln rs13181 Lys/Lys (28/67) Lys/Gln (54/18) Gln/Gln (22/2) <0.0001
XRCC1 Arg194Trp rs1799782 Arg/Arg (94/69) Arg/Trp (10/18) ― 0.0398
XRCC1 Arg280His rs25489 Arg/Arg (95/80) Arg/His (9/6) His/His (0/1) 0.5007
XRCC1 Arg399Gln rs25487 Arg/Arg (49/40) Arg/Gln (45/39) Gln/Gln (10/8) 0.9752
TP53 Arg72Pro rs1042522 Arg/Arg (52/47) Arg/Pro (40/35) Pro/Pro (12/5) 0.3733
CYP2E1 96bp insertion −/− (100/74) −/ins (4/13) ― 0.0097
CYP2E1 − 1053 C/T rs2031920 CC (102/68) CT (2/18) ― <0.0001
CYP2E1 7632 T/A rs6413432 TT (91/67) TA (12/20) AA (1/0) 0.0753
CYP2E1 9896 C/G rs2070676 CC (82/78) CG (20/9) GG (2/0) 0.0908

Table 1.

Genotype frequencies in Russian and Yakut patients.

The first value in parentheses means the number of patients with corresponding genotype in Russian group, the second one – in Yakut group.


The genotype was defined as positive if at least one copy of gene was present.


The corresponding genotype was not occurred in populations.


NA – not available (not determined with the genotyping method used).


Other polymorphisms were genotyped using a microarray “DNA repair single nucleotide polymorphism detection test” (version 2, Asper Biotech, Tartu, Estonia). The microarray genotypes 228 SNPs in 106 genes involved in1 DNA repair, cell cycle control, apoptosis, and xenobiotic metabolism. Most of manually genotyped loci were also in the list of the microarray’s polymorphisms and served as controls of genotyping efficiency. To check into account the potential mistakes in genotyping with the microarray [25], all polymorphisms, which were associated with any clinical endpoints, were additionally tested using the RFLP method.

2.3. Statistical analysis

A permutation exact test, a two-sided Fisher exact test, and a χ2 test were used to determine the relationship between the variables and alleles/genotypes tested. Correlations between survival and genotype or genetic polymorphism were assessed using the Kaplan-Meier product limit method and the log-rank test. The significance of associations was set at P < 0.05 [26]. The statistical analyses were performed using the Statistica software (version 6.0, StatSoft, Inc., Tulsa, OK, USA) or the IBM SPSS Statistics software package (version 19, SPSS, Inc., IBM Company, IBM Corporation, Armonk, NY, USA), GraphPadInStat (version 3.00, GraphPad Software, San Diego, CA, USA), and the PowerMarker software (version 3.0) [27].

Advertisement

3. Results and discussion

During 2003–2007 years, 104 Russian patients and 87 Yakut patients were enrolled in the study. The median age of patients was 52 and 51 years, respectively. The majority of patients in both groups had stage III disease (72 and 53 women, respectively). Stages I, II, and IV were detected in 14, 6, and 10 Russian patients and 1, 8, and 25 Yakut patients. A total of 21 Russian patients and 11 Yakut patients were receiving adjuvant chemotherapy and were not eligible for evaluation of tumor response (i.e., they had no residual disease after surgery). Overall response rates, comprising complete and partial responders, were 85% in the Russian group and 58% in the Yakut group.

The median progression-free survival (PFS) in the Russian group was 12 months, and the median overall survival (OS) was 55 months. In the Yakut group, both intervals were shorter —8 and 29 months, respectively. However, being adjusted for disease stage, the values became similar to those for the Russian group.

More contrast results were obtained in analysis of occurrence of adverse events. To assess the association between genotype and the toxicity of the treatment used, patients were classified as having good or poor tolerance to treatment (grades 3–4 of neutropenia, grades 2–4 of anemia, grades 2–4 of neuropathy, grades 3–4 of emesis, all grade of thrombocytopenia, nephrotoxicity, and ototoxicity were considered as clinically significant toxicities). Comparison of the frequencies of side effects registered in Russian and Yakut patients confirmed higher toxicity of platinum-based regimens for patients of Asian origin than for Europeans. Particularly, Yakut patients suffered more frequently than Russians from nephrotoxicity and severe emesis (P = 0.027 and P = 0.061, respectively), which both were known to be the most common adverse events observed in regimens using cisplatin [28].

Genetic testing of the patients from our groups was performed in two stages. At first, we explored the associations between outcomes of a cisplatin-cyclophosphamide regimen in Russian and Yakut ovarian cancer patients and some most common polymorphisms in several genes [21, 22], among the tested genes, were glutathione S-transferase (GST) genes (GSTA1, GSTM1, GSTM3, GSTP1 and GSTT1), DNA repair genes (ERCC1, ERCC2 and XRCC1) as well as TP53 and CYP2E1 genes (Table 1). GST and DNA repair genes have been described as important for cisplatin metabolism and activity [29, 30]. GSTs can directly limit the amount of reactive cisplatin species available for interaction with DNA, by catalyzing their binding to tripeptide glutathione. The resulting cisplatin-glutathione conjugates can be further easily excreted from the cell by the GS-X pump transporters [31]. DNA repair proteins remove platinum-DNA adducts, the persistence of which underpins the antitumor potential of platinum drugs. In contrast to GST and the DNA repair proteins, TP53 protein does not seem to directly affect cisplatin metabolism or transformation. At the same time, it has a crucial role in mediating cellular responses to DNA damage, initiating programmed cell death when the effective DNA repair is impossible [29, 30, 32]. There is also no evidence that cisplatin is metabolized by CYP2E1. However, CYP2E1 is a significant potential source of catalytic iron and can serve as a site for generating reactive oxygen species in the presence of cisplatin [33]. It has been proposed that this mechanism underlies cisplatin-induced nephrotoxicity and hepatotoxicity [34, 35].

One of the most significant associations found in the first part of the study was the correlation between the survival time intervals and GSTP1 Ile105Val polymorphism registered in Russian subjects (P = 0.004 and P = 0.016 for PFS and OS, respectively). Russian ovarian cancer patients with a homozygous Ile/Ile genotype had longer PFS and OS than those ones who carried Ile/Val and Val/Val genotypes. However, the association was not observed in Yakut patients. PFS and OS of Yakut women with Ile/Ile genotype did not differ from the corresponding time intervals of patients with 1 or 2 Val alleles. In the Yakut group, PFS correlated with CYP2E1 7632 T/A polymorphism (P = 0.015), being longer in patients with a homozygous TT genotype than in patients with the heterozygous TA genotype.

Analysis of genotype distribution in the population groups for toxicities revealed that occurrence of nephrotoxicity and severe emesis in Yakut patients correlated with GSTT1 and CYP2E1 genotypes, respectively. Patients with a homozygous GSTT1 gene deletion (GSTT1 null) suffered more frequently from nephrotoxicity than carriers of functional GSTT1 variants (OR = 3.31, 95% CI 1.15–9.54, P = 0.028). Patients who had a 96 bp insertion in the promoter region of the CYP2E1 were more prone to severe emesis (OR = 4.69, 95% CI 1.31–16.77, P = 0.027). Grade 3 or 4 emesis was also associated with another CYP2E1 polymorphism—a single nucleotide substitution (9896 C/G) in intron 7. Patients with a heterozygous CG genotype had a higher risk of severe emesis than patients with the homozygous CC genotype (OR = 16.96, 95% CI 2.01–143.16, P = 0.002). In contrast, in Russian patients, CYP2E1 polymorphisms were not associated with any clinical outcomes and distribution of GSTT1 genotypes correlated with severity of emesis. The risk of severe emesis was higher in Russian patients with the GSTT1-null genotype than in patients with a functional GSTT1 variant (OR = 4.06, 95% CI 1.40–11.78; P = 0.014). As for the nephrotoxicity in Russian subjects, it was associated with ERCC1 19007 T/C or 8092 C/A polymorphisms, and cases of renal dysfunction were more prevalent among patients with the heterozygous genotypes of each locus. Other found genotype-clinical end point associations were also discordant in Russians and Yakuts (Table 2).

Gene name #rs ID Clinical outcomes**
PFS OS Anemia Neutropenia Thrombocitopenia Nephrotoxicity Ototoxicity Emesis
R Y R Y R Y R Y R Y R Y R Y R Y
GSTA1 rs3957357 +
GSTM1 gene deletion + +
GSTM3 rs1799735 + +
GSTM3 rs7483
GSTP1 rs1695 + +
GSTP1 rs1138272
GSTT1 gene deletion + +
ERCC1 rs11615 +
ERCC1 rs3212986 +
ERCC2 rs1799793 +
ERCC2 rs13181
XRCC1 rs1799782
XRCC1 rs25489
XRCC1 rs25487 +
TP53 rs1042522 +
CYP2E1 96bp insertion +
CYP2E1 rs2031920
CYP2E1 rs6413432 +
CYP2E1 rs2070676 +

Table 2.

The associations between polymorphisms and clinical outcomes observed in Russian (R) and Yakut (Y) patient groups (the first stage of the study)*.

The registered associations are indicated by “+” in the corresponding cells.


Tumor response and ototoxicity were not included in the table as there were no associations between them and polymorphisms tested.


When genotype distributions in both groups were compared significant differences in population genotype frequencies were noted for 10 of 19 polymorphisms studied but only 5 of them were associated with clinical outcomes (Tables 1 and 2).

Evaluation of the direction/strength of the associations showed that they were not correlated with the differences in population frequencies of corresponding genotypes. For example, the absence of correlation between the GSTP1 Ile105Val polymorphism and survival in Yakut patients was not simply due to the higher prevalence of Ile/Ile genotype among them because carriers of Ile/Ile genotype did not differ in PFS or OS from those who had genotypes with 1 or 2 Val alleles. Similar results were obtained for the GSTA1-69 C/T polymorphism. Its CT and TT genotypes were associated with a risk of anemia in Yakuts; yet the greater frequencies of the CT and TT genotypes in Russians did not result in a higher risk of anemia. Similarly, risk genotypes of ERCC1 19007 T/C and ERCC2 Asp312Asn polymorphisms (i.e., heterozygous genotypes in Russians) were not rare among Yakut patients but they did not demonstrate correlations with the corresponding side effects (Tables 1 and 2). It seems that only in the case of CYP2E1 96 bp insertion polymorphism an effect of allele frequency differences could be proposed but due to small number of individuals with the insertion containing genotypes in Russians the suggestion requires verification in a larger sample.

Taken in the context of other data, the obtained results generally supported the role of ethnicity as an additional reason for differences in the outcomes of clinical trials in which the same treatment is used. At the same time, the results of genetic testing suggested that a single genotypic difference was unlikely to account for the observed ethnic variation in toxicity and survival. Moreover, they also suggested that assessing traditionally tested common polymorphisms in GST and DNA repair genes is not enough for relevant description of lesser tolerability of Asians (North/East Asians) to the effects of platinum-containing chemotherapies and further studies involving more polymorphic markers are required.

In the second part of our study, we systematically investigated the associations between patients’ outcomes and SNPs in more than 100 genes using the microarray “DNA repair single nucleotide polymorphism detection test” (version 2) [36, 37]. Like similar genotyping panels, the list of genes tested comprised candidate genes involved in key pathways of cellular response to different drugs [38, 39], including many genes that are related to the cisplatin pathway (platinum pathway) [40]. A total of 213 SNPs from 228 genotyped SNPs were new (i.e., they did not include SNPs from the first stage) and 27 SNPs were associated with one or more of the assessed clinical end points (Table 3).

Gene name #rs ID Clinical outcomes
Response PFS OS Anemia Neutropenia Thrombocitopenia Nephrotoxicity Ototoxicity Emesis
R Y R Y R Y R Y R Y R Y R Y R Y R Y
ADH1C rs698 +
ALDH2 rs4646777 +
APEX1 rs1048945 +
CCNH rs2266690 +
COMT rs4633 +
CDKN1B rs34330 + +
CYP1A1 rs4646903 +
CYP1A2 rs2470890 +
DRD2 rs1079597 +
EPHX1 rs1051740 + +
EPHX1 rs2234922 +
ERCC5 rs1047768 +
ERCC5 rs17655 +
GRPR rs4986946 +
GSTA4 rs405729 +
LIG3 rs1052536 +
MSH3 rs26279 +
MSH6 rs1042821 +
MUTYH rs3219484 +
MUTYH rs3219489 +
NAT2 rs1801280 +
NBN rs1063045 +
NQO1 rs1800566 + +
NQO1 rs4986998 + +
RAD52 rs11226 +
TPMT rs1142345 +

Table 3.

The associations between polymorphisms and clinical outcomes observed in Russian (R) and Yakut (Y) patient groups (the second stage of the study)*.

The designations are the same as in Table 2.


Increasing number of polymorphisms yielded an association with tumor response. To assess the association, patients who achieved a complete remission were compared with those without it (i.e., patients with partial response, stable and progressive disease). In the Russian group, a significant difference in complete response was observed according to polymorphism in the ADH1C gene (A/G, rs698) (P = 0.0002). The proportion of patients who achieved a complete response was higher among carriers of homozygous genotypes AA and GG compared with patients with a heterozygous variant AG. In Yakut patients, the occurrence of complete response was correlated with an allelic status of SNP in CDKN1B gene (T/C, rs34330), particularly with an allele C. There were no cases of complete remission among patients who carried a homozygous genotype TT at rs34330. The SNP was also associated with PFS in Yakut subjects (P = 0.0051); patients with the genotype TT had shorter PFS than patients with CC and CT genotypes. The protein encoded by CDKN1B gene participates in regulation of the cell cycle by binding and inhibiting activation of cyclin E-CDK2 or cyclin D-CDK4 complexes, and thus blocking the transition of the cell into the S-phase. C > T substitution at rs34330 locus results in decreasing the levels of mRNA and CDKN1B protein [41]. Reduced level of CDKN1B expression has been associated with a poor outcome in various cancers [42, 43]. In contrast, the ADH1C SNP (rs698) has been associated with a risk of alcoholism and ethanol-related cancers [44], but our study was the first to demonstrate an association with a chemotherapy outcome (i.e., tumor response) but the mechanism is not obvious.

Genotypes of seven SNPs were associated with differences in PFS in the Russian group (Table 3). The most significant SNPs were rs1142345 (A/G) in TPMT (P = 3 × 10−8) and rs4986998 (C/T) and rs1800566 (C/T) in NQO1 genes (P = 2 × 10−6 and P = 9 × 10−11, respectively). The longer PFS was seen in patients with the most frequent genotypes AA and CC. SNPs in NQO1 demonstrated similar correlations with OS.

Thiopurine S-methyltransferase (TPMT) is a cytosolic methylating enzyme with unknown physiological role [45]. However, this enzyme is known to be able to catalyze the S-methylation of some aromatic and heterocyclic compounds, particularly thio-compounds (e.g., 6-mercaptopurine and 6-thioguanine). Discussing the associations revealed between SNPs in TPMT and cisplatin ototoxicity, Ross et al. [46] have hypothesized that TPMT can affect cisplatin-induced hearing impairment through inactivation of cisplatin-purine compounds that form cytotoxic DNA cross-links, and cause cell death. As might be expected from that data, those patients in our study who had the loss-of-function genotype AG at rs1142345 should demonstrate a better outcome as a result of decreased inactivation of cisplatin-purine compounds, but such a correlation was not observed. Moreover, patients with an AG genotype had even shorter PFS than those who carried the functionally normal AA genotype.

The tested SNPs in NQO1 gene are characteristic polymorphic variants affecting functional ability of the corresponding protein — a cytosolic flavoenzyme NAD(P)H: quinone oxidoreductase 1 (NQO1). NQO1 polymorphic status has been associated with anticancer chemotherapy outcome (i.e., individuals with CT and TT genotypes at rs1800566 showed reduced survival compared to CC homozygotes) [47, 48]. The same correlations were observed in our study. Taking into account the key role of NQO1 in preventing the formation of reactive semiquinone radicals and generating reactive oxygen species (ROS) via redox cycling, one can propose that the worse survival of carriers of CT and TT genotypes is at least the consequence of a chronically elevated level of ROS, which results in enhanced ROS-mediated DNA damage, increased genetic instability, and further cancer progression [47].

In addition to CDKN1B, SNPs in CYP1A1 (T/C, rs4646903) and CYP1A2 (C/T, rs2470890) were found to also be associated with survival, particularly with OS, in Yakut patients (P = 0.007 and P = 0.0072, respectively). In each case the longer OS occurred in patients with homozygous genotypes TT. In contrast to TPMT and NQO1, the role of CYP1A1 and CYP1A2 in cisplatin metabolism or toxicity is difficult to discern. At the same time, it cannot be excluded that the observed associations are related to metabolic pathways of drugs used in the second and subsequent lines of the chemotherapy (taxanes and anthracyclines).

Totally, 16 SNPs were associated with the side effects of chemotherapy. Thirteen such SNPs were revealed in the Russian group and three SNPs in Yakuts (Table 3). A total of 6 of 13 SNPs were associated with an incidence of severe neutropenia in Russian patients. A strong association was estimated for SNP rs1052536 in LIG3. Carriers of its homozygous genotype CC had more than 20-fold higher risk of grade 3 or 4 neutropenia than patients with other genotypes (OR = 23.211, 95% CI =2.976–181.02, P = 2 × 10−6). However, the most significant was SNP rs3219484 in MUTYH. The SNP was represented by only two genotypes, and patients who carried a heterozygous genotype AG had very low (actually unobserved) risk of developing severe neutropenia (OR = 0.013, 95% CI 0.000–0.220, P = 4 × 10−8). MUTYH encodes a DNA glycosylase involved in repair of oxidatively damaged DNA, in particular by excising adenines misincorporated opposite 7,8-dihydro-8-oxoguanines. Such mispairs are promutagenic, and if left unrepaired before the next round of replication, they can give rise to CG → AT transversion mutations [49]. The observed association may reflect the substantial contribution of oxidative stress (i.e., ROS) into cisplatin-induced cytotoxicity. On the other hand, an associative grouping of MUTYH SNPs together with SNPs from other DNA repair genes, particularly RAD52 and ERCC5, may also indicate a role of MUTYH in the repair of cisplatin-produced DNA lesions (e.g., participation in detection of the lesions) [50].

Another side effect for which multiple associations were found in the Russian group was anemia. SNPs in NAT2, GSTA4, CCNH, and EPHX1 genes were associated with the toxicity (Table 3). The most significant was SNP rs1801280 in NAT2. Cases of anemia occurred more frequently among patients with the heterozygous CT genotypes (78.4%) compared with the homozygous variants (OR = 5.945, 95% CI 2.351–15.031, P = 0.00009). This association is of particular interest because there is no information about a role of NAT2 in the metabolism or toxicity of cisplatin or cyclophosphamide (the second drug in our chemotherapy regimen) [51]. One can propose that the association found is due to linkage between the SNP with a functional SNP(s) in other gene(s). Unlike NAT2, three other genes (i.e., GSTA4, CCNH, and EPHX1) are more relevant to the effects of intracellular processing of cisplatin. The cyclin encoded by CCNH is a part of a TFIIH complex that is an essential component of a nucleotide excision repair pathway, widely accepted as a main player in removing platinum-DNA adducts from DNA molecules [52]. GSTA4 plays an important role for the detoxification of 4-hydroxynonenal [53], a toxic product of lipid peroxidation, increasing immensely under oxidative stress conditions (e.g., overproduction of ROS), including cisplatin treatment [54, 55]. The role of epoxide hydrolases (EPXHs) in cisplatin-induced toxicity appears to be also related to the effects of oxidative stress. However, in contrast to GSTA4, EPXHs role is inhibitory and results from the abilities of epoxide hydrolases to metabolize epoxyeicosatrienoic acids (EETs) possessing multiple functions, particularly anti-inflammatory effects. The data about relationships between EET hydrolysis and cisplatin toxicity have been mainly obtained from the studies of cisplatin nephrotoxicity [56, 57]. It has been shown that the anti-inflammatory effect of EETs substantially depends on EPHX2, a cytosolic partner of EPHX1. EPHX1 also accepts EETs, although generally to a much lesser extent than EPHX2 [58]. Therefore, a role for EPHX1 in cisplatin toxicity should not be excluded, particularly because of its high expression in kidneys. The association between the SNP rs1051740 in EPHX1 and nephrotoxicity of the regimen used supports this suggestion.

Three SNPs in APEX1 (rs1048945), MSH3 (rs26279), and MSH6 (rs1042821) were associated with ototoxicity, thrombocytopenia, and emesis in Russian patients (Table 3). APEX1 gene encodes apurinic/apyrimidinic endodeoxyribonuclease 1 playing an essential role in the DNA base excision repair pathway, where it removes apurinic/apyrimidinic sites produced during the repair of bases modified by ROS, alkylating agents, or ionizing radiation [59]. High APEX1 expression has been associated with a poor outcome for chemoradiotherapy, poor complete response rate, shorter local relapse-free interval, poorer survival, and high angiogenesis [59]. At the same time, a role for APEX1 in protection against toxicity, particularly neurotoxicity, induced by ionizing radiation, and cisplatin treatment, has also been demonstrated [60, 61, 62]. ROS and oxidative DNA damage induced by them were shown to be important components of the deleterious effects of cisplatin on neuronal cells. Taking into account the proposed role of ROS in the mechanism of cisplatin-induced hearing loss [63], a contribution of APEX1 can also be hypothesized.

The protein products of MSH3 and MSH6 are essential components of the DNA mismatch repair system (MMR). The presence of MMR is thought to be important in mediating cisplatin and carboplatin cytotoxicity, whereas its deficiency, by contrast, may contribute to desensitization of cancer cells to the drugs [64, 65]. In our study, SNPs in MSH3 and MSH6 were not associated with tumor response or survival. Nevertheless, patients with minor alleles of the SNPs rs26279 and rs1042821 were at higher risk of thrombocytopenia and emesis, respectively.

Only one gene from the list above was also present among the genes whose polymorphisms were associated with the adverse reactions in Yakut patients, namely, EPXH1 gene. However, it was associated with a different side effect (i.e., ototoxicity). Furthermore, the corresponding polymorphisms were also different (A/G, rs2234922 and C/G, rs2260863) (Table 3). Higher risk of ototoxicity was observed in patients with the most frequent genotypes AA and CC (OR = 26.26, 95% CI 1.502–458.98, P = 0.0005). Although the role of EPXHs in cisplatin toxicity has been mainly associated with their effects on cisplatin-induced kidney injury, the observed link between the EPHX1 polymorphism and cisplatin ototoxicity can be due to similarity of mechanisms underlying cisplatin-induced hearing impairment and renal dysfunction [66].

The second gene whose allelic variants were associated with a side effect of chemotherapy in Yakut patients (i.e., severe emesis) was NBN (G/A, rs1063045). The risk factor for the development of severe emesis in patients was their heterozygous status at the rs1063045 locus. The protein encoded by NBN gene is an important component of the system repairing DNA double-strand breaks that can be induced by different environmental and endogenous agents, including cisplatin. The existing data suggest connections between polymorphic variants of the NBN gene and the results of cisplatin-based chemotherapy [67].

Intergroup comparison of genotypes generated with the microarrays revealed substantial differences in population frequencies of alleles and genotypes for many polymorphic markers. More than half of all markers differed significantly in the occurrence of their allelic variants in Russian and Yakut patients.

The proportion of significant genotype frequency differences resembled the results obtained in the first part of the study where a smaller number of polymorphic markers was involved (Table 2). Furthermore, the results of the comparisons of population-related associative spectra were also the same: there were no identical correlations for any of significant polymorphisms. All associations between the polymorphic markers and clinical outcomes were specific for each of the ethnic group studied.

These findings are generally compatible with the results of the HapMap project studying of the toxicity of platinum compounds (i.e., cisplatin and carboplatin) to lymphoblastoid cell lines from three groups of racially different individuals [19]. One can propose that the failure to detect common associations/commonly associated polymorphisms in our two groups was due to distinctive ethnic-related characteristics in the molecular mechanisms determining the sensitivity of patients to platinum drugs. Hence the difference in platinum drug sensitivity might not exclusively depend on the difference in variant frequencies of given polymorphisms. Another, but not exclusive, explanation of the findings could be a limitation of the number of polymorphisms tested and a possible omission of other potentially important markers. The latest may be mainly due to the misunderstanding of molecular phenotype(s) of the particular drug(s) [68]. The more relevant is the molecular phenotype, the higher is the potential to optimize the use of a particular drug. For some drugs, such as fluorouracil, irinotecan, and mercaptopurine, some relevant variants (i.e., DPYD*2A, DPYD 2846T/A, and TYMS 2R/3R; UGT1A1*28 and UGT1A1*6; TPMT *2, TPMT *3A, and TPMT*3C) have been established but for other ones, including platinum-containing agents, they are less apparent [68, 69].

The importance of DNA repair, particularly nucleotide excision repair, for platinum cytotoxicity is widely accepted [64]. However, the overall contribution of even the most common genetic variants to predictions of response to platinum-based therapy is not yet well established [70, 71]. In principle, the situation with other “canonical” pathways affecting mainly cisplatin pharmacokinetics could be described the same way [72]. Therefore, the role of additional mechanisms that are not directly related to cisplatin cellular processing has also been proposed [73]. The results of our study overrepresented with the associations with polymorphisms in genes for different metabolic enzymes (TPMT, NQO1, EPXH1, etc.) supports the suggestion (the associations would remain significant even if they were adjusted with the Bonferroni method). The abundance of associations with genes involved in processing of ROS or ROS-mediated lesions is of particular interest. First, it can point to the higher potential of ROS in total cisplatin-related cytotoxicity [66, 73]. Second, it has been proposed that populations from different geographic regions possess a difference in efficiency of coupling mitochondrial oxidation with phosphorylation, with more heat production and lower ROS generation in North/Northeastern Asians [74, 75]. Consequently, we can expect in Asians lower ability to utilize extra ROS and higher sensitivity to effects of platinum-based drugs. However, because of the relatively small sample sizes and limited number of markers tested, further studies are required to confirm this hypothesis.

In summary, comprehensive exploration of genotypes of polymorphisms in more than 100 genes in ovarian cancer patients from Russian and Yakut ethnic groups, receiving cisplatin-based chemotherapy, revealed pronounced differences in associative spectra between them. Taken in the context of absence of correlations between the associations and polymorphic genotype frequencies, the differences suggest a potential for distinct ethnic-related molecular mechanisms determining the sensitivity of patients to platinum drug effects. The mechanisms are thought to be associated with activity of different metabolic enzymes, including those involved in processing the reactive oxygen species. These genetic findings and differential responses to platinum-based chemotherapy between ethnic groups suggest that future genetic testing may be invaluable not only in predicting chemotherapy response but also in deciding the most appropriate chemotherapy regimen. It may be possible to identify in detail the susceptibility differences to chemotherapy sensitivity at the molecular level and harness this for therapeutic gains.

Advertisement

Acknowledgments

This study was supported by grants from the Programs “Fundamental Researches for Development of Biomedical Technologies” and “Molecular and Cell Biology” of the Russian Academy of Sciences and Russian Foundation for Basic Research.

References

  1. 1. O'Donnell PH, Dolan ME. Cancer pharmacoethnicity: Ethnic differences in susceptibility to the effects of chemotherapy. Clinical Cancer Research. 2009;15:4806-4814. DOI: 10.1158/1078-0432.CCR-09-0344
  2. 2. Ortega VE, Meyers DA. Pharmacogenetics: Implications of race and ethnicity on defining genetic profiles for personalized medicine. The Journal of Allergy and Clinical Immunology. 2014;133:16-26. DOI: 10.1016/j.jaci.2013.10.040
  3. 3. Morris AM, Rhoads KF, Stain SC, Birkmeyer JD. Understanding racial disparities in cancer treatment and outcomes. Journal of the American College of Surgeons. 2010;211:105-113. DOI: 10.1016/j.jamcollsurg.2010.02.051
  4. 4. Kidd KK, Pakstis AJ, Speed WC, Kidd JR. Understanding human DNA sequence variation. The Journal of Heredity. 2004;95:406-420
  5. 5. Li JZ, Absher DM, Tang H, Southwick AM, Casto AM, Ramachandran S, Cann HM, Barsh GS, Feldman M, Cavalli-Sforza LL, Myers RM. Worldwide human relationships inferred from genome-wide patterns of variation. Science. 2008;319:1100-1104. DOI: 10.1126/science.1153717
  6. 6. Barbujani G, Colonna V. Human genome diversity: Frequently asked questions. Trends in Genetics. 2010;26:285-295. DOI: 10.1016/j.tig.2010.04.002
  7. 7. Pena SD. The fallacy of racial pharmacogenomics. Brazilian Journal of Medical and Biological Research. 2011;44:268-275
  8. 8. Jobling MA, Rasteiro R, Wetton HJ. In the blood: The myth and reality of genetic markers of identity. Ethnic and Racial Studies. 2016;39:142-161. DOI: 10.1080/01419870.2016.1105990
  9. 9. Xie HG, Kim RB, Wood AJ, Stein CM. Molecular basis of ethnic differences in drug disposition and response. Annual Review of Pharmacology and Toxicology. 2001;41:815-850
  10. 10. Phan VH, Moore MM, McLachlan AJ, Piquette-Miller M, Xu H, Clarke SJ. Ethnic differences in drug metabolism and toxicity from chemotherapy. Expert Opinion on Drug Metabolism & Toxicology. 2009;5:243-257. DOI: 10.1517/17425250902800153
  11. 11. Phan VH, Tan C, Rittau A, Xu H, McLachlan AJ, Clarke SJ. An update on ethnic differences in drug metabolism and toxicity from anti-cancer drugs. Expert Opinion on Drug Metabolism & Toxicology. 2011;7:1395-1410. DOI: 10.1517/17425255.2011.624513
  12. 12. Tangamornsuksan W, Chaiyakunapruk N, Somkrua R, Lohitnavy M, Tassaneeyakul W. Relationship between the HLA-B*1502 allele and carbamazepine-induced Stevens-Johnson syndrome and toxic epidermal necrolysis: A systematic review and meta-analysis. JAMA Dermatology. 2013;149:1025-1032. DOI: 10.1001/jamadermatol.2013.4114
  13. 13. Limdi NA, Wadelius M, Cavallari L, Eriksson N, Crawford DC, Lee MT, Chen CH, Motsinger-Reif A, Sagreiya H, Liu N, Wu AH, Gage BF, Jorgensen A, Pirmohamed M, Shin JG, Suarez-Kurtz G, Kimmel SE, Johnson JA, Klein TE, Wagner MJ, International Warfarin Pharmacogenetics Consortium. Warfarin pharmacogenetics: A single VKORC1 polymorphism is predictive of dose across 3 racial groups. Blood. 2010;115:3827-3834. DOI: 10.1182/blood-2009-12-255992
  14. 14. Ma BB, Hui EP, Mok TS. Population-based differences in treatment outcome following anticancer drug therapies. The Lancet Oncology. 2010;11:75-84. DOI: 10.1016/S1470-2045(09)70160-3
  15. 15. Ho GY, Woodward N, Coward JI. Cisplatin versus carboplatin: Comparative review of therapeutic management in solid malignancies. Critical Reviews in Oncology/Hematology. 2016;102:37-46. DOI: 10.1016/j.critrevonc.2016.03.014
  16. 16. Watanabe A, Taniguchi M, Sasaki S. Induction chemotherapy with docetaxel, cisplatin, fluorouracil and l-leucovorin for locally advanced head and neck cancers: A modified regimen for Japanese patients. Anti-Cancer Drugs. 2003;14:801-807
  17. 17. Soo RA, Kawaguchi T, Loh M, Ou SH, Shieh MP, Cho BC, Mok TS, Soong R. Differences in outcome and toxicity between Asian and caucasian patients with lung cancer treated with systemic therapy. Future Oncology. 2012;8:451-462. DOI: 10.2217/fon.12.25
  18. 18. Gandara DR, Kawaguchi T, Crowley J, Moon J, Furuse K, Kawahara M, Teramukai S, Ohe Y, Kubota K, Williamson SK, Gautschi O, Lenz HJ, McLeod HL, Lara PN Jr, Coltman CA Jr, Fukuoka M, Saijo N, Fukushima M, Mack PC. Japanese-US common-arm analysis of paclitaxel plus carboplatin in advanced non-small-cell lung cancer: A model for assessing population-related pharmacogenomics. Journal of Clinical Oncology. 2009;27:3540-3546. DOI: 10.1200/JCO.2008.20.8793
  19. 19. O'Donnell PH, Gamazon E, Zhang W, Stark AL, Kistner-Griffin EO, Stephanie Huang R, Eileen Dolan M. Population differences in platinum toxicity as a means to identify novel genetic susceptibility variants. Pharmacogenetics and Genomics. 2010;20:327-337. DOI: 10.1097/FPC.0b013e3283396c4e
  20. 20. Wheeler HE, Gamazon ER, Stark AL, O'Donnell PH, Gorsic LK, Huang RS, Cox NJ, Dolan ME. Genome-wide meta-analysis identifies variants associated with platinating agent susceptibility across populations. The Pharmacogenomics Journal. 2013;13:35-43. DOI: 10.1038/tpj.2011.38
  21. 21. Khrunin AV, Moisseev A, Gorbunova V, Limborska S. Genetic polymorphisms and the efficacy and toxicity of cisplatin-based chemotherapy in ovarian cancer patients. The Pharmacogenomics Journal. 2010;10:54-61. DOI: 10.1038/tpj.2009.45
  22. 22. Khrunin A, Ivanova F, Moisseev A, Khokhrin D, Sleptsova Y, Gorbunova V, Limborska S. Pharmacogenomics of cisplatin-based chemotherapy in ovarian cancer patients of different ethnic origins. Pharmacogenomics. 2012;13:171-178. DOI: 10.2217/pgs.11.140
  23. 23. National Cancer Institute. Common Toxicity Criteria, version 2.0. April 30, 1999. Available from: https://ctep.cancer.gov/protocoldevelopment/electronic_applications/ctc.htm [Accessed: 2017-04-06]
  24. 24. Milligan BG. Total DNA isolation. In: Hoelzel AR, editor. Molecular Genetic Analysis of Populations. London: Oxford University Press; 1998. pp. 29-60
  25. 25. Kweekel DM, Antonini NF, Nortier JW, Punt CJ, Gelderblom H, Guchelaar HJ. Explorative study to identify novel candidate genes related to oxaliplatin efficacy and toxicity using a DNA repair array. British Journal of Cancer. 2009;101:357-362. DOI: 10.1038/sj.bjc.6605134
  26. 26. Perneger TV. What's wrong with Bonferroni adjustments. BMJ. 1998;316:1236-1238
  27. 27. Liu K, Muse SV. PowerMarker: An integrated analysis environment for genetic marker analysis. Bioinformatics. 2005;21:2128-2129
  28. 28. Ardizzoni A, Boni L, Tiseo M, Fossella FV, Schiller JH, Paesmans M, Radosavljevic D, Paccagnella A, Zatloukal P, Mazzanti P, Bisset D, Rosell R. Cisplatin- versus carboplatin-based chemotherapy in first-line treatment of advanced non – small-cell lung cancer: An individual patient data meta-analysis. Journal of the National Cancer Institute. 2007;99:847-857
  29. 29. Siddik ZH. Cisplatin: Mode of cytotoxic action and molecular basis of resistance. Oncogene. 2003;22:7265-7279
  30. 30. Jung Y, Lippard SJ. Direct cellular responses to platinum-induced DNA damage. Chemical Reviews. 2007;107:1387-1407
  31. 31. Hall MD, Okabe M, Shen DW, Liang XJ, Gottesman MM. The role of cellular accumulation in determining sensitivity to platinum-based chemotherapy. Annual Review of Pharmacology and Toxicology. 2008;48:495-535
  32. 32. Sullivan A, Syed N, Gasco M, Bergamaschi D, Trigiante G, Attard M, et al. Polymorphism in wild-type p53 modulates response to chemotherapy in vitro and in vivo. Oncogene. 2004;23:3328-3337
  33. 33. Liu H, Baliga M, Baliga R. Effect of cytochrome P450 2E1 inhibitors on cisplatin-induced cytotoxicity to renal proximal tubular epithelial cells. Anticancer Research. 2002;22:863-868
  34. 34. Liu H, Baliga R. Cytochrome P450 2E1 null mice provide novel protection against cisplatin-induced nephrotoxicity and apoptosis. Kidney International. 2003;63:1687-1696
  35. 35. Lu Y, Cederbaum AI. Cisplatin-induced hepatotoxicity is enhanced by elevated expression of cytochrome P450 2E1. Toxicological Sciences. 2006;89:515-523
  36. 36. Кhokhrin DV, Khrunin AV, Ivanova FG, Moiseev AA, Gorbunova VA, Limborskaia SA. Pharmacogenomics of cisplatin-based chemotherapy in ovarian cancer patients from Yakutia. Molekuliarnaia Genetika, Mikrobiologiia i Virusologiia. 2013;(4):6-9
  37. 37. Khrunin AV, Khokhrin DV, Moisseev AA, Gorbunova VA, Limborska SA.Pharmacogenomic assessment of cisplatin-based chemotherapy outcomes in ovarian cancer. Pharmacogenomics. 2014;15:329-337. DOI: 10.2217/pgs.13.237
  38. 38. Dai Z, Papp AC, Wang D, Hampel H, Wolfgang S. Genotyping panel for assessing response to cancer chemotherapy. BMC Medical Genomics. 2008;1:24. DOI: 10.1186/1755-8794-1-24
  39. 39. Sissung TM, English BC, Venzon D, Figg WD, Deeken JF. Clinical pharmacology and pharmacogenetics in a genomics era: The DMET platform. Pharmacogenomics. 2010;11:89-103. DOI: 10.2217/pgs.09.154
  40. 40. Platinum pathway. Available from: http://www.pharmgkb.org/pathway/PA150642262 [assessed 2017-03-27]
  41. 41. Landa I, Montero-Conde C, Malanga D, De Gisi S, Pita G, Leandro-García LJ, Inglada-Pérez L, Letón R, De Marco C, Rodríguez-Antona C, Viglietto G, Robledo M. Allelic variant at −79 (C/T) in CDKN1B (p27Kip1) confers an increased risk of thyroid cancer and alters mRNA levels. Endocrine-Related Cancer. 2010;17:317-328. DOI: 10.1677/ERC-09-0016
  42. 42. DE Almeida MR, Pérez-Sayáns M, Suárez-Peñaranda JM, Somoza-Martín JM, García-García A. p27Kip1 expression as a prognostic marker for squamous cell carcinoma of the head and neck. Oncology Letters. 2015;10:2675-2682
  43. 43. Lin TC, Tsai LH, Chou MC, Chen CY, Lee H. Association of cytoplasmic p27 expression with an unfavorable response to cisplatin-based chemotherapy and poor outcomes in non-small cell lung cancer. Tumour Biology. 2016;37:4017-4023. DOI: 10.1007/s13277-015-4272-7
  44. 44. Xue Y, Wang M, Zhong D, et al. ADH1C Ile350Val polymorphism and cancer risk: Evidence from 35 case-control studies. PLoS One. 2012;7:e37227. DOI: 10.1371/journal.pone.0037227
  45. 45. Fotoohi AK, Coulthard SA, Albertioni F. Thiopurines: Factors influencing toxicity and response. Biochemical Pharmacology. 2010;79:1211-1220. DOI: 10.1016/j.bcp.2010.01.006
  46. 46. Ross CJ, Katzov-Eckert H, Dubé MP, Brooks B, Rassekh SR, Barhdadi A, Feroz-Zada Y, Visscher H, Brown AM, Rieder MJ, Rogers PC, Phillips MS, Carleton BC, Hayden MR, CPNDS Consortium. Genetic variants in TPMT and COMT are associated with hearing loss in children receiving cisplatin chemotherapy. Nature Genetics. 2009;41:1345-1349. DOI: 10.1038/ng.478
  47. 47. Fagerholm R, Hofstetter B, Tommiska J, et al. NAD(P)H:Quinone oxidoreductase 1 NQO1*2 genotype (P187S) is a strong prognostic and predictive factor in breast cancer. Nature Genetics. 2008;40:844-853. DOI: 10.1038/ng.155
  48. 48. Kolesar JM, Dahlberg SE, Marsh S, et al. The NQO1*2/*2 polymorphism is associated with poor overall survival in patients following resection of stages II and IIIa non-small cell lung cancer. Oncology Reports. 2011;25:1765-1772. DOI: 10.3892/or.2011.1249
  49. 49. Markkanen E, Dorn J, Hübscher U. MUTYH DNA glycosylase: The rationale for removing undamaged bases from the DNA. Frontiers in Genetics. 2013;4:18. DOI: 10.3389/fgene.2013.00018
  50. 50. Jansson K, Alao JP, Viktorsson K, Warringer J, Lewensohn R, Sunnerhagen P. A role for Myh1 in DNA repair after treatment with strand-breaking and crosslinking chemotherapeutic agents. Environmental and Molecular Mutagenesis. 2013;54:327-337. DOI: 10.1002/em.21784
  51. 51. Elkiran T, Harputluoglu H, Yasar U, Babaoglu MO, Dincel AK, Altundag K, Ozisik Y, Guler N, Bozkurt A. Differential alteration of drug-metabolizing enzyme activities after cyclophosphamide/adriamycin administration in breast cancer patients. Methods and Findings in Experimental and Clinical Pharmacology. 2007;29:27-32
  52. 52. Zhovmer A, Oksenych V, Coin F. Two sides of the same coin: TFIIH complexes in transcription and DNA repair. ScientificWorldJournal. 2010;10:633-643. DOI: 10.1100/tsw.2010.46
  53. 53. Balogh LM, Atkins WM. Interactions of glutathione transferases with 4-hydroxynonenal. Drug Metabolism Reviews. 2011;43:165-178. DOI: 10.3109/03602532.2011.558092
  54. 54. Lee JE, Nakagawa T, Kim TS, Endo T, Shiga A, Iguchi F, Lee SH, Ito J. Role of reactive radicals in degeneration of the auditory system of mice following cisplatin treatment. Acta Oto-Laryngologica. 2004;124:1131-1135
  55. 55. Li W, Yan MH, Liu Y, Liu Z, Wang Z, Chen C, Zhang J, Sun YS. Ginsenoside Rg5 ameliorates Cisplatin-induced nephrotoxicity in mice through inhibition of inflammation, oxidative stress, and apoptosis. Nutrients. 2016;8:E566. DOI: 10.3390/nu8090566
  56. 56. Parrish AR, Chen G, Burghardt RC, Watanabe T, Morisseau C, Hammock BD. Attenuation of cisplatin nephrotoxicity by inhibition of soluble epoxide hydrolase. Cell Biology and Toxicology. 2009;25:217-225. DOI: 10.1007/s10565-008-9071-0
  57. 57. Liu Y, Webb HK, Fukushima H, et al. Attenuation of cisplatin-induced renal injury by inhibition of soluble epoxide hydrolase involves nuclear factor κB signaling. The Journal of Pharmacology and Experimental Therapeutics. 2012;341:725-734. DOI: 10.1124/jpet.111.191247
  58. 58. Decker M, Arand M, Cronin A. Mammalian epoxide hydrolases in xenobiotic metabolism and signalling. Archives of Toxicology. 2009;83:297-318. DOI: 10.1007/s00204-009-0416-0
  59. 59. Fishel ML, Kelley MR. The DNA base excision repair protein Ape1/Ref-1 as a therapeutic and chemopreventive target. Molecular Aspects of Medicine. 2007;28:375-395
  60. 60. Vasko MR, Guo C, Thompson EL, Kelley MR. The repair function of the multifunctional DNA repair/redox protein APE1 is neuroprotective after ionizing radiation. DNA Repair (Amst). 2011;10:942-952. DOI: 10.1016/j.dnarep.2011.06.004
  61. 61. Jiang Y, Guo C, Vasko MR, Kelley MR. Implications of apurinic/apyrimidinic endonuclease in reactive oxygen signaling response after cisplatin treatment of dorsal root ganglion neurons. Cancer Research. 2008;68:6425-6434. DOI: 10.1158/0008-5472.CAN-08-1173
  62. 62. Kim HS, Guo C, Thompson EL, Jiang Y, Kelley MR, Vasko MR, Lee SH. APE1, the DNA base excision repair protein, regulates the removal of platinum adducts in sensory neuronal cultures by NER. Mutation Research. 2015;779:96-104. DOI: 10.1016/j.mrfmmm.2015.06.010
  63. 63. Mukherjea D, Rybak LP. Pharmacogenomics of cisplatin-induced ototoxicity. Pharmacogenomics. 2011;12:1039-1050. DOI: 10.2217/pgs.11.48
  64. 64. Martin LP, Hamilton TC, Schilder RJ. Platinum resistance: The role of DNA repair pathways. Clinical Cancer Research. 2008;14:1291-1295. DOI: 10.1158/1078-0432.CCR-07-2238
  65. 65. Topping RP, Wilkinson JC, Scarpinato KD. Mismatch repair protein deficiency compromises cisplatin-induced apoptotic signaling. The Journal of Biological Chemistry. 2009;284:14029-14039. DOI: 10.1074/jbc.M809303200
  66. 66. Deavall DG, Martin EA, Horner JM, Roberts R. Drug-induced oxidative stress and toxicity. Journal of Toxicology. 2012;2012:645460. DOI: 10.1155/2012/645460
  67. 67. Xu JL, Hu LM, Huang MD, Zhao W, Yin YM, Hu ZB, Ma HX, Shen HB, Shu YQ. Genetic variants of NBS1 predict clinical outcome of platinum-based chemotherapy in advanced non-small cell lung cancer in Chinese. Asian Pacific Journal of Cancer Prevention. 2012;13:851-856
  68. 68. Loh M, Chua D, Yao Y, Soo RA, Garrett K, Zeps N, Platell C, Minamoto T, Kawakami K, Iacopetta B, Soong R. Can population differences in chemotherapy outcomes be inferred from differences in pharmacogenetic frequencies? The Pharmacogenomics Journal. 2013;13:423-429. DOI: 10.1038/tpj.2012.26
  69. 69. Patel JN. Cancer pharmacogenomics: Implications on ethnic diversity and drug response. Pharmacogenetics and Genomics. 2015;25:223-230. DOI: 10.1097/FPC.0000000000000134
  70. 70. Bowden NA. Nucleotide excision repair: Why is it not used to predict response to platinum-based chemotherapy? Cancer Letters. 2014;346:163-171. DOI: 10.1016/j.canlet.2014.01.005
  71. 71. Macerelli M, Ganzinelli M, Gouedard C, Broggini M, Garassino MC, Linardou H, Damia G, Wiesmüller L. Can the response to a platinum-based therapy be predicted by the DNA repair status in non-small cell lung cancer? Cancer Treatment Reviews. 2016;48:8-19. DOI: 10.1016/j.ctrv.2016.05.004
  72. 72. Campbell JM, Bateman E, MDj P, Bowen JM, Keefe DM, Stephenson MD. Fluoropyrimidine and platinum toxicity pharmacogenetics: An umbrella review of systematic reviews and meta-analyses. Pharmacogenomics. 2016;17:435-451. DOI: 10.2217/pgs.15.180
  73. 73. Macciò A, Madeddu C. Cisplatin: An old drug with a newfound efficacy – From mechanisms of action to cytotoxicity. Expert Opinion on Pharmacotherapy. 2013;14:1839-1857. DOI: 10.1517/14656566.2013.813934
  74. 74. Mishmar D, Ruiz-Pesini E, Golik P, Macaulay V, Clark AG, Hosseini S, Brandon M, Easley K, Chen E, Brown MD, Sukernik RI, Olckers A, Wallace DC. Natural selection shaped regional mtDNA variation in humans. Proceedings of the National Academy of Sciences of the United States of America. 2003;100:171-176
  75. 75. Ruiz-Pesini E, Mishmar D, Brandon M, Procaccio V, Wallace DC. Effects of purifying and adaptive selection on regional variation in human mtDNA. Science. 2004;303:223-226

Notes

  • Alternative variant – “genes which are involved in”.

Written By

Andrey Khrunin, Alexey Moisseev, Vera Gorbunova and Svetlana Limborska

Submitted: 30 November 2016 Reviewed: 11 January 2018 Published: 08 February 2018

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Continue reading from the same book

View All
Chapter 17 Novel Systemic Treatments in High Grade Ovarian Ca...

By Amit Samani, Charleen Chan and Jonathan Krell

1295 downloads

Chapter 1 Ovarian Cancer Genetics: Subtypes and Risk Factors

By Jeff Hirst, Jennifer Crow and Andrew Godwin

3268 downloads

Chapter 2 Signaling Pathways Related to Nerve Growth Factor ...

By Carolina Vera, Rocío Retamales-Ortega, Maritza Gar...

1188 downloads