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Informative gene network for chemotherapy-induced peripheral neuropathy

  • Cielito C. Reyes-Gibby1Email author,
  • Jian Wang2,
  • Sai-Ching J. Yeung1 and
  • Sanjay Shete2, 3
Contributed equally
BioData Mining20158:24

https://doi.org/10.1186/s13040-015-0058-0

Received: 23 April 2015

Accepted: 4 August 2015

Published: 12 August 2015

Abstract

Background

Host genetic variability has been implicated in chemotherapy-induced peripheral neuropathy (CIPN). A dose-limiting toxicity for chemotherapy agents, CIPN is also a debilitating condition that may progress to chronic neuropathic pain. We utilized a bioinformatics approach, which captures the complexity of intracellular and intercellular interactions, to identify genes for CIPN.

Methods

Using genes pooled from the literature as a starting point, we used Ingenuity Pathway Analysis (IPA) to generate gene networks for CIPN.

Results

We performed IPA core analysis for genes associated with platinum-, taxane- and platinum-taxane–induced neuropathy. We found that IL6, TNF, CXCL8, IL1B and ERK1/2 were the top genes in terms of the number of connections in platinum-induced neuropathy and TP53, MYC, PARP1, P38 MAPK and TNF for combined taxane-platinum–induced neuropathy.

Conclusion

Neurotoxicity is common in cancer patients treated with platinum compounds and anti-microtubule agents and CIPN is one of the debilitating sequela. The bioinformatic approach helped identify genes associated with CIPN in cancer patients.

Introduction

Chemotherapy-induced peripheral neuropathy (CIPN) is a debilitating condition. CIPN is a dose-limiting toxicity for chemotherapy agents, such as oxaliplatin, cisplatin, and platinum [14]. Chemotherapeutic agents may cause structural damage to peripheral nerves, which can result in aberrant somatosensory processing by the peripheral and/or central nervous system. The symptoms of CIPN vary depending on the type of chemotherapy administered and which nerve fibers are affected. Unusual sensations (paresthesia), numbness, balance problems or pain may result from chemotherapies that affect the sensory nerve fibers. When motor nerves are affected, patients may report weakness of the muscles in the feet and hands.

Patients who suffer from CIPN have a higher risk (as much as threefold higher) of developing neuropathic pain (NP) [5]. Defined as “pain initiated or caused by primary lesion or dysfunction in the nervous system,” NP occurs in nearly 40 % of patients who experience cancer pain [6, 7]. Patients with NP experience higher pain intensity and less effective control of their pain with conventional analgesia [8]. Further, patients with NP rate their level of pain relief to be significantly lower than those with nociceptive pain (defined as pain caused by activation of primary afferents in somatic or visceral tissues) in response to a single dose of an opioid [8, 9]. Patients with NP report twice as many visits to their health care provider (p = 0.02) and take more prescription (50 % versus 19 %; p = 0.001) and over-the-counter medications (62.5 % versus 45 %; p = 0.08) for pain than those without NP [5].

Published guidelines for the initial treatment of NP include the use of gabapentin, pregabalin, carbamazepine, tricyclic antidepressants, oxycodone, morphine, methadone, tramadol, duloxetine, and venlafaxine [10, 11]. However, placebo-controlled trials have shown that medications such as gabapentin [12] and glutamine [13] have no statistically significant effects on NP. Animal and human studies have been conducted to identify the best ways to treat and manage NP [1420]. Because CIPN is a risk factor for the development of NP in cancer patients, a better understanding of the potential biological mechanisms underlying CIPN has huge clinical significance.

Host genetic variability has been implicated in many pain conditions, including neuropathy. Each of these studies assessed different therapeutic agents and different genetic mechanisms. However, it is understood that as a complex trait, several genes are implicated in CIPN. Bioinformatics provides tools for using large-scale information to produce comprehensive networks of genes and the underlying biological pathways implicated in a phenotype. Therefore, in this study, we used the Ingenuity Pathway Analysis (IPA), a bioinformatic tool for analyzing biological data, and performed a comprehensive network-based approach to identify genes implicated in neuropathy induced by chemotherapy agents. Compared to traditional regression approaches, network-based approaches can provide a holistic picture that captures the complexity of intracellular and intercellular interactions in diseases [21]. Furthermore, the network-based approaches can identify genes and pathways related to a disease or phenotype, which will lead to a better understanding of the underlying biological mechanisms [22]. Further, networks generated from IPA core analysis may suggest new candidate genes for future studies of CIPN.

Methods

With the goal of identifying a comprehensive list of genes and potentially novel genes associated with CIPN, we first conducted a literature search as described below. Using genes pooled from the literature as a starting point, we used IPA to generate gene networks for CIPN.

Literature review

Using the PubMed database, we performed a comprehensive literature review, limiting our search to human studies and articles published in English before July 2014. The primary purpose of the literature search was to identify genes associated with CIPN in cancer patients. The terms we used were “cancer neuropathy SNP,” “cancer neuropathy SNPs,” “cancer neuropathy gene,” “cancer neuropathy genes,” “cancer neurotoxicity SNP,” “cancer neurotoxicity SNPs,” “cancer neurotoxicity gene” and “cancer neurotoxicity genes.” We then screened the resulting articles based on the title, abstract, and the full text, and excluded duplicate articles. Next, we manually searched the reference lists of the articles identified in our initial search and those in related review articles to identify additional relevant articles (Table 1). From these studies, we retrieved the information about genes harboring or close to the significantly associated genetic variants (SNPs or haplotypes) and included those genes in the IPA. In particular, we included only those genes for IPA analysis that (1) have been replicated in an independent study or meta-analysis, (2) have at least one SNP that reached the genome-wide significance level, or (3) have a known biological functional significance (e.g., multi-drug resistance, drug metabolism, and mediating developmental events in the nervous system). We also summarized the information based on the different chemotherapy agents used for cancer patients.
Table 1

Number of articles obtained using different search terms

Search terms

# of articles by PubMed search

# of articles by initial screen

# of articles from references

# of articles included

cancer neuropathy SNPs(SNP)

30

20

36

56

cancer neuropathy genes(gene)

266

1

0

1

cancer neurotoxicity SNPs(SNP)

37

6

0

6

cancer neurotoxicity genes(gene)

349

1

0

1

Total

682

28

36

64

Ingenuity pathway analysis

IPA (Ingenuity® Systems, www.ingenuity.com) is a software that connects a list of molecules in a set of networks based on the scientific information contained in the Ingenuity Knowledge Base of biological interactions and functional annotations from millions of relationships between proteins, genes, complexes, cells, tissues, drugs, and diseases [23, 21]. In the networks, nodes are used to represent molecules (e.g., genes, chemicals, protein families, complexes, microRNA species and biological processes) [24] and lines connecting two molecules are used to represent the relationship between them. Many different types of relationships are considered in the IPA analyses, including activation, binding, causation, chemical-chemical interaction, expression enzyme catalysis, inhibition, biochemical modification, protein-protein binding and transcription.

In this study, we utilized the IPA core analysis function to generate relevant networks that identify additional genes that interact with the genes identified from the literature review (denoted as focus genes in IPA). The IPA core analysis function is a process to create networks on the basis of the focus genes [25]. The working hypothesis for network generation is that the biological function involves locally dense interactions; thus, IPA uses an algorithm to attempt to generate networks that are as densely connected as possible [26]. The network generation process first ranks the focus genes in decreasing order on the basis of triangular connectivity, which measures the number of triangular connections in which a gene functions (or pairs of genes to which a gene is connected). The most connected focus gene (the top ranked gene) is considered to be the starting seed gene. Next, the remaining focus genes that are in the neighborhood of the starting seed gene are added to generate the first seed gene network. A neighborhood is defined as a gene plus the genes exactly one connection away from that gene. Then the second seed gene network is identified from the focus genes that are not included in the first seed gene network. The process continues until all focus genes are represented in a relevant network. Subsequently, all smaller networks are combined to make larger networks by connecting seed gene networks through an additional non-focus gene. If the gene network does not reach the maximum network size (140 genes in this study), IPA will then connect additional genes/networks from its database to any of the genes involved in the gene network. Specifically, given a network, to identify additional genes to be added, IPA gives priority to the genes that have the largest overlap with the existing network and have the least number of neighbors. This property is measured using a metric called specific connectivity, which is calculated by dividing the number of genes in the intersection of the neighborhood and the existing network by the union of the number of genes in the neighborhood and the existing network. The gene with the highest specific connectivity score is included in the existing network. Importantly, the IPA analysis can exclude a focus gene from the resulting network if such a gene is less likely to have connections (i.e., biological relationships) with the network.

The resulting functions/pathways/networks are evaluated using the right-tailed Fisher’s exact test, which provides p values based on the null hypothesis that the association between a set of focus genes and a given function/pathway/network is due to random chance [25]. Specifically, if the final network includes n genes and n f of them are focus genes, the p value is the probability of finding n f or more focus genes in a set of n genes randomly selected from the IPA pre-specified database [26]. A score, which is assessed as -log10(p value), is used to rank the resulting functions/pathways/networks. We used a significance level of <10−5 in our study (score > 5) when selecting networks [21].

We limited the IPA analysis to human studies. In the IPA core analysis, we used the Ingenuity Knowledge Base as the reference set. In order to generate networks in the core analysis, we used the settings of a maximum of 140 genes per network and 25 networks per analysis, because the networks for up to 140 genes allow for the possibility that the same network can include all focus genes [27]. We reported the most interconnected genes in the networks as the key genes of interest, because highly connected molecules (called hubs) are typically associated with biological functions or diseases [22, 24, 21, 26, 27].

Results

Literature review

From our search of the PubMed database, we initially identified 682 articles. After screening the title, abstract and full text, we excluded 654 articles for the following reasons (Table 1): (1) not human studies; (2) not published in English; (3) meta-analysis study, review or letter to the editor; (4) clinical trial studies; (5) not genetic association studies; (6) not neuropathy-related phenotypes studies; (7) not cancer studies; and (8) duplicate articles from different searches. We then manually searched the reference lists from the resulting 28 articles and from related review articles about genetic neuropathy studies, and identified 36 more articles. As a result, we had a total of 64 articles from which we extracted information to identify the focus genes and perform the analyses through IPA.

Table 2 lists the information we retrieved from each of the studies, including the year of publication, first author, ethnicity of patient population, cancer type, sample size, phenotypes, and significant genes. These studies included different cancer sites and patients of different ethnic groups. Neuropathy (or neurotoxicity) in cancer patients is usually induced by the chemotherapy agents used in cancer treatment, such as oxaliplatin, cisplatin, and platinum, and is usually measured according to the National Cancer Institute’s Common Terminology Criteria for Adverse Events or Common Toxicity Criteria.
Table 2

List of genetic association studies for chemotherapy-induced neuropathy in cancer patients, sorted by publication year and name of first author

Year

First author

Ethnicity

Cancer type

Sample size

Phenotype

Significant genes

2003

Aplenc R [41]

W, AA, H

Acute lymphoblastic leukemia

533

Peripheral neuropathy

CYP3A4, CYP3A5

2004

Isla D [42]

W

Lung

62

Docetaxel-cisplatin-treated neurological

None

2006

Lecomte T [43]

W

Gastrointestinal solid tumors

64

Oxaliplatin-related cumulative neuropathy

GSTP1

2006

Sissung TM [44]

W

N/A

26

Paclitaxel-induced neuropathy

ABCB1

2007

Gamelin L [45]

W

Colon, rectum

145

Oxaliplatin-induced neurotoxicity

AGXT

2007

Marsh S [46]

N/A

Ovarian

914

Paclitaxel/docetaxel-induced neuropathy

None

2007

Oldenburg J [47]

W

Testicular

238

Self-reported chemotherapy-induced long-term toxicities

GSTP1

2007

Ruzzo A [48]

W

Colorectal

166

Oxaliplatin-induced neurotoxicity

GSTP1

2008

Keam B [49]

A

Gastric

73

Peripheral sensory neuropathy

None

2008

Pare L [50]

W

Colorectal

126

Cumulative oxaliplatin-induced neuropathy

None

2008

Sissung TM [51]

N/A

Prostate

73

Docetaxel-induced neuropathy

ABCB1

2009

Argyriou AA [52]

W

Colorectal

62

Oxaliplatin-induced peripheral neuropathy

None

2009

Goekkurt E [53]

W

Gastric

134

Neurotoxicity

GSTP1

2009

Green H [54]

W

Ovarian

38

Sensory/motor neuropathy

None

2009

Kim HS [55]

A

Epithelial ovarian

118

Taxane/platinum- induced neurotoxicity

ERCC1

2009

Kweekel DM [56]

W

Colorectal

91

Neurotoxicity

None

2009

Mir O [57]

W

Breast, lung, prostate

58

Docetaxel(Taxotere)-induced peripheral neuropathy

GSTP1

2009

Seo BG [58]

A

Gastric

94

Neuropathy

None

2010

Antonacopoulou AG [59]

W

Colorectal

55

Chronic oxaliplatin-induced peripheral neuropathy

ITGB3

2010

Boige V [60]

W

Colorectal

349

FOLFOX-induced severe neurologic toxicity

None

2010

Chen YC [61]

A

Colorectal

166

Oxaliplatin-induced chronic cumulative neuropathy

GSTP1

2010

Cho HJ [62]

A

Diffuse large B-cell lymphoma

94

Chemotherapy-related neurotoxicity

None

2010

Inada M [63]

A

Colorectal

51

Oxaliplatin-induced peripheral neuropathy

ERCC1, GSTP1

2010

Kanai M [64]

A

Colorectal

82

Early-onset oxaliplatin-induced neuropathy

None

2010

Khrunin AV [65]

W

Ovarian

104

Cisplatin-based neuropathy

GSTM1, GSTM3

2010

Li QF [66]

A

Gastric

92

Neurological toxicity

GSTP1

2010

McLeod HL [67]

W, A, AA, H

Metastatic colorectal

520

Diarrhea, vomiting, paresthesia, febrile neutropenia and neutropenia

GSTP1

2010

Ofverholm A [68]

W

Breast, ovarian

36

Occurrence and degree of neurotoxicity

None

2010

Rizzo R [69]

W

Breast

95

Taxane-induced hypersensitivity and sensory neuropathy

None

2011

Basso M [70]

W

Colorectal, pancreatic, bile ducts

40

Acute oxaliplatin neurotoxicity

SK3

2011

Bergmann TK [71]

W

Ovarian

119

Sensory neuropathy

None

2011

Bergmann TK [72]

W

Ovarian

92

Sensory neuropathy

None

2011

Broyl A [73]

W

Multiple myeloma

369

Bortezomib/vincristine-induced peripheral neuropathy

RHOBTB2, CPT1C, SOX8, caspase 9, ALOX12, IGF1R, SOD2, MYO5A, MBL2, PPARD, ERCC4, ERCC3, AURKA, MKI67, GLI1, DPYD, ABCC1

2011

Cibeira MT [74]

W

Multiple myeloma

28

Thalidomide-induced peripheral neuropathy

GSTT1

2011

Corthals SL [75]

W

Multiple myeloma

238

Bortezomib induced peripheral neuropathy

CYP17A1

2011

Favis R [76]

W

Myeloma

139

Bortezomib-induced peripheral neuropathy

CTLA4, PSMB1, CTSS, GJE1, DYNC1I1, TCF4

2011

Hong J [77]

A

Colorectal

52

Sensory neuropathy

GSTP1

2011

Johnson DC [78]

W

Multiple myeloma

1495

Thalidomide-related peripheral neuropathy

ABCA1, ICAM1, PPARD, SERPINB2, SLC12A6

2011

Leskela S [79]

W

Lung, breast, ovary, uterus, head and neck

118

Neurotoxicity

CYP2C8, CYP3A5

2011

Sucheston LE [80]

W, AA

Breast

888

Taxane-induced neurotoxicity

FANCD2

2012

Baldwin RM [81]

W, AA, A

Breast

855

Paclitaxel induced peripheral sensory neuropathy

FGD4, FZD3, EPHA5

2012

Braunagel D [82]

W

Acute myeloid leukemia

360

Cytarabine-induced neurotoxicity

NME1

2012

Fung C [83]

W, A, AA, H

Testicular germ cell tumor

137

Cisplatin-induced neurotoxicity, peripheral neuropathy

None

2012

Hasmats J [84]

W

Ovarian, lung, carcinoma in uteri/peritoneal/breast

94

Paclitaxel/carboplatin-induced neuropathy

ABCA1

2012

Hertz DL [85]

W, AA

Breast

111

Peripheral neuropathy

CYP2C8

2012

Leandro-Garcia LJ [86]

W

Ovary, lung, breast

214

Paclitaxel-induced peripheral neuropathy

TUBB2A

2012

Won HH [87]

A

Colon

96

Severe oxaliplatin-induced chronic peripheral neuropathy

TAC1, FOXC1, GMDS, ITGA1, PELO, ACYP2, TSPYL6, DLEU7, BTG4, POU2AF1, CAMK2N1, FARS2, LYRM4

2013

Argyriou AA [88]

W

Colorectal

200

Oxaliplatin-induced peripheral neuropathy

SCN4A, SCN10A

2013

Bergmann TK [89]

W

Ovarian

241

Paclitaxel induced neuropathy

None

2013

Cecchin E [90]

W

Colorectal

144

Oxaliplatin neurotoxicity

ABCC1, ABCC2

2013

de Graan AJ [91]

W

Esophagus, ovary, cervix, endometrial, breast, lung, head/neck

261

Paclitaxel-induced neurotoxicity

CYP3A4

2013

Hertz DL [92]

W, AA

Breast

209

Paclitaxel-induced neuropathy

CYP2C8

2013

Kumamoto K [93]

A

Colorectal

63

Oxaliplatin-induced sensory peripheral neuropathy

GSTP1, GSTM1

2013

Leandro-Garcia LJ [94]

W

Ovary, fallopian tube, peritoneum, lung, uterus, breast

144

Paclitaxel induced peripheral sensory neuropathy

EPHA4, EPHA6, EPHA5, XKR4, LIMK2

2013

Lee KH [95]

A

Colon

292

Sensory neuropathy

XRCC1

2013

Liu YP [96]

A

Gastric

126

Oxaliplatin-induced neurotoxicity

GSTP1

2013

McWhinney-Glass S [97]

N/A

Ovarian

404

Platinum/taxane-induced neurotoxicity

SOX10, BCL2, OPRM1, TRPV1

2013

Oguri T [98]

A

Colorectal

70

Oxaliplatin-induced chronic peripheral neurotoxicity

ACYP2, FARS2, ERCC1, TAC1

2014

Abraham JE [99]

W

Breast

1303

Taxane-related sensory neuropathy

ABCB1, TUBB2A, CYP2C8, ABCC2, CYP1B1, KIAA0146-PRKD, SLCO1B1, EPHA6

2014

Bhojwani D [100]

N/A

Acute lymphoblastic leukemia

369

Methotrexate-induced neurotoxicity

ASTN2, PXDC1, IYD

2014

Custodio A [101]

W

Colon

206

Oxaliplatin-induced peripheral neuropathy

CCNH, ABCG2

2014

Hertz DL [102]

W, AA, A

Breast

412

Paclitaxel-induced peripheral neuropathy

CYP2C8, ABCG1

2014

Khrunin AV [103]

W

Ovarian

104

Cisplatin-based neurotoxicity

None

2014

Lee SY [104]

A

Breast

85

Paclitaxel and gemcitabine combination chemotherapy neurotoxicity

RRM1

W: White; A: Asian; AA: African American; H: Hispanic

In Table 3, we summarize the focus genes from the literature review with respect to neuropathy induced by different chemotherapy agents, including platinum, taxane, platinum/taxane, Bortezomib, bortezomib/vincristine, thalidomide, methotrexate, cytarabine, platinum/fluorouracil, platinum/S-1 (i.e., oral fluoropyrimidine consists of tegafur, 5-chloro-2,4 dihydroxypyrimidine, and potassium oxonate), taxane/gemcitabine, platinum/fluorouracil/leucovorin, platinum/fluorouracil/irinotecan, prednisone/vincristine/methotrexate, platinum/capecitabine, platinum/fluorouracil/irinotecan/leucovorin and rituximab/cyclophosphamide/doxorubicin/vincristine/prednisone. Among the different (or combined) chemotherapy agents, those studied most frequently in relation to drug-induced neuropathy were platinum, taxane and the combination of platinum/taxane, for which our literature search respectively produced 21, 19 and 5 related papers.
Table 3

Summary of genes associated with chemotherapy agent-specified neuropathy from the literature review. Number of papers for each agent-specified neuropathy, number of genes associated with each agent-specified neuropathy and number of agent-specified neuropathies associated with each gene are shown. For the association between a gene and an agent-specified neuropathy, the number of relating papers is listed

 

Agent

P

T

P/T

B

B/V

Th

M

Cyt

P/F

P/S

T/G

P/F/L

P/F/I

Pr/V/M

P/C

P/F/I/L

R/Cyc/D/V/Pr

Genes

# of papers

21

19

5

2

1

2

1

1

2

1

1

2

2

1

1

1

1

(IPA symbols)

# of genes

26

19

7

7

17

6

3

1

1

1

1

2

1

2

0

0

0

 

# of agents

                 

GSTP1

6

7

1

      

1

1

 

1

1

    

ERCC1

2

2

 

1

              

ACYP2

1

2

                

FARS2

1

2

                

GSTM1

1

2

                

TAC1

1

2

                

ABCC2

2

1

1

               

ABCC1

2

1

                

ABCG2

1

1

                

AGXT

1

1

                

BTG4

1

1

                

CAMK2N1

1

1

                

CCNH

1

1

                

DLEU7

1

1

                

FOXC1

1

1

                

GMDS

1

1

                

GSTM3

1

1

                

ITGA1

1

1

                

ITGB3

1

1

                

KCNN3

1

1

                

LYRM4

1

1

                

PELO

1

1

                

POU2AF1

1

1

                

SCN10A

1

1

                

SCN4A

1

1

                

TSPYL6

1

1

                

CYP2C8

2

 

5

1

              

ABCB1

1

 

3

               

EPHA5

1

 

2

               

EPHA6

1

 

2

               

TUBB2A

1

 

2

               

CYP3A4

2

 

1

           

1

   

CYP3A5

2

 

1

           

1

   

ABCG1

1

 

1

               

CYP1B1

1

 

1

               

EPHA4

1

 

1

               

FANCD2

1

 

1

               

FGD4

1

 

1

               

FZD3

1

 

1

               

LIMK2

1

 

1

               

SLCO1B1

1

 

1

               

SPIDR

1

 

1

               

XKR4

1

 

1

               

ABCA1

2

  

1

  

1

           

BCL2

1

  

1

              

OPRM1

1

  

1

              

SOX10

1

  

1

              

TRPV1

1

  

1

              

CTLA4

1

                 

CTSS

1

                 

CYP17A1

1

                 

DYNC1I1

1

                 

GJC3

1

                 

PSMB1

1

                 

TCF4

1

                 

PPARD

2

     

1

           

ALOX12

1

    

1

            

AURKA

1

    

1

            

CASP9

1

    

1

            

CPT1C

1

    

1

            

DPYD

1

    

1

            

ERCC3

1

    

1

            

ERCC4

1

    

1

            

GLI1

1

    

1

            

IGF1R

1

    

1

            

MBL2

1

    

1

            

MKI67

1

    

1

            

MYO5A

1

    

1

            

RHOBTB2

1

    

1

            

SOD2

1

    

1

            

SOX8

1

    

1

            

GSTT1

1

     

1

           

ICAM1

1

     

1

           

SERPINB2

1

     

1

           

SLC12A6

1

     

1

           

ASTN2

1

      

1

          

IYD

1

      

1

          

PXDC1

1

      

1

          

NME1

1

       

1

         

RRM1

1

          

1

      

XRCC1

1

           

1

     

P: Platinum; T: Taxane; P/T: Platinum/Taxane; B: Bortezomib; B/V: Bortezomib/Vincristine; Th: Thalidomide; M: Methotrexate; Cyt: Cytarabine; P/F: Platinum/Fluorouracil; P/S: Platinum/S-1; T/G: Taxane/Gemcitabine; P/F/L: Platinum/Fluorouracil/Leucovorin; P/F/I: Platinum/Fluorouracil/Irinotecan; Pr/V/M: Prednisone/Vincristine/Methotrexate; P/C: Platinum/Capecitabine; P/F/I/L: Platinum/Fluorouracil/Irinotecan/Leucovorin; R/Cyc/D/V/Pr: Rituximab/Cyclophosphamide/Doxorubicin/Vincristine/Prednisone

Among the focus genes reported in the articles, GSTP1, CYP2C8 and ABCB1 were studied the most frequently (Table 4). ABCC2 and GSTP1 were associated with both platinum- and taxane-induced neuropathy; CYP2C8 was associated with both taxane- and platinum/taxane-induced neuropathy; and ERCC1 was associated with platinum- and platinum/taxane-induced neuropathy. Besides platinum-, taxane- and platinum/taxane- induced neuropathy, neuropathy induced by other chemotherapy agents were not frequently studied. Therefore, we focused on the genes associated with platinum-, taxane- and platinum/taxane-induced neuropathy in our analyses.
Table 4

Focus genes* associated with platinum-, taxane-, and platinum/taxane- induced neuropathy, as identified through the literature review

Platinum-induced neuropathy

Taxane-induced neuropathy

Platinum/Taxane-induced neuropathy

ABCC1

ABCB1

ABCA1

ABCC2

ABCC2

BCL2

ABCG2

ABCG1

CYP2C8

ACYP2

CYP1B1

ERCC1

AGXT

CYP2C8

OPRM1

BTG4

CYP3A4

SOX10

CAMK2N1

CYP3A5

TRPV1

CCNH

EPHA4

 

DLEU7

EPHA5

 

ERCC1

EPHA6

 

FARS2

FANCD2

 

FOXC1

FGD4

 

GMDS

FZD3

 

GSTM1

GSTP1

 

GSTM3

LIMK2

 

GSTP1

SLCO1B1

 

ITGA1

SPIDR

 

ITGB3

TUBB2A

 

KCNN3

XKR4

 

LYRM4

  

PELO

  

POU2AF1

  

SCN10A

  

SCN4A

  

TAC1

  

TSPYL6

  

*Genes shown to be significant based on the literature

IPA core analysis

We performed the IPA core analysis for the focus genes reported to be associated with platinum-, taxane- and platinum/taxane- induced neuropathy. The significant networks revealed from the IPA core analyses are shown in Figs. 1, 2 and 3 for the focus genes reported to be associated with platinum-, taxane- and platinum/taxane- induced neuropathy, respectively. In the networks, the solid and dashed edges or arrows indicate direct and indirect interactions, respectively. In Table 5, we report the genes that had at least 15 connections (i.e., hubs, suggesting biological importance) in the networks, ranked by the number of connections for each gene.
Fig. 1

The most significant network (p value = 10−12) generated by IPA core analysis for 26 focus genes associated with platinum-induced neuropathy. Green: focus genes; red: genes with at least 15 connections; yellow: focus genes with at least 15 connections. Dashed and solid lines represent indirect and direct interactions, respectively

Fig. 2

The most significant networks (p values = 10−9 and 10−8) generated by IPA core analysis for 19 focus genes associated with taxane-induced neuropathy. Green: focus genes. Dashed and solid lines represent indirect and direct interactions, respectively. a network 1 (p values = 10−9). b network 2 (p values = 10−8)

Fig. 3

The most significant network (p value = 10−8) generated by IPA core analysis for 7 focus genes associated with platinum/taxane-induced neuropathy. Green: focus genes; red: genes with at least 15 connections; yellow: focus genes with at least 15 connections. Dashed and solid lines represent indirect and direct interactions, respectively

Table 5

List of genes with at least 15 connections (i.e., hubs*) in the networks, ranked by the number of connections for each gene

Platinum-induced CIPN

Platinum/taxane-induced CIPN

IPA Symbol

# of connections

IPA Symbol

# of connections

IL6

70

TP53

42

TNF

69

BCL2**

28

CXCL8

56

MYC

16

IL1B

55

PARP1

16

ERK1/2

54

P38 MAPK

15

VEGFA

52

TNF

15

MAPK1

51

  

NFkB (complex)

46

  

P38 MAPK

45

  

TGFB1

43

  

COL18A1

42

  

CCL2

39

  

IFNG

38

  

PTGS2

37

  

ERK

34

  

TP53

34

  

MAPK3

33

  

Akt

32

  

STAT3

30

  

CD3

29

  

JUN

29

  

PI3K (complex)

29

  

EGFR

28

  

MMP1

28

  

HGF

27

  

Jnk

27

  

CCL5

26

  

CD40

26

  

IL1A

26

  

ITGB1**

26

  

MMP2

25

  

Cg

24

  

FN1

24

  

RELA

24

  

TLR4

23

  

Vegf

23

  

CXCL10

22

  

EGF

21

  

ITGB3

21

  

MAPK14

21

  

NFKBIA

21

  

SP1

21

  

STAT1

21

  

AKT1

20

  

HIF1A

20

  

SRC

20

  

TERT

20

  

Pkc(s)

19

  

CTNNB1

18

  

Focal adhesion kinase

18

  

FOS

18

  

HDAC1

18

  

IgG

18

  

ITGAV

18

  

NFKB1

18

  

CD44

17

  

FGF2

17

  

Lh

17

  

MAPK8

17

  

SYK

17

  

Ap1

16

  

CCND1

16

  

IGF1

16

  

PRKCD

16

  

TREM1

16

  

OSM

15

  

*Suggests biological importance

**Focus genes

Platinum-induced neuropathy

The IPA core analysis revealed six networks associated with platinum-induced neuropathy. Using a nominal significance level of 10−5, of the 6 networks, we found only one network to be significant (p value of 10−12; Fig. 1. We note that 66 genes (one focus gene and 65 “novel” genes) out of 121 genes in the network have at least 15 connections (Table 5), suggesting the potential biological importance of these genes in CIPN associated with platinum-based chemotherapy. The gene ITGB3 was the only focus gene in the network, and the top 5 “novel” genes were IL6, TNF, CXCL8, IL1B and ERK1/2.

Taxane-induced neuropathy

The IPA core analysis for taxane-induced neuropathy revealed eight networks, two of which were significant, with p values of 10−9 and 10−8 (Fig. 2). There is no hub in the network generated by the IPA core analysis of the focus genes reported to be associated with taxane-induced neuropathy.

Platinum/taxane-induced neuropathy

The IPA core analysis for platinum/taxane-induced neuropathy identified three networks, one of which was significant, with a p value of 10−8 (Fig. 3). We note that 6 genes (one focus gene and 5 additional “novel” genes) out of 48 genes in the network have at least 15 connections. The gene BCL2 is the only focus gene included in the network that has more than 15 connections. The 5 additional genes that directly or indirectly interact with the corresponding focus genes associated with platinum/taxane-induced neuropathy based on the literature are TP53, MYC, PARP1, P38 MAPK and TNF.

Discussion

In this study, we performed a comprehensive literature review to identify genes implicated in CIPN and then used IPA bioinformatic tools to conduct comprehensive pathway and network analyses of the known genes identified in the literature. Neurotoxicity is common in cancer patients who are treated with platinum compounds and anti-microtubule agents, and the development of CIPN is a potentially debilitating sequela. From the literature review, we found that neuropathy induced by platinum compounds and taxanes (and a combination of these two agents) has been studied most frequently. Neuropathy induced by chemotherapy agents other than platinum, taxane and platinum/taxane combinations has not been adequately studied.

Among the focus genes identified from our literature search, GSTP1, CYP2C8 and ABCB1 were most frequently assessed as candidates for CIPN. From the literature review, we also found that the genomic variations of genes associated with neuropathy induced by platinum versus taxane compounds were different. For example, GSTP1, ERCC1, ACYP2, FARS2, GSTM1 and TAC1 were found to be associated with platinum-induced neuropathy in more than one study but were not associated with taxane-induced neuropathy. On the other hand, CYP2C8, ABCB1, EPHA5, EPHA6 and TUBB2A were found to be associated with taxane-induced neuropathy in more than one study, but not to be associated with platinum-induced neuropathy (Table 3). The overall theme is that these CIPN-associated genes are related to the networks that regulate intracellular drug concentrations (e.g., GSTP1, GSTM1 and ABCB1), response to DNA damage (e.g., ERCC1, FANCD2, BCL2, and SOX10), cellular stress response pathways (e.g., BCL2), inflammation (e.g., ABCC1, ABCC2, ABCG2, ITGA1, ITGB3, TAC1, ABCB1, ABCC2, EPHA4, EPHA6, SLCO1B1, TUBB2A, ABCA1, BCL2, OPRM1 and TRPV1), and neuronal plasticity (e.g., ERCC1 and TAC1).

We performed IPA core analysis for the genes associated with platinum-, taxane- and platinum/taxane-induced neuropathy. We found that IL6, TNF, CXCL8, IL1B and ERK1/2 were the top genes in terms of the number of connections in platinum-induced neuropathy, suggesting either direct or indirect interactions with nervous tissue leading to CIPN after exposure to platinum compounds. It is particularly interesting that studies of pain in cancer patients have shown the importance of cytokine genes [2837] including IL6, TNF and IL1B polymorphisms. These studies hypothesized that cytokines associated with inflammation or tissue damage modify the activity of nociceptors, which contributes to pain hypersensitivity. Studies also suggest that hyperexcitability in pain transmission neurons may also be caused by proinflammatory cytokines produced by glial cells that respond to inflammation or other cancer-produced cytokines. Substance P and excitatory amino acids released from presynaptic terminals result to an exaggerated pain response [38, 39]. In patients with lung cancer, polymorphisms in TNF and IL6 were significantly associated with pain severity (for TNF, GG = 4.12; GA = 5.38; AA = 5.50; p = 0.04) and with morphine-equivalent daily dose (IL-6, GG = 69.61; GC = 93.6; CC = 181.67; p = 0.004) [36]. An additive effect of mutant alleles in IL1B T-31C (odds ratio = 0.55, 95 % confidence interval = (0.31, 0.97)) was also found to be associated with high intensity of pain, depressed mood and fatigue in lung cancer patients [31].

In addition to the top connections in the networks, the overall biological processes involved in the networks help us to better understand the gene-phenotype association. The IPA core analysis is a process for creating molecule networks on the basis of focus genes, which are genes associated with the phenotypes of interest. Because all the focus and non-focus genes in the network have inter-connected relationships, it provides a list of novel candidate genes associated with the phenotype. The network also provides a clearer picture of the (possibly interacting) genes that might be directly or indirectly associated with chemotherapy-induced peripheral neuropathy. The most significant network generated by IPA core analysis for the focus genes associated with platinum-induced neuropathy (Fig. 1) contains genes for inflammation (multiple interleukins, TNF, IFNG, STAT3, STAT1), DNA damage response (TP53) and cell survival (MAPK, JUN, ERK, NFkB). Network 2, which relates to taxane-induced neuropathy (Fig. 2b), includes many genes that are involved in the DNA damage response. The network related to neuropathy induced by combined platinum and taxane therapy (Fig. 3) resembles Fig. 1 in terms of the cellular functions involved, i.e., inflammation, DNA damage response and cell survival. The major commonality among Figs. 1, 2b and 3 is TP53, which is a central hub in these three networks. Network 1, which relates to taxane-induced neuropathy (Fig. 2a), primarily involves drug metabolizing enzymes and transporter proteins that will affect the intracellular concentration of taxanes. These analyses suggest that genetic variations in the DNA damage response are associated with the risk of developing CIPN, and that taxane-induced neuropathy is also affected by genetic variations that regulate intracellular drug levels while this aspect may not be important for platinum compounds.

This bioinformatic approach to expanding gene networks and identifying connection hubs has limitations. First, many proteins do not interact, while others may connect to major hubs that interact with hundreds of genes and proteins. Therefore, it is believed that the degree of connectivity obeys a power law, which means that the network is scale-free, a desired property. However, we found that the IPA metric/algorithm that generates networks does not guarantee that the resulting networks are scale-free, even though the networks may exhibit certain scale-free behavior in which the major hubs are closely followed by smaller ones that have less connectivity, and the smaller hubs are then followed by other nodes with an even smaller degree of connectivity, and so on (see Figs. 1 and 3). Furthermore, the IPA algorithm that generates networks will not continue if the network reaches the pre-specified maximum network size (i.e., 140 genes), which might rule out many nodes with small degrees of connectivity and impact the scale-free behavior. We employed a widely used log-log plot to investigate whether the networks in Figs. 1 and 3 follow the power law [24, 40]. The log-log plot should appear as a decaying straight line if the network obeys the power law, which was not observed in our plot. Therefore, we cannot conclude that the resulting networks are scale-free.

Further limitations could be that the connections may be specific to certain tissues or physiological contexts that are not applicable to CIPN. Many of the connections have not been demonstrated in neural tissue. Nevertheless, this network analysis identified biological processes that are relevant to the mechanism of neuropathy induced by platinum compounds and taxanes, thus providing the basis for future studies of the genes involved in these biological processes. Our study has not discovered any pathways involved in pain perception. Perhaps, due to the fact that many studies in the literature were done as focused search for SNP associations in a relatively small set of genes in pre-selected pathways, such as glutathione, DNA repair, cell cycle, apoptosis, cell signaling, and metabolism. Whether new gene sequencing technology can discover genetic markers associated with differences in neuropathic pain perception remains to be seen. In conclusion, our study has shown putative genes associated with CIPN. Future studies will include the selection of pharmacogenomic panel tests that will help identify patients at risk for CIPN and the routine incorporation of such panels into clinical practice.

Notes

Declarations

Acknowledgements

This work was supported by National Institutes of Health grant R01DE022891 (CCR and SS), 1R01CA131324 (SS), R25DA026120 (SS), R03CA192197 (JW) and the Cancer Prevention Research Institute of Texas grant RP130123 (SS). This research was also supported in part by the Barnhart Family Distinguished Professorship in Targeted Therapy (SS) and the National Cancer Institute grant CA016672.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Emergency Medicine, The University of Texas MD Anderson Cancer Center
(2)
Department of Biostatistics, The University of Texas MD Anderson Cancer Center
(3)
Department of Epidemiology, The University of Texas MD Anderson Cancer Center

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