Open Access

Ion channels expression and function are strongly modified in solid tumors and vascular malformations

  • Antonella Biasiotta1,
  • Daniela D’Arcangelo2,
  • Francesca Passarelli2,
  • Ezio Maria Nicodemi2Email author and
  • Antonio Facchiano2Email author
Contributed equally
Journal of Translational Medicine201614:285

https://doi.org/10.1186/s12967-016-1038-y

Received: 31 May 2016

Accepted: 21 September 2016

Published: 4 October 2016

Abstract

Background

Several cellular functions relate to ion-channels activity. Physiologically relevant chains of events leading to angiogenesis, cell cycle and different forms of cell death, require transmembrane voltage control. We hypothesized that the unordered angiogenesis occurring in solid cancers and vascular malformations might associate, at least in part, to ion-transport alteration.

Methods

The expression level of several ion-channels was analyzed in human solid tumor biopsies. Expression of 90 genes coding for ion-channels related proteins was investigated within the Oncomine database, in 25 independent patients-datasets referring to five histologically-different solid tumors (namely, bladder cancer, glioblastoma, melanoma, breast invasive-ductal cancer, lung carcinoma), in a total of 3673 patients (674 control-samples and 2999 cancer-samples). Furthermore, the ion-channel activity was directly assessed by measuring in vivo the electrical sympathetic skin responses (SSR) on the skin of 14 patients affected by the flat port-wine stains vascular malformation, i.e., a non-tumor vascular malformation clinical model.

Results

Several ion-channels showed significantly increased expression in tumors (p < 0.0005); nine genes (namely, CACNA1D, FXYD3, FXYD5, HTR3A, KCNE3, KCNE4, KCNN4, CLIC1, TRPM3) showed such significant modification in at least half of datasets investigated for each cancer type. Moreover, in vivo analyses in flat port-wine stains patients showed a significantly reduced SSR in the affected skin as compared to the contralateral healthy skin (p < 0.05), in both latency and amplitude measurements.

Conclusions

All together these data identify ion-channel genes showing significantly modified expression in different tumors and cancer-vessels, and indicate a relevant electrophysiological alteration in human vascular malformations. Such data suggest a possible role and a potential diagnostic application of the ion–electron transport in vascular disorders underlying tumor neo-angiogenesis and vascular malformations.

Keywords

CancerIon-channelsAutonomic nervous systemSympathetic skin responseSSRFlat port-wine stains

Background

Several key cellular functions are related to transmembrane potentials and lie under the control of ion channels, pumps and gap junction complexes. Controlling transmembrane voltage represents a fundamental process in many physiologically relevant steps, including cell cycle progression [1] and different forms of cell death [2, 3]. Over expression or increased activity of ion channels has been demonstrated as a response to mitogens exposure [46]. Several studies show a direct link between the transmembrane ion flow and carcinogenesis [7, 8]. However, as pointed out [9], the role membrane potential plays in the pathogenesis of several disorders, including cancer, is still not well understood. Plasma membrane de-polarization has a pivotal role at different stages of cell cycle progression and in various cell types [9]. Namely, endothelial cells hyper-polarization has been shown to contribute to cell division arrest [10], and channels are known to control migratory cellular properties in wound healing [11]. Further, Ca2+, K+ and Cl channels are essential regulators of cell proliferation and cancer development [1216]. As recently further demonstrated, several ion-channels are directly involved in controlling tumor—[17] as well as non-tumor angiogenesis [18]. Expression and activity of TRPV4 channel have been found suppressed in tumor endothelium [19], and its activation has been found to normalize tumor vessels [20]; inhibiting Cl channel activity has anti-angiogenesis and anti-glioma properties [21]; finally, human voltage-dependent K+ channel has been found associated with cancer aggressiveness and angiogenesis [22]. Therefore, ion-channels play a fundamental role in cancer progression as well as in angiogenesis.

Flat port-wine stains are non-tumor malformations of the skin capillaries [23]. Cutaneous capillary malformations are usually isolated finding. However, they may occasionally coexist with cerebral or ocular vascular malformations, constituting the rare sporadic neurocutaneous Sturge-Weber syndrome (SWS) affecting the cephalic microvasculature, or may represent signs of more aggressive vascular malformations or even vascular tumors.

The sympathetic skin response (SSR) is an alteration in skin electrical potential evoked by strong stimuli; it consists of a multineuronal reflex activated by a variety of afferent inputs where the efferent branches involve sympathetic sudomotor fibers. The electrodermal activity reflects sympathetic cholinergic sudomotor function which induces changes in skin resistance to electrical conduction. The response is mediated by ions flux via activation of receptor-coupled Ca2+, Cl and K+ channels [24]. Since SSR reflects peripheral C fibers activity, it is considered a reliable quantitative measure of sympathetic function and dysfunction as well as in polyneuropathies and dysautonomic disorders [2527].

We have previously shown novel serum markers able to indicate cardiovascular diseases, [28, 29] as well as soluble factors able to affect angiogenesis [30] and to discriminate infantile hemangioma from more aggressive vascular malformations or tumors [31]. We also investigated novel molecular markers of melanoma set-up and progression [32].

In the present study, we further addressed the issue of altered angiogenesis in tumor and non-tumor conditions. The expression level of 90 ion-channel genes was investigated in five different solid tumors, having a different histological origin. The expression level of several ion-channels genes was found to be strongly modified; we thus hypothesized that ion-transport may represent a measurable sign of the altered underlying angiogenesis. We, therefore, measured in vivo the ion-channel function in a human vascular malformation model, namely flat port-wine stains, as a model to test electrical-stimuli transport in a human vascular disorder accepted by the Ethic Committee.

Methods

Ion-channel gene expression investigation

Gene expression levels were investigated by accessing human cancer datasets available at Oncomine (http://www.oncomine.org). The current Oncomine version contains several hundred different patients-datasets, referring to tumors biopsies obtained from almost any histological source; unfortunately vascular tumors (such as hemangioma, angiomas, hemangioendothelioma, angiosarcoma) are lacking from such database. In the current study 25, independent datasets from histologically different solid tumors were investigated, namely, bladder cancer, glioblastoma, melanoma, breast cancer, lung adenocarcinoma, as indicated in details in Table 1.
Table 1

Tumors types, datasets names, patients numerosity and reference of each dataset investigated in the present study, from oncomine database (http://www.oncomine.org)

 

Tumor type and dataset name

No of control samples

No of cancer samples

References n.

Superficial bladder cancer

 1

Dyrskjot dataset

14

28

[86]

 2

Lee dataset

68

126

[87]

 3

Sanchez dataset

48

28

[88]

 4

Blaveri dataset

2

25

[89]

Glioblastoma

 5

Lee dataset

3

78

[90]

 6

Bredel dataset

4

26

[91]

 7

Sun dataset

23

81

[92]

 8

Murat dataset

4

80

[93]

Melanoma

 9

Talantov dataset

7

45

[94]

 10

Riker dataset

5

14

[95]

 11

Critchley dataset

23

23

[96]

 12

Haqq dataset

3

23

[97]

Breast invasive ductal cancer

 13

Ma dataset

28

18

[98]

 14

Curtis dataset

144

1556

[99]

 15

Radvanji dataset

5

26

[100]

 16

Turashvi dataset

20

5

[101]

 17

Zhao dataset

4

154

[102]

Lung adenocarcinoma

 18

Bhattacharjee dataset

17

139

[103]

 19

Beer dataset

10

86

[104]

 20

Stearman dataset

19

20

[105]

 21

Hou dataset

65

45

[106]

 22

Okayama dataset

20

226

[107]

 23

Selamat dataset

58

58

[108]

 24

Landi dataset

49

58

[109]

 25

Su dataset

31

31

[110]

Totals

674

2999

Table 2 reports the detailed list of the 90 ion-channels and ion-channel related genes investigated in the present study. Briefly, different members were selected from 21 channel families, namely: amiloride-sensitive cation channels, calcium Channels voltage-dependent, cation channels sperm associated, FXYD domain containing ion transport regulators, gamma-aminobutyric acid (GABA) receptors, glutamate receptors ionotropic, potassium channels voltage gated subfamily, cholinergic receptors (Nicotinic), chloride channels, cyclic nucleotide gated channels, glutamate Receptors, sodium leak channels, purinergic receptors P2X, sodium-hydrogen exchanger regulatory factor 4, regulatory solute carrier proteins, sodium channels, glucose activated Ion channels, two pore segment channels, transient receptor potential cation channels, zinc activated ion channels, aquaporins.
Table 2

Complete list of ion-channel genes and ion-channel related genes investigated

Gene family

Gene name

Whole gene name

(A) Amiloride-sensitive cation channel

1

ACCN1

Amiloride-sensitive cation channel 1

2

ACCN2

Amiloride-sensitive cation channel 2

3

ACCN3

Amiloride-sensitive cation channel 3

4

ACCN4

Amiloride-sensitive cation channel 4

(B) Calcium channel, voltage-dependent

5

CACNA1A

Calcium channel, voltage-dependent, P/Q type, alpha 1A Subunit

6

CACNA1B

Calcium channel, voltage-dependent, N type, alpha 1B Subunit

7

CACNA1C

Calcium channel, voltage-dependent, L type, alpha 1C Subunit

8

CACNA1D

Calcium channel, voltage-dependent, L type, alpha 1D Subunit

(C) Cation channel, sperm associated

9

CATSPER1

Cation channel, sperm associated 1

10

CATSPER2

Cation channel, sperm associated 2

11

CATSPER3

Cation channel, sperm associated 3

12

CATSPER4

Cation channel, sperm associated 4

(D) FXYD domain containing ion transport regulator

13

FXYD1

FXYD domain containing ion transport regulator 1

14

FXYD2

FXYD domain containing ion transport regulator 2

15

FXYD3

FXYD domain containing ion transport regulator 3

16

FXYD4

FXYD domain containing ion transport regulator 4

17

FXYD5

FXYD domain containing ion transport regulator 5

(E) Gamma-aminobutyric acid (GABA) A receptor

18

GABRA1

Gamma-aminobutyric acid (GABA) A receptor, alpha 1

19

GABRB3

Gamma-aminobutyric acid (GABA) A receptor, beta 3

20

GABRP

Gamma-aminobutyric acid (GABA) A receptor, Pi

(F) Glutamate receptor, ionotropic

21

GRIA1

Glutamate receptor, ionotropic, AMPA 1

22

GRIN2A

Glutamate receptor, ionotropic, N-methyl d-aspartate 2A

23

HTR3A

5-Hydroxytryptamine (serotonin) receptor 3A, ionotropic

24

HTR3B

5-Hydroxytryptamine (serotonin) receptor 3B, ionotropic

(G) Potassium channel, voltage gated subfamily

25

KCNE3

Potassium channel, voltage gated subfam.E regulatory beta Sub. 3

26

KCNE4

Potassium channel, voltage gated subfam.E regulatory beta Sub. 4

27

KCNH2

Potassium channel, voltage gated Eag related subfamily H, member 2

28

KCNH1

Potassium channel, voltage gated Eag relat.subfam.H, Member 1

29

KCNJ11

Potassium channel, inwardly rectifying subfamily J, member 11

30

KCNJ12

Potassium channel, inwardly rectifying subfamily J, member 12

31

KCNMA1

Potassium channel, calcium activated large conductance subfam.M alpha, member 1

32

KCNMB2

Potassium channel subfamily M regulatory beta subunit 2

33

KCNMB4

Potassium channel subfamily M regulatory beta subunit 4

34

KCNQ1

Potassium channel, voltage gated KQT-Like Subfam. Q, Member 1

35

KCNRG

Potassium channel regulator, protein CLLD4

36

KCNV1

Potassium channel, voltage gated modifier subfamily V, Member 1

37

KCNN1

Potassium channel, calcium activated intermediate/small conductance subfamily N alpha, member 1

38

KCNN2

Potassium channel, calcium activated intermediate/small conductance subfamily N alpha, member 2

39

KCNN3

Potassium channel, calcium activated intermediate/small conductance subfamily N alpha, member 3

40

KCNN4

Potassium channel, calcium activated intermediate/small conductance subfamily N alpha, member 4

(H) Cholinergic receptor, nicotinic

41

CHRNA1

Cholinergic receptor, nicotinic, alpha 1 (muscle)

42

CHRNA2

Cholinergic receptor, nicotinic, alpha 2 (neuronal)

43

CHRNA3

Cholinergic receptor, nicotinic, alpha 3 (neuronal)

44

CHRNA5

Cholinergic receptor, nicotinic, alpha 5 (neuronal)

(I) Chloride channel

45

CFTR

Cystic fibrosis transmembrane conductance regulator

46

BEST1

Bestrophin 1

47

CLCN1

Chloride channel 1, skeletal muscle (CIC-1)

48

CLCN5

Chloride channel, voltage-sensitive 5 (CIC-5)

49

CLIC1

Chloride intracellular channel 1

50

CLIC4

Chloride intracellular channel 4

(L) Cyclic nucleotide gated channel

51

CNGB3

Cyclic nucleotide gated channel beta 3

(M) Glutamate receptor

52

GRID1

Glutamate receptor, ionotropic, delta 1

53

GRID2

Glutamate receptor, ionotropic, delta 2

(N) Sodium leak channel

54

NALCN

Sodium leak channel, non selective

(O) Purinergic receptor P2X

55

P2RX1

Purinergic receptor P2X, ligand gated ion channel, 1

56

P2RX2

Purinergic receptor P2X, ligand gated ion channel, 2

57

P2RX3

Purinergic receptor P2X, ligand gated ion channel, 3

58

P2RX4

Purinergic receptor P2X, ligand gated ion channel, 4

59

P2RX6

Purinergic receptor P2X, ligand gated ion channel, 6

60

P2RX7

Purinergic receptor P2X, ligand gated ion channel, 7

(P) Sodium-hydrogen exchanger regulatory factor 4

61

PDZD3

PDZ domain containing 3

(Q) Regulatory solute carrier protein

62

RSC1A1

Regulatory solute carrier protein, family 1, member 1

(R) Sodium channel

63

SCN1A

Sodium channel, voltage gated, type I alpha subunit

64

SCN2A

Sodium channel, voltage gated, type II alpha subunit

65

SCN3A

Sodium channel, voltage gated, type III alpha subunit

66

SCN4A

Sodium channel, voltage gated, type IV alpha subunit

67

SCN5A

Sodium channel, voltage gated, type V alpha subunit

68

SCN8A

Sodium channel, voltage gated, type VIII alpha subunit

(S) Glucose activated ion channel

69

SLC5A4

Solute carrier family 5 (glucose activated ion channel)

(T) Two pore segment channel

70

TPCN1

Two pore segment channel 1

71

TPCN2

Two pore segment channel 2

(W) Transient receptor potential cation channel

72

TRPC1

Transient recep. potential cation channel, subfamily C, member 1

73

TRPC2

Transient recep. potential cation channel, subfamily C, member 2

74

TRPC3

Transient recep. potential cation channel, subfamily C, member 3

75

TRPC4

Transient recep. potential cation channel, subfamily C, member 4

76

TRPM1

Transient recep. potential cation channel, subfamily M, member 1

77

TRPM2

Transient recep. potential cation channel, subfamily M, member 2

78

TRPM3

Transient recep. potential cation channel, subfamily M, member 3

79

TRPM4

Transient recep. potential cation channel, subfamily M, member 4

80

TRPM7

Transient recep. potential cation channel, subfamily M, member 7

81

TRPV1

Transient recep. potential cation channel, subfamily V, Member 1

82

TRPV2

Transient recep. potential cation channel, subfamily V, member 2

83

TRPV3

Transient recep. potential cation channel, subfamily V, member 3

84

TRPV4

Transient recep. potential cation channel, subfamily V, member 4

(Y) Zinc activated ion channel

85

ZACN

Zinc activated ligand-gated ion channel

(Z) Acquaporins

86

AQP1

Aquaporin 1

87

AQP2

Aquaporin 2

88

AQP3

Aquaporin 3

89

AQP4

Aquaporin 4

90

AQP5

Aquaporin 5

Expression of such 90 genes was evaluated in oncomine database by setting “cancer vs. normal analysis” and choosing as cancer type: “superficial bladder cancer” within the bladder cancer group, “glioblastoma” within the brain and CNS cancer group, “breast invasive ductal carcinoma” within the breast cancer group, “lung adenocarcinoma” within the lung cancer group, and “melanoma”.

Expression fold change (cancer vs. normal samples) and p values were reported for each analysis. Gene expression in tissue biopsies from 3673 patients was analyzed. Namely, 674 control-samples and 2999 cancer-samples were investigated.

Two additional datasets were identified and investigated within GEO database from NCBI (http://www.ncbi.nlm.nih.gov/gds), namely GSE41614 and GSE44115. Such datasets specifically refer to the vessels component within cancer samples; they were analyzed by means of the GEO2R interface available at the http://www.ncbi.nlm.nih.gov/gds site.

Patients recruitment

Several reports indicate that direct electrical stimulation may affect cell proliferation and dissemination in oncological setups and may induce other physiological effects [3339]. Thus a clinical-study involving any electrical stimulation in cancer patients would be not acceptable by the Ethic Committee, according to the articles n. 14 and n. 16 of the Helsinki declaration on biomedical studies involving human patients, and to the article n. 16 of the Oviedo Convention.

For such reasons we submitted to the Ethic Committee the request to authorize the in vivo investigation in non-tumor patients showing a pathological condition resembling, at least in part, the tumor neo-angiogenesis. Such request was authorized by the Ethic Committee and this explains way we investigated the SSR in angioma patients.

Fourteen patients (six males and eight females) affected by cutaneous flat port-wine stains were recruited at IDI-IRCCS, Rome. The study was approved by the institutional review board of IDI-IRCCS Hospital, Rome (IDI Ethic Committee 2011, n. 363). Patients with flat port-wine stains diagnosis (age 18–70 years) undergoing no treatment of any type were consecutively recruited. Patients did not show systemic or neurological disorders nor obvious psychological problems. Physical general and neurological examination were normal in all cases. The average lesion was about 25 cm × 10 cm, typically a portion of the limb. All patients signed an informed consent to participate in the study.

Sympathetic skin responses SSR recording

SSR study was carried out according to the technical standards of the International Federation of Clinical Neurophysiology [40]. During the test, subjects were kept relaxed with comfortable light and temperature (26–28 °C); the test was started after 5 min of previous adaptation. The apparatus used was an electromyography and evoked potential equipment (MedelecSynergy, Viasys Healthcare, Madison WI USA). Recording electrodes consisted of a pair of superficial electrodes: recording was carried out on the glabrous skin on the flat port-wine stain, and the reference was placed 2 cm away from the lesion. The ground electrode was proximal to the recording electrodes. Electrical stimulation was applied through superficial electrodes over the right median nerve. The stimulus was strong but tolerable (not noxious). The electrical stimulus was applied four times at irregular intervals of 30–60 s (stimulus duration: 0.1 ms; intensity: 80 mA) to avoid habituation, and SSR waves were obtained. SSR recordings were carried out in quadruplicates at the angiomas lesion sites and onto a contralateral healthy skin region in each patient.

The amplifier bandwidth was 0.1–100 Hz. Responses were recorded on the skin with an impedance <5 kΩ. The mean latency and peak-to-peak amplitude were calculated and used for the following analyses.

Statistical analysis

For gene expression data, the statistically significant threshold originally set at p = 0.05 was then corrected according to the Bonferroni correction for multiple comparisons, to take into account the multiple comparisons carried out. Therefore, the final corrected threshold was set at p < 0.0005 (value obtained from 0.05/90 comparisons, for each investigated dataset).

The expression level of any given gene was considered to be significantly altered vs control when the significant p value was matched in at least half—or in at least 1—of the specific databases investigated for each tumor type. Namely, regarding the “at least half datasets” stringency level, the significant p value had to be matched in at least 2 datasets out of the 4 investigated for bladder cancer; in at least 2 datasets out of the 4 studied for glioblastoma; in at least 2 datasets out of the 4 examined for melanoma; in at least 3 datasets out of the 5 investigated for invasive ductal breast carcinoma; in at least 4 datasets out of the 8 investigated for lung adenocarcinoma.

SSR was recorded four consecutive times for each patient on the diseased skin and four consecutive times on the healthy contralateral skin. Mean ± SE was computed; mean latency and mean peak-to-peak amplitude recorded at the diseased-skin level were compared to measures obtained on the contralateral healthy control site. Paired t Student test was carried out, and statistical significance was set at p < 0.05. Normal distribution of SSR data was tested according to the D’Agostino-Pearson test and carried out by the GraphPad software. Data with normal distribution were analyzed with the paired t test, while data with a not-normal distribution were analyzed with the non-parametric Wilcoxon match-paired signed ranked test.

Results

Expression level of ion-channels genes in tumors

The expression level of 90 ion-channels and ion-channels related genes (see Table 2 for the complete list) was analyzed in 3673 human biopsies of 5 histologically different solid tumors, namely: superficial bladder cancer, glioblastoma, melanoma, invasive ductal breast cancer, lung adenocarcinoma, as reported in Table 1 in more details.

Table 3 indicates the ion-channel families showing a significantly altered expression (p < 0.0005). For each cancer type, two columns are presented: the left-hand column (lighten) reports genes indicating a significantly modified expression in at least 1—or less than half-of the investigated datasets. The right-hand column of each tumor type (shadowed) reports in bold all genes showing a significantly modified expression in at least half of the examined datasets (see criteria detailed in “Methods” section). All genes matching the shadowed columns criteria were found overexpressed. More in detail:
Table 3

Genes reported show a significantly altered expression in each cancer type

For each cancer type the lighten column reports ion-channels genes significantly modified in at least 1 dataset. The shadowed column reports ion-channels genes significantly modified in at least half of the investigated datasets. Channel family codes as in Table 2

Significance threshold: p < 0.0005 (see “Methods” section)

  • Within the calcium channel, voltage-dependent family, expression of CACNAD1 gene was found significantly modified in superficial bladder cancer datasets, namely in Dyrskjot dataset (p = 4 × 10−6) and in Sanchez dataset (p = 5 × 10−8), with an average 3.7-fold increase vs. ctrls;

  • Within the FXYD domain containing ion transport regulator family, expression of FXYD3 gene was found significantly modified in bladder cancer (Dyskjot dataset, p = 1 × 10−6, Lee dataset, p = 3 × 10−6 and Sanchez dataset, p = 6 × 10−21) with an average 3.3-fold increase vs. ctrls. Furthermore, FXYD5 gene expression was found significantly modified in glioblastoma (in Lee dataset, p = 2 × 10−5 and in Sun dataset, p = 1 × 10−11) with an average 2.5-fold increase vs. ctrls;

  • Within the glutamate receptor, ionotropic family, expression of HTR3A gene was found significantly modified in 5 lung carcinoma datasets, namely in Beer dataset (p = 3 × 10−8), in Hou dataset (p = 7 × 10−6), in Okayama dataset (p = 2 × 10−13), in Selamat dataset (p = 1 × 10−8), and in Landi dataset (p = 8 × 10−6) with an average 5.08 fold increase vs ctrls;

  • Within the potassium channel, voltage gated family, expression of three genes was found significantly modified in two cancer types. Namely, KCNE3 and KCNE4 genes are modified in glioblastoma datasets. KCNE3 shows an average 5.3-fold increase vs. ctrls (in Lee dataset, p = 3 × 10−10 and in Sun dataset, 5 × 10−9). KCNE4 shows an average 2.9-fold increase vs ctrls in Lee dataset (p = 1 × 10−8) and in Sun dataset (p = 1 × 10−13). KCNN4 was found altered in nearly all lung carcinoma datasets, namely in Bhattacharjee dataset (p = 1 × 10−6), Stearman dataset (p = 3 × 10−7), Hou dataset (p = 3 × 10−9), Okayama dataset (p = 1 × 10−8), Selamat dataset (p = 2 × 10−14), Landi dataset (p = 2 × 10−17) and in Su dataset (p = 6 × 10−8) with an average 3.6-fold increase vs ctrls;

  • Within the chloride channel family, expression of CLIC1 gene was found significantly modified in bladder cancer (in Lee dataset, p = 8 × 10−8 and Sanchez dataset, p = 3 × 10−5) with an average 1.5-fold increase vs. ctrls. CLIC1 is also significantly modified in glioblastoma (in Bredel dataset, p = 3 × 10−7 and Sun dataset, p = 2 × 10−23) with an average 5.7-fold increase vs. ctrls;

  • Within the transient receptor potential cation channel family, expression of TRPM3 gene is altered in glioblastoma, i.e., in the Lee dataset (p = 5 × 10−5) and in the Sun dataset (p = 2 × 10−5) with an average 2.3-fold increase vs. ctrls.

Within the shadowed columns, glioblastoma appears to have the highest number of modified ion-channel genes (namely: FXYD5, KCNE3, KCNE4, CLIC1, TRPM3).

Melanoma and breast cancer show no genes in the shadowed columns. However, within the lighten columns, breast invasive ductal cancer and melanoma show significantly modified ion-channel genes from 13 families and 6 families, respectively.

SSR recording in flat port-wine stains patients

The above reported analyses demonstrated that the expression level of several ion-channels is significantly altered in several human cancer biopsies. Such tumors are histological different. However, they all present an altered vascular tree, due to the tumor neo-angiogenesis. We hence hypothesized that vascular alterations observed in several different cancer types may harbor, at least to a certain extent, the observed ion-channels expression modifications. According to these findings, we hypothesized that measuring ion-channel transport may represent a non-invasive technique to investigate alterations in tumor- as well non-tumor altered angiogenesis. In vivo analysis of ion transport in a vascular malformation, the clinical model was carried out. In fact, measuring in vivo ion-transport in tumor patients was considered ethically not acceptable; we were then forced to identify a non-tumor clinical condition showing clear vascular anomalies. The flat port-wine stains clinical model was approved by the Ethic Committee as a safe model to investigate Sympathetic Skin Responses and electrical signal transport, as the less invasive approach possible in the current study. SSR depends on Ca2+, K+, and Cl channels found to be altered in Table 3. Therefore, 14 patients with flat port-wine stains diagnosis were consecutively recruited, namely eight female (mean age 27 years) and six male (mean age 29.1 years). SSR recordings were carried out in quadruplicates at the angiomas lesion sites and onto a contralateral healthy skin region in each patient. Statistical analysis was performed with paired tests as reported in Methods.

Figure 1 shows the mean latency and means amplitude measured at diseased and healthy sites, expressed in mV. A strong and significant reduction in both latency and peak-to-peak amplitude signals was observed in the diseased site as compared to the healthy site, in the whole patients population. When a gender-specific analysis was carried out, both latency and amplitude were strongly reduced in female patients, while latency was reduced in male, although in a not-significant manner.
Fig. 1

SSR recordings carried out in 14 flat port-wine stains patients. Both latency and amplitude signals were measured on the angioma site and the contralateral healthy site of each patient. A paired test was carried out according to “Methods” section. **indicates p < 0.01; *indicates p < 0.05

Ion channel expression in normal vessels as compared to tumor derived vessels

Data reported in Table 3 and in Fig. 1 led us to hypothesize that ion channels genes may play a relevant role in cancers as well as in other pathological conditions of altered angiogenesis. To further support this hypothesis we investigated two human samples datasets available at GEO database. The first dataset (GSE41614) reports transcriptional profiling of tumor-associated blood vessels in human invasive bladder cancer samples. In such dataset the expression data were obtained on laser capture microdissected vessels isolated from normal bladder tissue or from tumor bladder tissues. Data from ten samples were analyzed, i.e., five normal samples vs five cancer samples.

The second dataset (GSE44115) reports gene expression data in OCT frozen human angiosarcoma compared to OCT frozen normal mesenchymal tissues. In this case 18 angiosarcoma samples were compared to four controls (two from skeletal muscle normal uninvolved tissue and two pooled RNA from normal tissues).

Tables 4 and 5 report the gene name, the log2 fold change, the p values adjusted according to the Benjamini and Hochberg false discovery rate methods, and the rank position (according to the by p value). Several genes, within the top 250 genes most significantly regulated, belong to ion channels families, either in bladder cancer blood vessels (9 genes, Table 4) and in angiosarcoma vessels (123 genes, Table 5). Such data indicate that several ion channels may play a key role in the vessels within cancer tissues.
Table 4

Ion channels genes most regulated in bladder cancer vessels vs control vessels

Rank position in the top 250 (by p value)

Gene identifier

Gene name

Adjusted p value*

log2 fold change

16th

KCNC4

Potassium voltage-gated channel subfamily C member 4

0.009

+0.507

42th

KCNG4

Potassium voltage-gated channel modifier subfamily G member 4

0.01

+0.415

75th

VDAC3

Voltage dependent anion channel 3

0.01

−1.511

90th

CRACR2B

Calcium release activated channel regulator 2B

0.01

+0.472

115th

KCNS2

Potassium voltage-gated channel modifier subfamily S member 2

0.01

+0.637

153th

SEC23B

Sec23 homolog B, coat complex II component (involved in vesicle trafficking)

0.01

−0.566

173th

CBARP

CACN Beta subunit associated regulatory protein

0.01

+0.627

218th

P2RX5

Purinergic receptor P2X 5 (ligand-gated ion channel)

0.01

+0.403

247th

SCN2B

Sodium voltage-gated channel beta subunit 2

0.02

+0.487

* According to the Benjamini and Hochberg false discovery rate method

Data from Geo dataset GSE41614, available at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE41614)

Table 5

Ion channels genes most regulated in angiosarcoma vs controls

Rank position in the top 250 (by value)

Gene identifier

Gene name

Adjusted p value*

log2 fold change

3th

KCNJ16

Potassium voltage-gated channel subfamily J member 16

0.0000003

+6.673

41th

CLCNKA

Chloride voltage-gated channel Ka

0.001

+3.516

52th

HCN2

Hyperpolarization activated cyclic nucleotide gated potassium channel 2

0.001

+2.099

53th

KCNQ2

Potassium voltage-gated channel subfamily Q member 2

0.001

+1.276

61th

FXYD4

FXYD domain containing ion transport regulator 4

0.0009

+6.247

75th

CRACR2B

Calcium release activated channel regulator 2B

0.002

+1.117

104th

AQP10

Aquaporin 10

0.004

+2.096

125th

KCNJ15

Potassium voltage-gated channel subfamily J member 15

0.004

+3.203

147th

KCNK12

Potassium two pore domain channel subfamily K member 12

0.004

+2.008

153th

FXYD2

FXYD domain containing ion transport regulator 2

0.005

+2.596

167th

KCNJ1

Potassium voltage-gated channel subfamily J member 1

0.01

+3.369

250th

AQP2

Aquaporin 2

0.01

+8.359

* According to the Benjamini and Hochberg false discovery rate method

Data from Geo dataset GSE44115, available at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE44115)

Discussion

It is widely known that nerves and vessels follow similar anatomical paths. Often nerves and vessels show an overlapping anatomy with overlapping branches and ramifications. Several molecular factors are reported to control their respective patterns and growth in a coordinated manner [41], including semaphorin, netrin and slit [42], all strongly regulated by Ca2+, Na+, and Cl channels [43, 44]. Thus, an architectural or functional modification of the ones may affect the architecture or function of the others. We, therefore, argued that unordered angiogenesis occurring in tumors and vascular malformations may associate to a corresponding unordered nerve formation and therefore to a measurable alteration of the electric stimulus transport. We hypothesized that (i) ion channels (which are known to regulate nerve- and vessel- formation) may show altered expression in tumors and (ii) SSR recording in vascular malformations patients may unreveal a clinical non-invasive sign of the unordered vessels formation.

The expression level of members of several ion-channel families was found significantly modified in histologically different human cancer biopsies, according to the measures reported in Oncomine database, in an almost 4000 patients-vs-controls group. While several genes were found significantly modified (p < 0.0005) in at least one human dataset, we limit here the discussion to the genes reported in the shadowed columns of Table 3 selected according to highly stringent criteria, i.e. to the ion-channel genes found altered in at least half of the investigated databases of each tumor. We report in the current study that such genes show an increased expression in cancer vs. ctrls samples and have in most cases a definite role in vascular biology and/or cancer setup/progression or nervous system biology.

CACNA1D, a calcium related transporter gene, shows an average 3.75-fold increased expression in superficial bladder cancer datasets. No reports are present in literature referring CACNA1D direct link to bladder cancer. Nevertheless, some studies relate its expression- and methylation-level to prostate cancer [45, 46], indicating CACNA1D as a possible regulator of prostate cancer aggressiveness [47], or refer it to CNS disorders [48], diabetes [49] or calcium level within the vessels [50].

FXYD3 shows a 3.3 average fold increase expression in bladder cancer. It encodes a cell membrane protein regulating ion-pumps and ion-channels function and is known to have a role in tumor progression. Its activity is related to glucose and Cl ions and has been indicated as a possible biomarker in bladder cancer [51, 52] as well as other cancers including breast [53], colorectal cancer [54], endometrial cancer [55] and intrahepatic cholangiocarcinoma [56].

FXYD5 is a transmembrane auxiliary subunit of the Na+-K+-ATPase; it shows a 2.5-fold increase in glioblastoma. No direct link with glioblastoma has been reported to date, however it has been found up-regulated in adamantinomatous craniopharyngiomas in children [57] and other members of the FXYD family are known to be associated with different cancer types such as urothelial carcinoma [58], esophageal squamous cell carcinoma [59] and cholangiocarcinoma [60]. FXYD channels are involved in the anti-oxidative stress in vascular smooth muscle, thus controlling the vascular tone [61] and blood pressure [62]. Most interestingly, expression of FXYD2 and FXYD4 genes is modified in angiosarcoma vs control human samples (Table 5).

The expression of serotonin receptor HTR3A was found increased by fivefold in lung carcinoma; no direct link has been reported between HTR3A and lung adenocarcinoma, yet; however, nucleotide polymorphisms of this gene have been related to opioid- or nausea/vomiting signaling pathways in cancer patients [63] and to bowel syndrome [64]. HTR3 is the only ligand-gated ion channel among the serotonin receptors, and it has been associated with neurological disorders such as depression [65] or schizophrenia [66]. Most interestingly about the current study, HTR3A acts as a ligand-gated ion channel neurotransmitter, and causes fast, depolarizing responses in neurons (http://www.genecards.org/cgi-bin/carddisp.pl?gene=HTR3A). It is up-regulated in rosacea, i.e., a chronic inflammatory skin disease often showing telangiectasias in the erythematotelangiectatic form (ETR) [67].

Within the potassium intermediate/small conductance calcium-activated channels, expression of 3 genes (namely KCNE3, KCNE4, KCNN4) has been found altered in the current study, namely in glioblastoma and lung adenocarcinoma. While no direct evidence relate KCNE3 or KCNE4 to glioblastoma, KCNE4 is most abundantly expressed in brain [68]; it exerts functions such as controlling the neuronal firing rate, the synaptic transmission [69] and the T-lymphocytes maturation [70] and it is known to regulate K-channels in vascular smooth muscle [71] and more in general neuronal excitability. Furthermore, KCNN4 single-nucleotide polymorphisms have been related to myocardial infarction [72]. Most interestingly, KCNN4 has been linked to vascular cells proliferation [73]. Notably, expression of several potassium channels is modified in bladder cancer vessels vs controls (KCNC4, KCNG4, KCNS2, see Table 4) and in angiosarcoma vs controls (namely KCNJ16, KCNQ2, KCNJ15, KCNJ12, KCNJ1, see Table 5).

Within the Cl- intracellular channels, CLIC1 expression was found altered in bladder cancer and glioblastoma. CLIC1 has been previously found up-regulated in glioblastoma [74], it is involved in different tumors and acts as an oncogene in pancreatic cancer [75], and has been indicated as a possible cancer biomarker [76]. Interestingly, CLIC1 has recently shown a key role in angiogenesis control in combination with integrins [77, 78]. Interestingly, expression of one Cl channel (namely CLCNKA) is strongly modified in angiosarcoma vs controls (see Table 5).

Within the transient receptor potential cation channels, TRPM3 gene expression was found increased in glioblastoma by 2.3-fold. Its expression has been previously found increased in glioblastoma [79] and is known to exhibit mechanosensitivity contributing to vascular and cardiac functions [80].

SSR is under the direct control of Ca2+, K, Cl ion channels and strictly depends on the sympathetic autonomous nerve function. In the current study, several ion channels related to the Ca2+, K+, and Cl have relevant, and significantly increased expression in different human cancers and SSR was found strongly altered in human vascular malformations. SSR has been previously indicated as a possible useful diagnostic technique in CNS pathologies [81, 82], as well as fibromyalgia [83] and diabetes [84]. Further, autonomic nerve development and function has been recently shown to play a key role in prostate cancer progression [85]. Thus, given the known role of several ion channels in the tumor, nerve, and vascular biology, we hypothesize that the altered SSR observed in vascular skin malformations, and the observed altered ion-channel gene-expression in several tumors may represent phenomena related to the unordered nerve- and vessel formation, common to tumor-related and non-tumor-related vascular anomalies.

SSR recording gave more significant results in female while in male the trend was present but with no statistical significance. Such difference may be related to a different transport of electrical stimuli in the female skin, which appears evident at both healthy (white boxes in Fig. 1) and diseased sites (black boxes in Fig. 1), as compared to male. A gender-related difference in the skin thickness may underlie, at least in part, such observation likely associated with the skin thickness and water retention induced by the menstrual phases and the hormonal status in females.

In conclusion, data reported in the current study allowed us to conclude that ion-channel expression and function may be strongly affected in pathological conditions where vessels’ (and nerves’) architecture is altered. SSR measurement may thus represent a non-invasive useful tool to investigate vascular skin alterations in both tumor and non-tumor conditions.

Conclusions

The present study reports for the first time a detailed analysis of the expression level of 90 ion-channel genes in 3673 biopsies form humans affected by solid tumors and from healthy controls. At least ten genes from different ion-channels families were found firmly and significantly up-regulated in histologically different tumors having in common the underlying unordered tumor neo-angiogenesis (Table 3). Moreover, expression of at least 20 ion channels has been found to be strongly modified in cancer associated vessels vs controls (Tables 4, 5). The sympathetic skin responses (SSR), an electrical feature closely related to the ion-channels activity, was then measured in vivo and was found strongly modified in the skin of patients affected by the flat port-wine stains vascular malformation. The present study indicates that modified expression and activity of ion channels is likely related to vascular alteration, in both tumor and non-tumor conditions, and suggests the non invasive technique SSR as a simple, useful tool to investigate skin vascular anomalies.

Notes

Declarations

Authors’ contributions

AB, DD, EMN, AF: design of the study; data collection; data interpretation; writing. FP: data interpretation. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Ethics approval and consent to participate

The study was approved by the institutional review board of IDI-IRCCS Hospital, Rome (IDI Ethic Committee 2011, n. 363). All patients signed an informed consent to participate in the study.

Funding

This study has been partially supported by Ministry of Health, Ric. Cor. 2013–2014, Line 3.4 to AF.

Open AccessThis 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 Neurology and Psychiatry, Sapienza University
(2)
Istituto Dermopatico dell’Immacolata, IDI-IRCCS, Fondazione Luigi Maria Monti

References

  1. Blackiston DJ, McLaughlin KA, Levin M. Bioelectric controls of cell proliferation: ion channels, membrane voltage and the cell cycle. Cell Cycle. 2009;8:3527–36.PubMedView ArticleGoogle Scholar
  2. Kunzelmann K. Ion channels in regulated cell death. Cell Mol Life Sci. 2016;73(11–12):2387–403.PubMedView ArticleGoogle Scholar
  3. Alfarouk KO. Tumor metabolism, cancer cell transporters, and microenvironmental resistance. J Enzyme Inhib Med Chem. 2016;31:859–66. doi:10.3109/14756366.2016.1140753.PubMedView ArticleGoogle Scholar
  4. Enomoto K, Cossu MF, Maeno T, Edwards C, Oka T. Involvement of the Ca2+ -dependent K+ channel activity in the hyperpolarizing response induced by epidermal growth factor in mammary epithelial cells. FEBS Lett. 1986;203:181–4.PubMedView ArticleGoogle Scholar
  5. Campbell TM, Main MJ, Fitzgerald EM. Functional expression of the voltage-gated Na+-channel Nav1.7 is necessary for EGF-mediated invasion in human non-small cell lung cancer cells. J Cell Sci. 2013;126:4939–49.PubMedView ArticleGoogle Scholar
  6. Frede J, Fraser SP, Oskay-Özcelik G, Hong Y, Ioana Braicu E, Sehouli J, Gabra H, Djamgoz MBA. Ovarian cancer: ion channel and aquaporin expression as novel targets of clinical potential. Eur J Cancer. 2013;49:2331–44.PubMedView ArticleGoogle Scholar
  7. Cone CD. Unified theory on the basic mechanism of normal mitotic control and oncogenesis. J Theor Biol. 1971;30:151–81.PubMedView ArticleGoogle Scholar
  8. Cone CD. Electroosmotic interactions accompanying mitosis initation in sarcoma cells in vitro. Trans N Y Acad Sci. 1969;31:404–27.PubMedView ArticleGoogle Scholar
  9. Bränström R, Chang Y-M, Kasparian N, Affleck P, Tibben A, Aspinwall LG, Azizi E, Baron-Epel O, Battistuzzi L, Bruno W, Chan M, Cuellar F, et al. Melanoma risk factors, perceived threat and intentional tanning: an international online survey. Eur J Cancer Prev. 2010;19:216–26.PubMedPubMed CentralView ArticleGoogle Scholar
  10. Wang E, Yin Y, Zhao M, Forrester JV, McCaig CD. Physiological electric fields control the G1/S phase cell cycle checkpoint to inhibit endothelial cell proliferation. FASEB J. 2003;17:458–60.PubMedGoogle Scholar
  11. Zhao M, Song B, Pu J, Wada T, Reid B, Tai G, Wang F, Guo A, Walczysko P, Gu Y, Sasaki T, Suzuki A, et al. Electrical signals control wound healing through phosphatidylinositol-3-OH kinase-gamma and PTEN. Nature. 2006;442:457–60.PubMedView ArticleGoogle Scholar
  12. Kunzelmann K. Ion channels and cancer. J Membr Biol. 2005;205:159–73.PubMedView ArticleGoogle Scholar
  13. Thongon N, Ketkeaw P, Nuekchob C. The roles of acid-sensing ion channel 1a and ovarian cancer G protein-coupled receptor 1 on passive Mg2+ transport across intestinal epithelium-like Caco-2 monolayers. J Physiol Sci. 2014;64:129–39.PubMedView ArticleGoogle Scholar
  14. Ko J-H, Ko EA, Gu W, Lim I, Bang H, Zhou T. Expression profiling of ion channel genes predicts clinical outcome in breast cancer. Mol Cancer. 2013;12:106.PubMedPubMed CentralView ArticleGoogle Scholar
  15. Han X, Xi L, Wang H, Huang X, Ma X, Han Z, Wu P, Ma X, Lu Y, Wang G, Zhou J, Ma D. The potassium ion channel opener NS1619 inhibits proliferation and induces apoptosis in A2780 ovarian cancer cells. Biochem Biophys Res Commun. 2008;375:205–9.PubMedView ArticleGoogle Scholar
  16. D’Arcangelo D, Silletta MG, Di Francesco AL, Bonfitto N, Di Cerbo A, Falasca M, Corda D. Physiological concentrations of thyrotropin increase cytosolic calcium levels in primary cultures of human thyroid cells. J Clin Endocrinol Metab. 1995;80:1136–43.PubMedGoogle Scholar
  17. Martial S. Involvement of ion channels and transporters in carcinoma angiogenesis and metastasis. Am J Physiol Cell Physiol. 2016. doi:10.1152/ajpcell.00218.2015.PubMedGoogle Scholar
  18. Shim JH, Lim JW, Kim BK, Park SJ, Kim SW, Choi TH. KCl mediates K(+) channel-activated mitogen-activated protein kinases signaling in wound healing. Arch Plast Surg. 2015;42:11–9.PubMedPubMed CentralView ArticleGoogle Scholar
  19. Thoppil RJ, Cappelli HC, Adapala RK, Kanugula AK, Paruchuri S, Thodeti CK. TRPV4 channels regulate tumor angiogenesis via modulation of Rho/Rho kinase pathway. Oncotarget. 2016;7:25849–61.PubMedGoogle Scholar
  20. Adapala RK, Thoppil RJ, Ghosh K, Cappelli HC, Dudley AC, Paruchuri S, Keshamouni V, Klagsbrun M, Meszaros JG, Chilian WM, Ingber DE, Thodeti CK. Activation of mechanosensitive ion channel TRPV4 normalizes tumor vasculature and improves cancer therapy. Oncogene. 2016;35:314–22.PubMedView ArticleGoogle Scholar
  21. Xu T, Fan Z, Li W, Dietel B, Wu Y, Beckmann MW, Wrosch JK, Buchfelder M, Eyupoglu IY, Cao Z, Savaskan NE. Identification of two novel chlorotoxin derivatives CA4 and CTX-23 with chemotherapeutic and anti-angiogenic potential. Sci Rep. 2016;6:19799.PubMedPubMed CentralView ArticleGoogle Scholar
  22. Crottès D, Rapetti-Mauss R, Alcaraz-Perez F, Tichet M, Gariano G, Martial S, Guizouarn H, Pellissier B, Loubat A, Popa A, Paquet A, Presta M, et al. SIGMAR1 regulates membrane electrical activity in response to extracellular matrix stimulation to drive cancer cell invasiveness. Cancer Res. 2016;76:607–18.PubMedView ArticleGoogle Scholar
  23. Lian CG, Sholl LM, Zakka LR, Liu C, Xu S, Stanek E, Garcia E, Jia Y, MacConaill LE, Murphy GF, Waner M, et al. Novel genetic mutations in a sporadic port-wine stain. JAMA Dermatol. 2014;150:1336–40.PubMedView ArticleGoogle Scholar
  24. Vetrugno R, Liguori R, Cortelli P, Montagna P. Sympathetic skin response: basic mechanisms and clinical applications. Clin Auton Res. 2003;13:256–70.PubMedView ArticleGoogle Scholar
  25. Maselli RA, Jaspan JB, Soliven BC, Green AJ, Spire JP, Arnason BG. Comparison of sympathetic skin response with quantitative sudomotor axon reflex test in diabetic neuropathy. Muscle Nerve. 1989;12:420–3.PubMedView ArticleGoogle Scholar
  26. Niakan E, Harati Y. Sympathetic skin response in diabetic peripheral neuropathy. Muscle Nerve. 1988;11:261–4.PubMedView ArticleGoogle Scholar
  27. Goizueta-San Martín G, Gutiérrez-Gutiérrez G, Godoy-Tundidor H, Mingorance-Goizueta B, Mingorance-Goizueta C, Vega-Piris L, Gutiérrez-Rivas E. Sympathetic skin response: reference data for 100 normal subjects. Rev Neurol. 2013;56:321–6.PubMedGoogle Scholar
  28. Cappuzzello C, Di Vito L, Melchionna R, Melillo G, Silvestri L, Cesareo E, Crea F, Liuzzo G, Facchiano A, Capogrossi MC, Napolitano M. Increase of plasma IL-9 and decrease of plasma IL-5, IL-7, and IFN-γ in patients with chronic heart failure. J Transl Med. 2011;9:28.PubMedPubMed CentralView ArticleGoogle Scholar
  29. Buttari B, Segoni L, Profumo E, D’Arcangelo D, Rossi S, Facchiano F, Businaro R, Iuliano L, Rigano R. 7-Oxo-cholesterol potentiates pro-inflammatory signaling in human M1 and M2 macrophages. Biochem Pharmacol. 2013;86:130–7.PubMedView ArticleGoogle Scholar
  30. Aguzzi MS, Facchiano F, Ribatti D, Gaeta R, Casadio R, Rossi I, Capogrossi MC, Facchiano A. A novel RGDS-analog inhibits angiogenesis in vitro and in vivo. Biochem Biophys Res Commun. 2004;321:809–14.PubMedView ArticleGoogle Scholar
  31. D’Arcangelo D, Nicodemi EM, Rossi S, Giampietri C, Facchiano F, Facchiano A. Identification of serum regression signs in infantile hemangioma. PLoS One. 2014;9:e88545.PubMedPubMed CentralView ArticleGoogle Scholar
  32. Faraone D, Aguzzi MS, Toietta G, Facchiano AM, Facchiano F, Magenta A, Martelli F, Truffa S, Cesareo E, Ribatti D, Capogrossi MC, Facchiano A. Platelet-derived growth factor-receptor α strongly inhibits melanoma growth in vitro and in vivo. Neoplasia. 2009;11:732.PubMedPubMed CentralView ArticleGoogle Scholar
  33. Hernández-Bule ML, Paíno CL, Trillo MÁ, Úbeda A. Electric stimulation at 448 kHz promotes proliferation of human mesenchymal stem cells. Cell Physiol Biochem. 2014;34:1741–55.PubMedView ArticleGoogle Scholar
  34. Yuan X, Arkonac DE, Chao PG, Vunjak-Novakovic G. Electrical stimulation enhances cell migration and integrative repair in the meniscus. Sci Rep. 2014;4:3674.PubMedPubMed CentralGoogle Scholar
  35. Chang K-A, Kim JW, Kim JA, Lee SE, Lee S, Kim S, Suh WH, Kim H-S, Kwon S, Kim SJ, Suh Y-H. Biphasic electrical currents stimulation promotes both proliferation and differentiation of fetal neural stem cells. PLoS One. 2011;6:e18738.PubMedPubMed CentralView ArticleGoogle Scholar
  36. Kim IS, Song JK, Zhang YL, Lee TH, Cho TH, Song YM, Kim DK, Kim SJ, Hwang SJ. Biphasic electric current stimulates proliferation and induces VEGF production in osteoblasts. Biochim Biophys Acta. 2006;1763:907–16.PubMedView ArticleGoogle Scholar
  37. Gu X, Fu J, Bai J, Zhang C, Wang J, Pan W. Low-frequency electrical stimulation induces the proliferation and differentiation of peripheral blood stem cells into Schwann cells. Am J Med Sci. 2015;349:157–61.PubMedView ArticleGoogle Scholar
  38. Lim J-H, McCullen SD, Piedrahita JA, Loboa EG, Olby NJ. Alternating current electric fields of varying frequencies: effects on proliferation and differentiation of porcine neural progenitor cells. Cell Reprogr. 2013;15:405–12.View ArticleGoogle Scholar
  39. Collard J-F, Lazar C, Nowé A, Hinsenkamp M. Statistical validation of the acceleration of the differentiation at the expense of the proliferation in human epidermal cells exposed to extremely low frequency electric fields. Prog Biophys Mol Biol. 2013;111:37–45.PubMedView ArticleGoogle Scholar
  40. Claus D, Schondorf R. Sympathetic skin response. The international federation of clinical neurophysiology. Electroencephalogr Clin Neurophysiol Suppl. 1999;52:277–82.PubMedGoogle Scholar
  41. Shi N, Chen S-Y. From nerve to blood vessel: a new role of Olfm2 in smooth muscle differentiation from human embryonic stem cell-derived mesenchymal cells. J Biomed Res. 2015;29:261–3.PubMedPubMed CentralView ArticleGoogle Scholar
  42. Melani M, Weinstein BM. Common factors regulating patterning of the nervous and vascular systems. Annu Rev Cell Dev Biol. 2010;26:639–65.PubMedView ArticleGoogle Scholar
  43. Behar O, Mizuno K, Badminton M, Woolf CJ. Semaphorin 3A growth cone collapse requires a sequence homologous to tarantula hanatoxin. Proc Natl Acad Sci USA. 1999;96:13501–5.PubMedPubMed CentralView ArticleGoogle Scholar
  44. Nishiyama M, von Schimmelmann MJ, Togashi K, Findley WM, Hong K. Membrane potential shifts caused by diffusible guidance signals direct growth-cone turning. Nat Neurosci. 2008;11:762–71.PubMedView ArticleGoogle Scholar
  45. Roudier MP, Winters BR, Coleman I, Lam H-M, Zhang X, Coleman R, Chéry L, True LD, Higano CS, Montgomery B, Lange PH, Snyder LA, et al. Characterizing the molecular features of ERG-positive tumors in primary and castration resistant prostate cancer. Prostate. 2016;76:810–22.PubMedView ArticleGoogle Scholar
  46. Geybels MS, Alumkal JJ, Luedeke M, Rinckleb A, Zhao S, Shui IM, Bibikova M, Klotzle B, van den Brandt PA, Ostrander EA, Fan J-B, Feng Z, et al. Epigenomic profiling of prostate cancer identifies differentially methylated genes in TMPRSS2:ERG fusion-positive versus fusion-negative tumors. Clin Epigenetics. 2015;7:128.PubMedPubMed CentralView ArticleGoogle Scholar
  47. Zhu G, Liu Z, Epstein JI, Davis C, Christudass CS, Carter HB, Landis P, Zhang H, Chung J-Y, Hewitt SM, Miller MC, Veltri RW. A novel quantitative multiplex tissue immunoblotting for biomarkers predicts a prostate cancer aggressive phenotype. Cancer Epidemiol Biomarkers Prev. 2015;24:1864–72.PubMedView ArticleGoogle Scholar
  48. Pinggera A, Striessnig J. Cav 1.3 (CACNA1D) L-type Ca(2+) channel dysfunction in CNS disorders. J Physiol. 2016. doi:10.1113/JP270672.PubMedPubMed CentralGoogle Scholar
  49. Reinbothe TM, Alkayyali S, Ahlqvist E, Tuomi T, Isomaa B, Lyssenko V, Renström E. The human L-type calcium channel Cav1.3 regulates insulin release and polymorphisms in CACNA1D associate with type 2 diabetes. Diabetologia. 2013;56:340–9.PubMedView ArticleGoogle Scholar
  50. Navedo MF, Amberg GC, Westenbroek RE, Sinnegger-Brauns MJ, Catterall WA, Striessnig J, Santana LF. Ca(v)1.3 channels produce persistent calcium sparklets, but Ca(v)1.2 channels are responsible for sparklets in mouse arterial smooth muscle. Am J Physiol Heart Circ Physiol. 2007;293:H1359–70.PubMedView ArticleGoogle Scholar
  51. Ramírez-Backhaus M, Fernández-Serra A, Rubio-Briones J, Cruz Garcia P, Calatrava A, Garcia Casado Z, Casanova Salas I, Rubio L, Solsona E, López-Guerrero JA. External validation of FXYD3 and KRT20 as predictive biomarkers for the presence of micrometastasis in muscle invasive bladder cancer lymph nodes. Actas Urol Españolas. 2015;39:473–81.Google Scholar
  52. Gazquez C, Ribal MJ, Marín-Aguilera M, Kayed H, Fernández PL, Mengual L, Alcaraz A. Biomarkers vs conventional histological analysis to detect lymph node micrometastases in bladder cancer: a real improvement? BJU Int. 2012;110:1310–6.PubMedView ArticleGoogle Scholar
  53. Liu C-C, Teh R, Mozar CA, Baxter RC, Rasmussen HH. Silencing overexpression of FXYD3 protein in breast cancer cells amplifies effects of doxorubicin and γ-radiation on Na(+)/K(+)-ATPase and cell survival. Breast Cancer Res Treat. 2016;155:203–13.PubMedView ArticleGoogle Scholar
  54. Simmer F, Venderbosch S, Dijkstra JR, Vink-Börger EM, Faber C, Mekenkamp LJ, Koopman M, De Haan AF, Punt CJ, Nagtegaal ID. MicroRNA-143 is a putative predictive factor for the response to fluoropyrimidine-based chemotherapy in patients with metastatic colorectal cancer. Oncotarget. 2015;6:22996–3007.PubMedPubMed CentralView ArticleGoogle Scholar
  55. Li Y, Zhang X, Xu S, Ge J, Liu J, Li L, Fang G, Meng Y, Zhang H, Sun X. Expression and clinical significance of FXYD3 in endometrial cancer. Oncol Lett. 2014;8:517–22.PubMedPubMed CentralGoogle Scholar
  56. Subrungruanga I, Thawornkunob C, Chawalitchewinkoon-Petmitrc P, Pairojkul C, Wongkham S, Petmitrb S. Gene expression profiling of intrahepatic cholangiocarcinoma. Asian Pac J Cancer Prev. 2013;14:557–63.PubMedView ArticleGoogle Scholar
  57. Gong J, Zhang H, Xing S, Li C, Ma Z, Jia G, Hu W. High expression levels of CXCL12 and CXCR4 predict recurrence of adamanti-nomatous craniopharyngiomas in children. Cancer Biomark. 2014;14:241–51.PubMedGoogle Scholar
  58. Zhang Z, Pang S-T, Kasper KA, Luan C, Wondergem B, Lin F, Chuang C-K, Teh BT, Yang XJ. FXYD3: a promising biomarker for urothelial carcinoma. Biomark Insights. 2011;6:17–26.PubMedPubMed CentralView ArticleGoogle Scholar
  59. Zhu Z-L, Yan B-Y, Zhang Y, Yang Y-H, Wang M-W, Zentgraf H, Zhang X-H, Sun X-F. Overexpression of FXYD-3 is involved in the tumorigenesis and development of esophageal squamous cell carcinoma. Dis Markers. 2013;35:195–202.PubMedPubMed CentralView ArticleGoogle Scholar
  60. Chen X, Sun M, Hu Y, Zhang H, Wang Z, Zhou N, Yan X. FXYD6 is a new biomarker of cholangiocarcinoma. Oncol Lett. 2014;7:393–8.PubMedGoogle Scholar
  61. Liu C-C, Karimi Galougahi K, Weisbrod RM, Hansen T, Ravaie R, Nunez A, Liu YB, Fry N, Garcia A, Hamilton EJ, Sweadner KJ, Cohen RA, et al. Oxidative inhibition of the vascular Na+ -K+ pump via NADPH oxidase-dependent β1-subunit glutathionylation: implications for angiotensin II-induced vascular dysfunction. Free Radic Biol Med. 2013;65:563–72.PubMedPubMed CentralView ArticleGoogle Scholar
  62. Huang X, Wang B, Yang D, Shi X, Hong J, Wang S, Dai X, Zhou X, Geng Y-J. Reduced expression of FXYD domain containing ion transport regulator 5 in association with hypertension. Int J Mol Med. 2012;29:231–8.PubMedGoogle Scholar
  63. Laugsand EA, Fladvad T, Skorpen F, Maltoni M, Kaasa S, Fayers P, Klepstad P. Clinical and genetic factors associated with nausea and vomiting in cancer patients receiving opioids. Eur J Cancer. 2011;47:1682–91.PubMedView ArticleGoogle Scholar
  64. Gu Q-Y, Zhang J, Feng Y-C, Dai G-R, Du W-P. Association of genetic polymorphisms in HTR3A and HTR3E with diarrhea predominant irritable bowel syndrome. Int J Clin Exp Med. 2015;8:4581–5.PubMedPubMed CentralGoogle Scholar
  65. Gatt JM, Williams LM, Schofield PR, Dobson-Stone C, Paul RH, Grieve SM, Clark CR, Gordon E, Nemeroff CB. Impact of the HTR3A gene with early life trauma on emotional brain networks and depressed mood. Depress Anxiety. 2010;27:752–9.PubMedView ArticleGoogle Scholar
  66. Schuhmacher A, Mössner R, Quednow BB, Kühn K-U, Wagner M, Cvetanovska G, Rujescu D, Zill P, Möller H-J, Rietschel M, Franke P, Wölwer W, et al. Influence of 5-HT3 receptor subunit genes HTR3A, HTR3B, HTR3C, HTR3D and HTR3E on treatment response to antipsychotics in schizophrenia. Pharmacogenet Genomics. 2009;19:843–51.PubMedView ArticleGoogle Scholar
  67. Steinhoff M, Schauber J, Leyden JJ. New insights into rosacea pathophysiology: a review of recent findings. J Am Acad Dermatol. 2013;69:S15–26.PubMedView ArticleGoogle Scholar
  68. Manderfield LJ, George AL. KCNE4 can co-associate with the I(Ks) (KCNQ1-KCNE1) channel complex. FEBS J. 2008;275:1336–49.PubMedView ArticleGoogle Scholar
  69. Grunnet M, Rasmussen HB, Hay-Schmidt A, Rosenstierne M, Klaerke DA, Olesen S-P, Jespersen T. KCNE4 is an inhibitory subunit to Kv1.1 and Kv1.3 potassium channels. Biophys J. 2003;85:1525–37.PubMedPubMed CentralView ArticleGoogle Scholar
  70. Grissmer S, Dethlefs B, Wasmuth JJ, Goldin AL, Gutman GA, Cahalan MD, Chandy KG. Expression and chromosomal localization of a lymphocyte K+ channel gene. Proc Natl Acad Sci USA. 1990;87:9411–5.PubMedPubMed CentralView ArticleGoogle Scholar
  71. Jepps TA, Carr G, Lundegaard PR, Olesen S-P, Greenwood IA. Fundamental role for the KCNE4 ancillary subunit in Kv7.4 regulation of arterial tone. J Physiol. 2015;593:5325–40.PubMedView ArticleGoogle Scholar
  72. Yamaguchi M, Nakayama T, Fu Z, Naganuma T, Sato N, Soma M, Doba N, Hinohara S, Morita A, Mizutani T. Relationship between haplotypes of KCNN4 gene and susceptibility to human vascular diseases in Japanese. Med Sci Monit. 2009;15:CR389–97.PubMedGoogle Scholar
  73. Cheong A, Bingham AJ, Li J, Kumar B, Sukumar P, Munsch C, Buckley NJ, Neylon CB, Porter KE, Beech DJ, Wood IC. Downregulated REST transcription factor is a switch enabling critical potassium channel expression and cell proliferation. Mol Cell. 2005;20:45–52.PubMedView ArticleGoogle Scholar
  74. Setti M, Osti D, Richichi C, Ortensi B, Del Bene M, Fornasari L, Beznoussenko G, Mironov A, Rappa G, Cuomo A, Faretta M, Bonaldi T, et al. Extracellular vesicle-mediated transfer of CLIC1 protein is a novel mechanism for the regulation of glioblastoma growth. Oncotarget. 2015;6:31413–27.PubMedPubMed CentralGoogle Scholar
  75. Lu J, Dong Q, Zhang B, Wang X, Ye B, Zhang F, Song X, Gao G, Mu J, Wang Z, Ma F, Gu J. Chloride intracellular channel 1 (CLIC1) is activated and functions as an oncogene in pancreatic cancer. Med Oncol. 2015;32:616.PubMedGoogle Scholar
  76. Peretti M, Angelini M, Savalli N, Florio T, Yuspa SH, Mazzanti M. Chloride channels in cancer: focus on chloride intracellular channel 1 and 4 (CLIC1 AND CLIC4) proteins in tumor development and as novel therapeutic targets. Biochim Biophys Acta. 2015;1848:2523–31.PubMedView ArticleGoogle Scholar
  77. Knowles LM, Malik G, Hood BL, Conrads TP, Pilch J. CLT1 targets angiogenic endothelium through CLIC1 and fibronectin. Angiogenesis. 2012;15:115–29.PubMedView ArticleGoogle Scholar
  78. Tung JJ, Kitajewski J. Chloride intracellular channel 1 functions in endothelial cell growth and migration. J Angiogenes Res. 2010;2:23.PubMedPubMed CentralView ArticleGoogle Scholar
  79. Alptekin M, Eroglu S, Tutar E, Sencan S, Geyik MA, Ulasli M, Demiryurek AT, Camci C. Gene expressions of TRP channels in glioblastoma multiforme and relation with survival. Tumour Biol. 2015;36:9209–13.PubMedView ArticleGoogle Scholar
  80. Inoue R, Jian Z, Kawarabayashi Y. Mechanosensitive TRP channels in cardiovascular pathophysiology. Pharmacol Ther. 2009;123:371–85.PubMedView ArticleGoogle Scholar
  81. Negami M, Maruta T, Takeda C, Adachi Y, Yoshikawa H. Sympathetic skin response and heart rate variability as diagnostic tools for the differential diagnosis of Lewy body dementia and Alzheimer’s disease: a diagnostic test study. BMJ Open. 2013;3:e001796.PubMedPubMed CentralView ArticleGoogle Scholar
  82. Nazliel B, Irkeç C, Koçer B. The roles of blink reflex and sympathetic skin response in multiple sclerosis diagnosis. Mult Scler. 2002;8:500–4.PubMedView ArticleGoogle Scholar
  83. Ozkan O, Yildiz M, Arslan E, Yildiz S, Bilgin S, Akkus S, Koyuncuoglu HR, Koklukaya E. A study on the effects of sympathetic skin response parameters in diagnosis of fibromyalgia using artificial neural networks. J Med Syst. 2016;40:54.PubMedView ArticleGoogle Scholar
  84. Ono S, Nishijo Y, Oishi M, Mizutani T. Comparison of the utility of sympathetic skin response and current perception threshold examinations with conventional examinations for the early electrophysiological diagnosis of diabetic polyneuropathy. Electromyogr Clin Neurophysiol. 2005;46:401–7.Google Scholar
  85. Magnon C, Hall SJ, Lin J, Xue X, Gerber L, Freedland SJ, Frenette PS. Autonomic nerve development contributes to prostate cancer progression. Science. 2013;341:1236361.PubMedView ArticleGoogle Scholar
  86. Dyrskjøt L, Kruhøffer M, Thykjaer T, Marcussen N, Jensen JL, Møller K, Ørntoft TF. Gene expression in the urinary bladder: a common carcinoma in situ gene expression signature exists disregarding histopathological classification. Cancer Res. 2004;64:4040–8.PubMedView ArticleGoogle Scholar
  87. Lee J-S, Leem S-H, Lee S-Y, Kim S-C, Park E-S, Kim S-B, Kim S-K, Kim Y-J, Kim W-J, Chu I-S. Expression signature of E2F1 and its associated genes predict superficial to invasive progression of bladder tumors. J Clin Oncol. 2010;28:2660–7.PubMedView ArticleGoogle Scholar
  88. Sanchez-Carbayo M, Socci ND, Lozano J, Saint F, Cordon-Cardo C. Defining molecular profiles of poor outcome in patients with invasive bladder cancer using oligonucleotide microarrays. J Clin Oncol. 2006;24:778–89.PubMedView ArticleGoogle Scholar
  89. Blaveri E, Simko JP, Korkola JE, Brewer JL, Baehner F, Mehta K, Devries S, Koppie T, Pejavar S, Carroll P, Waldman FM. Bladder cancer outcome and subtype classification by gene expression. Clin Cancer Res. 2005;11:4044–55.PubMedView ArticleGoogle Scholar
  90. Lee J, Kotliarova S, Kotliarov Y, Li A, Su Q, Donin NM, Pastorino S, Purow BW, Christopher N, Zhang W, Park JK, Fine HA. Tumor stem cells derived from glioblastomas cultured in bFGF and EGF more closely mirror the phenotype and genotype of primary tumors than do serum-cultured cell lines. Cancer Cell. 2006;9:391–403.PubMedView ArticleGoogle Scholar
  91. Bredel M, Bredel C, Juric D, Harsh GR, Vogel H, Recht LD, Sikic BI. Functional network analysis reveals extended gliomagenesis pathway maps and three novel MYC-interacting genes in human gliomas. Cancer Res. 2005;65:8679–89.PubMedView ArticleGoogle Scholar
  92. Sun L, Hui A-M, Su Q, Vortmeyer A, Kotliarov Y, Pastorino S, Passaniti A, Menon J, Walling J, Bailey R, Rosenblum M, Mikkelsen T, et al. Neuronal and glioma-derived stem cell factor induces angiogenesis within the brain. Cancer Cell. 2006;9:287–300.PubMedView ArticleGoogle Scholar
  93. Murat A, Migliavacca E, Gorlia T, Lambiv WL, Shay T, Hamou M-F, de Tribolet N, Regli L, Wick W, Kouwenhoven MCM, Hainfellner JA, Heppner FL, et al. Stem cell-related “self-renewal” signature and high epidermal growth factor receptor expression associated with resistance to concomitant chemoradiotherapy in glioblastoma. J Clin Oncol. 2008;26:3015–24.PubMedView ArticleGoogle Scholar
  94. Talantov D, Mazumder A, Yu JX, Briggs T, Jiang Y, Backus J, Atkins D, Wang Y. Novel genes associated with malignant melanoma but not benign melanocytic lesions. Clin Cancer Res. 2005;11:7234–42.PubMedView ArticleGoogle Scholar
  95. Riker AI, Enkemann SA, Fodstad O, Liu S, Ren S, Morris C, Xi Y, Howell P, Metge B, Samant RS, Shevde LA, Li W, et al. The gene expression profiles of primary and metastatic melanoma yields a transition point of tumor progression and metastasis. BMC Med Genomics. 2008;1:13.PubMedPubMed CentralView ArticleGoogle Scholar
  96. Critchley-Thorne RJ, Yan N, Nacu S, Weber J, Holmes SP, Lee PP. Down-regulation of the interferon signaling pathway in T lymphocytes from patients with metastatic melanoma. PLoS Med. 2007;4:e176.PubMedPubMed CentralView ArticleGoogle Scholar
  97. Haqq C, Nosrati M, Sudilovsky D, Crothers J, Khodabakhsh D, Pulliam BL, Federman S, Miller JR, Allen RE, Singer MI, Leong SPL, Ljung B-M, et al. The gene expression signatures of melanoma progression. Proc Natl Acad Sci USA. 2005;102:6092–7.PubMedPubMed CentralView ArticleGoogle Scholar
  98. Ma X-J, Dahiya S, Richardson E, Erlander M, Sgroi DC. Gene expression profiling of the tumor microenvironment during breast cancer progression. Breast Cancer Res. 2009;11:R7.PubMedPubMed CentralView ArticleGoogle Scholar
  99. Curtis C, Shah SP, Chin S-F, Turashvili G, Rueda OM, Dunning MJ, Speed D, Lynch AG, Samarajiwa S, Yuan Y, Gräf S, Ha G, et al. The genomic and transcriptomic architecture of 2000 breast tumours reveals novel subgroups. Nature. 2012;486:346–52.PubMedPubMed CentralGoogle Scholar
  100. Radvanyi L, Singh-Sandhu D, Gallichan S, Lovitt C, Pedyczak A, Mallo G, Gish K, Kwok K, Hanna W, Zubovits J, Armes J, Venter D, et al. The gene associated with trichorhinophalangeal syndrome in humans is overexpressed in breast cancer. Proc Natl Acad Sci USA. 2005;102:11005–10.PubMedPubMed CentralView ArticleGoogle Scholar
  101. Turashvili G, Bouchal J, Baumforth K, Wei W, Dziechciarkova M, Ehrmann J, Klein J, Fridman E, Skarda J, Srovnal J, Hajduch M, Murray P, et al. Novel markers for differentiation of lobular and ductal invasive breast carcinomas by laser microdissection and microarray analysis. BMC Cancer. 2007;7:55.PubMedPubMed CentralView ArticleGoogle Scholar
  102. Zhao H, Langerød A, Ji Y, Nowels KW, Nesland JM, Tibshirani R, Bukholm IK, Kåresen R, Botstein D, Børresen-Dale A-L, Jeffrey SS. Different gene expression patterns in invasive lobular and ductal carcinomas of the breast. Mol Biol Cell. 2004;15:2523–36.PubMedPubMed CentralView ArticleGoogle Scholar
  103. Bhattacharjee A, Richards WG, Staunton J, Li C, Monti S, Vasa P, Ladd C, Beheshti J, Bueno R, Gillette M, Loda M, Weber G, et al. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc Natl Acad Sci USA. 2001;98:13790–5.PubMedPubMed CentralView ArticleGoogle Scholar
  104. Beer DG, Kardia SLR, Huang C-C, Giordano TJ, Levin AM, Misek DE, Lin L, Chen G, Gharib TG, Thomas DG, Lizyness ML, Kuick R, et al. Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nat Med. 2002;8:816–24.PubMedGoogle Scholar
  105. Stearman RS, Dwyer-Nield L, Zerbe L, Blaine SA, Chan Z, Bunn PA, Johnson GL, Hirsch FR, Merrick DT, Franklin WA, Baron AE, Keith RL, et al. Analysis of orthologous gene expression between human pulmonary adenocarcinoma and a carcinogen-induced murine model. Am J Pathol. 2005;167:1763–75.PubMedPubMed CentralView ArticleGoogle Scholar
  106. Hou J, Aerts J, den Hamer B, van Ijcken W, den Bakker M, Riegman P, van der Leest C, van der Spek P, Foekens JA, Hoogsteden HC, Grosveld F, Philipsen S. Gene expression-based classification of non-small cell lung carcinomas and survival prediction. PLoS One. 2010;5:e10312.PubMedPubMed CentralView ArticleGoogle Scholar
  107. Okayama H, Kohno T, Ishii Y, Shimada Y, Shiraishi K, Iwakawa R, Furuta K, Tsuta K, Shibata T, Yamamoto S, Watanabe S, Sakamoto H, et al. Identification of genes upregulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas. Cancer Res. 2012;72:100–11.PubMedView ArticleGoogle Scholar
  108. Selamat SA, Chung BS, Girard L, Zhang W, Zhang Y, Campan M, Siegmund KD, Koss MN, Hagen JA, Lam WL, Lam S, Gazdar AF, et al. Genome-scale analysis of DNA methylation in lung adenocarcinoma and integration with mRNA expression. Genome Res. 2012;22:1197–211.PubMedPubMed CentralView ArticleGoogle Scholar
  109. Landi MT, Dracheva T, Rotunno M, Figueroa JD, Liu H, Dasgupta A, Mann FE, Fukuoka J, Hames M, Bergen AW, Murphy SE, Yang P, et al. Gene expression signature of cigarette smoking and its role in lung adenocarcinoma development and survival. PLoS One. 2008;3:e1651.PubMedPubMed CentralView ArticleGoogle Scholar
  110. Su L-J, Chang C-W, Wu Y-C, Chen K-C, Lin C-J, Liang S-C, Lin C-H, Whang-Peng J, Hsu S-L, Chen C-H, Huang C-YF. Selection of DDX5 as a novel internal control for Q-RT-PCR from microarray data using a block bootstrap re-sampling scheme. BMC Genom. 2007;8:140.View ArticleGoogle Scholar

Copyright

© The Author(s) 2016

Advertisement