Clinical Science (2015) 128, 29–37 (Printed in Great Britain) doi: 10.1042/CS20140007

Feasibility of global miRNA analysis from fine-needle biopsy FFPE material in patients with hepatocellular carcinoma treated with sorafenib

Clinical Science

www.clinsci.org

¨ Jan PEVELING-OBERHAG∗ , Claudia DORING†, Sylvia HARTMANN†, Natalie FILMANN‡, Angelika MERTENS∗ , ∗ Albrecht PIIPER , Eva HERRMANN‡, Martin-Leo HANSMANN†, Stefan ZEUZEM∗ , J¨org TROJAN∗1 and Martin-Walter WELKER∗1 ∗

Medizinische Klinik 1, Universit¨atsklinikum Frankfurt, Goethe-Universit¨at, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany †Senckenbergisches Institut f¨ur Pathologie, Universit¨atsklinikum Frankfurt, Goethe-Universit¨at, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany ‡Institut f¨ur Biostatistik und Mathematische Modellierung, Fachbereich Medizin, Goethe-Universit¨at, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany

Abstract Sorafenib is the standard treatment for patients with advanced hepatocellular carcinoma (HCC). However, the median overall survival (OS) benefit is only ∼3 months, and sufficient biomarkers predicting treatment response are not available. The aim of the present study was to evaluate miRNA expression patterns from HCC tissue biopsies as potential biomarkers in patients under sorafenib treatment. Nineteen patients with advanced HCC treated with sorafenib were included. RNA was extracted from formalin-fixed paraffin-embedded (FFPE) liver biopsies. miRNA expression profiling of 818 mature miRNAs was performed using GeneChip® miRNA Array 2.0 (Affymetrix). Global miRNA patterns were assessed using unsupervised hierarchical clustering analysis (UCA), and specific miRNAs with correlation with disease control rate (DCR) or good OS were evaluated by pairwise supervised analyses. UCA divided the patients into three distinct groups by their miRNA expression patterns. However, DCR or OS did not correlate with these sub-groups. We have identified several miRNAs that correlated with either DCR or OS (P < 0.05). However, with correction for multiple testing, these results did not reach statistical significance in this small cohort. Global miRNA analysis from very low input RNA deriving from liver biopsies showed distinctive clustering of molecular sub-groups in patients with intermediate and advanced HCC. Clinical response including OS under sorafenib did not correlate with global miRNA expression patterns, but we have identified candidate miRNAs for the prediction of DCR and OS to be evaluated in prospective studies and larger patient cohorts. Key words: cancer, hepatocellular carcinoma (HCC), liver, miRNA, sorafenib

INTRODUCTION Hepatocellular carcinoma (HCC) is a major complication of endstage liver disease [1–4]. The worldwide annual incidence of HCC is estimated to be 600 000 cases. In Western countries and Japan, the incidence of hepatitis C virus (HCV)-related liver cirrhosis and liver cancer is rising due to the HCV epidemic [5,6]. A further increase is assumed, since obesity, diabetes mellitus and non-alcoholic steatohepatitis have been identified as risk factors of HCC, especially in Western countries [7]. Other important risk

factors for HCC development are chronic hepatitis B virus (HBV) infection, haemochromatosis and alcohol-related liver cirrhosis [4,8]. According to the Barcelona Clinic Liver Cancer (BCLC) system, HCC is differentiated into five stages [3,9]. Curative treatment options are available in (very) early-stage HCC (BCLC-0, BCLC stage A) only, whereas treatment in BCLC stages B–D is non-curative and palliative, associated with median survival rates of less than 2 years [2,3]. A major step in HCC pathogenesis, in general, is the switch to arterial hypervascularization, which

Abbreviations: AFP, α-fetoprotein; BCLC, Barcelona Clinic Liver Cancer; DCR, disease control rate; FC, fold change; FDR, false discovery rate; FFPE, formalin-fixed paraffinembedded; HBV, hepatitis B virus; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; OS, overall survival; PI3K, phosphoinositide 3-kinase; Q-RT-PCR, quantitative real-time reverse transcription PCR; TGFβ, transforming growth factor β; UCA, unsupervised hierarchical clustering analysis. 1 These authors contributed equally to this work. Correspondence: Dr Jan Peveling-Oberhag (email [email protected]).

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principally occurs in nodules exceeding a diameter of ∼2 cm [10,11]. Anti-angiogenic treatment of HCC either by transarterial chemoembolization (TACE) or sorafenib, an oral multikinase inhibitor with activity against vascular endothelial growth factor receptor 2 (VEGFR2), platelet-derived growth factor receptor (PDGFR), c-Kit receptors, b-RAF and p38, is the current basic principle in HCC treatment in non-curable stages [12]. Sorafenib is currently the sole agent approved for HCC and has become the backbone in anti-angiogenic therapy in patients with HCC BCLC stage C and selected patients with HCC BCLC stage B [13]. In the pivotal study with sorafenib performed in a Western cohort, the objective response rate was less than 5 %, and the disease control rate (DCR) was 43 % in patients treated with sorafenib (n = 299) [14]. Moreover, the median overall survival (OS) benefit was 2.8 months compared with best supportive care [14]. Comparable results were seen in a large Asian-Pacific population [15]. Hence, the main therapeutic effect of sorafenib is disease stabilization [14]. However, significant tumour size reduction and long-lasting response under sorafenib therapy have been reported in single patients [16,17]. Numerous drug-related events were observed within these trials as well as in clinical practice, for example hand–foot skin reaction, fatigue, diarrhoea and weight loss [14,15,18,19]. Reliable biomarkers predicting treatment response to sorafenib in HCC are not available yet, although an α-fetoprotein (AFP) decline has been suggested as a predictive surrogate marker for efficacy in patients with baseline AFP >20 ng/ml before initiation of sorafenib [20]. Dysregulation, either over- or under-expression, of small regulatory non-coding RNA molecules (miRNAs) has been reported in various malignant entities, and dysregulation of miRNA expression is assumed to play a major role in cancer pathogenesis [21,22]. Moreover, a classification of HCC subpopulations by distinct miRNA patterns has been reported previously [23]. The aim of the present study was, therefore, to evaluate the feasibility of global miRNA expression analyses from formalinfixed paraffin-embedded (FFPE) liver biopsy specimens. Furthermore, we aimed at analysing whether miRNA expression patterns in advanced HCC are linked to treatment response to sorafenib.

MATERIALS AND METHODS Patient selection and treatment/ethics statement The present study is a retrospective analysis, which was approved by the local Ethics Committee of the University Hospital Frankfurt, Germany (Ethik-Kommission des Fachbereichs Medizin der Johann Wolfgang Goethe-Universit¨at). Written informed consent was obtained from all patients. In total, 19 patients with mainly intermediate and advanced liver cancer were treated with sorafenib (target dose, 400 mg twice daily) in a tertiary German liver centre (Table 1). Patients with intermediate HCC received sorafenib as second-line treatment or had contraindications to other treatment options.

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Table 1 Patient characteristics Values are means + − S.D., medians (minimum, maximum) or numbers (percentage). ∗ At first diagnosis of HCC; † at start of sorafenib. ECOG, Eastern Co-operative Oncology Group; MELD, Model for End-Stage Liver Disease. Parameter

Value

Age (years)∗

64 + − 14

Gender (n) Female

4 (21 %)

Male

15 (79 %)

Ancestry region (n) Europe

19

Cause of liver cirrhosis (n) Viral (HBV or HCV) Non-viral Body mass index (kg/m2 )†

5 (26 %) 14 (74 %) 29.3 + − 3.6

ECOG performance status (n)† 0

15 (79%)

1

4 (21%)

Child–Pugh class (n)† A B

18 (95 %) 1 (5 %)

MELD score∗

7 (6, 17)

AFP serum level (ng/ml)†

17 (1.6, 79579)

BCLC stage (n)† A

1 (5 %)

B

11 (58 %)

C

7 (37 %)

Histological grading (G) (n)∗ G1

2 (11 %)

G2

15 (79 %)

G3

1 (5 %)

G4

1 (5 %)

Second-line therapy after sorafenib (n)

4 (21 %)

Third-line therapy after sorafenib (n)

2 (11 %)

Evaluation of treatment response Survival was recorded in all patients and classified as good (longer than median survival of the cohort) or poor (shorter than median survival of the cohort). Furthermore, treatment response was assessed radiologically using either contrast-enhanced computed tomography (CT) or dynamic MRI according to the Response Evaluation Criteria In Solid Tumours (RECIST) [24]. DCR was defined as the percentage of patients who achieved complete response, partial response, or stable disease at first staging.

Liver biopsy and histological assessment of liver cancer Biopsy under ultrasound guidance was performed with an 18 gauge cutting needle to allow accurate histological evaluation. Liver biopsy specimens were fixed in formalin and embedded in paraffin for routine staining and immunohistochemistry. Diagnosis of HCC was confirmed by an experienced pathologist. Grading was assessed according to the current TNM (tumour node metastasis) classification of malignant tumours.

miRNA signature during sorafenib therapy

Immunohistochemical staining for glypican 3, glutamine synthetase and heat-shock protein 70 (HSP70) was used to support diagnosis and grading evaluation. All liver biopsies were microscopically reviewed by a pathologist, and tissue areas with a tumour cell content of more than 95 % were macro-dissected and used for further analyses.

Isolation and expression profiling analysis of miRNA Total RNA was extracted from tumour biopsy FFPE specimen using the RNeasy FFPE Kit (Qiagen) following the manufacturer’s protocol. RNA quantification was performed using the Nanodrop 2000 spectrometer (Thermo Fisher Scientific) using 50 ng of total RNA for further analyses.

Material preparation for validation experiments To test the performance of the procedure in low tissue amounts, technical and biological replicates were analysed. For technical validation, the array analysis was repeatedly performed (duplicate) from the same RNA extract. To evaluate biological variance, one HCC FFPE biopsy was separated into two fragments using a scalpel (blade no. 11), and RNA extraction as well as further analysis [microarray or quantitative real-time reverse transcription PCR (Q-RT-PCR)] were performed independently for the same patient.

Microarray analysis Global miRNA expression profiling analysis of 818 mature miRNAs using GeneChipR miRNA Array v1.0 (Affymetrix) was performed following the manufacturer’s protocol with the exception of the hybridization duration. Hybridization time was elongated from 18 to 40 h to compensate for low RNA input amount. The data discussed in the present study have been deposited in the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus [25] and are accessible through GEO series accession number GSE56059 (http://www. ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GSE56059).

Real-time PCR miRNA expression analysis Quantification of miRNA was performed by standardized TaqMan® MicroRNA Q-RT-PCR assays (Applied Biosystems) according to the manufacturer’s protocol. Expression was analysed for three miRNAs (hsa-miR-21, hsa-miR-126 and hsa-miR150) and one endogenous control (U6). Samples were analysed in triplicate, and Ct values were calculated using the endogenous control.

with more than two groups involved with either unrelated or related samples respectively. Statistical analysis of miRNA profiles was performed using the statistical computing environment R. Additional software packages (geneplotter, gplots) were taken from the Bioconductor project. Replicate correlation was calculated using Pearson’s correlation coefficient and depicted as a scatterplot. Unsupervised hierarchical clustering analysis (UCA) was performed for miRNAs with an S.D. 1.5 across all samples using the Manhattan distance method and the average linkage method. For the supervised analysis, an expression intensity and variance filter was used to reduce the dimension of microarray data. Data were filtered by an intensity filter (gene intensity >100 in at least 25 % of the samples, if the group size is equal) and a variance filter (the interquartile range of log 2 intensities >0.5, if the group size is equal). After the filtering process P values were calculated with two sample t tests (variance = equal) to identify differentially expressed miRNAs between two groups. For multiple testing problems, a false discovery rate (FDR) was used [26]. Also fold change (FC) between the two groups was calculated for each gene. The lists of differentially expressed genes were then filtered for P < 0.05 and FC > 1.5. DIANA miRPath v.2.0 was used as a computational predictive model to calculate potentially targeted genes and pathways using microT-CDS database (P value threshold 0.05, MicroT threshold 0.8, FDR correction and conservative statistics applied) [27]. Depicted pathways are derived from the KEGG database [25].

RESULTS Efficacy of sorafenib therapy Mean + − S.E.M. and median OS were 1247 + − 142 days and 1482 days respectively. First staging was performed at 102 (57– 208) days (median, range) after start of sorafenib therapy. In patients with available radiological response assessment (n = 15), median progression-free survival was 256 days (minimum 84, maximum 1824). Overall, seven out of 19 (37 %) patients showed a good response, defined as longer than mean survival, compared with 12 out of 19 (63 %) patients with poor response. The DCR was 15 out of 19 (79 %) patients. Tumour biopsies were acquired at 57 (6–159) days (median, range) before start of the sorafenib therapy.

Technical validation of miRNA analysis Bioinformatics and statistical analyses Clinical and biochemical characteristics of patients are expressed as means + − S.D. or medians and range as appropriate. Unless indicated otherwise, all tests were two tailed and P values < 0.05 were considered significant. Survival was assessed by Kaplan– Meier’s analysis. Pearson’s correlation or Spearman’s test was applied as appropriate for calculation of correlations between two variables. Wilcoxon Mann–Whitney’s U test or Wilcoxonpaired sample test was applied for comparisons of two groups with either unrelated or related samples respectively. Kruskal– Wallis’s test or Friedman’s test was used for group comparisons

The use of small liver biopsy specimen for array analysis yielded very low input RNA (50–100 ng of total RNA). To test the performance of the miRNA analysis in low tissue amounts, technical and biological replicates were analysed using two complimentary methods. For technical validation the array analysis was repeatedly performed (duplicate) from the same RNA extract [Pearson’s correlation coefficient (R) = 0.915, Figure 1A]. To evaluate biological variance within the tumour, one HCC FFPE biopsy was separated in two fragments and further analysis (microarray or Q-RT-PCR) was performed independently for the same patient. The microarray analysis showed a close

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Inter-individual correlation of miRNA expression profiles in advanced HCC

Figure 1 Technical validation of replicates (A) Array analysis was repeatedly performed (duplicate) to evaluate assay reproducibility. A scatterplot is shown depicting correlation of miRNA expression between two replicates [measurement 1 (y-axis) and measurement 2 (x-axis)] of the same RNA extract [Pearson’s correlation coefficient (R) = 0.915). (B) One HCC biopsy was separated into two and RNA extraction as well as microarray analysis were performed independently for the same patient (R1 compared with R1∗ ). A scatterplot is shown depicting correlation of miRNA expression between two replicates [R1∗ (y-axis) and R1 (x-axis)] of the same individual [Pearson’s correlation coefficient (R) = 0.692]. (C) Comparison of biological replicates using Q-RT-PCR. miRNA expression was analysed for three randomly chosen miRNAs (hsa-miR-21, hsa-miR-126 and hsa-miR-150) and one endogenous control (U6). Samples were analysed in triplicate, and Ct values were calculated using the endogenous control.

correlation for biological replicates (R = 0.69, Figure 1B). In addition, Q-RT-PCR was performed as a complimentary validation method. Expression of three randomly chosen miRNAs (miR-21, miR-126 and miR-150) correlated well between biological replicates, and quantitative expression differences were comparable with semi-quantitative assessment by microarray experiments (Figure 1C).

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After global filtering, a panel of 84 miRNAs was used to perform UCA. UCA divided the patients into three distinct subgroups by their respective global miRNA expression profile (Figure 2). The cluster features two equally large groups (group A, n = 8, and group B, n = 8) and a small cluster of three patients (group C). The small group C shows a general down-regulation of nearly all of the featured miRNAs. In particular the let-7 group of miRNAs is strongly down-regulated with up to 45-fold downregulation compared with the other groups (see Supplementary Table S1 at http://www.clinsci.org/cs/128/cs1280029add.htm). In the direct comparison of groups A and B, a relatively low general expression of miRNAs in group B with particularly strong down-regulation of some known tumour suppressor miRNAs (e.g. miR-29a, miR-126 and miR-26a) was observed, whereas group A featured a relative down-regulation of miR-99/100, miR1826 and miR-768-5p. The HCC miRNA cluster groups did not correlate with HCC aetiology, AFP level, histological grading, immunohistochemical markers of differentiation, radiological tumour stage (results not shown) or overall patient survival (P = non-significant for all; Figure 3). DIANA-miRPath v2.0 enrichment analysis of predicted miRNA target genes was used to identify pathways potentially influenced by the miRNA profiles for the respective cluster groups. For each group, miRNAs with differential expression and highest fold-change compared with the respective two other groups were selected as basis for the analysis (FC > 2 × S.D.; P < 10−4 , see Supplementary Table S2 at http://www.clinsci.org/cs/128/cs1280029add.htm). All three groups were enriched for well-known oncogenic signalling pathways. Group A was highly enriched for miRNAs with a role in the phosphoinositide 3-kinase (PI3K)/Akt pathway (P = 2.1×10−13 ). Group B was predicted to be associated with ErbB and the mitogen-activated protein kinase (MAPK) signalling cascades respectively (P = 9.2×10−16 and P = 3.0×10−13 ). miRNAs differentially expressed in group C were enriched for miRNA target genes involved in the transforming growth factor β (TGFβ) pathway (P = 4.2×10−7 ). PI3K/Akt, ErbB and TGFβ pathways with potentially affected genes are shown in Supplementary Figure S1 (http://www.clinsci.org/cs/128/cs1280029add.htm).

Association of single miRNAs with patient characteristics Several specific miRNAs showed correlations with clinical parameters of the included HCC patients in the supervised expression analysis. HCC arising in patients with non-viral liver disease (HBV or HCV) showed the up-regulation of miR494, miR-1826, miR-923 and miR-768-5p, whereas AFP elevation (>400 ng/ml) was associated with the up-regulation of miR-342-3p, miR-130a, miR-150, miR-574-3p and miR-15b and the down-regulation of miR-30c (see Supplementary Table S3 at http://www.clinsci.org/cs/128/cs1280029add.htm; FC  3 and P < 0.05 for all). Moreover, tumour expression levels of specific miRNAs were identified to correlate with the response to therapy and survival (Table 2). Down-regulation of miR-99b was associated with DCR (P < 0.05), whereas up-regulation of miR-140-3p, miR-100, miR-125 and miR-22 was associated with

miRNA signature during sorafenib therapy

Figure 2

UCA of miRNA expression profiles generated from 19 HCC tumour samples using GeneChipR miRNA Array (version 1.0) UCA was performed for miRNAs with an S.D. 1.5 across all samples using the Manhattan distance method and the average linkage method. High expression is given in red and low expression in green.

a good OS (P < 0.05 for all). Statistical significance of the abovementioned associations, however, was not maintained after correction for multiple testing (FDR > 0.05).

DISCUSSION Worldwide, HCC is the sixth most common cancer [1]. Most patients are diagnosed with intermediate or advanced stages, and thus overall therapeutic options are limited and prognosis is still poor [9]. Moreover, the clinical course and molecular alterations show a high variability [28,29]. Currently, no clinically reliable biomarker is known to predict the individual treatment response, mainly to sorafenib, in patients with intermediate or advanced HCC. miRNAs are involved in regulation of gene expression and thereby affect virtually all cell functions [30]. Consequently, miRNAs are promising putative biomarkers in HCC as their up-regulation and down-regulation have been associated with pathogenesis and clinical outcome in HCC [31–35]. For instance, miR-199a/b-3p has been found to be consistently down-regulated

compared with tumour-adjacent non-tumourous tissue in 255 out of 294 samples (87 %) and low miR-199a/b-3p expression correlated with poor OS [36]. Moreover, a classification of HCC based on miRNA expression levels has been proposed previously [23]. Nevertheless, it is yet unknown, whether miRNA patterns could be used as a biomarker to distinguish between HCC patients with better or worse course in advanced stages (BCLC stages B/C). In the present study, we have investigated whether miRNAs obtained from percutaneous liver biopsy specimen could be used to classify intermediate and advanced stage HCC and, moreover, predict treatment response to sorafenib. Toffanin et al. [23] and most others [33,37–40] performing global miRNA expression analyses have used surgically resected HCC specimens. In daily clinical practice and according to current guidelines [11,41], surgical treatment – either resection or liver transplantation – is suitable for early HCC stages only. Thus, studies investigating miRNA expression profiles have derived mainly from early liver cancer specimen. One group previously used fresh-tissue fine-needle HCC biopsies to perform an array-based miRNA analysis screening for only a small fragment of currently known miRNAs [42]. A custom microarray

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Figure 3 Kaplan–Meier’s survival analysis of 19 patients since the start of sorafenib treatment Patients were stratified for either of three HCC miRNA clusters groups deriving from the UCA (see Figure 2; dashed: group A, n = 8; dash-dotted: group B, n = 8; joined: group C, n = 3). OS was not associated with groups of miRNA expression patterns.

Table 2

Specific miRNAs associated with DCR or OS

(A) miRNA associated with DCR miRNA

FC

P value

FDR

hsa-miR-99b

−2.24

0.074

0.75

(B) miRNAs associated with OS miRNA

FC

P value

FDR

hsa-miR-140-3p

2.5

0.015

0.38

hsa-miR-100

3.5

0.023

0.38

hsa-miR-125b

2.9

0.026

0.38

hsa-miR-22

2.8

0.046

0.38

was used containing probes for 180 mature human miRNAs, and five down-regulated and three up-regulated miRNAs were discovered compared with non-tumourous liver tissue. Previously, other groups investigated miRNA expression from hepatic FFPE material using real-time PCR from different samples or demonstrating the feasibility of miRNA array experiments from tissue sections [43,44]. Also, FFPE tissue from unguided biopsies from non-cirrhotic non-tumorous liver has been successfully used for array-based miRNA analyses [45]. The novelty in the present study lies in the use of FFPE material from very small ultrasoundguided HCC biopsies of patients under sorafenib therapy, which, to our knowledge, has not been published to date. Liver biopsies can be performed in most patients with intermediate or advanced HCC, and archived FFPE biopsy tissue is readily available. Possible disadvantages are fixation-associated decrease in RNA quality and the much smaller amount of tissue available for analysis. With small modifications to the hybridization routine of the microarray platform, we were able to achieve a high-quality quantification of global miRNA expression from as low as 50 ng of input RNA deriving from FFPE tissue. Technical

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validation showed very good reproducibility, and UCA was comparable with previously published miRNA UCA patterns [23]. As expected the correlation coefficient of biological replicates was lower compared with technical replicates, probably due to intra-tumoural heterogeneity. However, the reproducibility was still very high, allowing for good quality miRNA screening from FFPE fine-needle biopsy specimen. In the present study, RNA extraction was performed from HCC areas only (tumour cell content >95 %). Thus, observed distinct miRNA cluster profiles are based on molecular differences in HCC itself rather than on differences of cirrhotic tissue. The data suggest that intermediate and advanced HCC can be classified into three groups by tumour HCC miRNA expression clusters, which is a similar finding to previous studies that included mostly early HCC stages [23]. One cluster (group C) featured a generally low expression of all miRNAs with marked down-regulation of let-7g, which has known tumour suppressive properties and was found to be down-regulated in HCC tissue by others [46,47]. Nevertheless, down-regulation of let-7g was not associated with the clinical or histopathological tumour phenotype in the present study. Group B also showed a general downregulation of miRNAs when compared with group A, including suppression of miR-26a, miR-29a and miR-126, all miRNAs whose down-regulation has been associated previously with HCC pathogenesis [48–50]. miR-99a and miR-100 are down-regulated in group A. Also, suppression of those two miRNAs has been implicated in HCC pathogenesis and prognosis before [51,52]. Furthermore, pathway analysis showed an enrichment of genes potentially influenced by detected miRNAs within the PI3K/Akt, ErbB and TGFβ pathways for groups A, B and C respectively. Those pathways have been associated with cancer development in general and were frequently found previously to be dysregulated in HCC [53–57]. However, the current pathways analyses have to be treated with caution as they are based on an in silico approach only and are not yet supported by mRNA gene expression data. We have found several miRNAs to be differentially expressed between viral and non-viral aetiologies of HCC underlying liver disease. In particular miR-494, which was up-regulated in HCC of non-viral origin, has been recently implicated in HCC carcinogenesis [58]. Among miRNAs that were associated with AFP elevation, miR-15b was found to be associated with HCC prognosis in previous studies [59,60]. Next, we have investigated whether miRNA profiles or dysregulation of distinct miRNA species may be associated with the treatment response to sorafenib. No association between the three identified tumour miRNA expression patterns and survival in sorafenib-treated patients was observed. Furthermore, we have analysed putative correlations of individual miRNAs with DCR or OS in patients with sorafenib-treated HCC. Indeed, several miRNAs were associated with either DCR or OS. However, this was not statistically significant after correction for multiple testing, which – in part – could be explained by the limited number of patients included in the present study. miRNAs with previously described correlation with the prognosis in surgically resected HCC, such as miR-199a/b, did not correlate with DCR or OS in the present study [61–63]. A possible explanation for this might be the fact that miR-199a/b is only predictive for surgical therapy

miRNA signature during sorafenib therapy

of less advanced HCC, as our cohort contained only advanced non-resectable HCC.

man Federal Ministry of Education and Research (BMBF, BioChancePlus [grant number #0316043E]).

CLINICAL PERSPECTIVES

REFERENCES

r

r

r

Sorafenib is the standard of care in patients with advanced HCC. However, the median OS benefit is approximately only 3 months, and sufficient biomarkers predicting treatment response are not available. The aim of the present study was to evaluate miRNA expression patterns from HCC tissue biopsies as potential biomarkers in patients under sorafenib treatment. We show the feasibility of global miRNA expression analyses from small FFPE liver biopsy specimens, and that the experimental protocol allows increased availability of tissue for future miRNA studies in HCC. Three different miRNA expression clusters were identified in patients with intermediate and advanced HCC in a Caucasian patient cohort, but were not linked to the sorafenib treatment response. This study demonstrates that miRNA analyses are feasible from fine needle biopsy specimens and is the first to correlate the response under sorafenib therapy with miRNA expression signatures in HCC. The data do not support that miRNA profiles function as reliable biomarkers for sorafenibresponse-prediction. Nevertheless, it might be worthwhile including the candidate miRNAs identified in the present study in biomarker protocols in ongoing or future studies on antiangiogenic agents beyond sorafenib.

AUTHOR CONTRIBUTION

Jan Peveling-Oberhag designed and performed the research, revised and analysed the clinical data and wrote the paper; Claudia D¨oring performed the bioinformatics and statistical analysis; Sylvia Hartmann provided advice, and collected and characterized the histological samples; Natalie Fillmann performed the statistical analysis; Angelika Mertens performed the research and collected histological samples; Albrecht Piiper provided advice and assisted in the correction of the paper; Eva Herrmann performed the statistical analysis, provided advice and revised the paper; Martin-Leo Hansmann designed the research, collected and characterized histological samples and revised the paper; Stefan Zeuzem designed the research, provided advice and revised the paper; J¨org Trojan designed the research, provided advice and revised the paper; MartinWalter Welker designed and performed the research, revised and analysed clinical data, and wrote the paper.

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15 ACKNOWLEDGEMENTS

We thank Ekaterini Hadzoglou and Sabine Albrecht for excellent technical assistance. 16 FUNDING

This work was supported by a ‘Patenschaftsmodell’ grant from the Medical Faculty of the J.W. Goethe-University Hospital and the Ger-

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Received 2 January 2014/22 May 2014; accepted 24 June 2014 Published as Immediate Publication 24 June 2014, doi: 10.1042/CS20140007

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37

Clinical Science (2015) 128, 29–37 (Printed in Great Britain) doi: 10.1042/CS20140007

SUPPLEMENTARY ONLINE DATA

Feasibility of global miRNA analysis from fine-needle biopsy FFPE material in patients with hepatocellular carcinoma treated with sorafenib ¨ Jan PEVELING-OBERHAG∗ , Claudia DORING†, Sylvia HARTMANN†, Natalie FILMANN‡, Angelika MERTENS∗ , ∗ Albrecht PIIPER , Eva HERRMANN‡, Martin-Leo HANSMANN†, Stefan ZEUZEM∗ , J¨org TROJAN∗1 and Martin-Walter WELKER∗1 ∗ Medizinische Klinik 1, Universit¨atsklinikum Frankfurt, Goethe-Universit¨at, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany †Senckenbergisches Institut f¨ur Pathologie, Universit¨atsklinikum Frankfurt, Goethe-Universit¨at, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany ‡Institut f¨ur Biostatistik und Mathematische Modellierung, Fachbereich Medizin, Goethe-Universit¨at, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany

See subsequent pages for Supplementary Figure S1 and Supplementary Tables S1–S3

1 These

authors contributed equally to this work.

Correspondence: Dr Jan Peveling-Oberhag (email [email protected]).

 C The Authors Journal compilation  C 2015 Biochemical Society

J. Peveling-Oberhag and others

 C The Authors Journal compilation  C 2015 Biochemical Society

miRNA signature during sorafenib therapy

Figure S1

Table S1

DIANA-miRPath v2.0 enrichment analysis of predicted miRNA target pathways Gene to miRNA interaction is calculated using DIANA-microT-CDS prediction software. Pathways deriving from KEGG database are marked for genes with potential interaction with miRNAs dysregulated in one miRNA cluster group compared with the two other groups respectively (genes with one miRNA match are depicted in yellow, >2 miRNAs in orange). (A) Group A, PI3K/Akt signalling pathway, P value: 2.1 × 10−13 . (B) Group B, ErbB signalling pathway, P value: 9.2 × 10−16 . (C) Group C, TGF-β signalling pathway, P value: 4.2 × 10−7 .

Differential miRNAs between UCA cluster groups (groups A–C according to Figure 2 of the main paper) Genes were filtered for likelihood of differential expression with P < 0.05 and FC > 1.5. Group A compared with group B

Group A compared with group C

miRNA

FC

P value

miRNA

FC

P value

Group B compared with group C miRNA

FC

P value

miR-28-3p

3.8

5.0 × 10−6

let-7g

45.3

3.89 × 10−7

miR-146a

11.3

3.04 × 10−5

miR-22

3.2

1.1 × 10−5

miR-126

16.7

1.04 × 10−6

miR-22

4.5

3.96 × 10−5

miR-27b

4.0

2.1 × 10−5

miR-29a

32.3

1.33 × 10−6

miR-146b-5p

17.3

4.35 × 10−5

miR-152

4.2

2.8 × 10−5

miR-27b

25.8

2.51 × 10−6

miR-29a

8.6

6.74 × 10−5

miR-30a

3.9

3.3 × 10−5

miR-151-5p

12.9

3.41 × 10−6

miR-130a

6.4

1.28 × 10−4

miR-29a

3.8

3.5 × 10−5

miR-152

19.4

3.95 × 10−6

miR-191

12.3

1.91 × 10−4

miR-126

2.9

5.0 × 10−5

miR-22

14.4

4.02 × 10−6

miR-27b

6.4

3.40 × 10−4

miR-26a

2.6

6.9 × 10−5

let-7f

28.4

5.54 × 10−6

miR-30b

13.8

4.17 × 10−4

let-7c

2.1

1.3 × 10−4

miR-378

23.9

6.69 × 10−6

miR-30d

7.3

4.19 × 10−4

miR-148a

5.4

1.4 × 10−4

miR-16

23.5

8.89 × 10−6

miR-126

5.8

4.40 × 10−4

3.5

−4

15.1

−6

miR-15b

21.6

5.30 × 10−4

−6

miR-151-5p

6.9

6.12 × 10−4

−5

miR-30a

4.9

6.35 × 10−4

−5

miR-26a

7.3

6.91 × 10−4

−5

miR-93

11.9

9.01 × 10−4

−5

miR-425

9.9

9.72 × 10−4

−5

miR-30c

10.6

9.76 × 10−4

−5

let-7f

8.2

9.79 × 10−4

−5

miR-106a

9.7

1.15 × 10−3

−5

miR-148a

5.3

1.23 × 10−3

−5

miR-23b

9.6

1.25 × 10−3

−5

miR-34a

8.4

1.33 × 10−3

−5

miR-19b

9.1

1.35 × 10−3

−5

miR-130b

5.0

1.54 × 10−3

−5

miR-20a

13.0

1.60 × 10−3

−5

miR-17

12.9

1.63 × 10−3

−5

let-7g

10.1

1.65 × 10−3

−5

miR-103

9.4

1.69 × 10−3

−5

miR-16

14.0

1.73 × 10−3

−5

miR-378

6.4

2.84 × 10−3

−5

miR-107

13.6

3.02 × 10−3

−5

miR-24

8.9

3.03 × 10−3

−5

miR-192

22.4

3.18 × 10−3

−4

miR-222

12.8

3.19 × 10−3

let-7f miR-100

−4.4 4.5

let-7g

3.3

miR-27a miR-99a

−5.4 4.5

miR-30e miR-143 miR-125b

4.4 3.2 2.2

miR-24

2.3

let-7a miR-1274b ∗

miR-30a

miR-378 let-7d miR-30b miR-1826 miR-151-5p let-7i miR-15a miR-34a miR-10a miR-532-5p miR-192 miR-194

4.9 4.5 3.7 2.3 2.7 −1.4 1.9 3.4 2.8 2.9 3.4 2.9 3.5 3.3

1.8 × 10

−4

2.1 × 10

−4

2.2 × 10

−4

2.3 × 10

−4

2.3 × 10

−4

2.4 × 10

−4

2.4 × 10

−4

3.0 × 10

−4

3.1 × 10

−4

3.4 × 10

−4

6.9 × 10

−3

1.4 × 10

−3

1.5 × 10

−3

2.2 × 10

−3

2.2 × 10

−3

3.2 × 10

−3

5.0 × 10

−3

5.0 × 10

−3

6.4 × 10

−3

8.3 × 10

−3

8.7 × 10

−2

1.2 × 10

−2

1.2 × 10

−2

1.7 × 10

miR-425 miR-30d miR-27a miR-93 miR-99a miR-100 miR-106a miR-146b-5p miR-34a miR-20a let-7i miR-26a miR-28-3p miR-148a miR-30b miR-146a miR-191 miR-30a miR-21 miR-17 miR-125b miR-15a miR-106b miR-25

12.1 18.1 21.2 22.2 15.1 17.0 23.2 24.5 29.1 21.6 18.8 7.9 29.0 37.1 22.4 15.3 19.1 23.4 22.9 9.9 15.9 23.3 20.7

9.05 × 10 9.16 × 10 1.02 × 10 1.47 × 10

1.61 × 10 1.75 × 10 1.79 × 10

2.08 × 10 2.16 × 10 2.47 × 10 2.88 × 10

2.93 × 10 3.52 × 10 3.80 × 10 3.83 × 10 3.88 × 10 5.28 × 10 5.36 × 10 5.75 × 10 6.40 × 10

7.80 × 10 8.10 × 10 9.59 × 10 1.11 × 10

 C The Authors Journal compilation  C 2015 Biochemical Society

J. Peveling-Oberhag and others

Table S1

Continued Group A compared with group B

Group A compared with group C

miRNA

FC

P value

miRNA

FC

P value

Group B compared with group C miRNA

FC

P value

miR-200c

4.2

1.8 × 10−2

let-7a

16.5

1.26 × 10−4

miR-27a

5.5

3.25 × 10−3

miR-221

3.2

1.9 × 10−2

miR-15b

27.9

1.67 × 10−4

let-7a

7.3

3.26 × 10−3

miR-106b

2.8

2.4 × 10−2

miR-10a

8.5

1.72 × 10−4

miR-106b

8.3

3.26 × 10−3

miR-497

3.0

2.4 × 10−2

miR-222

22.7

1.74 × 10−4

miR-23a

10.6

3.87 × 10−3

miR-768-5p

−1.9

2.5 × 10−2

miR-143

10.2

1.94 × 10−4

miR-193b

4.5

5.22 × 10−3

miR-193b

2.1

2.6 × 10−2

miR-23b

16.9

2.49 × 10−4

miR-194

10.7

5.28 × 10−3

miR-20a

2.2

3.4 × 10−2

miR-20b

16.5

2.78 × 10−4

miR-152

4.6

5.57 × 10−3

miR-195

2.5

3.5 × 10−2

miR-19b

19.2

2.83 × 10−4

let-7d

7.8

8.65 × 10−3

miR-30c

2.5

3.6 × 10−2

miR-221

24.1

3.02 × 10−4

miR-99a

4.1

1.09 × 10−2

miR-146a

2.0

3.6 × 10−2

miR-24

19.3

3.51 × 10−4

miR-155

6.5

1.09 × 10−2

miR-19b

2.1

3.7 × 10−2

miR-30c

27.0

3.88 × 10−4

let-7i

6.4

1.22 × 10−2

miR-21

3.3

4.1 × 10−2

miR-193b

9.6

3.94 × 10−4

miR-25

8.1

1.27 × 10−2

miR-23b

1.8

4.2 × 10−2

miR-192

78.8

4.06 × 10−4

miR-221

7.6

1.36 × 10−2

miR-30d

1.7

4.4 × 10−2

let-7c

5.5

4.13 × 10−4

miR-125b

3.1

1.44 × 10−2

let-7d

17.9

4.43 × 10−4

miR-15a

5.7

1.58 × 10−2

miR-103

11.8

5.25 × 10−4

miR-20b

7.5

1.93 × 10−2

miR-194

35.1

7.44 × 10−4

miR-92a

5.6

2.13 × 10−2

miR-30e

13.8

8.44 × 10−4

miR-100

3.4

2.16 × 10−2

miR-130a

9.1

8.91 × 10−4

let-7c

2.7

2.30 × 10−2

miR-23a

16.5

1.27 × 10−3

miR-195

6.8

3.02 × 10−2

miR-107

16.6

1.41 × 10−3

miR-28-3p

2.1

4.31 × 10−2

miR-18a

6.5

1.45 × 10−3

miR-1274b

6.6

1.52 × 10−3

miR-155

7.3

2.82 × 10−3

miR-532-5p

6.8

2.95 × 10−3

miR-497

7.8

3.62 × 10−3

miR-195

16.9

4.27 × 10−3

miR-92a

5.8

4.84 × 10−3

miR-30a

5.7

8.24 × 10−3

miR-130b

5.7

1.74 × 10−2

let-7e

5.9

1.83 × 10−2

miR-451

11.1

1.90 × 10−2

miR-199b-3p

7.6

2.24 × 10−2

miR-224

5.0

2.31 × 10−2

miR-199a-3p

8.9

2.38 × 10−2

miR-145

6.5

3.25 × 10−2

 C The Authors Journal compilation  C 2015 Biochemical Society

miRNA signature during sorafenib therapy

Table S2 Top differentially expressed miRNAs of each UCA cluster group Groups A–C according to Figure 2 in the main paper; FC > 2 × S.D., P < 10 × 10−4 .

Table S3 Specific miRNAs associated with clinical attributes of HCC patients (A) miRNA associated with viral aetiology of liver disease miRNA

FC

P value

FDR

miR-494

−3.82

0.006

0.382

miR-1826

−3.44

0.014

0.408

miRNA

miR-923

−2.95

0.014

0.408

miR-126

miR-30b

miR-768-5p

−3.65

0.030

0.595

miR-100

miR-26a

miR-17

(B) miRNAs associated with high AFP level (>400 ng/ml)

miR-148a

miR-1274b

miR-115b

miRNA

FC

P value

FDR

miR-152

miR-200c

miR-20a

miR-342-3p

3.58

0.011

0.50

Group A compared with groups B and C

Group B compared with groups A and C

Group C compared with groups A and B

miRNA

miRNA

miR-99a

miR-30a

let-7g

miR-27b

miR-192 miR-194

miR-130a

4.51

0.012

0.50

miR-150

4.04

0.015

0.50

miR-574-3p

3.13

0.022

0.50

miR-15b

9.03

0.023

0.50

miR-30c

−4.89

0.048

0.50

Received 2 January 2014/22 May 2014; accepted 24 June 2014 Published as Immediate Publication 24 June 2014, doi: 10.1042/CS20140007

 C The Authors Journal compilation  C 2015 Biochemical Society

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