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Gut and Liver is an international journal of gastroenterology, focusing on the gastrointestinal tract, liver, biliary tree, pancreas, motility, and neurogastroenterology. Gut atnd Liver delivers up-to-date, authoritative papers on both clinical and research-based topics in gastroenterology. The Journal publishes original articles, case reports, brief communications, letters to the editor and invited review articles in the field of gastroenterology. The Journal is operated by internationally renowned editorial boards and designed to provide a global opportunity to promote academic developments in the field of gastroenterology and hepatology. +MORE
Yong Chan Lee |
Professor of Medicine Director, Gastrointestinal Research Laboratory Veterans Affairs Medical Center, Univ. California San Francisco San Francisco, USA |
Jong Pil Im | Seoul National University College of Medicine, Seoul, Korea |
Robert S. Bresalier | University of Texas M. D. Anderson Cancer Center, Houston, USA |
Steven H. Itzkowitz | Mount Sinai Medical Center, NY, USA |
All papers submitted to Gut and Liver are reviewed by the editorial team before being sent out for an external peer review to rule out papers that have low priority, insufficient originality, scientific flaws, or the absence of a message of importance to the readers of the Journal. A decision about these papers will usually be made within two or three weeks.
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Hyun Chang*, Nayoung Kim*,†, Ji Hyun Park†, Ryoung Hee Nam*, Yoon Jeong Choi*, Hye Seung Lee‡, Hyuk Yoon*, Cheol Min Shin*, Young Soo Park*,†, Jung Min Kim§, and Dong Ho Lee*,†
*Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
†Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea
‡Department of Pathology, Seoul National University Bundang Hospital, Seongnam, Korea
§NAR Center, Inc., Daejeon Oriental Hospital of Daejeon University, Daejeon, Korea
Correspondence to: Nayoung Kim, Department of Internal Medicine, Seoul National University Bundang Hospital, 82 Gumi-ro 173beon-gil, Bundang-gu, Seongnam 463-707, Korea, Tel: +82-31-787-7008, Fax: +82-31-787-4051, E-mail: nayoungkim49@empas.com
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Gut Liver 2015;9(2):188-196. https://doi.org/10.5009/gnl13371
Published online June 18, 2014, Published date March 31, 2015
Copyright © Gut and Liver.
This study was conducted to identify microRNAs (miRNAs) that are differentially expressed in
Total RNA was extracted from the cancerous and noncancerous regions of formalin-fixed, paraffin-embedded tissues of
A total of 219 miRNAs in the aberrant miRNA profiles across the miRNA microarray showed at least a 2-fold change differential expression in
miRNA expression in the intestinal type of
Keywords: Gastric carcinogenesis,
About 20 length nucleotides of nonprotein coding microRNA (miRNA) regulates gene expression by hybridizing to the 3′ untranslated region of specific messenger RNA (mRNA) targets. Up to now, approximately 1,600 human miRNAs have been studied and the relationship of miRNAs with human diseases is being intensively studied.1,2
Microarray-based hybridization profiling is a powerful technique for screening and use of fresh tissue specimens recommended to reduce collateral damage of miRNAs. However, it is hard to get fresh tissue specimens right after operations. Therefore, it is helpful to use the miRNA preserving formalin-fixed paraffin-embedded (FFPE) tissue for miRNA screening analysis. It has been used for extraction of miRNAs and a few studies have examined the correlation with clinical data.3,4 In addition, a strong correlation in global miRNA expression between fresh frozen and FFPE human cancer samples has been revealed.5
Epidemiological studies have implicated that colonization of the stomach by
The occurrence of gastric cancer still remains very high in much of Asia and especially, à Laurens’ classification divided gastric cancer into two histological main types; intestinal-type and diffuse-type,8,9 in which the number of intestinal-type gastric cancer patients in South Korea is more prevalent than the other type.10
On the other hand, 5.3% of gastric cancer patients were not infected with
From this background, the present study was undertaken to identify whether miRNA expression profiles differ between
Sixteen gastric cancer patients matched for age, sex, and
Three types of
After manual dissection under microscopic guidance avoiding the contamination of inflammatory cells and stromal cells, hematoxylin and eosin stained sections 50 μm in thickness from cancerous and noncancerous regions of intestinal type of gastric cancer FFPE samples were reviewed by one pathologist (H.S.L.). Each section was incubated in xylene and total RNA was extracted using a RecoverAll™ Total Nucleic Acid Isolation kit (Life Technologies, Carlsbad, CA, USA). Each 400 ng RNA was dephosphorylated with 15 units of calf intestine alkaline phosphatase, followed by RNA denaturation with 40% dimethylsulfoxide. Dephosphorylated RNA was ligated with pCp-Cy3 mononucleotide and resuspended in Gene Expression Blocking Reagent and Hi-RPM Hybridization buffer. The denatured, labeled samples were pipetted onto assembled Agilent Human miRNA microarray Release 16.0 platform and hybridized at 55°C for 20 hours at 20 rpm. The hybridization images were analyzed using a DNA microarray scanner (Agilent Technologies, Palo Alto, CA, USA). The average fluorescence intensity for each spot was calculated and local background was subtracted. Data visualization and analysis were performed with GeneSpring GX 7.3 software (Agilent Technologies). Signal cutoff measurements were <0.01.
The microarray showed 219 miRNAs which were at least 2-fold change between the
miRNA was extracted from the frozen gastric cancer tissue in gastric cancer patients and gastric body in control cases, which had been obtained during gastroscopy and had been kept at −80°C, with a mirVana™ miRNA Isolation Kit (Invitrogen, Carlsbad, CA, USA). Reverse transcription was performed using 5 μL of miRNA and TaqMan MicroRNA Reverse Transcription Kit and miRNA-specific stem-loop primers (Applied Biosystems, Foster City, CA, USA). The assays were carried in duplicate. The 20 μL reaction mixture contained reverse transcription reaction product, TaqMan Universal PCR Master Mix without uracil-N-glycosylase, TaqMan miRNA assay mix, and nuclease-free water. Amplification was performed using the 7500/7500 Fast PCR system (Applied Biosystems) at 50°C for 2 minutes and 95°C for 10 minutes, followed by 40 cycles of 95°C for 15 seconds and 60°C for 60 seconds. Amplification signals were computed with 7500 software v2.0.6 (Applied Biosystems). Relative miRNA expression levels are presented as 2−ΔΔCt method.
No interarray normalization was applied on the array, because the similarity between matched normal and cancer sample arrays was unknown. To identify distinct miRNAs hybridization signals, one-way analysis of variance (ANOVA) (p<0.05) and multiple testing correction (Benjamini and Hochberg false discovery rate) were employed for microarray clustering analysis. Relationship between two assays was evaluated by calculation of Spearman correlation tests. All statistical analyses were performed using the SPSS version 13.0 (SPSS Inc., Chicago, IL, USA).
In all FFPE individual samples, the low intensity hybridization signals (<0.01) between miRNAs and probes were filtered out and 1,781 of 3,523 (50.55%) miRNA probes remained as the dataset and were used for further analysis. Among the four subdivided groups (current
Next, miRNA candidates which might be associated with gastric cancer were selected for validation assay. When 18 highly expressed miRNAs in
Finally, we used seven commercially available primers in TaqMan miRNA assays to confirm the miRNA microarray results (Table 3).
All TaqMan miRNA assays examined the fold-change of absolute expression levels of candidate miRNAs of each sample. To identify the correlation between the two assays, we compared the normalized ratio of the miRNA microarray hybridization signal and the fold-increase levels of the TaqMan miRNA assay. Although these two assays showed a low correlation (r2=0.618, p=0.004) (Fig. 2A) with
There are some concerns about the integrity of miRNA from FFPE specimens and its suitability in the microarray assay because RNA in the FFPE tissue is fragmented and might be modified in the chemical reaction.19 However, it is reported that miR-NA is so small (about 20 nucleotides) that it cannot be degraded in FFPE preparation.3,4 And commercially available microarray platforms help to profile miRNA expression. Furthermore, there were a report which has shown a strong correlation in global miRNA expression between fresh frozen and FFPE human cancer samples using miRNA microarray platforms.3–5 Supporting miRNA preserving characteristics of FFPE samples, our FFPE samples showed biologically-useful RNA integrity and optical density value (RIN=2.26±0.04 and OD260/280=1.99±0.01, data not shown) in all eight paired RNAs. We found different result of cancerous region from noncancerous regions in the FFPE samples, and screened 219 miRNAs depending on
The miRWalk and HMDD v2.0 were employed to select candidate RNAs from 2-fold changed statistically significant 37 miRNAs. These two databases were created to offer a platform to scrutinize the mechanisms of miRNAs in disease.17,18 miRWalk has a comprehensive database of miRNAs on experimentally validated miRNA targets associated with 549 diseases.17 Also HMDD v2.0 provides experimentally supported miRNA and 397 diseases association data.18 Because the aim of our study was screening and selecting specific miRNAs in gastric cancer before functional study, we found seven candidate miRNAs after comparing screened results with validated miRNA lists of “stomach neoplasms.”
These seven miRNAs were presently validated with a good correlation (r2=0.878, p=0.032) between the microarray and TaqMan miRNA assays. Similarly, a few studies also reported similar correlation tendency between Agilent miRNA microarrays and TaqMan miRNA assays, with r2>0.9 and r2=0.83.20,21 Interestingly, this good correlation between microarray assay and TaqMan assay was not observed in normal mucosa of control group. The miRNA profile of noncancerous mucosa in cancer patients was not same as that of control patients22,23 and we also got different hybridization signal between cancerous and noncancerous mucosa in the cancer patients. This less correlation in the normal mucosa of controls may be attributed to different molecular background. Anyway, in contrast to the different expression of microRNA between cancer tissue of
All of the seven miRNA candidates have been previously identified as potential regulator in gastric cancer aside from
Other four miRNAs (
Especially, a significant inverse correlation between
This study has a few limitations. First, microarray experiments were performed in the only 16 cancer patients. However, our data showed good correlation between the microarray and TaqMan miRNA assay. In addition, we tried to leave little sample-to-sample variation in this validation assay by distinguishing the patients according not only to the
In conclusion, with the findings of microRNA microarray using FFPE specimens, the results of this study demonstrated that there are somewhat different miRNA expression patterns in cancerous region of intestinal type gastric cancer depending on
*p<0.05; †p<0.01.
GC, gastric cancer group.
Cont., noncancer control groups; GC, gastric cancer group;
Characteristics of the Subjects Used in the MicroRNA Microarray and TaqMan Assay Analyses
miRNA microarray | TaqMan miRNA assay | |||||
---|---|---|---|---|---|---|
Age, yr | 69.3±1.7 | 67.8±3.4 | 60.1±11.0 | 61.4±8.5 | 66.5±8.8 | 67.3±8.1 |
Male sex | 6 (75) | 5 (62.5) | 17 (70.8) | 15 (62.5) | 19 (79.2) | 18 (64.3) |
Intestinal type histology | 8 (100.0) | 8 (100.0) | - | - | 24 (100.0) | 28 (100.0) |
Differential Expression of 37 MicroRNAs between the
miRNA | Fold change* | p-value† | miRNA | Fold change | p-value | ||
---|---|---|---|---|---|---|---|
Up in | 3.55 | <0.0213 | Up in | 4.11 | <0.0102 | ||
3.36 | <0.0193 | 3.70 | <0.0193 | ||||
3.22 | <0.0168 | 3.57 | <0.015 | ||||
3.01 | <0.0279 | 3.51 | <0.0458 | ||||
2.83 | <0.0236 | 3.42 | <0.0085 | ||||
2.80 | <0.0446 | 3.05 | <0.0244 | ||||
2.70 | <0.0227 | 2.90 | <0.0169 | ||||
2.54 | <0.0055 | 2.73 | <0.0182 | ||||
2.40 | <0.0322 | 2.67 | <0.0406 | ||||
2.38 | <0.0268 | 2.65 | <0.0368 | ||||
2.37 | <0.0312 | 2.55 | <0.0049 | ||||
2.26 | <0.006 | 2.25 | <0.0076 | ||||
2.25 | <0.0273 | 2.17 | <0.024 | ||||
2.24 | <0.0309 | 2.14 | <0.0366 | ||||
2.10 | <0.0394 | 2.09 | <0.0233 | ||||
2.03 | <0.021 | 2.07 | <0.0445 | ||||
2.03 | <0.0292 | 2.04 | <0.0237 | ||||
2.02 | <0.0363 | 2.03 | <0.0078 | ||||
2.00 | <0.0428 |
miRNA, microRNA;
†Differences in fold-change were considered statistically significant if the p-value of the one-way analysis of variance was <0.05;
‡Up in
§Up in
List of the Validation Assay Targets
Stomach neoplasms* | Assay ID‡ | Sequence | |||
---|---|---|---|---|---|
miRWalk | HMDD | Conserved miRNAs† | |||
Up in | 002196 | CAAGCUCGUGUCUGUGGGUCCG | |||
001531 | AGGCACGGUGUCAGCAGGC | ||||
001582 | AGGGAUCGCGGGCGGGUGGCGGCCU | ||||
Up in | 000508 | UUCCCUUUGUCAUCCUAUGCCU | |||
002658 | AACAAUAUCCUGGUGCUGAGUG | ||||
000564 | UUUGUUCGUUCGGCUCGCGUGA | ||||
0001590 | CAAAAAUCUCAAUUACUUUUGC | ||||
miRNA, microRNA;
†Conserved miRNAs denotes overlapping miRNAs in the screened 37 miRNAs and the miRNA list from miRWalk and HMDD;
‡ID of TaqMan miRNA assays in miRBase version 19.0. RNU6B was used as an endogenous control.
Gut Liver 2015; 9(2): 188-196
Published online March 31, 2015 https://doi.org/10.5009/gnl13371
Copyright © Gut and Liver.
Hyun Chang*, Nayoung Kim*,†, Ji Hyun Park†, Ryoung Hee Nam*, Yoon Jeong Choi*, Hye Seung Lee‡, Hyuk Yoon*, Cheol Min Shin*, Young Soo Park*,†, Jung Min Kim§, and Dong Ho Lee*,†
*Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
†Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea
‡Department of Pathology, Seoul National University Bundang Hospital, Seongnam, Korea
§NAR Center, Inc., Daejeon Oriental Hospital of Daejeon University, Daejeon, Korea
Correspondence to: Nayoung Kim, Department of Internal Medicine, Seoul National University Bundang Hospital, 82 Gumi-ro 173beon-gil, Bundang-gu, Seongnam 463-707, Korea, Tel: +82-31-787-7008, Fax: +82-31-787-4051, E-mail: nayoungkim49@empas.com
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This study was conducted to identify microRNAs (miRNAs) that are differentially expressed in
Total RNA was extracted from the cancerous and noncancerous regions of formalin-fixed, paraffin-embedded tissues of
A total of 219 miRNAs in the aberrant miRNA profiles across the miRNA microarray showed at least a 2-fold change differential expression in
miRNA expression in the intestinal type of
Keywords: Gastric carcinogenesis,
About 20 length nucleotides of nonprotein coding microRNA (miRNA) regulates gene expression by hybridizing to the 3′ untranslated region of specific messenger RNA (mRNA) targets. Up to now, approximately 1,600 human miRNAs have been studied and the relationship of miRNAs with human diseases is being intensively studied.1,2
Microarray-based hybridization profiling is a powerful technique for screening and use of fresh tissue specimens recommended to reduce collateral damage of miRNAs. However, it is hard to get fresh tissue specimens right after operations. Therefore, it is helpful to use the miRNA preserving formalin-fixed paraffin-embedded (FFPE) tissue for miRNA screening analysis. It has been used for extraction of miRNAs and a few studies have examined the correlation with clinical data.3,4 In addition, a strong correlation in global miRNA expression between fresh frozen and FFPE human cancer samples has been revealed.5
Epidemiological studies have implicated that colonization of the stomach by
The occurrence of gastric cancer still remains very high in much of Asia and especially, à Laurens’ classification divided gastric cancer into two histological main types; intestinal-type and diffuse-type,8,9 in which the number of intestinal-type gastric cancer patients in South Korea is more prevalent than the other type.10
On the other hand, 5.3% of gastric cancer patients were not infected with
From this background, the present study was undertaken to identify whether miRNA expression profiles differ between
Sixteen gastric cancer patients matched for age, sex, and
Three types of
After manual dissection under microscopic guidance avoiding the contamination of inflammatory cells and stromal cells, hematoxylin and eosin stained sections 50 μm in thickness from cancerous and noncancerous regions of intestinal type of gastric cancer FFPE samples were reviewed by one pathologist (H.S.L.). Each section was incubated in xylene and total RNA was extracted using a RecoverAll™ Total Nucleic Acid Isolation kit (Life Technologies, Carlsbad, CA, USA). Each 400 ng RNA was dephosphorylated with 15 units of calf intestine alkaline phosphatase, followed by RNA denaturation with 40% dimethylsulfoxide. Dephosphorylated RNA was ligated with pCp-Cy3 mononucleotide and resuspended in Gene Expression Blocking Reagent and Hi-RPM Hybridization buffer. The denatured, labeled samples were pipetted onto assembled Agilent Human miRNA microarray Release 16.0 platform and hybridized at 55°C for 20 hours at 20 rpm. The hybridization images were analyzed using a DNA microarray scanner (Agilent Technologies, Palo Alto, CA, USA). The average fluorescence intensity for each spot was calculated and local background was subtracted. Data visualization and analysis were performed with GeneSpring GX 7.3 software (Agilent Technologies). Signal cutoff measurements were <0.01.
The microarray showed 219 miRNAs which were at least 2-fold change between the
miRNA was extracted from the frozen gastric cancer tissue in gastric cancer patients and gastric body in control cases, which had been obtained during gastroscopy and had been kept at −80°C, with a mirVana™ miRNA Isolation Kit (Invitrogen, Carlsbad, CA, USA). Reverse transcription was performed using 5 μL of miRNA and TaqMan MicroRNA Reverse Transcription Kit and miRNA-specific stem-loop primers (Applied Biosystems, Foster City, CA, USA). The assays were carried in duplicate. The 20 μL reaction mixture contained reverse transcription reaction product, TaqMan Universal PCR Master Mix without uracil-N-glycosylase, TaqMan miRNA assay mix, and nuclease-free water. Amplification was performed using the 7500/7500 Fast PCR system (Applied Biosystems) at 50°C for 2 minutes and 95°C for 10 minutes, followed by 40 cycles of 95°C for 15 seconds and 60°C for 60 seconds. Amplification signals were computed with 7500 software v2.0.6 (Applied Biosystems). Relative miRNA expression levels are presented as 2−ΔΔCt method.
No interarray normalization was applied on the array, because the similarity between matched normal and cancer sample arrays was unknown. To identify distinct miRNAs hybridization signals, one-way analysis of variance (ANOVA) (p<0.05) and multiple testing correction (Benjamini and Hochberg false discovery rate) were employed for microarray clustering analysis. Relationship between two assays was evaluated by calculation of Spearman correlation tests. All statistical analyses were performed using the SPSS version 13.0 (SPSS Inc., Chicago, IL, USA).
In all FFPE individual samples, the low intensity hybridization signals (<0.01) between miRNAs and probes were filtered out and 1,781 of 3,523 (50.55%) miRNA probes remained as the dataset and were used for further analysis. Among the four subdivided groups (current
Next, miRNA candidates which might be associated with gastric cancer were selected for validation assay. When 18 highly expressed miRNAs in
Finally, we used seven commercially available primers in TaqMan miRNA assays to confirm the miRNA microarray results (Table 3).
All TaqMan miRNA assays examined the fold-change of absolute expression levels of candidate miRNAs of each sample. To identify the correlation between the two assays, we compared the normalized ratio of the miRNA microarray hybridization signal and the fold-increase levels of the TaqMan miRNA assay. Although these two assays showed a low correlation (r2=0.618, p=0.004) (Fig. 2A) with
There are some concerns about the integrity of miRNA from FFPE specimens and its suitability in the microarray assay because RNA in the FFPE tissue is fragmented and might be modified in the chemical reaction.19 However, it is reported that miR-NA is so small (about 20 nucleotides) that it cannot be degraded in FFPE preparation.3,4 And commercially available microarray platforms help to profile miRNA expression. Furthermore, there were a report which has shown a strong correlation in global miRNA expression between fresh frozen and FFPE human cancer samples using miRNA microarray platforms.3–5 Supporting miRNA preserving characteristics of FFPE samples, our FFPE samples showed biologically-useful RNA integrity and optical density value (RIN=2.26±0.04 and OD260/280=1.99±0.01, data not shown) in all eight paired RNAs. We found different result of cancerous region from noncancerous regions in the FFPE samples, and screened 219 miRNAs depending on
The miRWalk and HMDD v2.0 were employed to select candidate RNAs from 2-fold changed statistically significant 37 miRNAs. These two databases were created to offer a platform to scrutinize the mechanisms of miRNAs in disease.17,18 miRWalk has a comprehensive database of miRNAs on experimentally validated miRNA targets associated with 549 diseases.17 Also HMDD v2.0 provides experimentally supported miRNA and 397 diseases association data.18 Because the aim of our study was screening and selecting specific miRNAs in gastric cancer before functional study, we found seven candidate miRNAs after comparing screened results with validated miRNA lists of “stomach neoplasms.”
These seven miRNAs were presently validated with a good correlation (r2=0.878, p=0.032) between the microarray and TaqMan miRNA assays. Similarly, a few studies also reported similar correlation tendency between Agilent miRNA microarrays and TaqMan miRNA assays, with r2>0.9 and r2=0.83.20,21 Interestingly, this good correlation between microarray assay and TaqMan assay was not observed in normal mucosa of control group. The miRNA profile of noncancerous mucosa in cancer patients was not same as that of control patients22,23 and we also got different hybridization signal between cancerous and noncancerous mucosa in the cancer patients. This less correlation in the normal mucosa of controls may be attributed to different molecular background. Anyway, in contrast to the different expression of microRNA between cancer tissue of
All of the seven miRNA candidates have been previously identified as potential regulator in gastric cancer aside from
Other four miRNAs (
Especially, a significant inverse correlation between
This study has a few limitations. First, microarray experiments were performed in the only 16 cancer patients. However, our data showed good correlation between the microarray and TaqMan miRNA assay. In addition, we tried to leave little sample-to-sample variation in this validation assay by distinguishing the patients according not only to the
In conclusion, with the findings of microRNA microarray using FFPE specimens, the results of this study demonstrated that there are somewhat different miRNA expression patterns in cancerous region of intestinal type gastric cancer depending on
*p<0.05; †p<0.01.
GC, gastric cancer group.
Cont., noncancer control groups; GC, gastric cancer group;
Table 1 Characteristics of the Subjects Used in the MicroRNA Microarray and TaqMan Assay Analyses
miRNA microarray | TaqMan miRNA assay | |||||
---|---|---|---|---|---|---|
Age, yr | 69.3±1.7 | 67.8±3.4 | 60.1±11.0 | 61.4±8.5 | 66.5±8.8 | 67.3±8.1 |
Male sex | 6 (75) | 5 (62.5) | 17 (70.8) | 15 (62.5) | 19 (79.2) | 18 (64.3) |
Intestinal type histology | 8 (100.0) | 8 (100.0) | - | - | 24 (100.0) | 28 (100.0) |
Data are presented as mean±standard error or number (%).
miRNA, microRNA;
Table 2 Differential Expression of 37 MicroRNAs between the
miRNA | Fold change* | p-value† | miRNA | Fold change | p-value | ||
---|---|---|---|---|---|---|---|
Up in | 3.55 | <0.0213 | Up in | 4.11 | <0.0102 | ||
3.36 | <0.0193 | 3.70 | <0.0193 | ||||
3.22 | <0.0168 | 3.57 | <0.015 | ||||
3.01 | <0.0279 | 3.51 | <0.0458 | ||||
2.83 | <0.0236 | 3.42 | <0.0085 | ||||
2.80 | <0.0446 | 3.05 | <0.0244 | ||||
2.70 | <0.0227 | 2.90 | <0.0169 | ||||
2.54 | <0.0055 | 2.73 | <0.0182 | ||||
2.40 | <0.0322 | 2.67 | <0.0406 | ||||
2.38 | <0.0268 | 2.65 | <0.0368 | ||||
2.37 | <0.0312 | 2.55 | <0.0049 | ||||
2.26 | <0.006 | 2.25 | <0.0076 | ||||
2.25 | <0.0273 | 2.17 | <0.024 | ||||
2.24 | <0.0309 | 2.14 | <0.0366 | ||||
2.10 | <0.0394 | 2.09 | <0.0233 | ||||
2.03 | <0.021 | 2.07 | <0.0445 | ||||
2.03 | <0.0292 | 2.04 | <0.0237 | ||||
2.02 | <0.0363 | 2.03 | <0.0078 | ||||
2.00 | <0.0428 |
miRNA, microRNA;
†Differences in fold-change were considered statistically significant if the p-value of the one-way analysis of variance was <0.05;
‡Up in
§Up in
Table 3 List of the Validation Assay Targets
Stomach neoplasms* | Assay ID‡ | Sequence | |||
---|---|---|---|---|---|
miRWalk | HMDD | Conserved miRNAs† | |||
Up in | 002196 | CAAGCUCGUGUCUGUGGGUCCG | |||
001531 | AGGCACGGUGUCAGCAGGC | ||||
001582 | AGGGAUCGCGGGCGGGUGGCGGCCU | ||||
Up in | 000508 | UUCCCUUUGUCAUCCUAUGCCU | |||
002658 | AACAAUAUCCUGGUGCUGAGUG | ||||
000564 | UUUGUUCGUUCGGCUCGCGUGA | ||||
0001590 | CAAAAAUCUCAAUUACUUUUGC | ||||
miRNA, microRNA;
†Conserved miRNAs denotes overlapping miRNAs in the screened 37 miRNAs and the miRNA list from miRWalk and HMDD;
‡ID of TaqMan miRNA assays in miRBase version 19.0. RNU6B was used as an endogenous control.