miRNA-mRNA相互作用同定を用いた腎芽腫関連遺伝子の推定

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(1)Vol.2016-BIO-48 No.1 2016/12/9. ØCrg¶qZ€C IPSJ SIG Technical Report. miRNA-mRNA ì“^;‰ › ;Mh j È¨; w* >±y³Â1,a). “A• j xz –Çw ~w°mpK“ z 8 wsMÔùw 5 å\ px 90 ËŽÍpK” Uz C\; Ïsr x‘µz ÆÌpK” { ‡ hz ÕUœ~ [åUœwÔùw BRCA1 w7s ~ RtŠí$s!Ÿ¨ ; ‹ _mTl o MsM{ ŠZ€-hp xz ‡¯ ”Å RNA w° p K” miRNA t ‘ ” mRNA wCq Mš;ÏwŸ×U j wC\j¼pK” q MO >†t,nV z mRNA q miRNA wCqÓé Ñ • çw wùrs› æl o z. j tSMo ›t mRNA-miRNA w. ¢ ì £ UGV X !=` o M” Öž › ‰. ` h{ ‰ ^ •h mRNA wO j z ó:xw miRNA wª$tsl o M” q ¥˜•” mRNA wGæüx' ™rs¢ \ Â¢£ t Mo Uœt0` o ™s P ‹› Ël o M” \ q UQÌ` h{ \ w\ q T’ z \ •’ w¨;. wCqŸ×U. j. wC\t. ` o M” ‹ wq AænZh{. Inference of Wilms timor causing genes using miRNA-mRNA interaction ideitification Y-h. Taguchi1,a). M” \ q x‡×t. 1. xa Št y. j x–Ç. Uœw° pK“ z ã8tC_^ ••. å\ px. ËwUœpK” { ` T` z °Mp!Ÿ. UK” q. 2.. ®pK” q ßQ ’ •” {. O. ¶.wv•x$ 1 t³Mh{. j UC\b” ‘ O sj¼¨; x› ^ •o. MsM [1]{ qOxÓ é Þ ”» ”Ý ½ ç=sr w¤ Ð ´ £ É Â Ÿ ¿ « s®L‹. Šo. j. w\RA¼U^—$t. sg^ •o M ” [2]{ ŠZ€p x‡¯ ”Å RNA w°. p. 2.1 mRNA/miRNA Óé Ñ • mRNA/miRNA Ó é Ñ • ´ [7] t î÷^ •o M ” getGEO. šwŸ×U. \ œi{ ¤Óé Ñ •. wj¼p xsMTq MO >†t ,nV z. mRNA,miRNA CqÓé Ñ • q s” mRNA › › Â¢q ’ Uœ. ™t È¨;. çwwùrs› æMz j¼. ` h{ f •’ w. Xx. †1. a). t miRNA-mRNA ì“^;› ;. ¤ G¶g»¶æúg¶J Department of Physics, Chuo University, Tokyo 112–8551, Japan qO| ØCrgG¶ Presently with Johoshori Uniersity [email protected]. ⓒ 2016 Information Processing Society of Japan. :› –l o R t ¡ˆ. çx±ï Óç] q t. É | ü„. tF¨=` o T’ –;` h{. 2.2. Rüüs› ;Mh-£s` ¶6t‘ ” !:¬R. miRNA-mRNA ì“^;w‰ +. 1. [5] w. Uœ w\. ` o M” \ q U˜Tl h{ \ w\ q T w‰. ç x GEO. GSE66405/GSE57370 T’ R [6] ºw GEOquery Í¿ - ”. K ” microRNA(miRNA) t ‘ ” mRNA w8ø™CqM j. ç. w²t z. ~—Y×. p Cq)UK” miRNA/mRNA wµ « æ ”Çï ¬ ›. æl h{ f w ^ •o M” [8]. Oq ` o xp˜è$t. ®pK” \ q UÔ. Rüüs› ;Mh-£s` ¶6t ‘ ” !. :¬RO [9–24] › ;Mh{ Š OtmMo wÄIxj¶æ \ wZ€x IEEE BIBE2016 w Proceedings w°æ [3, 4] q ` o 7C¯pK”. 1.

(2) Vol.2016-BIO-48 No.1 2016/12/9. ØCrg¶qZ€C IPSJ SIG Technical Report. Éwg•g•› ¸é t` hÔùw®Lx×ÌpxsX z \. mRNA. miRNA. w. mw. Rüüsx°`txŸl hAL› )Q ” \ q t. s“ z r w7tŸs” T› Ä²t-‰b” \ q ‹ pV sM. iRNA /mRNA. :x«™› Ab” { ‡ hz ±ï Óç. Éq ¨;. É› ‰. Ìt¸é tb” \ q xpV sMwpz r j ’ T°M› ¬R b” \ q ts” {. !:¬RtSMo z ±ï Óç. mRNAs. miRNAs. Rüüs› ;Mh-£s` ¶6t‘ ” É› ¸é tb” ¨; ’Š. ˆwM› ¬Rb” g xz °`t¨; CqÓé Ñ • çw- pxˆ0‹w-‰xÆDópK“ z sœ’ TwY F=UžAshŠpK” { ¨; ç’Š. É› ¸é tb” ±ï Ó. ˆwÔùxz ²rgq ` o ¨; CqÓé Ñ •. çU±ï Óç] q t?’ Tw> t,nMo K’ Ta ŠY. vs. F=^ •o M” \ q U. M{ ` T` z f \ tÚ™QUÖl. o ` ‡ l hwpxz dl TX w-£s` ¶6w™¯UsM{ f \ pz è×z. Rüüs› ;Mh-£s` ¶6t‘ ” !. :¬Rpx±ï Óç. É› ¸é tb” MU¬R^ •” {. Ítz ¨; ¬Rt;M” t¬Rb” {. miRTarBase. wÔùz. ’ •o M” hŠtz. Rüüs› ;Mh-£s` ¶6t‘ ” !. :¬R› ;Mo z mRNA/miRNA. ‘ t¬R› æO { é.$. t x mRNA q miRNA › ÿÍit ’Š. ˆz Ž•‹t sl. o M” mRNA q miRNA › ¬R{ ^ ’ t¬R^ •h mRNA q miRNA wO j T’ z. RüÛY”x±ï Óçt¥ÇZ. RüÛY”›. q UpV ” { ŠZ€wÔùtxz )UK”. ¶.wv•{ ‡ cz. RüÛY”› €ß b” \ q pr w. Rüt\ú¶$t™¯UK” ›ÃU¯•o M” T› Œ” \. miRNA-mRNA. $1. Rü›. ~—Y×. +. p. ™t Cq)U. RüÛY”› ¬œi{. 7™tz ¬R^ •h t. ~—Y× + pCq. RüÛY”t0 b”. O¨¢ µüÍ› > ` z. Rü˜:. ËÐüÍ› &;` o P ‹›. -‰` z Ž•‹q sl o M” ¨;. › ¬Rb ” (. Oz±. 4Y^ •h P ‹U 0.01 Ž<› Ž•‹q b ” £{ ses’ z. K ” ‹ w› ¬•{ \ •’ wO j z miRTarBase t Jå^ •o. \ w‘ O s¨; x«èb”. M” Ûì. ÌpV sMGV s/)› Ël o M” z m‡ “ z *8Qt›. wÖž › miRNA-mRNA Öž q ` o ‰. b” {. Fig. 1 Workflow of this study. miRNA/mRNA expression pro-. Rüt0` o z îµpx†. Ÿ$t/)` o M” ¨; pK” q ˆsb\ q UpV ” T. files were separately embedded into low dimensional. ’ pK” {. space by PCA (feature embedding). After identifying. ‡tx^æUK” ‹ wq ¥˜•” Uz \ w7s> x¬p. PCs used for FE, outlier miRNAs/mRNAs are selected. miRNAs/mRNAs exhibiting significant differential ex-. Rü˜:U¨¢ µüÍtHO q MO > wK. Rüüsq zy•” z. Rüüsww-¶6$Ñ è ”Ü. pression between tumor and normal kidney were further. pw6r. selected among those selected as outliers, and pairs as-. •h‹ wpxsMq ¥˜•” {. p‹ >;^ •o S“ [25]z f •„r qîT’ m. sociated with reciprocal expression were compared with those listed in miRTarBase.. ~—Y×. 2.3. +. t. mRNA/miRNA wÜ“ [3, 4] › _o MhiX q ` o “A› \‚” { ‡ cz H° t. Rüüs› ;Mo ¨; › ÿÍií t’Š. wALz ±ï Óçt. Rü˜:Uz ¨; t. UÂ“ po ’ •” è×w±ï Óç’Š t. Rü˜:Uz ±ï Óçt. è×w±ï Óç’Š. ‰{ \. RüÛY”. ˆq xotz ¨;. ˆ. §2.2 p µ « æ ”Çï ¬ ^ •h mRNA/miRNA w¤T’ Ët t U p › Ü“. ~—Y× + t)UK” miRNA/mRNA. ‰{ ˜’ •h P ‹› BH ,j [26] p. Oz±4. Y` o P < 0.05 w‹ wwˆ› ¬Rb” {. RüÛY”UÇ)^ •” {. ˆq w§Mxz ±ï Óç’Š. ˆw. Ôùxžü„æ»z ‡ hxz ì. :æ»U0¯=^ •”. hŠt¨; ] q tCqÓé Ñ •. çw. wt0` o z ¨; ’Š. ™t Cq)UK ”. 2.4 miRTarBase q wz± miRTarBase [27] xîg$t¬Ý^ •h miRNA-mRNA. ÉU¸é ts”. ì“^;iZ › )B` hôTSwôM miRNA-mRNA ì. ˆwÔùx¬å Üæ»U0¯=. “^;Ã”» Õ”µpK” { §2.3 pµ« æ ”Çï ¬^ •h. ^ •” hŠt±ï Óç] q w. ÉÓé Ñ •. ” :pK” { ‡ hz °`tz ±ï Óç ⓒ 2016 Information Processing Society of Japan. çU¸é ts. Éz ¨; ] q. mRNA/miRNA wO j z miRTarBase tJå^ •o M” Õ ž t˜pb” ‹ w› ¬R` (`` z mRNA q miRNA xo 2.

(3) Vol.2016-BIO-48 No.1 2016/12/9. ØCrg¶qZ€C IPSJ SIG Technical Report ¯ 1. ~—Y×. +. wQ. üs{ æU'. p »UYr{ mRNA. xH° RüÛY”z miRNA xH°T’ Hã RüÛY”› ;MhÔùUÕµ Ä. Table 1 Discrimination between normal kidneys and Wilms tumors. Row: prediction, column: true classes. The. •o S“ z %psALpK” \ q U•˜•” {. 4. ^æ 4.1 É ¿ Ä ë ”« w¯ ž mRNA x\ üst. first PC loading for mRNA (L = 1) and the first seven. $ 2 t³T•hÉ¿ Ä ë ”« w\ú¶$s%pQ› UÂ. PC loadings for miRNA (L = 7) were employed for. b ” hŠz $ 2 wËÒ mRNA › OncoLnc [28] t ž ¿ Ó. the discrimination. mRNA. é ”Å ` h{ OncoLnc x7 wÃ”» T’ ¤ wUœw\. miRNA ~. ~. üstx‘ w¨; U/)` o M” Tr O T› Gå` h. ~. 4. 1. 4. 1. 0. 27. 0. 61. Ã”» Õ”µpK” { ¯ 2 xf wALpK” { ’æsU’ sMU„q œ r w¨;. ìw‹ wz m‡ “ z mRNA U x. ~»Y×. ™wè. ¹› Ëm. ~¼Y× +s’ miRNA. +z ot mRNA U. ~»Y×. +s ’. p. U. ¨w. j x. ‡ •o M. Uœ¢. È¯G£. ™w\ üs•w/)› Ël o M” { \ w\ q xom. s mRNA wCq)iZ T’ Uœ t. ` h¨;. ›‰. miRNA x ~¼Y× +pK” ‹ w£z \ •› ‰ ^ •h. b ” ‘ “ ‹ z miRNA wª$q sl o M” Tr O T› ß€. miRNA-mRNA ì“^;q b ” {. b” \ q p‘ “ $¬sUœ¨; w‰ UpV ” q tO Ä î› Ôbq žtz. ~—Y×. 2.5. +. wQ. tI¼b” q MO psw> › §Ëb” ALpK” q ˆs. üs. §2.2 p µ « æ ”Çï ¬ ^ •h mRNA/miRNA › –l o Q. üs› æO { ‡ cz ¬R^ •h mRNA/miRNA iZ. › ;Mo. Rüüs› 6Sæl o z. ” { -‰^ •h. RüÛY”› -‰b. RüÛY”¢ ±ï ÓçtÇ)£ › ;Mo z. ~—Y× + w¢ Q üs› æO { –;b” ÛY”w:› !Q z ‹ l q ‹ ‘ MQ. wÌ› C. Rü. b\ q UpV ” i– O {. 5. ‡ q Š ŠZ€-hpx. K” Uœ. miRNA/mRNA Óé Ñ •. çrs•w. miRNA/mRNA Ó é Ñ • w miRNA q. j¶æ. ¦ Ú”§ ”—Ï•ª. ;pK” \ q U84^ •” {. [3, 4] p x^ ’ t. X w\ú¶$sßo› æl. çt &;` h ALz. xw mRNA › ¯ ”Å ` hÓ é ” €ß [1]. 3.2 Q üs §2.5 t K ” MOp z §3.1 p ¬R^ •h miRNA/mRNA ~—Y× + wQ üs› æl hALUz. ¯ 1 pK” { Q x‡×t‘ X z. Rüüs› ;Mh!:. [2]. ~—Y× + pCqt)UK” miRNA/mRNA. › V j l q ¬‚o M” \ q U¬ÝpV ” { [3]. 3.3 Ûì › Pl h miRNA-mRNA Öž w‰ $ 2 x$ 1 t³T•h. qp74$t¬y•h miRNA-. mRNA ÖžpÏR^ •hÉ¿ Ä ë ”« pK” { ›t mRNA ~¼Y×. j wC\;ÏwZ€tþ. o M” wpµ¯K” Ôùtx€°^ •hM{. Ò U¬R^ •” \ q U˜Tl h{. U. ™w. qj z ‡ hz ¯ 2 tK” ¨; xÌ $q ` o. ;. §2.2 p G \ ^ • h è “ w M O › §2.1 t K ”. ¬Rx. È¨; › ‰ pV ” \ q › Ô` h{ $ 2 tÔ. ^ •hÉ¿ Ä ë ”« x. Rüüs› ;Mh-£s` ¶6t ‘ ” !:¬Rw. wˆ› ;Mo. Rüüs› ;Mh-£s` ¶6t‘ ”. !:¬Rp µ « æ ”Çï ¬ ` h miRNA/mRNA w¤T’. miRNA-mRNA Öž › ¬•\ q pz ‘ “ \ú¶$t™¯U. b” {. 3. AL 3.1. j wC\j¼U miRNA wCqŸ×. +z miRNA U. ~»Y×. +z wCq›. Ël o M” Ôù¢ mRNA UUœ¨; pz miRNA U. [4]. ~. HM¼ pK“ z Uœ¨; › ª$q b” miRNA wCq Uÿ<` hhŠtUœtsl hq r pV ” £ x¶.Um sUl hGV sÉ¿ Ä ë ”« › ÏRb” ‘ O tÖž U¬y ⓒ 2016 Information Processing Society of Japan. [5]. Y Chu, A., Heck, J. E., Ribeiro, K. B., Brennan, P., Boffetta, P., Buffler, P. and Hung, R. J.: Wilms’ tumour: a systematic review of risk factors and meta-analysis, Paediatr Perinat Epidemiol, Vol. 24, No. 5, pp. 449–469 (2010). Tian, F., Yourek, G., Shi, X. and Yang, Y.: The development of Wilms tumor: from WT1 and microRNA to animal models, Biochim. Biophys. Acta, Vol. 1846, No. 1, pp. 180–187 (2014). Taguchi, Y. H.: microRNA-mRNA interaction identification in Wilms tumor using principal component analysis based unsupervised feature extraction, 2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (Ng, K. L., ed.), Los Alamitos, California, IEEE, IEEE Computer Society, pp. 71–78 (2016). Taguchi, Y. H.: microRNA-mRNA interaction identification in Wilms tumor using principalcomponent analysis based unsupervised feature extraction, bioRxiv, (online), DOI: 10.1101/059295 (2016). NCBI: Gene Expression Omnibus, NCBI (online), available from hhttps://www.ncbi.nlm.nih.gov/geo/i (ac-. 3.

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(5) Vol.2016-BIO-48 No.1 2016/12/9. ØCrg¶qZ€C IPSJ SIG Technical Report ¯ 2. OncoLnc t ‘ ” z ¤. ~p w\. ¬p•w. FDR 4Y^ •h P ‹U 0.05 Ž<w mRNA{ œx. Èp¯G{ LGG x. ™w. {. w. U. [9]. Uœq ‰ÌtC\b” \ q U. Mwpü.p¯G` h. Table 2 Significant relationships to survival probabilities in various cancers provided by OncoLnc. Those associ-. [10]. ated with corrected FDR < 0.05. Two renal cancers are in bold. LGG was in italic in order to emphasize the association with renal cancers. FDR ¨;. ~. Cox. P ‹. 4Y P ‹. w miRNA tª$q ^ •o M” mRNA. CBX2. KIRP. 0.908. 2.90e-07. LIHC. 0.501. 1.70e-06. 8.43e-04. LGG. 0.295. 4.40e-03. 1.22e-02. KIRC. 0.199. 1.40e-02. 4.29e-02. [11]. 3.22e-05. [12]. w miRNA tª$q ^ •o M” mRNA. IGF2. KIRP. 0.436. 6.40e-03. 3.67e-02. CCND1. KIRC. -0.248. 3.60e-03. 1.35e-02. COL3A1. KIRP. 0.825. 3.00e-06. 1.71e-04. COL5A2. LGG. 0.518. 5.90e-07. 8.14e-06. 0.920. 1.30e-07. 1.63e-05. LGG. -0.380. 7.10e-05. 3.84e-04. SARC. 0.394. 7.70e-04. 2.96e-02. KIRP WASF3 NREp. [13]. [14]. — w miRNA tª$q ^ •o M” mRNA. PXDN HMGA2. LOXL2. COL1A1. KIRC. 0.217. 7.70e-03. 2.55e-02. CESC. 0.615. 4.70e-05. 3.93e-02. KIRC. 0.283. 2.20e-04. 1.57e-03. PAAD. 0.520. 7.70e-06. 4.20e-03. KIRP. 0.520. 6.70e-04. 7.81e-03. SARC. 0.373. 3.10e-04. 2.00e-02. LUAD. 0.234. 2.50e-03. 4.05e-02. LGG. 0.342. 6.50e-04. 2.43e-03. LUAD. 0.298. 6.80e-05. 7.66e-03. CESC. 0.628. 7.90e-06. 2.46e-02. KIRC. 0.205. 1.00e-02. 3.11e-02. KIRP. 0.419. 7.30e-03. 4.03e-02. KIRP. 0.881. 4.90e-07. 4.77e-05. KIRC. 0.252. 1.80e-03. 8.14e-03. LGG. 0.216. 2.30e-02. 4.88e-02. VIM. LGG. 0.526. 2.40e-08. 7.01e-07. TUBB3. KIRC. 0.344. 4.00e-05. 4.28e-04. FN1. LGG. 0.309. 1.20e-03. 4.06e-03. KIRP. 0.484. 1.30e-03. 1.21e-02. BLCA. 0.294. 5.70e-04. 2.90e-02. RPL12. KIRC LGG. 0.304. 1.70e-04. 1.29e-03. -0.320. 1.50e-03. 4.89e-03. KIRP: Kidney renal papillary cell carcinoma, LIHC: Liver Hepatocellular Carcinoma, LGG: Lower Grade Glioma, KIRC: Kidney Renal Clear Cell Carcinom, SARC: Sarcoma, CESC: Cervical squamous cell carcinoma and endocervical adenocarcinoma, PAAD: Pancreatic Adenocarcinoma, BLCA: Bladder Urothelial Carcinoma, LUAD: Lung Adenocarcinoma. ⓒ 2016 Information Processing Society of Japan. [15]. [16]. [17]. [18]. [19]. [20]. p. E696 (2016). Taguchi, Y. H., Iwadate, M. and Umeyama, H.: SFRP1 is a possible candidate for epigenetic therapy in nonsmall cell lung cancer, BMC Med Genomics, Vol. 9 Suppl 1, p. 28 (2016). Taguchi, Y. H., Iwadate, M. and Umeyama, H.: Heuristic principal component analysis-based unsupervised feature extraction and its application to gene expression analysis of amyotrophic lateral sclerosis data sets, Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2015 IEEE Conference on, pp. 1–10 (online), DOI: 10.1109/CIBCB.2015.7300274 (2015). Taguchi, Y. 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