utilizing-functional-genomics-screening-to-identify-potentially-novel

Utilizing Functional Genomics Screening to Identify Potentially Novel Drug Targets in Cancer Cell Spheroid Cultures

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery ...

The Institute of Cancer Research

BRCA1 &#x5BF9;&#x53D1;&#x6325;&#x67A2;&#x7EBD;&#x4F5C;&#x7528;&#xFF0C;&#x5728;&#x540C;&#x6E90;&#x91CD;&#x7EC4; (HR) DNA &#x4FEE;&#x590D;&#x3001; &#x7EC6;&#x80DE;&#x5468;&#x671F;&#x68C0;&#x67E5;&#x70B9;&#x548C;&#x8F6C;&#x5F55;&#x8C03;&#x63A7;&#x7684;&#x80BF;&#x7624;&#x6291;&#x5236;&#x86CB;&#x767D;&#x8FDB;&#x884C;&#x7F16;&#x7801;&#x3002;BRCA1 &#x80DA;&#x7CFB;&#x7A81;&#x53D8;&#x8D4B;&#x4E88;&#x65E9;&#x53D1;&#x6027;&#x4E73;&#x817A;&#x764C;&#x548C;&#x5375;&#x5DE2;&#x764C;&#x7684;&#x9AD8;&#x7684;&#x98CE;&#x9669;&#x3002;&#x5728; 80%&#x4EE5;&#x4E0A;&#x7684;&#x60C5;&#x51B5;&#x4E0B;&#xFF0C;&#x4EA7;&#x751F;&#x7684; BRCA1 &#x80DA;&#x7CFB;&#x7A81;&#x53D8;&#x8F7D;&#x4F53;&#x7684;&#x80BF;&#x7624;&#x662F;&#x96CC;&#x6FC0;&#x7D20;&#x53D7;&#x4F53; (ER)-&#x8D1F; &#xFF1B;&#x7136;&#x800C;&#xFF0C;&#x4E0A;&#x5347;&#x81F3; 15%&#x662F;&#x96CC;&#x6FC0;&#x7D20;&#x53D7;&#x4F53;&#x9633;&#x6027;&#x3002;&#x6709;&#x4EBA; BRCA1 ER &#x9633;&#x6027;&#x4E73;&#x817A;&#x764C;&#x6784;&#x6210;&#x7684; BRCA1 &#x80DA;&#x7CFB;&#x7A81;&#x53D8;&#xFF0C;&#x800C;&#x4E0D;&#x662F;&#x6B63;&#x5728;&#x5411; BRCA1 &#x635F;&#x5931;&#x7684;&#x51FD;&#x6570;&#x6709;&#x76F4;&#x63A5;&#x56E0;&#x679C;&#x5173;&#x7CFB;&#x65B9;&#x9762;&#x51FA;&#x73B0;&#x7684;&#x96F6;&#x661F;&#x764C;&#x75C7;&#x3002;&#x5927;&#x89C4;&#x6A21;&#x5E76;&#x884C;&#x7684;&#x5168;&#x57FA;&#x56E0;&#x7EC4;&#x6D4B;&#x5E8F;&#x7684;&#x96CC;&#x6FC0;&#x7D20;&#x53D7;&#x4F53;&#x9633;&#x6027;&#x548C;&#x96CC;&#x6FC0;&#x7D20;&#x53D7;&#x4F53;&#x9634;&#x6027; BRCA1 &#x4E73;&#x817A;&#x764C;&#x548C;&#x6307;&#x5B9A;&#x56FD;&#x5BB6;&#x4E3B;&#x7BA1;&#x90E8;&#x95E8;&#xFF0C;&#x4ED6;&#x4EEC;&#x5404;&#x81EA;&#x751F;&#x6B96;&#x88AB;&#x7528;&#x6765;&#x5B9A;&#x6027;&#x7684;&#x78B1;&#x57FA;&#x5BF9;&#x51B3;&#x8BAE;&#x5728; BRCA1 &#x764C;&#x75C7;&#x9057;&#x4F20;&#x666F;&#x89C2;&#x3002;&#x53EA;&#x6709; BRCA1 &#x80DA;&#x7CFB;&#x7A81;&#x53D8;&#xFF0C;&#x91CE;&#x751F;&#x578B;&#x7B49;&#x4F4D;&#x57FA;&#x56E0;&#x548C; TP53 &#x4F53;&#x7EC6;&#x80DE;&#x7A81;&#x53D8;&#x4F53;&#x7EC6;&#x80DE;&#x635F;&#x5931;&#x6B83;&#x53CA;&#x627E;&#x5230;&#x7D22;&#x5F15;&#x7684;&#x60C5;&#x51B5;&#x4E0B;&#x3002;BRCA1 &#x4E73;&#x817A;&#x764C;&#x663E;&#x793A;&#x7A81;&#x53D8;&#x7684;&#x7B7E;&#x540D;&#x4E0E; HR DNA &#x4FEE;&#x590D;&#x5728;&#x96CC;&#x6FC0;&#x7D20;&#x53D7;&#x4F53;&#x9633;&#x6027;&#x548C;&#x96CC;&#x6FC0;&#x7D20;&#x53D7;&#x4F53;&#x9634;&#x6027;&#x7684;&#x60C5;&#x51B5;&#x4E0B;&#x7F3A;&#x4E4F;&#x6240;&#x81F4;&#x7684;&#x4E00;&#x81F4;&#x3002;&#x6D4B;&#x5E8F;&#x5206;&#x6790;&#x7684;&#x7EC4;&#x7FA4;&#x7684;&#x9057;&#x4F20;&#x6027; BRCA1 &#x548C;&#x96F6;&#x661F;&#x975E; BRCA1 &#x4E73;&#x817A;&#x764C;&#x590D;&#x53D1;&#x6027;&#x81F4;&#x75C5;&#x57FA;&#x56E0;&#x7A81;&#x53D8;&#x548C;/&#x6216;&#x7EAF;&#x5408;&#x5220;&#x9664;&#x7D22;&#x5F15;&#x6848;&#x4EF6;&#x4E2D;&#x53D1;&#x73B0;&#x7684;&#x5B58;&#x5728;&#x8868;&#x660E; DAPK3&#x3001; TMEM135&#x3001; KIAA1797&#x3001; PDE4D &#x548C; GATA4 &#x662F;&#x4E73;&#x817A;&#x764C;&#x7684;&#x6F5C;&#x5728;&#x989D;&#x5916;&#x9A71;&#x52A8;&#x7A0B;&#x5E8F;&#x3002;&#x8FD9;&#x9879;&#x7814;&#x7A76;&#x8868;&#x660E; BRCA1 &#x81F4;&#x75C5;&#x6027;&#x80DA;&#x7CFB;&#x7A81;&#x53D8;&#x52A0;&#x4E0A;&#x91CE;&#x751F;&#x578B;&#x7B49;&#x4F4D;&#x57FA;&#x56E0;&#x7684;&#x4F53;&#x7EC6;&#x80DE;&#x635F;&#x5931;&#x5E76;&#x4E0D;&#x8DB3;&#x591F;&#xFF0C;&#x9057;&#x4F20;&#x6027;&#x4E73;&#x764C;&#x663E;&#x793A; ER &#x9634;&#x6027;&#x8868;&#x578B;&#xFF0C;&#x5BFC;&#x81F4;&#x4E86;&#x4E09;&#x4E2A;&#x6F5C;&#x5728;&#x65B0;&#x578B;&#x4E73;&#x817A;&#x764C;&#x57FA;&#x56E0; (&#x5373; DAPK3&#x3001; TMEM135&#x3001; &#x548C; GATA4) &#x7684;&#x9274;&#x5B9A;&#x3002;&#x7248;&#x6743;&#x6240;&#x6709; &copy; 2012&#x5E74;&#x5927;&#x4E0D;&#x5217;&#x98A0;&#x53CA;&#x7231;&#x5C14;&#x5170;&#x7684;&#x75C5;&#x6001;&#x793E;&#x4F1A;&#x3002;&#x7531;&#x7EA6;&#x7FF0; &middot; &#x5A01;&#x5229; &amp; &#x513F;&#x5B50;&#x6709;&#x9650;&#x516C;&#x53F8;&#x51FA;&#x7248;

BRCA1 &#x7A81;&#x53D8;&#x4F53;&#x96CC;&#x6FC0;&#x7D20;&#x53D7;&#x4F53;&#x9634;&#x6027;&#x548C;-&#x79EF;&#x6781;&#x4E73;&#x817A;&#x764C;&#x5168;&#x57FA;&#x56E0;&#x7EC4;&#x5E76;&#x884C;&#x5E8F;&#x5217;&#x5206;&#x6790;&#x3002;

BRCA1 encodes a tumour suppressor protein that plays pivotal roles in homologous recombination (HR) DNA repair, cell-cycle checkpoints, and transcriptional regulation. BRCA1 germline mutations confer a high risk of early-onset breast and ovarian cancer. In more than 80% of cases, tumours arising in BRCA1 germline mutation carriers are oestrogen receptor (ER)-negative; however, up to 15% are ER-positive. It has been suggested that BRCA1 ER-positive breast cancers constitute sporadic cancers arising in the context of a BRCA1 germline mutation rather than being causally related to BRCA1 loss-of-function. Whole-genome massively parallel sequencing of ER-positive and ER-negative BRCA1 breast cancers, and their respective germline DNAs, was used to characterize the genetic landscape of BRCA1 cancers at base-pair resolution. Only BRCA1 germline mutations, somatic loss of the wild-type allele, and TP53 somatic mutations were recurrently found in the index cases. BRCA1 breast cancers displayed a mutational signature consistent with that caused by lack of HR DNA repair in both ER-positive and ER-negative cases. Sequencing analysis of independent cohorts of hereditary BRCA1 and sporadic non-BRCA1 breast cancers for the presence of recurrent pathogenic mutations and/or homozygous deletions found in the index cases revealed that DAPK3, TMEM135, KIAA1797, PDE4D, and GATA4 are potential additional drivers of breast cancers. This study demonstrates that BRCA1 pathogenic germline mutations coupled with somatic loss of the wild-type allele are not sufficient for hereditary breast cancers to display an ER-negative phenotype, and has led to the identification of three potential novel breast cancer genes (ie DAPK3, TMEM135, and GATA4). Copyright Â© 2012 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

A whole-genome massively parallel sequencing analysis of BRCA1 mutant oestrogen receptor-negative and -positive breast cancers.

BRCA1 code pour une prot&eacute;ine suppresseur de tumeur qui joue un r&ocirc;le essentiel dans la r&eacute;paration de l&#39;ADN recombinaison homologue (HR), points de contr&ocirc;le du cycle cellulaire et la r&eacute;gulation transcriptionnelle. Mutations germinales BRCA1 conf&egrave;rent un risque &eacute;lev&eacute; de cancer du sein pr&eacute;coce et cancer de l&#39;ovaire. Dans plus de 80 % des cas, les tumeurs qui en d&eacute;coulent chez les porteurs de mutation germinale BRCA1 sont r&eacute;cepteurs de &oelig;strog&egrave;ne (ER)-n&eacute;gatif ; Cependant, jusqu&#39;&agrave; 15 % sont s&eacute;ropositifs au ER. Il a &eacute;t&eacute; sugg&eacute;r&eacute; que les cancers du sein BRCA1 ER positives constituent cancers sporadiques survenant dans le cadre d&#39;une mutation germinale de BRCA1, et non en lien causal avec perte de fonction BRCA1. Whole-genome massivement parall&egrave;le s&eacute;quen&ccedil;age d&#39;ER-positif et cancers du sein BRCA1 ER n&eacute;gatifs et leur lign&eacute;e germinale respectif d&#39;ADN, a servi &agrave; caract&eacute;riser le paysage g&eacute;n&eacute;tique de BRCA1 cancers &agrave; r&eacute;solution de paires de bases. Seulement BRCA1, mutations germinales, perte somatique de l&#39;all&egrave;le sauvage et mutations somatiques TP53 trouv&eacute;es r&eacute;currente dans les cas d&#39;index. Cancers du sein BRCA1 affichent une mutation signature conforme &agrave; celle caus&eacute;e par l&#39;absence de r&eacute;paration de l&#39;ADN de RH dans les ER-positifs et n&eacute;gatifs ER. Analyse des cohortes ind&eacute;pendantes du BRCA1 h&eacute;r&eacute;ditaires et les cancers du sein sporadiques non-BRCA1 pour la pr&eacute;sence de mutations pathog&egrave;nes r&eacute;currentes et/ou homozygotes destructions constat&eacute;es dans les affaires de l&#39;index de s&eacute;quen&ccedil;age a r&eacute;v&eacute;l&eacute; que DAPK3, TMEM135, KIAA1797, PDE4D et GATA4 sont des pilotes suppl&eacute;mentaires potentiels des cancers du sein. Cette &eacute;tude d&eacute;montre que BRCA1 mutations germinales pathog&egrave;nes coupl&eacute;es avec perte somatique de l&#39;all&egrave;le sauvage ne sont pas suffisantes pour les cancers du sein h&eacute;r&eacute;ditaire afficher un ph&eacute;notype ER-n&eacute;gatif et a conduit &agrave; l&#39;identification des trois potentiels g&egrave;nes de cancer du sein roman (c&#39;est &agrave; dire DAPK3, TMEM135 et GATA4). Copyright &copy; 2012 Pathological Society of Great Britain and Ireland. Publi&eacute; par John Wiley &amp; Sons, Ltd.

Une analyse de s&eacute;quen&ccedil;age massivement parall&egrave;le du g&eacute;nome entier de cancers du &oelig;strog&egrave;ne mutant BRCA1 r&eacute;cepteur n&eacute;gatif et - positifs de poitrine.

BRCA1 codiert ein Tumor Tumorsuppressor-Protein, das zentrale Rollen in homologe Rekombination (HR) DNA-Reparatur, Zellzyklus Kontrollpunkte und transkriptionelle Regulation spielt. BRCA1 Keimbahn-Mutationen verleihen ein hohes Risiko der fr&uuml;h beginnende Brust- und Eierstockkrebs. In mehr als 80 % der F&auml;lle, Tumoren entstehen in BRCA1 Germline Mutation Luftfahrtunternehmen sind &Ouml;strogen-Rezeptor (ER)-negativ; Allerdings sind bis zu 15 % ER-positivem. Es wurde vermutet, dass BRCA1 ER-positivem Brustkrebs sporadische Tumoren entstehen im Zusammenhang mit einer BRCA1-Mutation Keimbahn, anstatt dass BRCA1 Verlustfunktion kausal mit darstellen. Ganz-Genom massiv parallelen Sequenzierung des ER-positivem BRCA1 ER-negativen Brustkrebs-Arten und ihre jeweiligen Germline DNAs, diente die genetische Landschaft des BRCA1 Krebserkrankungen bei Basenpaar Aufl&ouml;sung zu charakterisieren. Nur BRCA1 Keimbahn-Mutationen, somatische Verlust der Wildtyp-Allel und TP53 somatische Mutationen wurden Mindestlaufzeit in den Index-F&auml;llen gefunden. BRCA1 Brustkrebserkrankungen angezeigt eine teilhabende Signatur entsprechen, die durch Mangel an HR DNA-Reparatur in ER-positivem und ER-negativen F&auml;llen verursacht. Sequenz-Analyse der unabh&auml;ngige Kohorten von erblichen BRCA1 und sporadischen nicht-BRCA1 Brustkrebse auf das Vorhandensein von wiederkehrenden pathogenen Mutationen und/oder Homozygote Deletionen gefunden in den Index-F&auml;llen gezeigt, dass DAPK3, TMEM135, KIAA1797, PDE4D und GATA4 m&ouml;gliche zus&auml;tzliche Treiber Brustkrebserkrankungen. Diese Studie zeigt, dass BRCA1 pathogenen Keimbahn-Mutationen mit somatischen Verlust von Wildtyp-Allel gekoppelt sind nicht ausreichend f&uuml;r erblichen Brustkrebsf&auml;lle ein ER-Negative Ph&auml;notyp angezeigt, und f&uuml;hrte zur Identifizierung der drei m&ouml;glichen neuartigen Brustkrebs-Gene (dh DAPK3, TMEM135 und GATA4). Copyright &copy; 2012 pathologischen Gesellschaft von Gro&szlig;britannien und Irland. Ver&ouml;ffentlicht von John Wiley &amp; S&ouml;hne, Ltd.

Eine ganze-massiv-parallelen Sequenzierung Genomanalyse BRCA1 mutant &Ouml;strogen-Rezeptor-negativen und -positiven Brustkrebserkrankungen.

BRCA1 codifica per una proteina soppressore tumorale che interpreta ruoli cardine nella riparazione del DNA ricombinazione omologa (HR), Checkpoint del ciclo cellulare e regolazione trascrizionale. BRCA1 mutazioni germinali conferiscono un alto rischio di precoce al seno e cancro ovarico. In pi&ugrave; di 80% dei casi, tumori derivanti in portatori di mutazione germinale BRCA1 sono il recettore degli estrogeni (ER)-negativo; Tuttavia, fino al 15% sono ER-positivo. &Egrave; stato suggerito che il tumore BRCA1 ER-positivi costituiscono tumori sporadici derivanti nel contesto di una mutazione germinale BRCA1, piuttosto che essere causalmente a BRCA1 perdita di funzione. Whole-genome massively parallel sequenziamento di ER-positivo e tumori al seno ER negativo BRCA1 e loro rispettivi germline DNAs, &egrave; stata utilizzata a caratterizzare il paesaggio genetico dei tumori BRCA1 alla risoluzione di base-coppia. Solo BRCA1 mutazioni germinali, perdita somatica del selvaggio-tipo allele e mutazioni somatiche TP53 ricorrentemente trovate nei casi di indice. Tumori al seno BRCA1 visualizzata una firma mutazionale coerenza con quella causata dalla mancanza di riparazione del DNA HR nei casi sia ER-positivo ed ER-negativo. Sequenziamento analisi delle coorti indipendente di BRCA1 ereditaria e sporadica non BRCA1 cancri della mammella per la presenza di mutazioni patogene ricorrenti e/o delezioni omozigoti trovati nei casi di indice ha rivelato che DAPK3, TMEM135, KIAA1797, PDE4D e GATA4 sono possibili ulteriori driver di tumori al seno. Questo studio dimostra BRCA1 mutazioni germinali patogeni accoppiate con la perdita somatica dell&#39;allele wild-type non sono sufficienti per tumori al seno ereditario visualizzare un fenotipo ER-negativo che ha portato all&#39;identificazione di tre i geni di cancro al seno romanzo potenziale (cio&egrave; DAPK3, TMEM135 e GATA4). Copyright &copy; 2012 societ&agrave; patologica della Gran Bretagna e Irlanda. Pubblicato da John Wiley &amp; Sons, Ltd.

Un&#39;analisi di sequenziamento massively parallel intero genoma di BRCA1 mutante estrogeno recettore-negativo e - positivi cancri della mammella.

BRCA1 &#x816B;&#x760D;&#x6291;&#x5236;&#x30BF;&#x30F3;&#x30D1;&#x30AF;&#x8CEA;&#x306E;&#x76F8;&#x540C;&#x7D44;&#x63DB;&#x3048; (HR) DNA &#x4FEE;&#x5FA9;&#x3001;&#x7D30;&#x80DE;&#x5468;&#x671F;&#x30C1;&#x30A7;&#x30C3;&#x30AF;&#x30DD;&#x30A4;&#x30F3;&#x30C8;&#x3001;&#x304A;&#x3088;&#x3073;&#x8EE2;&#x5199;&#x5236;&#x5FA1;&#x306E;&#x6975;&#x3081;&#x3066;&#x91CD;&#x8981;&#x306A;&#x5F79;&#x5272;&#x3092;&#x30A8;&#x30F3;&#x30B3;&#x30FC;&#x30C9;&#x3057;&#x307E;&#x3059;&#x3002;BRCA1 &#x751F;&#x6B96;&#x7D30;&#x80DE;&#x7CFB;&#x5217;&#x5909;&#x7570;&#x767A;&#x75C7;&#x65E9;&#x671F;&#x4E73;&#x764C;&#x3068;&#x5375;&#x5DE3;&#x764C;&#x306E;&#x30EA;&#x30B9;&#x30AF;&#x304C;&#x9AD8;&#x3044;&#x5354;&#x8B70;&#x3057;&#x307E;&#x3059;&#x3002;&#x30B1;&#x30FC;&#x30B9;&#x306E; 80% &#x4EE5;&#x4E0A;&#x306E;&#x816B;&#x760D;&#x306B;&#x304A;&#x3051;&#x308B; BRCA1 &#x751F;&#x6B96;&#x7D30;&#x80DE;&#x7A81;&#x7136;&#x5909;&#x7570;&#x306E;&#x30AD;&#x30E3;&#x30EA;&#x30A2;&#x3092;&#x751F;&#x3058;&#x308B;&#x30A8;&#x30B9;&#x30C8;&#x30ED;&#x30B2;&#x30F3;&#x53D7;&#x5BB9;&#x4F53; (ER) &#x3067;&#x3059;-&#x8CA0;&#x306E;;&#x305F;&#x3060;&#x3057;&#x3001;&#x6700;&#x5927; 15 &#xFF05; &#x306B; ER &#x967D;&#x6027;&#x3067;&#x3059;&#x3002;BRCA1 ER &#x967D;&#x6027;&#x4E73;&#x764C;&#x56E0;&#x679C; BRCA1 &#x640D;&#x5931;&#x95A2;&#x6570;&#x306B;&#x95A2;&#x9023;&#x3057;&#x3066;&#x3044;&#x308B;&#x306E;&#x3067;&#x306F;&#x306A;&#x304F;&#x3001;BRCA1 &#x751F;&#x6B96;&#x7D30;&#x80DE;&#x306E;&#x5909;&#x7570;&#x306E;&#x30B3;&#x30F3;&#x30C6;&#x30AD;&#x30B9;&#x30C8;&#x3067;&#x751F;&#x3058;&#x308B;&#x6563;&#x767A;&#x6027;&#x764C;&#x3092;&#x69CB;&#x6210;&#x3059;&#x308B;&#x3053;&#x3068;&#x304C;&#x793A;&#x5506;&#x3055;&#x308C;&#x3066;&#x3044;&#x307E;&#x3059;&#x3002;&#x5168;&#x30B2;&#x30CE;&#x30E0;&#x306E;&#x8D85;&#x4E26;&#x5217; ER &#x967D;&#x6027;&#x3068;&#x8CA0;&#x306E; ER BRCA1 &#x4E73;&#x764C;&#x3068;&#x5F7C;&#x3089;&#x306E;&#x305D;&#x308C;&#x305E;&#x308C;&#x306E;&#x751F;&#x6B96;&#x7D30;&#x80DE;&#x306E; Dna &#x306E;&#x30B7;&#x30FC;&#x30B1;&#x30F3;&#x30B7;&#x30F3;&#x30B0; BRCA1 &#x764C;&#x5869;&#x57FA;&#x5BFE;&#x306E;&#x89E3;&#x50CF;&#x5EA6;&#x3067;&#x306E;&#x907A;&#x4F1D;&#x7684;&#x98A8;&#x666F;&#x3092;&#x7279;&#x5FB4;&#x3065;&#x3051;&#x308B;&#x306B;&#x4F7F;&#x7528;&#x3055;&#x308C;&#x307E;&#x3057;&#x305F;&#x3002;&#x306E;&#x307F; BRCA1 &#x751F;&#x6B96;&#x7D30;&#x80DE;&#x5909;&#x7570;&#x4F53;&#x7D30;&#x80DE;&#x306E;&#x640D;&#x5931;&#x306F;&#x91CE;&#x751F;&#x578B;&#x5BFE;&#x7ACB;&#x907A;&#x4F1D;&#x5B50;&#x3068; TP53 &#x4F53;&#x7D30;&#x80DE;&#x7A81;&#x7136;&#x5909;&#x7570;&#x306E;&#x30A4;&#x30F3;&#x30C7;&#x30C3;&#x30AF;&#x30B9;&#x306E;&#x5834;&#x5408;&#x304C;&#x767A;&#x898B;&#x3055;&#x308C;&#x305F;&#x53CD;&#x5FA9;&#x7684;&#x3002;BRCA1 &#x4E73;&#x764C; ER &#x967D;&#x6027;&#x3068; ER &#x8CA0;&#x306E;&#x4E21;&#x65B9;&#x306E;&#x30B1;&#x30FC;&#x30B9;&#x3067; HR DNA &#x4FEE;&#x5FA9;&#x306E;&#x6B20;&#x5982;&#x306B;&#x3088;&#x3063;&#x3066;&#x5F15;&#x304D;&#x8D77;&#x3053;&#x3055;&#x308C;&#x308B;&#x3068;&#x6574;&#x5408;&#x5909;&#x7570;&#x7F72;&#x540D;&#x8868;&#x793A;&#x3002;&#x907A;&#x4F1D;&#x6027; BRCA1 &#x3068;&#x6563;&#x767A;&#x7684;&#x975E; BRCA1 &#x4E73;&#x764C;&#x518D;&#x767A;&#x306E;&#x75C5;&#x539F;&#x6027;&#x5909;&#x7570;&#x304A;&#x3088;&#x3073;/&#x307E;&#x305F;&#x306F;&#x30DB;&#x30E2;&#x6B20;&#x843D;&#x30A4;&#x30F3;&#x30C7;&#x30C3;&#x30AF;&#x30B9; &#x30B1;&#x30FC;&#x30B9;&#x3067;&#x767A;&#x898B;&#x306E;&#x5B58;&#x5728;&#x306E;&#x305F;&#x3081;&#x306E;&#x72EC;&#x7ACB;&#x3057;&#x305F;&#x30B3;&#x30DB;&#x30FC;&#x30C8;&#x306E;&#x5206;&#x6790;&#x3092;&#x30B7;&#x30FC;&#x30B1;&#x30F3;&#x30B9; TMEM135&#x3001;KIAA1797&#x3001;PDE4D&#x3001;DAPK3&#x3001;GATA4 &#x4E73;&#x764C;&#x306E;&#x6F5C;&#x5728;&#x7684;&#x306A;&#x8FFD;&#x52A0;&#x306E;&#x30C9;&#x30E9;&#x30A4;&#x30D0;&#x30FC;&#x3067;&#x3042;&#x308B;&#x3053;&#x3068;&#x3092;&#x660E;&#x3089;&#x304B;&#x306B;&#x3057;&#x307E;&#x3057;&#x305F;&#x3002;&#x672C;&#x7814;&#x7A76;&#x306F;&#x75C5;&#x539F;&#x6027;&#x306E;&#x751F;&#x6B96;&#x7D30;&#x80DE;&#x7A81;&#x7136;&#x5909;&#x7570;&#x306F;&#x91CE;&#x751F;&#x578B;&#x5BFE;&#x7ACB;&#x907A;&#x4F1D;&#x5B50;&#x306E;&#x4F53;&#x7D30;&#x80DE;&#x306E;&#x640D;&#x5931;&#x3068;&#x76F8;&#x307E;&#x3063;&#x3066; BRCA1 &#x3092; ER &#x9670;&#x6027;&#x8868;&#x73FE;&#x578B;&#x3092;&#x8868;&#x793A;&#x3059;&#x308B;&#x907A;&#x4F1D;&#x6027;&#x4E73;&#x764C;&#x306E;&#x305F;&#x3081;&#x306B;&#x5341;&#x5206;&#x3067;&#x306F;&#x306A;&#x3044;&#x3068; 3 &#x6F5C;&#x5728;&#x7684;&#x306A;&#x65B0;&#x898F;&#x4E73;&#x764C;&#x907A;&#x4F1D;&#x5B50; (DAPK3&#x3001;TMEM135&#x3001;GATA4 ie) &#x306E;&#x540C;&#x5B9A;&#x306B;&#x3064;&#x306A;&#x304C;&#x3063;&#x3066;&#x3044;&#x308B;&#x3053;&#x3068;&#x3092;&#x793A;&#x3057;&#x307E;&#x3059;&#x3002;&#x8457;&#x4F5C;&#x6A29; &copy; 2012&#x5E74;&#x30B0;&#x30EC;&#x30FC;&#x30C8; &#x30FB; &#x30D6;&#x30EA;&#x30C6;&#x30F3;&#x304A;&#x3088;&#x3073;&#x30A2;&#x30A4;&#x30EB;&#x30E9;&#x30F3;&#x30C9;&#x306E;&#x75C5;&#x7406;&#x5B66;&#x4F1A;&#x3002;John Wiley &amp; &#x30B5;&#x30F3;&#x30BA;&#x682A;&#x5F0F;&#x4F1A;&#x793E;&#x306B;&#x3088;&#x308B;&#x516C;&#x958B;

&#x5168;&#x30B2;&#x30CE;&#x30E0;&#x306E;&#x5927;&#x91CF;&#x4E26;&#x5217;&#x30B7;&#x30FC;&#x30B1;&#x30F3;&#x30B9;&#x5206;&#x6790; BRCA1 &#x5909;&#x7570;&#x4F53;&#x306E;&#x30A8;&#x30B9;&#x30C8;&#x30ED;&#x30B2;&#x30F3;&#x53D7;&#x5BB9;&#x4F53;&#x5426;&#x5B9A;&#x3068;&#x80AF;&#x5B9A;&#x7684;&#x306A;&#x4E73;&#x764C;&#x306E;&#x3002;

BRCA1 &#xB3D9;&#xC885; &#xC7AC;&#xC870;&#xD569; (HR) DNA &#xC218;&#xB9AC;, &#xC138;&#xD3EC; &#xC8FC;&#xAE30; &#xAC80;&#xC0AC;&#xC810; &#xBC0F; transcriptional &#xADDC;&#xC81C;&#xC5D0; &#xC911;&#xCD94;&#xC801;&#xC778; &#xC5ED;&#xD560;&#xC744; &#xC218;&#xD589; &#xD558;&#xB294; &#xC885;&#xC591; &#xC5B5;&#xC81C; &#xB2E8;&#xBC31;&#xC9C8;&#xC744; &#xC778;&#xCF54;&#xB529;&#xD569;&#xB2C8;&#xB2E4;. BRCA1 &#xBC88;&#xC9F8; &#xBCC0;&#xC774; &#xBC1C;&#xBCD1; &#xCD08;&#xAE30; &#xC720;&#xBC29;&#xC554; &#xBC0F; &#xB09C;&#xC18C; &#xC554; &#xC704;&#xD5D8;&#xC774; &#xB192;&#xC740; &#xBD80;&#xC5EC;. &#xACBD;&#xC6B0; 80% &#xC774;&#xC0C1;&#xC5D0;&#xC11C; &#xC885;&#xC591; BRCA1 &#xBC88;&#xC9F8; &#xB3CC;&#xC5F0;&#xBCC0;&#xC774; &#xC0AC;&#xC5C5;&#xC790;&#xC5D0;&#xC11C; &#xBC1C;&#xC0DD; &#xD558;&#xB294; &#xC2A4; &#xD2B8;&#xB85C; &#xAC90; &#xC218;&#xC6A9; &#xCCB4; (ER)-&#xBD80;&#xC815;; &#xADF8;&#xB7EC;&#xB098;, &#xCD5C;&#xB300; 15%&#xB294; ER-&#xC591;&#xC131;&#xC785;&#xB2C8;&#xB2E4;. BRCA1 ER &#xC591;&#xC131; &#xC720;&#xBC29;&#xC554; &#xC0B0;&#xBC1C;&#xC801; &#xC554; BRCA1 &#xAE30;&#xB2A5; &#xC190;&#xC2E4;&#xC5D0; &#xAD00;&#xB828;&#xC774; &#xB418; &#xACE0; causally BRCA1 &#xBC88;&#xC9F8; &#xB3CC;&#xC5F0;&#xBCC0;&#xC774;&#xC758; &#xB9E5;&#xB77D;&#xC5D0;&#xC11C; &#xBC1C;&#xC0DD; &#xD558;&#xB294; &#xAD6C;&#xC131;&#xC73C;&#xB85C; &#xC81C;&#xC548; &#xB418;&#xC5C8;&#xC2B5;&#xB2C8;&#xB2E4;. &#xC804;&#xCCB4; &#xAC8C;&#xB188; &#xB300;&#xADDC;&#xBAA8; &#xBCD1;&#xB82C; ER-&#xC591;&#xC131; &#xBC0F; &#xC751;&#xAE09;&#xC2E4; &#xC74C;&#xC218;&#xAC00; BRCA1 &#xC720;&#xBC29;&#xC554;, &#xBC0F; &#xADF8;&#xB4E4;&#xC758; &#xAC01;&#xAC01; &#xBC88;&#xC9F8; DNAs, &#xC2DC;&#xD000;&#xC2F1; &#xC790;&#xB8CC; &#xC30D; &#xD574;&#xC0C1;&#xB3C4; BRCA1 &#xC554; &#xC720;&#xC804;&#xC790; &#xD504;&#xB9AC;&#xC758; &#xD2B9;&#xC131;&#xC744; &#xC0AC;&#xC6A9; &#xD588;&#xC2B5;&#xB2C8;&#xB2E4;. BRCA1 &#xBC88;&#xC9F8; &#xB3CC;&#xC5F0;&#xBCC0;&#xC774; &#xC57C;&#xC0DD; &#xD615; &#xB300;&#xB9BD; &#xC720;&#xC804;&#xC790; &#xBC0F; TP53 &#xCCB4;&#xC138;&#xD3EC; &#xB3CC;&#xC5F0;&#xBCC0;&#xC774;&#xC758; &#xCCB4;&#xC138;&#xD3EC; &#xAC10;&#xC18C; &#xD588;&#xB2E4; recurrently &#xC0C9;&#xC778; &#xACBD;&#xC6B0;&#xC5D0; &#xBC1C;&#xACAC; &#xB429;&#xB2C8;&#xB2E4;. BRCA1 &#xC720;&#xBC29;&#xC554; mutational &#xC11C;&#xBA85; &#xC77C;&#xCE58; ER-&#xC591;&#xC131; &#xBC0F; &#xC5B4; &#xC74C;&#xC758; &#xACBD;&#xC6B0; HR DNA &#xC218;&#xB9AC;&#xC758; &#xBD80;&#xC871;&#xC5D0; &#xC758;&#xD574; &#xBC1C;&#xC0DD; &#xD45C;&#xC2DC; &#xB429;&#xB2C8;&#xB2E4;. &#xC720;&#xC804; BRCA1 &#xBC0F; &#xC0B0;&#xBC1C;&#xC801; &#xBE44; BRCA1 &#xC720;&#xBC29;&#xC554; &#xC7AC;&#xBC1C; &#xC131; &#xBCD1;&#xC6D0; &#xC131; &#xBCC0;&#xC774; homozygous &#xC0AD;&#xC81C; &#xC778;&#xB371;&#xC2A4; &#xACBD;&#xC6B0;&#xC5D0;&#xC11C; &#xBC1C;&#xACAC;&#xC758; &#xC874;&#xC7AC;&#xC5D0; &#xB300; &#xD55C; &#xB3C5;&#xB9BD;&#xC801;&#xC778; &#xB3D9;&#xB8CC;&#xC758; &#xBD84;&#xC11D; &#xC2DC;&#xD000;&#xC2F1; DAPK3, TMEM135, KIAA1797, PDE4D, &#xBC0F; GATA4 &#xC720;&#xBC29;&#xC554;&#xC758; &#xC7A0;&#xC7AC;&#xC801;&#xC778; &#xCD94;&#xAC00; &#xB4DC;&#xB77C;&#xC774;&#xBC84;&#xB294; &#xBC1D;&#xD614;&#xB2E4;. &#xC774; &#xC5F0;&#xAD6C; BRCA1 &#xC57C;&#xC0DD; &#xD615; &#xB300;&#xB9BD; &#xC720;&#xC804;&#xC790;&#xC758; &#xCCB4;&#xC138;&#xD3EC; &#xAC10;&#xC18C;&#xC640; &#xACB0;&#xD569; &#xD558; &#xC5EC; &#xBCD1;&#xC6D0; &#xC131; &#xBC88;&#xC9F8; &#xB3CC;&#xC5F0;&#xBCC0;&#xC774; &#xC751;&#xAE09;&#xC2E4; &#xC74C;&#xC218;&#xAC00; phenotype &#xD45C;&#xC2DC; &#xC720;&#xC804; &#xC131; &#xC720;&#xBC29;&#xC554;&#xC5D0; &#xB300; &#xD55C; &#xCDA9;&#xBD84; &#xD558;&#xC9C0; &#xC54A;&#xC2B5;&#xB2C8;&#xB2E4; &#xADF8;&#xB9AC;&#xACE0; 3 &#xAC1C;&#xC758; &#xC7A0;&#xC7AC;&#xC801;&#xC778; &#xC18C;&#xC124; &#xC720; &#xBC29; &#xC554; &#xC720;&#xC804;&#xC790; (&#xC989; DAPK3, TMEM135, &#xBC0F; GATA4)&#xC758; &#xC2DD;&#xBCC4;&#xC744; &#xC8FC;&#xB3C4;&#xD558; &#xACE0; &#xC788;&#xB2E4; &#xBCF4;&#xC5EC; &#xC90D;&#xB2C8;&#xB2E4;. &#xC800;&#xC791;&#xAD8C; &copy; 2012 &#xB300; &#xBE0C;&#xB9AC;&#xD2BC;&#xACFC; &#xC544;&#xC77C;&#xB79C;&#xB4DC;&#xC758; &#xBCD1; &#xC801;&#xC778; &#xC0AC;&#xD68C;. &#xC874;&#xC640; &#xC77C;&#xB9AC; &amp; &#xC544;&#xB4E4;, &#xC8FC;&#xC2DD; &#xD68C;&#xC0AC;&#xC5D0; &#xC758;&#xD574; &#xAC8C;&#xC2DC;

&#xC804;&#xCCB4; &#xAC8C;&#xB188; &#xB300;&#xADDC;&#xBAA8; &#xBCD1;&#xB82C; &#xC2DC;&#xD000;&#xC2F1; &#xBD84;&#xC11D; BRCA1 &#xB3CC;&#xC5F0;&#xBCC0;&#xC774; &#xC2A4; &#xD2B8;&#xB85C; &#xAC90; &#xC218;&#xC6A9; &#xCCB4; &#xB124;&#xAC70;&#xD2F0;&#xBE0C;&#xC640;-&#xAE0D;&#xC815;&#xC801;&#xC778; &#xC720; &#xBC29; &#xC554;.

BRCA1 codifica una prote&iacute;na supresora de tumor que juega un papel fundamental en la regulaci&oacute;n transcripcional, puestos de control del ciclo celular y reparaci&oacute;n del ADN recombinaci&oacute;n hom&oacute;loga (HR). Mutaciones de l&iacute;nea germinal del BRCA1 confieren un alto riesgo de aparici&oacute;n temprana de mama y ovario. En m&aacute;s del 80% de los casos, los tumores que se presentan en BRCA1 portadores de la mutaci&oacute;n de l&iacute;nea germinal son receptores de estr&oacute;geno (ER)-negativo; sin embargo, hasta 15% son positivos. Se ha sugerido que los c&aacute;nceres de mama BRCA1 positivos constituyen c&aacute;nceres espor&aacute;dicos que se presentan en el contexto de una mutaci&oacute;n de l&iacute;nea germinal del BRCA1 en lugar de estar causalmente relacionados con BRCA1 p&eacute;rdida de funci&oacute;n. Todo el genoma masivamente paralelo secuenciaci&oacute;n de ER-positivo y los c&aacute;nceres de mama BRCA1 ER-negativo y su germline respectivo DNAs, fue utilizado para caracterizar el paisaje gen&eacute;tico de BRCA1 c&aacute;nceres en resoluci&oacute;n de base-par. S&oacute;lo mutaciones de la l&iacute;nea germinal del BRCA1, p&eacute;rdida som&aacute;tica del alelo y mutaciones som&aacute;ticas TP53 recurrentemente encontradas en los casos del &iacute;ndice. Los c&aacute;nceres de mama BRCA1 aparecen una firma mutacional consistente con la causada por la falta de reparaci&oacute;n del ADN de HR en casos tanto positivos como negativos ER. Secuencia de an&aacute;lisis de cohortes independientes de hereditario BRCA1 y c&aacute;ncer de mama espor&aacute;dico no-BRCA1 para la presencia de mutaciones patog&eacute;nicas recurrentes o deleciones homocig&oacute;ticas encontrados en los casos del &iacute;ndice revel&oacute; que DAPK3, TMEM135, KIAA1797, PDE4D y GATA4 son potenciales controladores adicionales de c&aacute;ncer de mama. Este estudio demuestra que el BRCA1 mutaciones patog&eacute;nicas del germline junto con p&eacute;rdida som&aacute;tica del alelo no son suficientes para los c&aacute;nceres de mama hereditario Mostrar un fenotipo de ER-negativo y ha llevado a la identificaci&oacute;n de tres potenciales novela mama c&aacute;ncer genes (es decir DAPK3, TMEM135 y GATA4). Copyright &copy; 2012 sociedad patol&oacute;gica de Gran Breta&ntilde;a e Irlanda. Publicado por John Wiley &amp; Sons, Ltd.

Un an&aacute;lisis de secuenciaci&oacute;n masiva y en paralelo de todo el genoma de c&aacute;nceres de mama de BRCA1 mutante estr&oacute;geno receptor negativo y - positivos.

Micropapillary carcinoma (MPC) is a rare histological special type of breast cancer, characterized by an aggressive clinical behaviour and a pattern of copy number aberrations (CNAs) distinct from that of grade- and oestrogen receptor (ER)-matched invasive carcinomas of no special type (IC-NSTs). The aims of this study were to determine whether MPCs are underpinned by a recurrent fusion gene(s) or mutations in 273 genes recurrently mutated in breast cancer. Sixteen MPCs were subjected to microarray-based comparative genomic hybridization (aCGH) analysis and Sequenom OncoCarta mutation analysis. Eight and five MPCs were subjected to targeted capture and RNA sequencing, respectively. aCGH analysis confirmed our previous observations about the repertoire of CNAs of MPCs. Sequencing analysis revealed a spectrum of mutations similar to those of luminal B IC-NSTs, and recurrent mutations affecting mitogen-activated protein kinase family genes and NBPF10. RNA-sequencing analysis identified 17 high-confidence fusion genes, eight of which were validated and two of which were in-frame. No recurrent fusions were identified in an independent series of MPCs and IC-NSTs. Forced expression of in-frame fusion genes (SLC2A1-FAF1 and BCAS4-AURKA) resulted in increased viability of breast cancer cells. In addition, genomic disruption of CDK12 caused by out-of-frame rearrangements was found in one MPC and in 13% of HER2-positive breast cancers, identified through a re-analysis of publicly available massively parallel sequencing data. In vitro analyses revealed that CDK12 gene disruption results in sensitivity to PARP inhibition, and forced expression of wild-type CDK12 in a CDK12-null cell line model resulted in relative resistance to PARP inhibition. Our findings demonstrate that MPCs are neither defined by highly recurrent mutations in the 273 genes tested, nor underpinned by a recurrent fusion gene. Although seemingly private genetic events, some of the fusion transcripts found in MPCs may play a role in maintenance of a malignant phenotype and potentially offer therapeutic opportunities.

Characterization of the genomic features and expressed fusion genes in micropapillary carcinomas of the breast.

Mutations in genes encoding proteins involved in RNA splicing have been found to occur at relatively high frequencies in several tumour types including myelodysplastic syndromes, chronic lymphocytic leukaemia, uveal melanoma, and pancreatic cancer, and at lower frequencies in breast cancer. To investigate whether dysfunction in RNA splicing is implicated in the pathogenesis of breast cancer, we performed a re-analysis of published exome and whole genome sequencing data. This analysis revealed that mutations in spliceosomal component genes occurred in 5.6% of unselected breast cancers, including hotspot mutations in the SF3B1 gene, which were found in 1.8% of unselected breast cancers. SF3B1 mutations were significantly associated with ER-positive disease, AKT1 mutations, and distinct copy number alterations. Additional profiling of hotspot mutations in a panel of special histological subtypes of breast cancer showed that 16% and 6% of papillary and mucinous carcinomas of the breast harboured the SF3B1 K700E mutation. RNA sequencing identified differentially spliced events expressed in tumours with SF3B1 mutations including the protein coding genes TMEM14C, RPL31, DYNL11, UQCC, and ABCC5, and the long non-coding RNA CRNDE. Moreover, SF3B1 mutant cell lines were found to be sensitive to the SF3b complex inhibitor spliceostatin A and treatment resulted in perturbation of the splicing signature. Albeit rare, SF3B1 mutations result in alternative splicing events, and may constitute drivers and a novel therapeutic target in a subset of breast cancers.

SF3B1 mutations constitute a novel therapeutic target in breast cancer.

HER2 is overexpressed and amplified in approximately 15% of invasive breast cancers, and is the molecular target and predictive marker of response to anti-HER2 agents. In a subset of these cases, heterogeneous distribution of HER2 gene amplification can be found, which creates clinically challenging scenarios. Currently, breast cancers with HER2 amplification/overexpression in just over 10% of cancer cells are considered HER2-positive for clinical purposes; however, it is unclear as to whether the HER2-negative components of such tumors would be driven by distinct genetic alterations. Here we sought to characterize the pathologic and genetic features of the HER2-positive and HER2-negative components of breast cancers with heterogeneous HER2 gene amplification and to define the repertoire of potential driver genetic alterations in the HER2-negative components of these cases.

Intra-tumor genetic heterogeneity and alternative driver genetic alterations in breast cancers with heterogeneous HER2 gene amplification.

The initiation and progression of breast cancer from the transformation of the normal epithelium to ductal carcinoma in situ (DCIS) and invasive disease is a complex process involving the acquisition of genetic alterations and changes in gene expression, alongside microenvironmental and recognized histological alterations. Here, we sought to comprehensively characterise the genomic and transcriptomic features of the MCF10 isogenic model of breast cancer progression, and to functionally validate potential driver alterations in three-dimensional (3D) spheroids that may provide insights into breast cancer progression, and identify targetable alterations in conditions more similar to those encountered in vivo. We performed whole genome, exome and RNA sequencing of the MCF10 progression series to catalogue the copy number and mutational and transcriptomic landscapes associated with progression. We identified a number of predicted driver mutations (including PIK3CA and TP53) that were acquired during transformation of non-malignant MCF10A cells to their malignant counterparts that are also present in analysed primary breast cancers from The Cancer Genome Atlas (TCGA). Acquisition of genomic alterations identified MYC amplification and previously undescribed RAB3GAP1-HRAS and UBA2-PDCD2L expressed in-frame fusion genes in malignant cells. Comparison of pathway aberrations associated with progression showed that, when cells are grown as 3D spheroids, they show perturbations of cancer-relevant pathways. Functional interrogation of the dependency on predicted driver events identified alterations in HRAS, PIK3CA and TP53 that selectively decreased cell growth and were associated with progression from preinvasive to invasive disease only when cells were grown as spheroids. Our results have identified changes in the genomic repertoire in cell lines representative of the stages of breast cancer progression, and demonstrate that genetic dependencies can be uncovered when cells are grown in conditions more like those in vivo. The MCF10 progression series therefore represents a good model with which to dissect potential biomarkers and to evaluate therapeutic targets involved in the progression of breast cancer. © 2016 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Three-dimensional modelling identifies novel genetic dependencies associated with breast cancer progression in the isogenic MCF10 model.

The matrisome is a complex and heterogeneous collection of extracellular matrix (ECM) and ECM-associated proteins that play important roles in tissue development and homeostasis. While several strategies for matrisome enrichment have been developed, it is currently unknown how the performance of these different methodologies compares in the proteomic identification of matrisome components across multiple tissue types. In the present study, we perform a comparative proteomic assessment of two widely used decellularisation protocols and two extraction methods to characterise the matrisome in four murine organs (heart, mammary gland, lung and liver). We undertook a systematic evaluation of the performance of the individual methods on protein yield, matrisome enrichment capability and the ability to isolate core matrisome and matrisome-associated components. Our data find that sodium dodecyl sulphate (SDS) decellularisation leads to the highest matrisome enrichment efficiency, while the extraction protocol that comprises chemical and trypsin digestion of the ECM fraction consistently identifies the highest number of matrisomal proteins across all types of tissue examined. Matrisome enrichment had a clear benefit over non-enriched tissue for the comprehensive identification of matrisomal components in murine liver and heart. Strikingly, we find that all four matrisome enrichment methods led to significant losses in the soluble matrisome-associated proteins across all organs. Our findings highlight the multiple factors (including tissue type, matrisome class of interest and desired enrichment purity) that influence the choice of enrichment methodology, and we anticipate that these data will serve as a useful guide for the design of future proteomic studies of the matrisome.

Comparative proteomic assessment of matrisome enrichment methodologies.

Subunits of the SWI/SNF chromatin remodeling complex are mutated in a significant proportion of human cancers. Malignant rhabdoid tumors (MRTs) are lethal pediatric cancers characterized by a deficiency in the SWI/SNF subunit SMARCB1. Here, we employ an integrated molecular profiling and chemical biology approach to demonstrate that the receptor tyrosine kinases (RTKs) PDGFRα and FGFR1 are coactivated in MRT cells and that dual blockade of these receptors has synergistic efficacy. Inhibitor combinations targeting both receptors and the dual inhibitor ponatinib suppress the AKT and ERK1/2 pathways leading to apoptosis. MRT cells that have acquired resistance to the PDGFRα inhibitor pazopanib are susceptible to FGFR inhibitors. We show that PDGFRα levels are regulated by SMARCB1 expression, and assessment of clinical specimens documents the expression of both PDGFRα and FGFR1 in rhabdoid tumor patients. Our findings support a therapeutic approach in cancers with SWI/SNF deficiencies by exploiting RTK coactivation dependencies.

Article	Year
A whole-genome massively parallel sequencing analysis of BRCA1 mutant oestrogen receptor-negative and -positive breast cancers. The Journal of pathology\| PubMed ID: 22362584	2012
Characterization of the genomic features and expressed fusion genes in micropapillary carcinomas of the breast. The Journal of pathology\| PubMed ID: 24395524	2014
SF3B1 mutations constitute a novel therapeutic target in breast cancer. The Journal of pathology\| PubMed ID: 25424858	2015
Intra-tumor genetic heterogeneity and alternative driver genetic alterations in breast cancers with heterogeneous HER2 gene amplification. Genome biology\| PubMed ID: 25994018	2015
Three-dimensional modelling identifies novel genetic dependencies associated with breast cancer progression in the isogenic MCF10 model. The Journal of pathology\| PubMed ID: 27512948	2016
Comparative proteomic assessment of matrisome enrichment methodologies. The Biochemical journal\| PubMed ID: 27589945	2016
Dual Targeting of PDGFRα and FGFR1 Displays Synergistic Efficacy in Malignant Rhabdoid Tumors. Cell reports\| PubMed ID: 27783942	2016

Patty Wai

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