Centro de Investigación del Cáncer

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies. Results for the final phase of the 1000 Genomes Project are presented including whole-genome sequencing, targeted exome sequencing, and genotyping on high-density SNP arrays for 2,504 individuals across 26 populations, providing a global reference data set to support biomedical genetics. The 1000 Genomes Project has sought to comprehensively catalogue human genetic variation across populations, providing a valuable public genomic resource. The data obtained so far have found applications ranging from association studies and fine mapping studies to the filtering of likely neutral variants in rare-disease cohorts. The authors now report on the final phase of the project, phase 3, which covers previously uncharacterized areas of human genetic diversity in terms of the populations sampled and categories of characterized variation. The sample now includes more than 2,500 individuals from 26 global populations, with low coverage whole-genome and deep exome sequencing, as well as dense microarray genotyping. They find that while most common variants are shared across populations, rarer variants are often restricted to closely related populations. The authors also demonstrate the use of the phase 3 dataset as a reference panel for imputation to improve the resolution in genetic association studies.

The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles ("MISEV") guidelines for the field in 2014. We now update these "MISEV2014" guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.

By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations. This report from the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations; hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites, can be found in each individual. This report by the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations. Integrative analyses reveal profiles of rare and common variants in different populations. The frequencies of rare variants vary across biological pathways, and hundreds of rare, non-coding variants at conserved sites — such as changes disrupting transcription-factor motifs — can be established for each individual.

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,
\nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981,
\nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826,
\nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376,
\nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294,
\nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198,
\nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544,
\nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107,
\nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756,
\nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6,
\nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58,
\nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007,
\nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591,
\nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930,
\nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794,
\nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727,
\nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986,
\nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409,
\nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368,
\nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884,
\nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239,
\nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997,
\nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798,
\nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909,
\nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336,
\nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419,
\nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490,
\nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401,
\nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880,
\nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913,
\nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381,
\nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112,
\nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812,
\nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287,
\nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308,
\nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901,
\nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141,
\nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374,
\nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822,
\nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480,
\nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171,
\nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789,
\nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217,
\nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24,
\nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700,
\nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983,
\nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002,
\nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318,
\nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462,
\nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884,
\nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996,
\nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628,
\nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003,
\nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434,
\nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783,
\nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514,
\nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172,
\nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113,
\nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135,
\nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702,
\nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703,
\nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308,
\nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290,
\nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105,
\nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563,
\nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936,
\nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657,
\nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254,
\nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694,
\nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781,
\nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533,
\nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829,
\nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395,
\nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566,
\nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767,
\nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301,
\nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919,
\nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576,
\nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572,
\nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940,
\nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340,
\nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254,
\nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604,
\nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182,
\nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775,
\nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,

Gene transcription can be activated or inhibited by a reversible modification of the gene; this modification is termed an epigenetic change. This account of epigenetics in cancer reviews the mechanisms and consequences of epigenetic changes in cancer cells and concludes with the implications of these changes for the diagnosis, prognosis, and treatment of cancer.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

BACKGROUND: Multiple loss-of-function alterations in genes that are involved in DNA repair, including homologous recombination repair, are associated with response to poly(adenosine diphosphate-ribose) polymerase (PARP) inhibition in patients with prostate and other cancers. METHODS: ; cohort B (142 patients) had alterations in any of 12 other prespecified genes, prospectively and centrally determined from tumor tissue. Patients were randomly assigned (in a 2:1 ratio) to receive olaparib or the physician's choice of enzalutamide or abiraterone (control). The primary end point was imaging-based progression-free survival in cohort A according to blinded independent central review. RESULTS: In cohort A, imaging-based progression-free survival was significantly longer in the olaparib group than in the control group (median, 7.4 months vs. 3.6 months; hazard ratio for progression or death, 0.34; 95% confidence interval, 0.25 to 0.47; P<0.001); a significant benefit was also observed with respect to the confirmed objective response rate and the time to pain progression. The median overall survival in cohort A was 18.5 months in the olaparib group and 15.1 months in the control group; 81% of the patients in the control group who had progression crossed over to receive olaparib. A significant benefit for olaparib was also seen for imaging-based progression-free survival in the overall population (cohorts A and B). Anemia and nausea were the main toxic effects in patients who received olaparib. CONCLUSIONS: In men with metastatic castration-resistant prostate cancer who had disease progression while receiving enzalutamide or abiraterone and who had alterations in genes with a role in homologous recombination repair, olaparib was associated with longer progression-free survival and better measures of response and patient-reported end points than either enzalutamide or abiraterone. (Funded by AstraZeneca and Merck Sharp & Dohme; PROfound ClinicalTrials.gov number, NCT02987543.).

Analysis of the genomes of four patients with chronic lymphocytic leukaemia, and validation in more than 300 patients, has identified four genes — NOTCH1, MYD88, XPO1 and KLHL6 — that are recurrently mutated in the condition. Mutations in NOTCH1, MYD88 and XPO1 are thought to contribute to the clinical evolution of the disease. Evidence that NOTCH1 and MYD88 mutations are activating events highlights them as potential therapeutic targets. Chronic lymphocytic leukaemia (CLL), the most frequent leukaemia in adults in Western countries, is a heterogeneous disease with variable clinical presentation and evolution1,2. Two major molecular subtypes can be distinguished, characterized respectively by a high or low number of somatic hypermutations in the variable region of immunoglobulin genes3,4. The molecular changes leading to the pathogenesis of the disease are still poorly understood. Here we performed whole-genome sequencing of four cases of CLL and identified 46 somatic mutations that potentially affect gene function. Further analysis of these mutations in 363 patients with CLL identified four genes that are recurrently mutated: notch 1 (NOTCH1), exportin 1 (XPO1), myeloid differentiation primary response gene 88 (MYD88) and kelch-like 6 (KLHL6). Mutations in MYD88 and KLHL6 are predominant in cases of CLL with mutated immunoglobulin genes, whereas NOTCH1 and XPO1 mutations are mainly detected in patients with unmutated immunoglobulins. The patterns of somatic mutation, supported by functional and clinical analyses, strongly indicate that the recurrent NOTCH1, MYD88 and XPO1 mutations are oncogenic changes that contribute to the clinical evolution of the disease. To our knowledge, this is the first comprehensive analysis of CLL combining whole-genome sequencing with clinical characteristics and clinical outcomes. It highlights the usefulness of this approach for the identification of clinically relevant mutations in cancer.

Since the publication of the Revised European-American Classification of Lymphoid Neoplasms in 1994, subsequent updates of the classification of lymphoid neoplasms have been generated through iterative international efforts to achieve broad consensus among hematopathologists, geneticists, molecular scientists, and clinicians. Significant progress has recently been made in the characterization of malignancies of the immune system, with many new insights provided by genomic studies. They have led to this proposal. We have followed the same process that was successfully used for the third and fourth editions of the World Health Organization Classification of Hematologic Neoplasms. The definition, recommended studies, and criteria for the diagnosis of many entities have been extensively refined. Some categories considered provisional have now been upgraded to definite entities. Terminology for some diseases has been revised to adapt nomenclature to the current knowledge of their biology, but these modifications have been restricted to well-justified situations. Major findings from recent genomic studies have impacted the conceptual framework and diagnostic criteria for many disease entities. These changes will have an impact on optimal clinical management. The conclusions of this work are summarized in this report as the proposed International Consensus Classification of mature lymphoid, histiocytic, and dendritic cell tumors.

MicroRNAs (miRNAs) are small, noncoding RNAs that can contribute to cancer development and progression by acting as oncogenes or tumor suppressor genes. Recent studies have also linked different sets of miRNAs to metastasis through either the promotion or suppression of this malignant process. Interestingly, epigenetic silencing of miRNAs with tumor suppressor features by CpG island hypermethylation is also emerging as a common hallmark of human tumors. Thus, we wondered whether there was a miRNA hypermethylation profile characteristic of human metastasis. We used a pharmacological and genomic approach to reveal this aberrant epigenetic silencing program by treating lymph node metastatic cancer cells with a DNA demethylating agent followed by hybridization to an expression microarray. Among the miRNAs that were reactivated upon drug treatment, miR-148a, miR-34b/c, and miR-9 were found to undergo specific hypermethylation-associated silencing in cancer cells compared with normal tissues. The reintroduction of miR-148a and miR-34b/c in cancer cells with epigenetic inactivation inhibited their motility, reduced tumor growth, and inhibited metastasis formation in xenograft models, with an associated down-regulation of the miRNA oncogenic target genes, such as C-MYC, E2F3, CDK6, and TGIF2. Most important, the involvement of miR-148a, miR-34b/c, and miR-9 hypermethylation in metastasis formation was also suggested in human primary malignancies ( n = 207) because it was significantly associated with the appearance of lymph node metastasis. Our findings indicate that DNA methylation-associated silencing of tumor suppressor miRNAs contributes to the development of human cancer metastasis.

BACKGROUND: Teclistamab is a T-cell-redirecting bispecific antibody that targets both CD3 expressed on the surface of T cells and B-cell maturation antigen expressed on the surface of myeloma cells. In the phase 1 dose-defining portion of the study, teclistamab showed promising efficacy in patients with relapsed or refractory multiple myeloma. METHODS: In this phase 1-2 study, we enrolled patients who had relapsed or refractory myeloma after at least three therapy lines, including triple-class exposure to an immunomodulatory drug, a proteasome inhibitor, and an anti-CD38 antibody. Patients received a weekly subcutaneous injection of teclistamab (at a dose of 1.5 mg per kilogram of body weight) after receiving step-up doses of 0.06 mg and 0.3 mg per kilogram. The primary end point was the overall response (partial response or better). RESULTS: Among 165 patients who received teclistamab, 77.6% had triple-class refractory disease (median, five previous therapy lines). With a median follow-up of 14.1 months, the overall response rate was 63.0%, with 65 patients (39.4%) having a complete response or better. A total of 44 patients (26.7%) were found to have no minimal residual disease (MRD); the MRD-negativity rate among the patients with a complete response or better was 46%. The median duration of response was 18.4 months (95% confidence interval [CI], 14.9 to not estimable). The median duration of progression-free survival was 11.3 months (95% CI, 8.8 to 17.1). Common adverse events included cytokine release syndrome (in 72.1% of the patients; grade 3, 0.6%; no grade 4), neutropenia (in 70.9%; grade 3 or 4, 64.2%), anemia (in 52.1%; grade 3 or 4, 37.0%), and thrombocytopenia (in 40.0%; grade 3 or 4, 21.2%). Infections were frequent (in 76.4%; grade 3 or 4, 44.8%). Neurotoxic events occurred in 24 patients (14.5%), including immune effector cell-associated neurotoxicity syndrome in 5 patients (3.0%; all grade 1 or 2). CONCLUSIONS: Teclistamab resulted in a high rate of deep and durable response in patients with triple-class-exposed relapsed or refractory multiple myeloma. Cytopenias and infections were common; toxic effects that were consistent with T-cell redirection were mostly grade 1 or 2. (Funded by Janssen Research and Development; MajesTEC-1 ClinicalTrials.gov numbers, NCT03145181 and NCT04557098.).

We previously showed that the availability of a nonamer peptide derived from certain HLA class I signal sequences is a necessary requirement for the stabilization of endogenous HLA-E expression on the surface of 721.221 cells. This led us to examine the ability of HLA-E to protect HLA class I transfectants from natural killer (NK) cell-mediated lysis. It was possible to implicate the CD94/NKG2A complex as an inhibitory receptor recognizing this class Ib molecule by using as target a .221 transfectant selectively expressing surface HLA-E. HLA-E had no apparent inhibitory effect mediated through the identified Ig superfamily (Ig-SF) human killer cell inhibitory receptors or ILT2/LIR1. Further studies of CD94/NKG2+ NK cell-mediated recognition of .221 cells transfected with different HLA class I allotypes (i.e., -Cw4, -Cw3, -B7) confirmed that the inhibitory interaction was mediated by CD94/NKG2A recognizing the surface HLA-E molecule, because only antibodies directed against either HLA-E, CD94, or CD94/NKG2A specifically restored lysis. Surface stabilization of HLA-E in cold-treated .221 cells loaded with appropriate peptides was sufficient to confer protection, resulting from recognition of the HLA class Ib molecule by the CD94/NKG2A inhibitory receptor. Consistent with the prediction that the ligand for CD94/NKG2A is expressed ubiquitously, our examination of HLA-E antigen distribution indicated that it is detectable on the surface of a wide variety of cell types.

It is essential that there be consistency in the conduct, analysis, and reporting of clinical trial results in myeloma. The goal of the International Myeloma Workshop Consensus Panel 1 was to develop a set of guidelines for the uniform reporting of clinical trial results in myeloma. This paper provides a summary of the current response criteria in myeloma, detailed definitions for patient populations, lines of therapy, and specific endpoints. We propose that future clinical trials in myeloma follow the guidelines for reporting results proposed in this manuscript.

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.

The identification of new pharmacological approaches to effectively prevent, treat, and cure the metabolic syndrome is of crucial importance. Excessive exposure to dietary lipids causes inflammatory responses, deranges the homeostasis of cellular metabolism, and is believed to constitute a key initiator of the metabolic syndrome. Mammalian Sirt1 is a protein deacetylase that has been involved in resveratrol-mediated protection from high-fat diet-induced metabolic damage, but direct proof for the implication of Sirt1 has remained elusive. Here, we report that mice with moderate overexpression of Sirt1 under the control of its natural promoter exhibit fat mass gain similar to wild-type controls when exposed to a high-fat diet. Higher energy expenditure appears to be compensated by a parallel increase in food intake. Interestingly, transgenic Sirt1 mice under a high-fat diet show lower lipid-induced inflammation along with better glucose tolerance, and are almost entirely protected from hepatic steatosis. We present data indicating that such beneficial effects of Sirt1 are due to at least two mechanisms: induction of antioxidant proteins MnSOD and Nrf1, possibly via stimulation of PGC1alpha, and lower activation of proinflammatory cytokines, such as TNFalpha and IL-6, via down-modulation of NFkappaB activity. Together, these results provide direct proof of the protective potential of Sirt1 against the metabolic consequences of chronic exposure to a high-fat diet.

Proliferation is an important part of cancer development and progression. This is manifest by altered expression and/or activity of cell cycle related proteins. Constitutive activation of many signal transduction pathways also stimulates cell growth. Early steps in tumor development are associated with a fibrogenic response and the development of a hypoxic environment which favors the survival and proliferation of cancer stem cells. Part of the survival strategy of cancer stem cells may manifested by alterations in cell metabolism. Once tumors appear, growth and metastasis may be supported by overproduction of appropriate hormones (in hormonally dependent cancers), by promoting angiogenesis, by undergoing epithelial to mesenchymal transition, by triggering autophagy, and by taking cues from surrounding stromal cells. A number of natural compounds (e.g., curcumin, resveratrol, indole-3-carbinol, brassinin, sulforaphane, epigallocatechin-3-gallate, genistein, ellagitannins, lycopene and quercetin) have been found to inhibit one or more pathways that contribute to proliferation (e.g., hypoxia inducible factor 1, nuclear factor kappa B, phosphoinositide 3 kinase/Akt, insulin-like growth factor receptor 1, Wnt, cell cycle associated proteins, as well as androgen and estrogen receptor signaling). These data, in combination with bioinformatics analyses, will be very important for identifying signaling pathways and molecular targets that may provide early diagnostic markers and/or critical targets for the development of new drugs or drug combinations that block tumor formation and progression.

BACKGROUND: We previously reported that olaparib led to significantly longer imaging-based progression-free survival than the physician's choice of enzalutamide or abiraterone among men with metastatic castration-resistant prostate cancer who had qualifying alterations in homologous recombination repair genes and whose disease had progressed during previous treatment with a next-generation hormonal agent. The results of the final analysis of overall survival have not yet been reported. METHODS: , and cohort B included 142 patients with at least one alteration in any of the other 12 prespecified genes. Crossover to olaparib was allowed after imaging-based disease progression for patients who met certain criteria. Overall survival in cohort A, a key secondary end point, was analyzed with the use of an alpha-controlled, stratified log-rank test at a data maturity of approximately 60%. The primary and other key secondary end points were reported previously. RESULTS: The median duration of overall survival in cohort A was 19.1 months with olaparib and 14.7 months with control therapy (hazard ratio for death, 0.69; 95% confidence interval [CI], 0.50 to 0.97; P = 0.02). In cohort B, the median duration of overall survival was 14.1 months with olaparib and 11.5 months with control therapy. In the overall population (cohorts A and B), the corresponding durations were 17.3 months and 14.0 months. Overall, 86 of 131 patients (66%) in the control group crossed over to receive olaparib (56 of 83 patients [67%] in cohort A). A sensitivity analysis that adjusted for crossover to olaparib showed hazard ratios for death of 0.42 (95% CI, 0.19 to 0.91) in cohort A, 0.83 (95% CI, 0.11 to 5.98) in cohort B, and 0.55 (95% CI, 0.29 to 1.06) in the overall population. CONCLUSIONS: and whose disease had progressed during previous treatment with a next-generation hormonal agent, those who were initially assigned to receive olaparib had a significantly longer duration of overall survival than those who were assigned to receive enzalutamide or abiraterone plus prednisone as the control therapy, despite substantial crossover from control therapy to olaparib. (Funded by AstraZeneca and Merck Sharp and Dohme; PROfound ClinicalTrials.gov number, NCT02987543.).

The EU-supported EuroFlow Consortium aimed at innovation and standardization of immunophenotyping for diagnosis and classification of hematological malignancies by introducing 8-color flow cytometry with fully standardized laboratory procedures and antibody panels in order to achieve maximally comparable results among different laboratories. This required the selection of optimal combinations of compatible fluorochromes and the design and evaluation of adequate standard operating procedures (SOPs) for instrument setup, fluorescence compensation and sample preparation. Additionally, we developed software tools for the evaluation of individual antibody reagents and antibody panels. Each section describes what has been evaluated experimentally versus adopted based on existing data and experience. Multicentric evaluation demonstrated high levels of reproducibility based on strict implementation of the EuroFlow SOPs and antibody panels. Overall, the 6 years of extensive collaborative experiments and the analysis of hundreds of cell samples of patients and healthy controls in the EuroFlow centers have provided for the first time laboratory protocols and software tools for fully standardized 8-color flow cytometric immunophenotyping of normal and malignant leukocytes in bone marrow and blood; this has yielded highly comparable data sets, which can be integrated in a single database.

We conducted a pooled analysis of 869 individual newly diagnosed elderly patient data from 3 prospective trials. At diagnosis, a geriatric assessment had been performed. An additive scoring system (range 0-5), based on age, comorbidities, and cognitive and physical conditions, was developed to identify 3 groups: fit (score = 0, 39%), intermediate fitness (score = 1, 31%), and frail (score ≥2, 30%). The 3-year overall survival was 84% in fit, 76% in intermediate-fitness (hazard ratio [HR], 1.61; P = .042), and 57% in frail (HR, 3.57; P < .001) patients. The cumulative incidence of grade ≥3 nonhematologic adverse events at 12 months was 22.2% in fit, 26.4% in intermediate-fitness (HR, 1.23; P = .217), and 34.0% in frail (HR, 1.74; P < .001) patients. The cumulative incidence of treatment discontinuation at 12 months was 16.5% in fit, 20.8% in intermediate-fitness (HR, 1.41; P = .052), and 31.2% in frail (HR, 2.21; P < .001) patients. Our frailty score predicts mortality and the risk of toxicity in elderly myeloma patients. The International Myeloma Working group proposes this score for the measurement of frailty in designing future clinical trials. These trials are registered at www.clinicaltrials.gov as #NCT01093136 (EMN01), #NCT01190787 (26866138MMY2069), and #NCT01346787 (IST-CAR-506).

BACKGROUND: Ciltacabtagene autoleucel (cilta-cel), a B-cell maturation antigen (BCMA)-directed CAR T-cell therapy, is effective in heavily pretreated patients with relapsed or refractory multiple myeloma. We investigated cilta-cel in earlier treatment lines in patients with lenalidomide-refractory disease. METHODS: In this phase 3, randomized, open-label trial, we assigned patients with lenalidomide-refractory multiple myeloma to receive cilta-cel or the physician's choice of effective standard care. All the patients had received one to three previous lines of treatment. The primary outcome was progression-free survival. RESULTS: A total of 419 patients underwent randomization (208 to receive cilta-cel and 211 to receive standard care). At a median follow-up of 15.9 months (range, 0.1 to 27.3), the median progression-free survival was not reached in the cilta-cel group and was 11.8 months in the standard-care group (hazard ratio, 0.26; 95% confidence interval [CI], 0.18 to 0.38; P<0.001). Progression-free survival at 12 months was 75.9% (95% CI, 69.4 to 81.1) in the cilta-cel group and 48.6% (95% CI, 41.5 to 55.3) in the standard-care group. More patients in the cilta-cel group than in the standard-care group had an overall response (84.6% vs. 67.3%), a complete response or better (73.1% vs. 21.8%), and an absence of minimal residual disease (60.6% vs. 15.6%). Death from any cause was reported in 39 patients and 46 patients, respectively (hazard ratio, 0.78; 95% CI, 0.5 to 1.2). Most patients reported grade 3 or 4 adverse events during treatment. Among the 176 patients who received cilta-cel in the as-treated population, 134 (76.1%) had cytokine release syndrome (grade 3 or 4, 1.1%; no grade 5), 8 (4.5%) had immune effector cell-associated neurotoxicity syndrome (all grade 1 or 2), 1 had movement and neurocognitive symptoms (grade 1), 16 (9.1%) had cranial nerve palsy (grade 2, 8.0%; grade 3, 1.1%), and 5 (2.8%) had CAR-T-related peripheral neuropathy (grade 1 or 2, 2.3%; grade 3, 0.6%). CONCLUSIONS: A single cilta-cel infusion resulted in a lower risk of disease progression or death than standard care in lenalidomide-refractory patients with multiple myeloma who had received one to three previous therapies. (Funded by Janssen and Legend Biotech; CARTITUDE-4 ClinicalTrials.gov number, NCT04181827.).