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93 citation(s) found for "Nam, Y".

NCI protocol 10250: A phase II study of temozolomide and olaparib for the treatment of advanced uterine leiomyosarcoma.
Allred, Jacob B., Gano, Katherine, Attia, Steven , Boikos, Sosipatros A. , Chen, James Lin, Close, Julia , Seetharam, ­Mahesh , Ingham, Matthew , George, Suzanne , Burgess, Melissa , Bui, Nam Q. , Thaker, Premal H. , Schwartz, Gary K.

Journal of Clinical Oncology | May 25, 2020 | Volume: 38 | Issue: 15_suppl | Pages: TPS11570-TPS11570

10.1200/jco.2020.38.15_suppl.tps11570 Get It

TPS11570 Background: Soft tissue sarcoma (STS) is a heterogenous malignancy of mesenchymal origin and includes more than 50 biologically distinct subtypes. Leiomyosarcoma (LMS), a neoplasm of smooth muscle origin, represents up to 20% of STS. The uterus is the most common site of origin in women. Advanced uterine LMS (uLMS) is initially treated with gemcitabine + docetaxel or anthracycline-based chemotherapy but overall survival remains < 24 mos. Besides recurrent alterations in RB1, TP53 and ATRX, insight into cancer biology of uLMS remains limited. Recently, whole exome and transcriptomic sequencing studies suggest uLMS harbors characteristic defects in the homologous recombination (HR) DNA repair pathway and thus features of BRCAness. HR-deficient cancers are unable to efficiently repair double-stranded DNA breaks and appear sensitive to treatment with poly ADP-ribose polymerase (PARP) inhibitors. In preclinical studies, the combination of temozolomide (T), an alkylating agent, and olaparib (O), a PARP inhibitor, was synergistic and markedly suppressed proliferation of uLMS models. A recent phase II study in small cell lung cancer defined the RP2D for T + O where the chief toxicity was myelosuppression. Methods: NCI Protocol #10250 is a single-arm, open-label, multi-center phase II clinical trial of T + O in patients with advanced uLMS. Eligible pts have ECOG PS ≤ 2, progression on ≥ 1 prior line of therapy and disease measurable by RECIST v1.1 and amenable to image-guided biopsy. Pts receive T 75 mg/m2 PO daily + O 200 mg PO BID on days 1-7 in 21-day cycles. The 1° endpoint is objective response rate (ORR). A one-stage binomial design is used to evaluate for an ORR ≤ 10% (null hypothesis) versus ≥ 35% (alternative hypothesis). The design calls for 22 patients. If 5/22 respond, the treatment is promising. This design yields 93% power and 1-sided type I error of 6%. 2° endpoints include progression free survival and safety. All pts undergo tumor biopsies pre-treatment and during cycle 2. Tissue is used for correlative analysis interrogating uLMS for features of BRCAness through (a) whole exome sequencing/RNAseq to evaluate for alterations in HR pathway component genes, (b) RAD51 foci formation by immunohistochemistry as a functional marker of HR pathway activity and (c) protein expression of Schlafen family member number 11 (SLFN11), an emerging biomarker for PARPi. Tumors are also evaluated for MGMT protein expression, a known determinant of sensitivity to T. The study opened to accrual 10/2019. Clinical trial information: NCT03880019.
511 Point-of-care 3-dimensional Body Mapping for Determining Total Body Surface Area in Severely Burned Patients
Loegering, Julia, Webb, Kevin, Ahlquist, Jesse , Krause, Kevin, Xu, Karen , Palmieri, Tina L. , Webb, Kevin L., Greenhalgh, David G. , Tran, Nam K

Journal of Burn Care & Research | March 4, 2020 | Volume: 41 | Issue: Supplement_1 | Pages: S92-S93

10.1093/jbcr/iraa024.143 Get It

Abstract Introduction With severe burn injury, there is systemic fluid loss due to inflammatory responses in damaged tissue, leading to disruption of cellular processes. Patient fluid levels are restored with the calculation of total body surface area (TBSA). Clinically used TBSA equations are often outdated and inaccurate with error up to 20%, resulting in misinformed treatment and subsequent sequelae including prolonged hospital length of stay and increased mortality. Our objective, therefore, was to create a point-of-care (POC) system employing 3D imaging technology to accurately calculate TBSA for all patient population varieties. Methods Our team employed an iPad attachable, infrared scanner to create 3D models of the human body. From these models, TBSA can be extrapolated using scan processing software. Subject scans were collected on our device and on a gold standard scanner for comparison of TBSA output. Clinical testing on burn patients is occurring at present to establish scanning precision of TBSA in the burn care environment. Results Non-clinical verification tests of the 3D scanned TBSA revealed a 4.05% error when compared to the gold standard, and precision error of 3.8%. Additionally, we introduced the device into the burn unit for preliminary testing with a physician user and non-patient subjects. The subjects were scanned in a prone position to mimic burn care workflow. Clinician scanning error was 1.41% when compared to the gold standard scan of the same subject. Clinical precision study results are on-going in collection. Conclusions Our device introduces an improved method of TBSA estimation to assist clinicians in making accurate burn care decisions and further precision medicine with greater anthropomteric data, notably for children. This device is one of the first POC-3D scanning technologies to be used in a burn setting and may also be employed at outlying medical facilities. Destructive wildfires and combat burn injuries highlight the need for such a device to standardize the triage of burn victims with and away from experienced medical staff. Applicability of Research to Practice 3D body mapping points to an enhanced method of TBSA calculation and minimally disruptive to the burn workflow. Future developments of 3D scanning include deep learning algorithms to identify and better assess burned surface area. Additionally, further automation of TBSA scan processing to reduce user error in calculation and improve burn injury outcomes.
Point-of-care 3D body-mapping for determining total body surface area of severely burned patients
Loegering, Julia, Krause, Kevin, Ahlquist, Jesse , Webb, Kevin, Xu, Karen , Greenhalgh, David , Palmieri, Tina L. , Webb, Kevin L., Tran, Nam K , Greenhalgh, David

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) | January 21, 2020 | Volume: No volume available | Issue: No issue available | Pages: 111-114

10.1109/hi-poct45284.2019.8962792 Get It

Neurogranin Regulates Alcohol Sensitivity through AKT Pathway in the Nucleus Accumbens
Nam, Hyung Wook , Grant, Caleb A., Jorgensen, Ashton N., Holtz‐Heppelmann, Carrie J., Cvek, Urška , Nam, Hyung W , Trutschl, Marjan

PROTEOMICS | December 9, 2019 | Volume: 20 | Issue: 1 | Pages: No page available

10.1002/pmic.201900266 | PMID 31814311 Get It

AbstractDysfunction of glutamate neurotransmission in the nucleus accumbens (NAc) has been implicated in the pathophysiology of alcohol use disorders (AUD). Neurogranin (Ng) is exclusively expressed in the brain and mediates N‐methyl‐d‐aspartate receptor (NMDAR) hypo‐function by regulating the intracellular calcium‐calmodulin (Ca2+‐CaM) pathway. Ng null mice (Ng–/– mice) demonstrate increased alcohol drinking compared to wild‐type mice, while also showing less tolerance to the effect of alcohol. To identify the molecular mechanism related to alcohol seeking, both in vivo microdialysis and label‐free quantification proteomics comparing Ng genotype and effects of alcohol treatment on the NAc are utilized. There is significant difference in glutamate and gamma‐aminobutyric acid (GABA) neurotransmission between genotypes; however, alcohol administration normalizes both glutamate and GABA levels in the NAc. Using label‐free proteomics, 427 protein expression changes are identified against alcohol treatment in the NAc among 4347 total proteins detected. Bioinformatics analyses reveal significant molecular differences in Ng null mice in response to acute alcohol treatment. Ingenuity pathway analysis found that the AKT network is altered significantly between genotypes, which may increase the sensitivity of alcohol in Ng null mice. The pharmacoproteomics results presented here illustrate a possible molecular basis of the alcohol sensitivity through Ng signaling in the NAc.
Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2017
Fitzmaurice, Christina , Abate, Degu , Abbasi, Naghmeh , Abbastabar, Hedayat , Abdelalim, Ahmed , Abdoli, Amir , Abdulle, Abdishakur S. M., Abebe, Nebiyu Dereje , Abraha, Haftom Niguse , Abualhasan, Ahmed , Adedeji, Isaac Akinkunmi , Advani, Shailesh M, Afarideh, Mohsen , Afshari, Mahdi , Aghaali, Mohammad , Agius, Dominic, Agrawal, Sutapa , Ahmadi, Ayat , Ahmed, Muktar Beshir , Akbari, Mohammad Esmaeil , AlAbdulKader, Assim M. , Alahdab, Fares , Alam, Shazia , Alamene, Genet Melak, Alene, Kefyalew Addis , Alipour, Vahid, Bakeshei, Fatemeh Allah, Almadi, Majid A. , Alsharif, Ubai , Alsowaidi, Shirina, Alvis‐Guzmán, Nelson , Amini, Saeed, Anbari, Zohreh , Anber, Nahla , Andrei, Cătălina Liliana , Anjomshoa, Mina, Ansari, Fereshteh, Ansariadi, Ansariadi , Appiah, Seth Christopher Yaw , Arabloo, Jalal , Arefi, Zohreh , Aremu, Olatunde , Areri, Habtamu Abera , Artaman, Al, Asfaw, Ephrem Tsegay, Ashagre, Alebachew Fasil, Assadi, Reza , Atalay, Hagos Tasew , Ataro, Zerihun , Atique, Suleman , Ávila‐Burgos, Leticia , Avokpaho, Euripide , Awasthi, Ashish , Awoke, Nefsu , Quintanilla, Beatriz Paulina Ayala , Ayanore, Martin Amogre , Ayele, Henok Tadesse, Babaee, Ebrahim , Bacha, Umar, Badawi, Alaa, Bagherzadeh, Mojtaba , Bagli, Eleni , Balakrishnan, Senthilkumar , Bärnighausen, Till , Battista, Robert J., Behzadifar, Meysam, Belay, Yared Belete , Berfield, Kathleen, Berhane, Adugnaw , Bernabé, Eduardo , Beuran, Mircea , Bhakta, Nickhill , Bhattacharyya, Krittika , Biadgo, Belete , Bijani, Ali , Sayeed, Muhammad Shahdaat Bin , Bisignano, Catherine, Bitew, Helen , Bjørge, Tone , Bogale, Kassawmar Angaw , Bojia, Hunduma Amensisa, Borzì, Antonio Maria , Bou-Orm, Ibrahim R. , Brenner, Hermann , Brewer, Jerry D., Briko, Andrey , Брико, Н. И. , Bustamante-Teixeira, Maria Teresa , Butt, Zahid A , Carreras, Giulia , Carvalho, Félix , Castro, Clara , Castro, Franz , Catalá-López, Ferrán , Cerin, Ester , Chaiah, Yazan , Chanie, Wagaye Fentahun, Chattu, Vijay Kumar , Chaturvedi, Pankaj, Chauhan, Neelima Singh, Chiang, Peggy Pei-Chia, Chichiabellu, Tesfaye Yitna , Chido‐Amajuoyi, Onyema Greg , Chimed‐Ochir, Odgerel , Choi, Jee-Young Jasmine , Christopher, Devasahayam Jesudas , Chu, Dinh‐Toi , Costa, Vera Marisa , Crowe, Christopher S. , Curado, María Paula , Dahlawi, Saad M A , Damiani, Giovanni , Darwish, Amira Hamed , Demissie, Birhanu Wondimeneh , Demoz, Gebre Teklemariam , Derakhshani, Afshin , Deribe, Kalkidan Solomon, Desai, Rupak , Desalegn, Beruk Berhanu , Dey, Subhojit , Dhimal, Meghnath , Díaz, Daniel , Dinberu, Mesfin Tadese, Djalalinia, Shirin, Drake, Thomas M , Dubljanin, Eleonora , Duken, Eyasu Ejeta, Effiong, Andem , Eftekhari, Aziz , El-Jaafary, Shaimaa I , El‐Khatib, Ziad , Elemineh, Demelash Abewa , Elkout, Hajer , Ellenbogen, Richard G. , Elsharkawy, Aisha , Emamian, Mohammad Hassan , Endalew, Daniel Adane , Endries, Aman Yesuf , Eshrati, Babak, Fadhil, Ibtihal , Farzadfar, Farshad , Fentahun, Netsanet , Fernandes, Eduarda , Feyissa, Garumma Tolu , Fischer, Florian , Fisher, James L. , Force, Lisa M , Freitas, Marisa , Fukumoto, Takeshi , Futran, Neal D. , Gallus, Silvano , Gankpé, Fortuné Gbètoho , Gayesa, Reta Tsegaye, Gebrehiwot, Tsegaye Tewelde , Gebremeskel, Gebreamlak Gebremedhn , Gedefaw, Getnet , Gelaw, Belayneh K., Geta, Birhanu, Getachew, Sefonias , Gezae, Kebede Embaye , Ghafourifard, Mansour , Ghajar, Alireza , Ghashghaee, Ahmad , Gholamian, Asadollah , Ginindza, Themba G. , Girmay, Alem, Gizaw, Muluken , Gomez, Ricardo Santiago , Gopalani, Sameer Vali , Gorini, Giuseppe , Goulart, Bárbara Niegia Garcia de , Grada, Ayman , Guerra, Maximiliano Ribeiro, Guimarães, André Luiz Sena , Gupta, Prakash C. , Hadkhale, Kishor , Haj‐Mirzaian, Arvin , Haj‐Mirzaian, Arya , Hamadeh, Randah R , Hamidi, Samer , Hanfore, Lolemo Kelbiso , Hasankhani, Milad , Hasanzadeh, Amir , Hassen, Hamid Yimam , Hay, Simon I , Henok, Andualem , Herţeliu, Claudiu , Hoang, Chi Linh , Hole, Michael K., Hoogar, Praveen , Hosseini, Mostafa, Hosseinzadeh, Mehdi , Hostiuc, Mihaela, Hostiuc, Sorin , Househ, Mowafa , Hussen, Mohammedaman Mama, Ileanu, Bogdan Vasile , Ilić, Milena , Innos, Kaire , Irvani, Seyed Sina Naghibi , Iseh, Kufre Robert , Islam, Sheikh Mohammed Shariful , Balalami, Nader Jafari, Jafarinia, Morteza , Jahangiry, Leila , Jahanmehr, Nader , Jakovljević, Mihajlo, James, Spencer L , Jayaraman, Sudha , Jha, Ravi Prakash , Jonas, Jost B, Joó, Tamás , Jürisson, Mikk , Kamangar, Farin , Karimi, Narges , Karimian, Ansar , Kasaeian, Amir , Kasahun, Gebremicheal Gebreslassie , Kassa, Belete, Kassaw, Mesfin Wudu , Kaul, Anil, Keiyoro, Peter Njenga, Kelbore, Abraham Getachew , Khader, Yousef , Khalilarjmandi, Maryam, Khan, Ejaz Ahmad , Khan, Gulfaraz , Khang, Young-Ho, Khater, Amir M, Khayamzadeh, Maryam , Khazaee-Pool, Maryam , Khosravi, Mohammad Hossein , Khubchandani, Jagdish , Kianipour, Neda, Kim, Daniel , Kısa, Adnan , Kısa, Sezer , Komaki, Hamidreza , Krohn, Kristopher J, Biçer, Burcu Küçük , Kugbey, Nuworza , Kumar, Vivek , Kuupiel, Desmond , Lad, Deepesh , Lake, Eyasu Alem , Lakew, Ayenew Molla , Lal, Dharmesh Kumar, Lami, Faris , Lan, Qing , Lasrado, Savita , Lazarus, Jeffrey V. , Leigh, James , Leshargie, Cheru Tesema , Liao, Yu , Limenih, Miteku Andualem , Listl, Stefan , Lopukhov, Platon D , Lunevičius, Raimundas , Madadin, Mohammed , Razek, Hassan Magdy Abd El , Majeed, Azeem , Manafi, Ali, Manafi, Navid , Manamo, Wondimu Ayele, Mantovani, LG , Martini, Santi , Mashamba-Thompson, Tivani P. , Massenburg, Benjamin B. , Maswabi, Motswadi Titus, McAlinden, Colm , Meheretu, Hailemariam Abiy Alemu , Mehrotra, Ravi , Meles, Gebrekiros Gebremichael , Meles, Hagazi Gebre , Melku, Mulugeta , Memiah, Peter , Mendoza, Walter, Menezes, Ritesh G. , Merat, Shahin , Meretoja, Tuomo J , Miazgowski, Bartosz , Miazgowski, Tomasz , Mihretie, Kebadnew Mulatu M., Miller, Ted R. , Mills, Edward J , Mir, Seyed Mostafa , Mishra, Rashmi , Moazen, Babak , Mohammad, Dara K., Mohammad, Karzan Abdulmuhsin , Mohammad, Yousef , Mohammadi, Moslem, Mohammadian, Mahdi , Mohammadian-Hafshejani, Abdollah , Mohammadoo-Khorasani, Milad, Mohammed, Ammas Siraj , Mohammed, Jemal , Mohammed, Shafiu , Mohebi, Farnam , Mokdad, Ali H. , Monasta, Lorenzo , Moodley, Yoshan , Moosazadeh, Mahmood , Moossavi, Maryam , Moradi, Ghobad , Moradi-Joo, Mohammad , Moradpour, Farhad , Morawska, Lídia , Morgado-da-Costa, Joana, Mosapour, Abbas , Mousavi, Seyyed Meysam , Muche, Achenef Asmamaw , Muhammed, Oumer Sada , Musa, Jonah , Nabhan, Ashraf , Naderi, Mehdi , Nagarajan, Ahamarshan Jayaraman , Nagel, Gabriele , Naik, Gurudatta , Nam, Hae‐Sung , Nazari, Javad , Negoi, Ionuţ , Neupane, Subas , Nggada, Haruna Asura , Ngunjiri, Josephine W, Nguyen, Cuong Tat , Nikniaz, Leila , Ningrum, Dina Nur Anggraini , Nirayo, Yirga Legesse, Nixon, Molly R, Nnaji, Chukwudi A , Shiadeh, Malihe Nourollahpour , Obsa, Mohammed Suleiman , Ofori‐Asenso, Richard , Ogbo, Felix Akpojene , Olagunju, Andrew T , Olagunju, Tinuke O , Oluwasanu, Mojisola , Omonisi, Abidemi , Onwujekwe, Obinna , Oommen, Anu Mary , Ortega-Altamirano, Doris V , Otstavnov, Stanislav S , Mahesh, P A , Padubidri, Jagadish Rao , Pakhalé, Smita , Pakpour, Amir H. , Pană, Adrian , Park, Eun‐Kee , Patel, Shanti, Patil, Snehal T, Pennini, Alyssa, Piccinelli, Cristiano, Pillay, Julian David , Pirestani, Majid , Postma, Maarten J. , Pourmalek, Farshad , Pourshams, Akram , Prakash, Swayam , Rabiee, Navid , Radfar, Amir , Rafiei, Alireza , Rahim, Fakher , Rahimi, Mahdi , Rahman, Muhammad Aziz , Rajati, Fatemeh , Rana, Saleem M., Raoofi, Samira , Rath, Goura Kishor, Rawaf, David Laith , Reiner, Robert C. , Renzaho, André M. N. , Rezapour, Aziz, Ribeiro, Ana Isabel , Ribeiro, Daniela , Roro, Elias Merdassa , Rostami, Ali , Saad, Ragy , Sabbagh, Parisa , Saddik, Basema , Safiri, Saeid , Salahshoor, Mohammad Reza , Salehi, Farkhonde , Salem, Hosni , Salem, Marwa Rashad , Salimzadeh, Hamideh , Salomon, Joshua A. , Samy, Abdallah M , Sanabria, Juan , Santric-Milicevic, Milena M , Sartorius, Benn , Sarveazad, Arash , Sathian, Brijesh , Satpathy, Maheswar , Savic, Miloje , Sawhney, Monika, Seyedmousavi, Seyedmojtaba , Shaahmadi, Faramarz , Shabaninejad, Hosein , Shahbaz, Mohammad , Shaikh, Masood Ali, Shamshirian, Amir , Shamsizadeh, Morteza , Sharafi, Zeinab , Sharifi, Ali , Sharifi, Hamid , Shirkoohi, Reza , Shukla, Sharvari , Si, Si , Siabani, Soraya , Silva, Diego Augusto Santos , Singh, Ambrish , Sisay, Solomon , Sobngwi, Eugène , Soofi, Moslem , Soriano, Joan B. , Stathopoulou, Vasiliki, Sufiyan, Mu’awiyyah Babale , Tabarés‐Seisdedos, Rafael , Tabuchi, Takahiro , Takahashi, Ken , Tarawneh, Mohammed Rasoul , Tassew, Segen Gebremeskel , Taymoori, Parvaneh , Temsah, Mohamad‐Hani , Temsah, Omar, Tesfay, Fisaha Haile , Teshale, Manaye Yihune, Tessema, Gizachew Assefa , Thapa, Subash , Tlaye, Kenean Getaneh , Topór-Mądry, Roman , Tovani‐Palone, Marcos Roberto , Traini, Eugenio , Tran, Khanh Bao , Tsadik, Afewerki Gebremeskel , Ullah, Irfan , Vaezi, Maryam, Pérez, Patricia Varona , Vidale, Simone , Violante, Francesco Saverio , Vollset, Stein Emil, Vos, Theo , Vosoughi, Kia , Vu, Giang Thu , Vujcic, Isidora S , Wabinga, Henry, Wachamo, Tesfahun Mulatu , Wagnew, Fasil Shiferaw, Waheed, Yasir , Weldegebreal, Fitsum , Weldesamuel, Girmay Teklay, Wijeratne, Tissa , Wonde, Tewodros Eshete , Workie, Hailemariam Mekonnen , Yadav, Rajaram , Yadegar, Abbas , Yadollahpour, Ali , Yaseri, Mehdi , Yazdi‐Feyzabadi, Vahid , Yeshaneh, Alex , Yimam, Mohammed , Yisma, Engida , Younis, Mustafa Z , Zadnik, Vesna, Moghadam, Telma Zahirian , Zandian, Hamed , Zangeneh, Alireza , Zaki, Leila , Zendehdel, Kazem , Zenebe, Zerihun Menlkalew, Zewale, Taye Abuhay , Ziapour, Arash , Zodpey, Sanjay , Murray, Christopher J L , Topór‐Mądry, Roman , Deribe, Kebede , Teklay, Girmay , Wijeratne, T , Kumar, Vivek , Lazarus, Jeffrey V , Brenner, Hermann , Farzadfar, Farshad , Islam, Sheikh Mohammed Shariful , Assadi, Reza , Rahman, Muhammad Aziz , Abd-Allah, Foad , Abdel-Rahman, Omar Mohammed , Abdollahpour, Ibrahim , Abu-Raddad, Laith Jamal , Ahmadian, Elham , Ahmadpour, Ehsan , Akinyemiju, Tomi , Al‐Aly, Ziyad , Alemnew, Birhan , Alinia, Cyrus , Aljunid, Syed Mohamed , Almasi‐Hashiani, Amir , Amini, Erfan , Amini, Saeed, Amoako, Yaw Ampem , Arab-Zozani, Morteza , Asayesh, Hamid , Fasil, Alebachew , Ataeinia, Bahar , Ausloos, Marcel , Balouchi, Abbas , Behzadifar, Masoud , Behzadifar, Meysam, Bekele, Bayu Begashaw , Belayneh, Yaschilal Muche , Birungi, Charles , Bleyer, Archie , Bosetti, Cristina , Carrero, Juan Jesús , Chaturvedi, Pankaj , Chehrazi, Mohammad , Constantin, María Magdalena , Crocetti, Emanuele , Daryani, Ahmad , Neves, José das , Demeke, Feleke Mekonnen , Demis, Asmamaw , Denova‐Gutiérrez, Edgar , Deribe, Kalkidan Solomon, Desta, Melaku , Dharmaratne, Samath Dhamminda , Doku, David Teye , Dubey, Manisha , Ebrahimi, Hedyeh , Sayed, Iman El , Zaki, Maysaa El Sayed , Adane, Daniel, Omrani, Vahid Fallah , Faramarzi, Mahbobeh , Farhangi, Mahdieh Abbasalizad , Farioli, Andrea , Filip, Irina , Foroutan, Masoud , Tsegaye, Reta , Gelaw, Belayneh K., Gill, Paramjit Singh , Gupta, Rahul, Haro, Josep María , Hay, Roderick J. , Henry, Nathaniel J , Hidru, Hagos Degefa , Horita, Nobuyuki , Hosgood, H. Dean, Hostiuc, Mihaela, Hussen, Mohammedaman Mama, Islami, Farhad , Jahani, Mohammad Ali , Jakovljević, Mihajlo , Javanbakht, Mehdi , Jee, Sun Ha , Jenabi, Ensiyeh , Jonnagaddala, Jitendra, Jungari, Suresh Banayya , Kabir, Ali , Karch, André , Kassa, Tesfaye , Kerbo, Amene Abebe , Khang, Young-Ho, Khatab, Khaled , Khazaei, Salman , Khoja, Abdullah T , Kim, Yun Jin , Kissimova‐Skarbek, Katarzyna , Koyanagi, Ai , Vecchia, Carlo La , Lal, Dharmesh Kumar, Lauriola, Paolo , Lopez, Alan D , Magdeldin, Sameh , Maleki, Afshin , Malekzadeh, Reza , Manamo, Wondimu Ayele, Mansourian, Morteza , Mansournia, Mohammad Alì , Maroufizadeh, Saman , Mathur, Manu Raj , McKee, Martin , Mehta, Varshil , Meier, Toni , Melaku, Yohannes Adama , Melese, Addisu Dagnaw , Meštrović, Tomislav , Mulatu, Kebadnew , Mirzaei, Hamed , Mirzaei, Hamid Reza , Mohammad, Dara K., Darwesh, Aso Mohammad , Mohammadbeigi, Abolfazl , Mohammadi, Hiwa , Mohammadi, Moslem, Mohammadpourhodki, Reza , Moradi‐Lakeh, Maziar , Morisaki, Naho , Morrison, Shane D. , Nahvijou, Azin , Najafi, Farid , Naldi, Luigi , Nasiri, Naser , Newcomb, Polly A. , Nojomi, Marzieh , Nosratnejad, Shirin , Oh, In‐Hwan , Oren, Eyal , Ota, Erika , Owolabi, Mayowa , Parsian, Hadi , Pashaei, Tahereh , Pereira, David M. , Pishgar, Farhad , Pourjafar, Hadi , Prasad, Narayan , Qorbani, Mostafa , Rabiee, Mohammad , Rana, Saleem M., Rawaf, Salman , Rezaei, Nima , Ronfani, Luca , Roshandel, Gholamreza , Saad, Ragy , Sabbagh, Parisa, Sabour, Siamak , Sahebkar, Amirhossein , Sayyah, Mehdi , Schneider, Ione Jayce Ceola , Schöttker, Ben , Šekerija, Mario , Sepanlou, Sadaf Ghajarieh , Sepehrimanesh, Masood , Sharafi, Heidar , Sharif, Mehdi , Sharma, Rajesh , Sheikh, Aziz , Silveira, Dayane Gabriele Alves , Singh, Jasvinder A. , Sitas, Freddy , Tamtaji, Omid Reza , Tehrani‐Banihashemi, Arash , Tesfay, Berhe Etsay , Teshale, Manaye Yihune, Tran, Bach Xuan , Uthman, Olalekan Abdulrahman , Vacante, Marco , Vaezi, Maryam, Veisani, Yousef , Vlassov, Vasily , Vollset, Stein Emil, Wagnew, Fasil , Wondafrash, Dawit Zewdu , Wondmieneh, Adam Belay , Yimer, Ebrahim M , Yonemoto, Naohiro , Yousefi, Bahman , Yousefifard, Mahmoud , Yu, Chuanhua , Zabeh, Erfan , Zaidi, Zoubida , Zamani, Mohammad , Olagunju, Andrew T , Bhakta, Nickhill , Desai, Rupak , Alahdab, Fares , Rahim, Fakher

JAMA Oncology | September 27, 2019 | Volume: 5 | Issue: 12 | Pages: 1749

10.1001/jamaoncol.2019.2996 | PMID 31560378 Get It

Adenoviral gene transfer of a single‐chain IL‐23 induces psoriatic arthritis–like symptoms in NOD mice
Flores, Rafael R. , Carbo, Lana, Meter, Montina Van, Padilla, Consuelo M. López de , Zhao, Jing , Colangelo, Debora , Yousefzadeh, Negar , Angelini, Luise, Zhang, Lei , Pola, Enrico , Evans, Christopher H. , Gambotto, Andrea , Niedernhofer, Laura J. , Robbins, Paul D. , De Padilla, Consuelo M Lopez, Niedernhofer, Laura J , Robbins, Paul D , Zhang, Lei , Kim, Eun Young , Yousefzadeh, Matthew J., Vo, Nam

The FASEB Journal | June 6, 2019 | Volume: 33 | Issue: 8 | Pages: 9505-9515

10.1096/fj.201900420r | PMID 31170010 Get It

ABSTRACT Previously, we demonstrated that intratumoral delivery of adenoviral vector encoding single‐chain (sc) IL‐23 (Ad.scIL‐23) was able to induce systemic antitumor immunity. Here, we examined the role of IL‐23 in diabetes in nonobese diabetic mice. Intravenous delivery of Ad.scIL‐23 did not accelerate the onset of hyperglycemia but instead resulted in the development of psoriatic arthritis. Ad.scIL‐23–treated mice developed erythema, scales, and thickening of the skin, as well as intervertebral disc degeneration and extensive synovial hypertrophy and loss of articular cartilage in the knees. Immunological analysis revealed activation of conventional T helper type 17 cells and IL‐17–producing γδ T cells along with a significant depletion and suppression of T cells in the pancreatic lymph nodes. Furthermore, treatment with anti–IL‐17 antibody reduced joint and skin psoriatic arthritis pathologies. Thus, these Ad.scIL‐23–treated mice represent a physiologically relevant model of psoriatic arthritis for understanding disease progression and for testing therapeutic approaches.—Flores, R. R., Carbo, L., Kim, E., Van Meter, M., De Padilla, C. M. L., Zhao, J., Colangelo, D., Yousefzadeh, M. J., Angelini, L. A., Zhang, L., Pola, E., Vo, N., Evans, C. H., Gambotto, A., Niedernhofer, L. J., Robbins, P. D. Adenoviral gene transfer of a single‐chain IL‐23 induces psoriatic arthritis–like symptoms in NOD mice. FASEB J. 33, 9505–9515 (2019). www.fasebj.org
Accurate Precursor Mass Assignment Improves Peptide Identification in Data-Independent Acquisition Mass Spectrometry
Nam, Dowoon , Kim, Hokeun , Pandey, Akhilesh , Lee, Sang‐Won , Pandey, Akhilesh , Lee, Sang-Won , Mun, Dong‐Gi

Analytical Chemistry | June 3, 2019 | Volume: 91 | Issue: 13 | Pages: 8453-8460

10.1021/acs.analchem.9b01474 | PMID 31247731 Get It

Phase 1 study of selinexor plus carfilzomib and dexamethasone for the treatment of relapsed/refractory multiple myeloma
Jakubowiak, Andrzej , Jasielec, Jagoda, Rosenbaum, Cara A. , Cole, Craig E. , Chari, Ajai , Nam, Jennifer, McIver, Amanda, Severson, Erica, Stephens, Leonor A, Tinari, Kathryn M., Rosebeck, Shaun , Zimmerman, Todd M., Hycner, Tyler, Turowski, Agata, Karrison, Theodore, Zonder, Jeffrey A. , Jakubowiak, Andrzej J , Mıkhael, Joseph , Zonder, Jeffrey A , Chari, Ajai

British Journal of Haematology | May 24, 2019 | Volume: 186 | Issue: 4 | Pages: 549-560

10.1111/bjh.15969 | PMID 31124580 Get It

SummarySelinexor, an oral Selective Inhibitor of Nuclear Export, targets Exportin 1 (XPO1, also termed CRM1). Non‐clinical studies support combining selinexor with proteasome inhibitors (PIs) and corticosteroids to overcome resistance in relapsed/refractory multiple myeloma (RRMM). We conducted a phase I dose‐escalation trial of twice‐weekly selinexor in combination with carfilzomib and dexamethasone (SKd) to determine maximum tolerated dose in patients with RRMM (N = 21), with an expansion cohort to assess activity in carfilzomib‐refractory disease and identify a recommended phase II dose (RP2D). During dose escalation, there was one dose‐limiting toxicity (cardiac failure). The RP2D of twice‐weekly SKd was selinexor 60 mg, carfilzomib 20/27 mg/m2 and dexamethasone 20 mg. The most common grade 3/4 treatment‐emergent adverse events included thrombocytopenia (71%), anaemia (33%), lymphopenia (33%), neutropenia (33%) and infections (24%). Rates of ≥minimal response, ≥partial response and very good partial response were 71%, 48% and 14%, respectively; similar response outcomes were observed for dual‐class refractory (PI and immunomodulatory drug)/quad‐exposed (carfilzomib, bortezomib, lenalidomide and pomalidomide) patients (n = 17), and patients refractory to carfilzomib in last line of therapy (n = 13). Median progression‐free survival was 3·7 months, and overall survival was 22·4 months in the overall population. SKd was tolerable and re‐established disease control in RRMM patients, including carfilzomib‐refractory patients.Registered at ClinicalTrials.gov (NCT02199665)
Cell-level somatic mutation detection from single-cell RNA sequencing
Vu, Trung Nghia , Nguyen, Ha-Nam, Calza, Stefano , Wang, Liewei , Kalari, Krishna R. , Pawitan, Yudi

Bioinformatics | April 17, 2019 | Volume: 35 | Issue: 22 | Pages: 4679-4687

10.1093/bioinformatics/btz288 | PMID 31028395 Get It

Abstract Motivation Both single-cell RNA sequencing (scRNA-seq) and DNA sequencing (scDNA-seq) have been applied for cell-level genomic profiling. For mutation profiling, the latter seems more natural. However, the task is highly challenging due to the limited input materials from only two copies of DNA molecules, while whole-genome amplification generates biases and other technical noises. ScRNA-seq starts with a higher input amount, so generally has better data quality. There exists various methods for mutation detection from DNA sequencing, it is not clear whether these methods work for scRNA-seq data. Results Mutation detection methods developed for either bulk-cell sequencing data or scDNA-seq data do not work well for the scRNA-seq data, as they produce substantial numbers of false positives. We develop a novel and robust statistical method—called SCmut—to identify specific cells that harbor mutations discovered in bulk-cell data. Statistically SCmut controls the false positives using the 2D local false discovery rate method. We apply SCmut to several scRNA-seq datasets. In scRNA-seq breast cancer datasets SCmut identifies a number of highly confident cell-level mutations that are recurrent in many cells and consistent in different samples. In a scRNA-seq glioblastoma dataset, we discover a recurrent cell-level mutation in the PDGFRA gene that is highly correlated with a well-known in-frame deletion in the gene. To conclude, this study contributes a novel method to discover cell-level mutation information from scRNA-seq that can facilitate investigation of cell-to-cell heterogeneity. Availability and implementation The source codes and bioinformatics pipeline of SCmut are available at https://github.com/nghiavtr/SCmut. Supplementary information Supplementary data are available at Bioinformatics online.
Core‐binding factor acute myeloid leukemia with t(8;21): Risk factors and a novel scoring system (I‐CBFit)
Üstün, Celalettin , Pullarkat, Sheeja T. , Yeung, Cecilia C.S. , Broesby‐Olsen, Sigurd , Ohgami, Robert S. , Kim, Young , Vestergaard, Hanne , Chen, Dong , Kluin, Philip M., Dolan, Michelle, Mrózek, Krzysztof , Czuchlewski, David R., Horny, Hans‐Peter, George, Tracy I. , Kristensen, Thomas Kielsgaard , Ku, Nam K., Yi, Cecilia Arana , Møller, Michael , Marcucci, Guido , Hilberink, Jacobien R. , Pullarkat, Vinod , Shanley, Ryan , Kohlschmidt, Jessica, Coulombe, Janie , Salhotra, Amandeep , Soma, Lori , Cho, Christina , Hoermann, Gregor , Nakamura, Ryo , Deeg, Joachim, Bloomfield, Clara D. , Weisdorf, Daniel J. , Litzow, Mark R. , Valent, Peter , Huls, Gerwin , Yeung, Cecilia , Baughn, Linda, Chen, Dong , Møller, Michael Boe , Weisdorf, Dan , George, Tracy I , Arana Yi, Cecilia , Valent, Peter , Morgan, Elizabeth A. , Moodie, Erica E. M. , Sperr, Wolfgang R. , Baughn, Linda B. , Schiefer, Ana-Iris , Linden, Michael A. , Akin, Cem , Gotlib, Jason , Hornick, Jason L. , Nakamura, Ryo, Perales, Miguel‐Angel , Borthakur, Gautam

Cancer Medicine | August 17, 2018 | Volume: 7 | Issue: 9 | Pages: 4447-4455

10.1002/cam4.1733 | PMID 30117318 Get It

AbstractBackgroundAlthough the prognosis of core‐binding factor (CBF) acute myeloid leukemia (AML) is better than other subtypes of AML, 30% of patients still relapse and may require allogeneic hematopoietic cell transplantation (alloHCT). However, there is no validated widely accepted scoring system to predict patient subsets with higher risk of relapse.MethodsEleven centers in the US and Europe evaluated 247 patients with t(8;21)(q22;q22).ResultsComplete remission (CR) rate was high (92.7%), yet relapse occurred in 27.1% of patients. A total of 24.7% of patients received alloHCT. The median disease‐free (DFS) and overall (OS) survival were 20.8 and 31.2 months, respectively. Age, KIT D816V mutated (11.3%) or nontested (36.4%) compared with KIT D816V wild type (52.5%), high white blood cell counts (WBC), and pseudodiploidy compared with hyper‐ or hypodiploidy were included in a scoring system (named I‐CBFit). DFS rate at 2 years was 76% for patients with a low‐risk I‐CBFit score compared with 36% for those with a high‐risk I‐CBFit score (P < 0.0001). Low‐ vs high‐risk OS at 2 years was 89% vs 51% (P < 0.0001).ConclusionsI‐CBFit composed of readily available risk factors can be useful to tailor the therapy of patients, especially for whom alloHCT is not need in CR1 (ie, patients with a low‐risk I‐CBFit score).