Also published as: A Ram Kim, Ae-Jung Kim, Ah-Ram Kim, Albert H Kim, Alison J Kim, Andrea J Kim, Angela H Kim, Angela Kim, Angela S Kim, Anna Kim, Anthony S Kim, Aram Kim, Arie Kim, B T Kim, B-Y Kim, Baek Kim, Beom-Jun Kim, Beomsoo Kim, Beomsu Kim, Bo Ri Kim, Bo Young Kim, Bo-Eun Kim, Bo-Ra Kim, Bo-Rahm Kim, Bomi Kim, Bong-Jo Kim, Bongjun Kim, Boo-Young Kim, Borahm Kim, Boram Kim, Brandon J Kim, Brian S Kim, Byeong-Won Kim, Byoung Jae Kim, Byron Kim, Byung Guk Kim, Byung Jin Kim, Byung-Chul Kim, Byung-Gyu Kim, Byung-Taek Kim, Byungwook Kim, C H Kim, Carla F Kim, Caroline Kim, Cecilia E Kim, Cecilia Kim, Chae-Hyun Kim, Chan Wook Kim, Chan-Duck Kim, Chan-Hee Kim, Chan-Wha Kim, Chang Seong Kim, Chang-Gu Kim, Chang-Yub Kim, Chanhee Kim, Cheol-Hee Kim, Cheol-Su Kim, Cheorl-Ho Kim, Choel Kim, Chong Ae Kim, Chong Kook Kim, Chongtae Kim, Choon Ok Kim, Choon-Song Kim, Chu-Young Kim, Chul Hoon Kim, Chul Hwan Kim, Chul-Hong Kim, Chunki Kim, D-W Kim, Da Sol Kim, Da-Hyun Kim, Da-Sol Kim, Dae Hyun Kim, Dae In Kim, Dae Keun Kim, Dae-Eun Kim, Dae-Jin Kim, Dae-Kyeong Kim, Dae-Kyum Kim, Dae-Soo Kim, Daeeun Kim, Daegyeom Kim, Daeseung Kim, Daesik Kim, Daham Kim, Dahee Kim, Dakyung Kim, Dan Say Kim, David E Kim, Dayoung Kim, Dennis Y Kim, Deok Ryong Kim, Deok-Ho Kim, Deokhoon Kim, Do Hyung Kim, Do Yeon Kim, Do-Hyung Kim, Do-Kyun Kim, Dokyoon Kim, Don-Kyu Kim, Dong Gwang Kim, Dong Ha Kim, Dong Hyun Kim, Dong Il Kim, Dong Joon Kim, Dong Wook Kim, Dong-Eun Kim, Dong-Hee Kim, Dong-Hoon Kim, Dong-Hyeok Kim, Dong-Hyun Kim, Dong-Ik Kim, Dong-Kyu Kim, Dong-Seok Kim, Dong-Wook Kim, Dong-Yi Kim, Dong-il Kim, Donghee Kim, Donghyeon Kim, Donghyun Kim, Dongjoon Kim, Dongkyun Kim, Dongwoo Kim, Doo Yeon Kim, Doo Yeong Kim, Doyeon Kim, Duck-Hee Kim, E Kim, E-S Kim, Edwin H Kim, Eiru Kim, Elizabeth H Kim, Ellen Kim, Eonmi Kim, Eosu Kim, Eric Eunshik Kim, Eric Kim, Esl Kim, Esther Kim, Eui Hyun Kim, Eui Jin Kim, Eui-Soon Kim, Eun Hee Kim, Eun Ho Kim, Eun Ji Kim, Eun Kim, Eun Young Kim, Eun-Jin Kim, Eun-Joo Kim, Eun-Jung Kim, Eun-Kyung Kim, Eunae Kim, Eung Yeop Kim, Eung-Gook Kim, Eungseok Kim, Eunha Kim, Eunhyun Kim, Eunjoon Kim, Eunju Kim, Eunkyeong Kim, Eunmi Kim, Gahyun Kim, Geun-Young Kim, Gi Beom Kim, Gibae Kim, Gitae Kim, Go Woon Kim, Goo-Young Kim, Goun Kim, Grace Kim, Gu-Hwan Kim, Gukhan Kim, Gunhee Kim, Gwang Sik Kim, Gwangil Kim, Gye Lim Kim, Gyeonghun Kim, Gyudong Kim, H Kim, H S Kim, Ha-Jung Kim, Ha-Neui Kim, Hae Won Kim, Haein Kim, Haelee Kim, Haeryoung Kim, Hail Kim, Han Gyung Kim, Han Young Kim, Han-Kyul Kim, Hana Kim, Hanah Kim, Hang-Rai Kim, Hannah Kim, Hark Kyun Kim, Hee Jeong Kim, Hee Jin Kim, Hee Jong Kim, Hee Nam Kim, Hee Su Kim, Hee Young Kim, Hee-Jin Kim, Hee-Sun Kim, Heebal Kim, Heegoo Kim, Heejin Kim, Hei Sung Kim, Helen B Kim, Helen Kim, Heung-Joong Kim, Ho Shik Kim, Ho-Sook Kim, Hoguen Kim, Hong Sug Kim, Hong-Gi Kim, Hong-Hee Kim, Hong-Kook Kim, Hong-Kyu Kim, Hoon Kim, Hoon Seok Kim, Howard H Kim, Hwa-Jung Kim, Hwajung Kim, Hwi Seung Kim, Hwijin Kim, Hye Jin Kim, Hye Ran Kim, Hye Ree Kim, Hye Young Kim, Hye Yun Kim, Hye-Jin Kim, Hye-Jung Kim, Hye-Ran Kim, Hye-Sung Kim, Hye-Yeon Kim, Hye-Young H Kim, Hyejin Kim, Hyelim Kim, Hyemin Kim, Hyeon Ho Kim, Hyeon Jeong Kim, Hyeon-Ah Kim, Hyeong Hoe Kim, Hyeong Su Kim, Hyeong-Geug Kim, Hyeong-Jin Kim, Hyeong-Rok Kim, Hyeong-Taek Kim, Hyeonwoo Kim, Hyeseon Kim, Hyesung Kim, Hyeung-Rak Kim, Hyeyoon Kim, Hyeyoung Kim, Hyo Jong Kim, Hyo Jung Kim, Hyo-Soo Kim, Hyojin Kim, Hyojung Kim, Hyoun Ju Kim, Hyoun-Ah Kim, Hyoung Kyu Kim, Hyuk Soon Kim, Hyun Eun Kim, Hyun Gi Kim, Hyun Joon Kim, Hyun Ju Kim, Hyun Kim, Hyun Sil Kim, Hyun Soo Kim, Hyun Sook Kim, Hyun-Ji Kim, Hyun-Jin Kim, Hyun-Jung Kim, Hyun-Kyong Kim, Hyun-Sic Kim, Hyun-Soo Kim, Hyun-Yi Kim, Hyun-Young Kim, Hyun-ju Kim, Hyunbae Kim, Hyung Bum Kim, Hyung Hoi Kim, Hyung Min Kim, Hyung Yoon Kim, Hyung-Goo Kim, Hyung-Gu Kim, Hyung-Jun Kim, Hyung-Mi Kim, Hyung-Ryong Kim, Hyung-Seok Kim, Hyung-Sik Kim, Hyung-Suk Kim, Hyungjun Kim, Hyungkuen Kim, Hyungsoo Kim, Hyunjin Kim, Hyunjoon Kim, Hyunju Kim, Hyunki Kim, Hyunmi Kim, Hyunsoo Kim, Hyunwoo Kim, Hyunwook Kim, Hyunyoung Kim, Ick Young Kim, Il-Chan Kim, Il-Man Kim, Il-Sup Kim, In Ja Kim, In Joo Kim, In Kyoung Kim, In Su Kim, In Suk Kim, In-Hoo Kim, J H Kim, J Julie Kim, J Y Kim, Jae Bum Kim, Jae Geun Kim, Jae Gon Kim, Jae Hoon Kim, Jae Hun Kim, Jae Hyoung Kim, Jae Hyun Kim, Jae Seon Kim, Jae Suk Kim, Jae T Kim, Jae-Ick Kim, Jae-Jun Kim, Jae-Jung Kim, Jae-Min Kim, Jae-Ryong Kim, Jae-Yong Kim, Jae-Yoon Kim, Jae-Young Kim, Jaegil Kim, Jaehoon Kim, Jaemi Kim, Jaeuk U Kim, Jaewon Kim, Jaeyeon Kim, Jaeyoon Kim, Jang Heub Kim, Jang-Hee Kim, Jason K Kim, Jason Kim, Jayoun Kim, Jee Ah Kim, Jeeho Kim, Jeewoo Kim, Jeeyoung Kim, Jeffrey J Kim, Jeffrey Kim, Jenny H Kim, Jeong Hee Kim, Jeong Kyu Kim, Jeong Su Kim, Jeong-Han Kim, Jeong-Min Kim, Jeonghan Kim, Jeongseon Kim, Jeongseop Kim, Jeri Kim, Jessica Kim, Jewoo Kim, Ji Eun Kim, Ji Hun Kim, Ji Hye Kim, Ji Hyun Kim, Ji Won Kim, Ji Yeon Kim, Ji Young Kim, Ji-Dam Kim, Ji-Eun Kim, Ji-Hoon Kim, Ji-Man Kim, Ji-Won Kim, Ji-Woon Kim, Ji-Young Kim, Ji-Yul Kim, Ji-Yun Kim, Jieun Kim, Jiha Kim, Jiho Kim, Jihoon Kim, Jihye Kim, Jihyun Kim, Jimi Kim, Jin Cheon Kim, Jin Gyeom Kim, Jin Hee Kim, Jin Kim, Jin Kyong Kim, Jin Man Kim, Jin Seok Kim, Jin Won Kim, Jin Woo Kim, Jin Young Kim, Jin-Chul Kim, Jin-Soo Kim, Jina Kim, Jinhee Kim, Jinho Kim, Jinkyeong Kim, Jinsoo Kim, Jinsu Kim, Jinsup Kim, Jisook Kim, Jisu Kim, Jisun Kim, Jisup Kim, Jiwon Kim, Jiyea Kim, Jiyeon Kim, Jong Deog Kim, Jong Geun Kim, Jong Han Kim, Jong Heon Kim, Jong Ho Kim, Jong Hwan Kim, Jong Won Kim, Jong Woo Kim, Jong Yeol Kim, Jong-Ho Kim, Jong-Hyun Kim, Jong-Il Kim, Jong-Joo Kim, Jong-Ki Kim, Jong-Kyu Kim, Jong-Oh Kim, Jong-Seo Kim, Jong-Seok Kim, Jong-Won Kim, Jong-Yeon Kim, Jong-Youn Kim, JongKyong Kim, Jongchan Kim, Jonggeol J Kim, Jonggeol Jeffrey Kim, Jongho Kim, Jongkyu Kim, Jongmyung Kim, Jongwan Kim, Jooho Kim, Joon Kim, Joong Sun Kim, Joong-Seok Kim, Joonki Kim, Joonseok Kim, Joonyoung Kim, Joonyoung R Kim, Joori Kim, Joseph C Kim, Joseph Han Sol Kim, Joung Sug Kim, Joungmok Kim, Ju Deok Kim, Ju Han Kim, Ju Young Kim, Ju-Kon Kim, Ju-Ryoung Kim, Ju-Wan Kim, Juhyun Kim, Jun Chul Kim, Jun Hee Kim, Jun Hoe Kim, Jun Pyo Kim, Jun Seok Kim, Jun Suk Kim, Jun W Kim, Jun-Hyung Kim, Jun-Mo Kim, Jun-Sik Kim, June Hee Kim, June Soo Kim, June-Bum Kim, Junesun Kim, Jung Dae Kim, Jung H Kim, Jung Hee Kim, Jung Ho Kim, Jung Ki Kim, Jung Oh Kim, Jung Soo Kim, Jung Sun Kim, Jung-Ha Kim, Jung-Hyun Kim, Jung-In Kim, Jung-Lye Kim, Jung-Taek Kim, Jung-Woong Kim, JungMin Kim, Jungeun Kim, Jungsu Kim, Jungwoo Kim, Juyeong Kim, Juyong B Kim, Juyoung Kim, K-K Kim, K-S Kim, Kahye Kim, Kang Ho Kim, Kangjoon Kim, Kee-Pyo Kim, Kee-Tae Kim, Kellan Kim, Keun You Kim, Kevin K Kim, Ki Hyun Kim, Ki Kwon Kim, Ki Tae Kim, Ki Woong Kim, Kil-Nam Kim, Kiyoung Kim, Kook Hwan Kim, Kwan Hyun Kim, Kwan-Suk Kim, Kwang Dong Kim, Kwang Pyo Kim, Kwang-Eun Kim, Kwang-Pyo Kim, Kwangho Kim, Kwangwoo Kim, Kwonseop Kim, Kye Hun Kim, Kye Hyun Kim, Kye-Seong Kim, Kyeong Jin Kim, Kyeong-Min Kim, Kyeongjin Kim, Kyeongmi Kim, Kyong Min Kim, Kyong-Tai Kim, Kyoung Hoon Kim, Kyoung Hwan Kim, Kyoung Oh Kim, Kyoungtae Kim, Kyu-Kwang Kim, Kyuho Kim, Kyung An Kim, Kyung Do Kim, Kyung Han Kim, Kyung Hee Kim, Kyung Mee Kim, Kyung Sup Kim, Kyung Woo Kim, Kyung-Chang Kim, Kyung-Hee Kim, Kyung-Sub Kim, Kyung-Sup Kim, Kyunga Kim, Kyunggon Kim, Kyungjin Kim, Kyungsook Kim, Kyungtae Kim, Kyungwon Kim, Leen Kim, Leo A Kim, Leo Kim, Lia Kim, Luke Y Kim, M J Kim, M Kim, M V Kim, Maya Kim, Meelim Kim, Meesun Kim, Mi Jeong Kim, Mi Kyung Kim, Mi Ok Kim, Mi Ra Kim, Mi Young Kim, Mi-Hyun Kim, Mi-Na Kim, Mi-Sung Kim, Mi-Yeon Kim, Mi-Young Kim, Mijeong Kim, Mijung Kim, Min Bum Kim, Min Cheol Kim, Min Chul Kim, Min Joo Kim, Min Ju Kim, Min Jung Kim, Min Kim, Min Kyeong Kim, Min Seo Kim, Min Soo Kim, Min Wook Kim, Min-A Kim, Min-Gon Kim, Min-Hyun Kim, Min-Seo Kim, Min-Seon Kim, Min-Sik Kim, Min-Sun Kim, Min-Young Kim, Mina K Kim, Minah Kim, Minchul Kim, Minhee Kim, Minjae Kim, Minjeong Kim, Minji Kim, Minjoo Kim, Minju Kim, Minkyeong Kim, Minkyung Kim, Minseon Kim, Minsik Kim, Minsoon Kim, Minsu Kim, Minsuk Kim, Miri Kim, Miso Kim, Misu Kim, Misun Kim, Misung Kim, Moo-Yeon Kim, Moon Suk Kim, Myeong Ji Kim, Myeong Ok Kim, Myeong-Kyu Kim, Myeoung Su Kim, Myoung Hee Kim, Myoung Ok Kim, Myoung Sook Kim, Myung Jin Kim, Myung-Jin Kim, Myung-Sun Kim, Myung-Sunny Kim, Myungshin Kim, Myungsuk Kim, Na Yeon Kim, Na-Kuang Kim, Na-Young Kim, Nam Hee Kim, Nam-Eun Kim, Nam-Ho Kim, Nam-Hyung Kim, NamDoo Kim, NamHee Kim, Namkyoung Kim, Namphil Kim, Nan Young Kim, Nari Kim, Ngoc Thanh Kim, Ngoc-Thanh Kim, Oc-Hee Kim, Oh Yoen Kim, Ohn Soon Kim, Ok Jin Kim, Ok-Hwa Kim, Ok-Hyeon Kim, Ok-Kyung Kim, Okhwa Kim, Paul H Kim, Paul Kim, Paul T Kim, Peter K Kim, Reuben H Kim, Richard B Kim, Richard Kim, Rokki Kim, Rosalind Kim, Ryung S Kim, S Kim, S Y Kim, Sae Hun Kim, Saerom Kim, Sang Chan Kim, Sang Eun Kim, Sang Geon Kim, Sang Hyuk Kim, Sang Jin Kim, Sang Ryong Kim, Sang Soo Kim, Sang Wun Kim, Sang-Gun Kim, Sang-Hoon Kim, Sang-Min Kim, Sang-Tae Kim, Sang-Woo Kim, Sang-Young Kim, Sangchul Kim, Sangmi Kim, Sangsoo Kim, Sangwoo Kim, Scott Y H Kim, Se Hyun Kim, Se-Wha Kim, Sejoong Kim, Seohyeon Kim, Seohyun Kim, Seok Won Kim, Seokhwi Kim, Seokjoong Kim, Seol-A Kim, Seon Hee Kim, Seon Hwa Kim, Seon-Kyu Kim, Seon-Young Kim, Seong Jun Kim, Seong Kim, Seong-Hyun Kim, Seong-Ik Kim, Seong-Jin Kim, Seong-Min Kim, Seong-Seop Kim, Seong-Tae Kim, Seonggon Kim, Seongho Kim, Seongmi Kim, Seonhee Kim, Seoyeon Kim, Seoyoung Kim, Serim Kim, Seul Young Kim, Seul-Ki Kim, Seulhee Kim, Seung Chul Kim, Seung Jun Kim, Seung Tea Kim, Seung Won Kim, Seung Woo Kim, Seung-Jin Kim, Seung-Ki Kim, Seung-Whan Kim, Seungsoo Kim, Sewoon Kim, Shi-Mun Kim, Shin Kim, Sin Gon Kim, Sinai Kim, So Ree Kim, So Yeon Kim, So Young Kim, So-Hee Kim, So-Woon Kim, So-Yeon Kim, Soee Kim, Soeun Kim, Sohee Kim, Sol Kim, Song-Rae Kim, Soo Hyun Kim, Soo Jung Kim, Soo Wan Kim, Soo Whan Kim, Soo Yoon Kim, Soo Young Kim, Soo-Hyun Kim, Soo-Rim Kim, Soo-Youl Kim, SooHyeon Kim, Sook Young Kim, Soon Hee Kim, Soon Sun Kim, Soon-Hee Kim, Soriul Kim, Soung Jung Kim, Sowon Kim, Soyeong Kim, Steve Kim, Stuart K Kim, Su Jin Kim, Su Kang Kim, Su-Hyeong Kim, Su-Jeong Kim, Su-Jin Kim, Su-Yeon Kim, Suhyun Kim, Suhyung Kim, Suji Kim, Sujin Kim, Sujung Kim, Suk Jae Kim, Suk-Jeong Kim, Suk-Kyung Kim, Sukjun Kim, Sun Hee Kim, Sun Hye Kim, Sun Woong Kim, Sun Yeou Kim, Sun-Gyun Kim, Sun-Hee Kim, Sun-Hong Kim, Sun-Joong Kim, Sung Eun Kim, Sung Han Kim, Sung Hyun Kim, Sung Kyun Kim, Sung Mok Kim, Sung Soo Kim, Sung Tae Kim, Sung Won Kim, Sung Woo Kim, Sung Yeol Kim, Sung Young Kim, Sung-Bae Kim, Sung-Eun Kim, Sung-Hee Kim, Sung-Hoon Kim, Sung-Hou Kim, Sung-Jo Kim, Sung-Kyu Kim, Sung-Mi Kim, Sung-Wan Kim, Sunggun Kim, Sunghak Kim, Sunghoon Kim, Sunghun Kim, Sunghwan Kim, Sungjoo Kim, Sungmin Kim, Sungrae Kim, Sungryong Kim, Sungup Kim, Sungyeon Kim, Sungyun Kim, Sunkyu Kim, Sunoh Kim, Sunyoung Kim, Susy Kim, Sydney Y Kim, Tae Hoen Kim, Tae Hoon Kim, Tae Hun Kim, Tae Hyun Kim, Tae Il Kim, Tae Jin Kim, Tae Min Kim, Tae Wan Kim, Tae-Eun Kim, Tae-Gyu Kim, Tae-Hyoung Kim, Tae-Hyun Kim, Tae-Mi Kim, Tae-Min Kim, Tae-Woon Kim, Tae-You Kim, TaeHyung Kim, TaeYeong Kim, Taeeun Kim, Taehyeung Kim, Taehyoun Kim, Taeil Kim, Taejung Kim, Taek-Kyun Kim, Taek-Yeong Kim, Taewan Kim, Taeyoung Kim, Tai Kyoung Kim, Un Gi Kim, Un-Kyung Kim, Vladimir Kim, Wanil Kim, William Kim, Won Dong Kim, Won Ho Kim, Won J Kim, Won Jeoung Kim, Won Kim, Won Kon Kim, Won Kyung Kim, Won Seok Kim, Won Tae Kim, Won-Tae Kim, Wondong Kim, Woo Jin Kim, Woo Kim, Woo Kyung Kim, Woo Sik Kim, Woo-Jin Kim, Woo-Kyun Kim, Woo-Shik Kim, Woo-Yang Kim, Woojin Scott Kim, Wook Kim, Woong-Ki Kim, Woonhee Kim, Wootae Kim, Wun-Jae Kim, Y A Kim, Y S Kim, Y-D Kim, Y-M Kim, Yangseok Kim, Ye-Ri Kim, Yeaseul Kim, Yeeun Kim, Yeji Kim, Yejin Kim, Yekaterina Kim, Yeon Ju Kim, Yeon-Hee Kim, Yeon-Jeong Kim, Yeon-Jung Kim, Yeon-Ki Kim, Yeong-Sang Kim, Yeonhwa Kim, Yeonjung Kim, Yeonsoo Kim, Yerin Kim, Yeseul Kim, Yeul Hong Kim, Yo-Han Kim, Yong Deuk Kim, Yong Kwan Kim, Yong Kyun Kim, Yong Kyung Kim, Yong Sig Kim, Yong Sik Kim, Yong Sook Kim, Yong Sung Kim, Yong-Hoon Kim, Yong-Lim Kim, Yong-Ou Kim, Yong-Sik Kim, Yong-Soo Kim, Yong-Wan Kim, Yong-Woon Kim, Yongae Kim, Yonghwan Kim, Yongjae Kim, Yongkang Kim, Yongmin Kim, Yoo Ri Kim, Yoojin Kim, Yoon Sook Kim, Yoongeum Kim, Yoonjung Kim, You Sun Kim, You-Jin Kim, You-Sun Kim, Youbin Kim, Youn Shic Kim, Youn-Jung Kim, Youn-Kyung Kim, Young Eun Kim, Young Hee Kim, Young Ho Kim, Young Hun Kim, Young Hwa Kim, Young Jin Kim, Young Ju Kim, Young Mi Kim, Young Nam Kim, Young Rae Kim, Young Ree Kim, Young S Kim, Young Sam Kim, Young Sik Kim, Young Tae Kim, Young Woo Kim, Young-Bum Kim, Young-Cho Kim, Young-Chul Kim, Young-Dae Kim, Young-Eun Kim, Young-Ho Kim, Young-Hoon Kim, Young-Il Kim, Young-Im Kim, Young-Jin Kim, Young-Joo Kim, Young-Mi Kim, Young-Saeng Kim, Young-Won Kim, Young-Woo Kim, Young-Woong Kim, Young-Youn Kim, Youngchang Kim, Youngchul Kim, Youngeun Kim, Younghoon Kim, Youngjoo Kim, Youngmi Kim, Youngsin Kim, Youngsoo Kim, Youngsook Kim, Youngwoo Kim, Yu Kyeong Kim, Yu Mi Kim, Yu-Jin Kim, Yul-Ho Kim, Yuli Kim, Yumi Kim, Yun Gi Kim, Yun Hye Kim, Yun Joong Kim, Yun Seok Kim, Yun-Jin Kim, Yunjung Kim, Yunwoo Kim
As few genotype-phenotype correlations are available for nonsyndromic hereditary colorectal cancer (CRC), we implemented genomic analysis on the basis of the revised Bethesda guideline (RBG) and exten Show more
As few genotype-phenotype correlations are available for nonsyndromic hereditary colorectal cancer (CRC), we implemented genomic analysis on the basis of the revised Bethesda guideline (RBG) and extended (12 items) to verify possible subtypes. Patients with sporadic CRC (n = 249) were enrolled, stratified according to the revised Bethesda guidelines (RBG+ and RBG- groups) plus additional criteria. Exome/transcriptome analyses (n = 98) and cell-based functional assays were conducted. We detected 469 somatic and 830 germline gene mutations differing significantly between the positive and negative groups, associated with 12 RBG items/additional criteria. Twenty-one genes had significantly higher mutation rates in left, relative to right, colon cancer, while USP40, HCFC1, and HSPG2 mutation rates were higher in rectal than colon cancer. FAT4 mutation rates were lower in early-onset CRC, in contrast to increased rates in microsatellite instability (MSI)-positive tumors, potentially defining an early-onset microsatellite-stable subtype. The mutation rates of COL6A5 and MGAM2 were significantly and SETD5 was assumably, associated CRC pedigree with concurrent gastric cancer (GC). The predicted deleterious/damaging germline variants, SH2D4A rs35647122, was associated with synchronous/metachronous CRC with related tumors, while NUP160 rs381660 and KRTAP27-1 rs2244485 were potentially associated with a GC pedigree and less strictly defined hereditary CRC, respectively. SH2D4A and NUP160 acted as oncogenic facilitators. Our limited genomic analysis for RBG and additional items suggested that specific somatic alterations in the respective items may enlighten relevant pathogenesis along with the knowledge of germline mutations. Further validation is needed to indicate appropriate surveillance in suspected individuals. Show less
Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-repo Show more
Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-reported daytime napping in the UK Biobank (n = 452,633) and identify 123 loci of which 61 replicate in the 23andMe research cohort (n = 541,333). Findings include missense variants in established drug targets for sleep disorders (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Association signals are concordant with accelerometer-measured daytime inactivity duration and 33 loci colocalize with loci for other sleep phenotypes. Cluster analysis identifies three distinct clusters of nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization shows potential causal links between more frequent daytime napping and higher blood pressure and waist circumference. Show less
Autophagy is a lysosome-dependent degradation program to maintain cellular homeostasis in response to a variety of stressful conditions, such as long-lived or non-functional subcellular organelles, pr Show more
Autophagy is a lysosome-dependent degradation program to maintain cellular homeostasis in response to a variety of stressful conditions, such as long-lived or non-functional subcellular organelles, protein aggregates, nutrient limitation, and virus/bacteria infection. Accordingly, dysregulation of autophagy is closely associated with many human pathophysiological conditions, such as neurodegenerative diseases, aging, and cancer, and autophagy is highlighted as an important therapeutic target for these human diseases. In autophagy process, PIK3C3/VPS34 complex plays important roles in autophagosome biogenesis. Accumulating evidences that inhibition of PIK3C3/VPS34 complex successfully blocks autophagy make the complex as an attractive target for the development of autophagy-specific inhibitors. However, considering that various forms of PIK3C3/VPS34 complex exist and they are involved in many different cellular functions, the targeting of the pro-autophagy PIK3C3/VPS34 complex is required to specifically inhibit autophagy. To identify autophagy inhibitors targeting the pro-autophagy complex, we have performed the screening of a customized natural product library consisting of 35 herbal extracts which are widely used in the oriental medicine as anti-inflammation and/or anti-tumor reagents. We discovered that an alcoholic extract of Thuja orientalis L. leaves inhibits pro-autophagy complex formation by disrupting the interaction between autophagy-specific factor, ATG14L, and the complex core unit Vps34-Beclin 1 in vitro. Also, it inhibits the nutrient starvation induced autophagy and diminished pro-autophagy PIK3C3/VPS34 complex containing either ATG14L or UVRAG in several cell lines. Our results strongly suggest that Thuja orientalis L. leave extract functions as an autophagy-specific inhibitor not decreasing the complex activity nor the protein level, but preventing protein-protein interaction between autophagy-specific factor (ATG14L and UVRAG) and PIK3C3/VPS34 complex core unit, Vps34-Beclin 1, thereby specifically depleting the pro-autophagy complex to inhibit autophagy. Show less
Low temperature is a critical environmental factor restricting the physiology of organisms across kingdoms. In prokaryotes, cold shock induces the expression of various genes and proteins involved in Show more
Low temperature is a critical environmental factor restricting the physiology of organisms across kingdoms. In prokaryotes, cold shock induces the expression of various genes and proteins involved in cellular processes. Here, a cold-shock protein (ArCspA) from the South Pole-dwelling soil bacterium Show less
Background inflammatory status indicators have been reported as prognostic biomarkers of colorectal cancer (CRC). However, since inflammatory interactions with the colon involve various modes of actio Show more
Background inflammatory status indicators have been reported as prognostic biomarkers of colorectal cancer (CRC). However, since inflammatory interactions with the colon involve various modes of action, the biological mechanism linking inflammation and CRC prognosis has not been fully elucidated. We comprehensively evaluated the predictive roles of the expression and methylation levels of inflammation-related genes for CRC prognosis and their pathophysiological associations. An integrative analysis of 247 patients with stage I-III CRC from The Cancer Genome Atlas was conducted. Lasso-penalized Cox proportional hazards regression (Lasso-Cox) and statistical Cox proportional hazard regression (CPH) were used for the analysis. Models to predict overall survival were designed with respective combinations of clinical variables, including age, sex, stage, gene expression, and methylation. An integrative model combining expression, methylation, and clinical features performed better (median C-index = 0.756) than the model with clinical features alone (median C-index = 0.726). Based on multivariate CPH with features from the best model, the methylation levels of CEP250, RAB21, and TNPO3 were significantly associated with overall survival. They did not share any biological process in functional networks. The 5-year survival rate was 29.8% in the low methylation group of CEP250 and 79.1% in the high methylation group ( Our study results implicate the importance of integrating expression and methylation information along with clinical information in the prediction of survival. CEP250, RAB21, and TNPO3 in the prediction model might have a crucial role in CRC prognosis and further improve our understanding of potential mechanisms linking inflammatory reactions and CRC progression. Show less
Drug screening strategies focus on quantifying the phenotypic effects of different compounds on biological systems. High-throughput technologies have the potential to understand further the mechanisms Show more
Drug screening strategies focus on quantifying the phenotypic effects of different compounds on biological systems. High-throughput technologies have the potential to understand further the mechanisms by which these drugs produce the desired outcome. Reverse causal reasoning integrates existing biological knowledge and measurements of gene and protein abundances to infer their function. This approach can be employed to appraise the existing biological knowledge and data to prioritize targets for cancer therapies. We applied text mining and a manual literature search to extract known interactions between several metastasis suppressors and their regulators. We then identified the relevant interactions in the breast cancer cell line MCF7 using a knockdown dataset. We finally adopted a reverse causal reasoning approach to evaluate and prioritize pathways that are most consistent and responsive to drugs that inhibit cell growth. We evaluated this model in terms of agreement with the observations under treatment of several drugs that produced growth inhibition of cancer cell lines. In particular, we suggested that the metastasis suppressor PEBP1/RKIP is on the receiving end of two significant regulatory mechanisms. One involves RELA (transcription factor p65) and SNAI1, which were previously reported to inhibit PEBP1. The other involves the estrogen receptor (ESR1), which induces PEBP1 through the kinase NME1. Our model was derived in the specific context of breast cancer, but the observed responses to drug treatments were consistent in other cell lines. We further validated some of the predicted regulatory links in the breast cancer cell line MCF7 experimentally and highlighted the points of uncertainty in our model. To summarize, our model was consistent with the observed changes in activity with drug perturbations. In particular, two pathways, including PEBP1, were highly responsive and would be likely targets for intervention. Show less
The epithelial-mesenchymal transition (EMT) comprises an important biological mechanism not only for cancer progression but also in the therapeutic resistance of cancer cells. While the importance of Show more
The epithelial-mesenchymal transition (EMT) comprises an important biological mechanism not only for cancer progression but also in the therapeutic resistance of cancer cells. While the importance of the protein abundance of EMT-inducers, such as Snail (SNAI1) and Zeb1 (ZEB1), during EMT progression is clear, the reciprocal interactions between the untranslated regions (UTRs) of EMT-inducers via a competing endogenous RNA (ceRNA) network have received little attention. In this study, we found a synchronized transcript abundance of Snail and Zeb1 mediated by a non-coding RNA network in colorectal cancer (CRC). Importantly, the Show less
MUC4 is a predominant membrane-tethered mucin lubricating and protecting the epithelial surface and playing various biological roles in the renewal and differentiation of epithelial cells, cell signal Show more
MUC4 is a predominant membrane-tethered mucin lubricating and protecting the epithelial surface and playing various biological roles in the renewal and differentiation of epithelial cells, cell signaling, cell adhesion, and carcinogenesis. Interestingly, recent studies have demonstrated that MUC4 expression regulates the epithelial-mesenchymal transition (EMT) of cancer cells in ovarian, pancreatic, and lung cancer. However, the effects of MUC4 expression on EMT in human airway epithelial cells are not yet well known. Here, we describe the effects of transforming growth factor beta 1 (TGF-β1)-induced MUC4 expression on EMT and evaluate its downstream signaling pathway in human airway epithelial cells. In human airway epithelial NCI-H292 cells, exposure to TGF-β1 induced expression of MUC4, CDH2, VIM and SNAI1 genes and encoded by them proteins, MUC4, N-cadherin, vimentin and Snail, and reduced the level of CDH1 and its product, E-cadherin. In MUC4-knockdown cells, TGF-β1-induced expression levels of MUC4, CDH2, VIM and SNAI1 and corresponding proteins were suppressed, but CDH1 and E-cadherin levels were not. In addition, TGF-β1-induced phosphorylation of extracellular signal regulated kinase 1/2 (ERK1/2) was suppressed, but that of Smad2/3, Akt, and p38 was not. The results of this study suggest that MUC4 silencing inhibits TGF-β1 -induced EMT via the ERK1/2 pathway, and a possible role of MUC4 in the induction of EMT in human airway epithelial cells. Show less
Sedum species are reported to possess diverse pharmacological activities in various solid tumors. However, the anticancer functions of Sedum orizyfolium and its constituents have never been determined Show more
Sedum species are reported to possess diverse pharmacological activities in various solid tumors. However, the anticancer functions of Sedum orizyfolium and its constituents have never been determined in human cancers. The present study focused on addressing the inhibition efficacy of the methanol extract of S. orizyfolium (MESO) and its constituents and the molecular mechanism underlying invasion and epithelial-to-mesenchymal transition (EMT) in oral squamous cell carcinoma (OSCC) cell lines. After MESO treatment, a wound-healing assay, an invasion assay, and immunocytochemistry were performed in OSCC cell lines, coupled with in silico analysis and immunohistochemistry in OSCC patient samples, to investigate the role of the EMT transcription factor Slug. Trehalose, an active component of MESO, was identified through gas chromatography-mass spectrometry. Among the methanol extracts of 18 various wild plants from South Korea, MESO exhibited the highest anticancer functionality in OSCC cells by downregulating Slug expression. In silico analysis and immunohistochemistry indicated that elevated Slug levels are remarkably associated with tumor progression and invasion in patients with OSCC, suggesting that changes in Slug expression alter EMT progression and invasion in OSCC. Notably, treatment with trehalose, a sugar component of MESO, inhibited invasiveness and Slug expression in OSCC cells. Cumulatively, this study highlighted the beneficial role of MESO and trehalose in the inhibition of invasiveness of OSCC cells via suppression of Slug expression and suggested a new design for potential chemotherapeutic drugs against OSCC. Show less
The ovarian hormones estrogen and progesterone (EP) are implicated in breast cancer causation. A specific consequence of progesterone exposure is the expansion of the mammary stem cell (MSC) and lumin Show more
The ovarian hormones estrogen and progesterone (EP) are implicated in breast cancer causation. A specific consequence of progesterone exposure is the expansion of the mammary stem cell (MSC) and luminal progenitor (LP) compartments. We hypothesized that this effect, and its molecular facilitators, could be abrogated by progesterone receptor (PR) antagonists administered in a mouse model. Ovariectomized FVB mice were randomized to 14 days of treatment: sham, EP, EP + telapristone (EP + TPA), EP + mifepristone (EP + MFP). Mice were then sacrificed, mammary glands harvested, and mammary epithelial cell lineages separated by flow cytometry using cell surface markers. RNA from each lineage was sequenced and differential gene expression was analyzed using DESeq. Quantitative PCR was performed to confirm the candidate genes discovered in RNA seq. ANOVA with Tukey post hoc analysis was performed to compare relative expression. Alternative splicing events were examined using the rMATs multivariate analysis tool. Significant increases in the MSC and luminal mature (LM) cell fractions were observed following EP treatment compared to control (p < 0.01 and p < 0.05, respectively), whereas the LP fraction was significantly reduced (p < 0.05). These hormone-induced effects were reversed upon exposure to TPA and MFP (p < 0.01 for both). Gene Ontology analysis of RNA-sequencing data showed EP-induced enrichment of several pathways, with the largest effect on Wnt signaling in MSC, significantly repressed by PR inhibitors. In LP cells, significant induction of Wnt4 and Rankl, and Wnt pathway intermediates Lrp2 and Axin2 (confirmed by qRTPCR) were reversed by TPA and MFP (p < 0.0001). Downstream signaling intermediates of these pathways (Lrp5, Mmp7) showed similar effects. Expression of markers of epithelial-mesenchymal transition (Cdh1, Cdh3) and the induction of EMT regulators (Zeb1, Zeb2, Gli3, Snai1, and Ptch2) were significantly responsive to progesterone. EP treatment was associated with large-scale alternative splicing events, with an enrichment of motifs associated with Srsf, Esrp, and Rbfox families. Exon skipping was observed in Cdh1, Enah, and Brd4. PR inhibition reverses known tumorigenic pathways in the mammary gland and suppresses a previously unknown effect of progesterone on RNA splicing events. In total, our results strengthen the case for reconsideration of PR inhibitors for breast cancer prevention. Show less
Autophagy is a highly conserved metabolic process involved in the degradation of intracellular components including proteins and organelles. Consequently, it plays a critical role in recycling metabol Show more
Autophagy is a highly conserved metabolic process involved in the degradation of intracellular components including proteins and organelles. Consequently, it plays a critical role in recycling metabolic energy for the maintenance of cellular homeostasis in response to various stressors. In cancer, autophagy either suppresses or promotes cancer progression depending on the stage and cancer type. Epithelial-mesenchymal transition (EMT) and cancer metastasis are directly mediated by oncogenic signal proteins including SNAI1, SLUG, ZEB1/2, and NOTCH1, which are functionally correlated with autophagy. In this report, we discuss the crosstalk between oncogenic signaling pathways and autophagy followed by possible strategies for cancer treatment via regulation of autophagy. Although autophagy affects EMT and cancer metastasis, the overall signaling pathways connecting cancer progression and autophagy are still illusive. In general, autophagy plays a critical role in cancer cell survival by providing a minimum level of energy via self-digestion. Thus, cancer cells face nutrient limitations and challenges under stress during EMT and metastasis. Conversely, autophagy acts as a potential cancer suppressor by degrading oncogenic proteins, which are essential for cancer progression, and by removing damaged components such as mitochondria to enhance genomic stability. Therefore, autophagy activators or inhibitors represent possible cancer therapeutics. We further discuss the regulation of autophagy-dependent degradation of oncogenic proteins and its functional correlation with oncogenic signaling pathways, with potential applications in cancer therapy. Show less
Hypoxia has been suggested to induce epithelial-mesenchymal transition (EMT) in various cancer types via the transcription factor hypoxia-inducible factor-1 alpha (HIF-1α). Here, we demonstrated that Show more
Hypoxia has been suggested to induce epithelial-mesenchymal transition (EMT) in various cancer types via the transcription factor hypoxia-inducible factor-1 alpha (HIF-1α). Here, we demonstrated that TOPK upregulates EMT and the invasion of H460 nonsmall-cell lung cancer cells through the induction of the HIF-1α/Snail axis and hypoxic signaling. The expression of endogenous TOPK, phosphorylated TOPK, HIF-1α and Snail was significantly increased upon hypoxia exposure, but TOPK depletion markedly abrogated the induced mRNA and protein levels of HIF-1α and Snail. Interestingly, TOPK knockdown restored the hypoxia-induced suppression of E-cadherin and diminished hypoxia-induced N-cadherin expression. In addition, Snail depletion suppressed hypoxia-induced N-cadherin expression, which was attenuated by TOPK knockdown. Moreover, knockdown of Snail decreased hypoxia-induced nonsmall-cell lung cancer cell migration and invasion, which were suppressed by TOPK depletion. In summary, we conclude that TOPK positively regulates HIF-1α expression through hypoxia signaling and thereby promotes Snail expression, leading to EMT and the invasion of nonsmall-cell lung cancer cells. These findings suggest that TOPK plays a critical role as a novel mediator of hypoxia signaling that regulates nonsmall-cell lung cancer development. Show less
Eunhyang Park, Sang Wun Kim, Sunghoon Kim+4 more · 2021 · Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · Nature · added 2026-04-24
Gastric-type mucinous carcinoma (GAS) is a recently established variant of endocervical mucinous adenocarcinoma that is characterized as being unrelated to HPV and having aggressive behavior and chemo Show more
Gastric-type mucinous carcinoma (GAS) is a recently established variant of endocervical mucinous adenocarcinoma that is characterized as being unrelated to HPV and having aggressive behavior and chemoresistance. GAS has a distinct morphology resembling nonneoplastic gastric glands or pancreaticobiliary adenocarcinoma, and their possible genetic similarity has been posed. In this study, next-generation sequencing was performed in 21 GAS cases using a customized panel including 94 cancer-associated genes. A total of 54 nonsynonymous somatic mutations were detected with an average mutation rate of 2.6 per lesion (range: 0-9). The most frequently mutated gene was TP53 (11/21, 52.4%), followed by STK11, HLA-B, PTPRS (4/21, 19.0%), FGFR4 (3/21, 14.3%), GNAS, BRCA2, ELF3, ERBB3, KMT2D, SLX4 (2/21, 9.5%), CDH1, EPCAM, KRAS, MLH1, RNF43, SNAI1, TWIST1, ZEB1, ZEB2, and so on (1/21, 4.8%). The mutated genes were mostly involved in signal transduction, DNA damage repair, and epithelial-mesenchymal transition (EMT). Correlation of TP53 mutation and p53 protein expression demonstrated that 31.3% with abnormal p53 expression harbored wild-type TP53. Compared to genetic features of gastric and pancreaticobiliary adenocarcinoma, TP53 mutations were frequent in both GAS and gastrointestinal adenocarcinoma. While KMT2D, ERBB3, and RNF43 mutations were shared between GAS and gastric adenocarcinoma, highly mutated genes in pancreatic ductal adenocarcinoma such as KRAS, SMAD4, and CDKN2A were rarely mutated in GAS. Of frequently mutated genes in cholangiocarcinoma, BAP1 and HLA-B were identified in GAS. Frequent EMT-related gene mutations suggested a possible role of EMT-related pathways in tumor dissemination and chemoresistance of GAS. In addition, GAS shared some genetic features with gastrointestinal adenocarcinoma. These findings provide a clue in understanding the biological basis of GAS. Show less
The pluripotency transcription factor SOX2 is essential for the maintenance of glioblastoma stem cells (GSC), which are thought to underlie tumor growth, treatment resistance, and recurrence. To under Show more
The pluripotency transcription factor SOX2 is essential for the maintenance of glioblastoma stem cells (GSC), which are thought to underlie tumor growth, treatment resistance, and recurrence. To understand how SOX2 is regulated in GSCs, we utilized a proteomic approach and identified the E3 ubiquitin ligase TRIM26 as a direct SOX2-interacting protein. Unexpectedly, we found TRIM26 depletion decreased SOX2 protein levels and increased SOX2 polyubiquitination in patient-derived GSCs, suggesting TRIM26 promotes SOX2 protein stability. Accordingly, TRIM26 knockdown disrupted the SOX2 gene network and inhibited both self-renewal capacity as well as in vivo tumorigenicity in multiple GSC lines. Mechanistically, we found TRIM26, via its C-terminal PRYSPRY domain, but independent of its RING domain, stabilizes SOX2 protein by directly inhibiting the interaction of SOX2 with WWP2, which we identify as a bona fide SOX2 E3 ligase in GSCs. Our work identifies E3 ligase competition as a critical mechanism of SOX2 regulation, with functional consequences for GSC identity and maintenance. Show less
Glioblastoma (GBM), a lethal primary brain tumor, contains glioma stem cells (GSCs) that promote malignant progression and therapeutic resistance. SOX2 is a core transcription factor that maintains th Show more
Glioblastoma (GBM), a lethal primary brain tumor, contains glioma stem cells (GSCs) that promote malignant progression and therapeutic resistance. SOX2 is a core transcription factor that maintains the properties of stem cells, including GSCs, but mechanisms associated with posttranslational SOX2 regulation in GSCs remain elusive. Here, we report that DNA-dependent protein kinase (DNA-PK) governs SOX2 stability through phosphorylation, resulting in GSC maintenance. Mass spectrometric analyses of SOX2-binding proteins showed that DNA-PK interacted with SOX2 in GSCs. The DNA-PK catalytic subunit (DNA-PKcs) was preferentially expressed in GSCs compared to matched non-stem cell tumor cells (NSTCs) isolated from patient-derived GBM xenografts. DNA-PKcs phosphorylated human SOX2 at S251, which stabilized SOX2 by preventing WWP2-mediated ubiquitination, thus promoting GSC maintenance. We then demonstrated that when the nuclear DNA of GSCs either in vitro or in GBM xenografts in mice was damaged by irradiation or treatment with etoposide, the DNA-PK complex dissociated from SOX2, which then interacted with WWP2, leading to SOX2 degradation and GSC differentiation. These results suggest that DNA-PKcs-mediated phosphorylation of S251 was critical for SOX2 stabilization and GSC maintenance. Pharmacological inhibition of DNA-PKcs with the DNA-PKcs inhibitor NU7441 reduced GSC tumorsphere formation in vitro and impaired growth of intracranial human GBM xenografts in mice as well as sensitized the GBM xenografts to radiotherapy. Our findings suggest that DNA-PK maintains GSCs in a stem cell state and that DNA damage triggers GSC differentiation through precise regulation of SOX2 stability, highlighting that DNA-PKcs has potential as a therapeutic target in glioblastoma. Show less
Renal dysfunction, a major complication of type 2 diabetes, can be predicted from estimated glomerular filtration rate (eGFR) and protein markers such as albumin concentration. Urinary protein biomark Show more
Renal dysfunction, a major complication of type 2 diabetes, can be predicted from estimated glomerular filtration rate (eGFR) and protein markers such as albumin concentration. Urinary protein biomarkers may be used to monitor or predict patient status. Urine samples were selected from patients enrolled in the retrospective diabetic kidney disease (DKD) study, including 35 with good and 19 with poor prognosis. After removal of albumin and immunoglobulin, the remaining proteins were reduced, alkylated, digested, and analyzed qualitatively and quantitatively with a nano LC-MS platform. Each protein was identified, and its concentration normalized to that of creatinine. A prognostic model of DKD was formulated based on the adjusted quantities of each protein in the two groups. Of 1296 proteins identified in the 54 urine samples, 66 were differentially abundant in the two groups (area under the curve (AUC): Show less
Major depressive disorder is associated with weight loss and decreased appetite; however, the signaling that connects these conditions is unclear. Here, we show that MC
Diabetes is mostly assessed by the fasting glucose level. Several studies reported that serum fasting glucose levels and cardiovascular disease are associated with MC4R. A total of 4294 subjects parti Show more
Diabetes is mostly assessed by the fasting glucose level. Several studies reported that serum fasting glucose levels and cardiovascular disease are associated with MC4R. A total of 4294 subjects participated in this study. There were 1810 subjects with cardiovascular disease among the 4294 subjects. We used multivariate linear regression models and multiple logistic regression analysis. Individuals with the TC/CC genotype had a 1.29-fold higher risk of diabetes than did those with the TT genotype when adjusting for age, sex, and BMI (OR, 1.29; 95% CI, 1.04-1.60). For healthy subjects, the association was significant in women (OR, 1.99; 95% CI, 1.01-3.93). Men with the TC/CC genotype had a 1.21-fold higher risk of cardiovascular disease than did those with the TT genotype when adjusting for age, sex, and BMI (OR, 1.21; 95% CI, 1.04-1.41). The relationship between MC4R and cardiovascular disease was stronger in lean men (OR, 1.40; 95% CI, 1.12-1.74, p = 0.0028) than in overweight men. This study suggests that the rs17782313 SNP in MC4R is related to diabetes and the SNP is also associated with cardiovascular disease in lean men. Show less
Genomic evaluation has been widely applied to several species using commercial single nucleotide polymorphism (SNP) genotyping platforms. This study investigated the informative genomic regions and th Show more
Genomic evaluation has been widely applied to several species using commercial single nucleotide polymorphism (SNP) genotyping platforms. This study investigated the informative genomic regions and the efficiency of genomic prediction by using two Bayesian approaches (BayesB and BayesC) under two moderate-density SNP genotyping panels in Korean Duroc pigs. Growth and production records of 1026 individuals were genotyped using two medium-density, SNP genotyping platforms: Illumina60K and GeneSeek80K. These platforms consisted of 61,565 and 68,528 SNP markers, respectively. The deregressed estimated breeding values (DEBVs) derived from estimated breeding values (EBVs) and their reliabilities were taken as response variables. Two Bayesian approaches were implemented to perform the genome-wide association study (GWAS) and genomic prediction. Multiple significant regions for days to 90 kg (DAYS), lean muscle area (LMA), and lean percent (PCL) were detected. The most significant SNP marker, located near the MC4R gene, was detected using GeneSeek80K. Accuracy of genomic predictions was higher using the GeneSeek80K SNP panel for DAYS (Δ2%) and LMA (Δ2-3%) with two response variables, with no gains in accuracy by the Bayesian approaches in four growth and production-related traits. Genomic prediction is best derived from DEBVs including parental information as a response variable between two DEBVs regardless of the genotyping platform and the Bayesian method for genomic prediction accuracy in Korean Duroc pig breeding. Show less
Patients with tall stature often remain undiagnosed after clinical investigation and few studies have genetically assessed this group, most of them without a systematic approach. To assess prospective Show more
Patients with tall stature often remain undiagnosed after clinical investigation and few studies have genetically assessed this group, most of them without a systematic approach. To assess prospectively a group of individuals with tall stature, with and without syndromic features, and to establish a molecular diagnosis for their growth disorder. Screening by karyotype (n = 42), chromosome microarray analyses (CMA) (n = 16), MS-MLPA (n = 2) targeted panel (n = 12) and whole-exome sequencing (n = 31). We selected 42 patients with tall stature after exclusion of pathologies in GH/IGF1 axis and divided them into syndromic (n = 30) and non-syndromic (n = 12) subgroups. Frequencies of pathogenic findings. We identified two patients with chromosomal abnormalities including SHOX trisomy by karyotype, one 9q22.3 microdeletion syndrome by CMA, two cases of Beckwith-Wiedemann syndrome by targeted MS-MLPA analysis and nine cases with heterozygous pathogenic or likely pathogenic genetic variants by multigene analysis techniques (FBN1 = 3, NSD1 = 2, NFIX = 1, SUZ12 = 1, CHD8 = 1, MC4R = 1). Three of 20 patients analyzed by WES had their diagnosis established. Only one non-syndromic patient had a definitive diagnosis. The sequential genetic assessment diagnosed 14 out of 42 (33.3%) tall patients. A systematic molecular approach of patients with tall stature was able to identify the etiology in 13 out of 30 (43.3%) syndromic and 1 out of 12 (8.3%) non-syndromic patients, contributing to the genetic counseling and avoiding unfavorable outcomes in the syndromic subgroup. Show less
Pancreatitis is the inflammation of the pancreas. However, little is known about the genes associated with pancreatitis severity. Our microarray analysis of pancreatic tissues from mild and severe acu Show more
Pancreatitis is the inflammation of the pancreas. However, little is known about the genes associated with pancreatitis severity. Our microarray analysis of pancreatic tissues from mild and severe acute pancreatitis mice models identified angiopoietin-like 4 (ANGPTL4) as one of the most significantly upregulated genes. Clinically, ANGPTL4 expression was also increased in the serum and pancreatic tissues of pancreatitis patients. The deficiency in ANGPTL4 in mice, either by gene deletion or neutralizing antibody, mitigated pancreatitis-associated pathological outcomes. Conversely, exogenous ANGPTL4 exacerbated pancreatic injury with elevated cytokine levels and apoptotic cell death. High ANGPTL4 enhanced macrophage activation and infiltration into the pancreas, which increased complement component 5a (C5a) level through PI3K/AKT signaling. The activation of the C5a receptor led to hypercytokinemia that accelerated acinar cell damage and furthered pancreatitis. Indeed, C5a neutralizing antibody decreased inflammatory response in LPS-activated macrophages and alleviated pancreatitis severity. In agreement, there was a significant positive correlation between C5a and ANGPTL4 levels in pancreatitis patients. Taken together, our study suggests that targeting ANGPTL4 is a potential strategy for the treatment of pancreatitis. Show less
Eun Ji Lee, Eunjeong Seo, Jin Won Kim+9 more · 2020 · Proceedings of the National Academy of Sciences of the United States of America · National Academy of Sciences · added 2026-04-24
CKD-519 is a selective and potent cholesteryl ester transfer protein (CETP) inhibitor that is being developed for dyslipidemia. Even though CKD-519 has shown potent CETP inhibition, the exposure of CK Show more
CKD-519 is a selective and potent cholesteryl ester transfer protein (CETP) inhibitor that is being developed for dyslipidemia. Even though CKD-519 has shown potent CETP inhibition, the exposure of CKD-519 was highly varied, depending on food and dose. For highly variable exposure drugs, it is crucial to use modeling and simulation to plan proper dose selection. This study aimed to develop population pharmacokinetic (PK) and pharmacodynamics (PD) models of CKD-519 and to predict the proper dose of CKD-519 to achieve target levels for HDL-C and LDL-C using results from multiple dosing study of CKD-519 with a standard meal for two weeks in healthy subjects. The results showed that a 3-compartment with Erlang's distribution, followed by the first-order absorption, adequately described CKD-519 PK, and the bioavailability, which decreased by dose and time was incorporated into the model (NONMEM version 7.3). After the PK model development, the CETP activity and cholesterol (HDL-C and LDL-C) levels were sequentially modeled using the turnover model, including the placebo effect. According to PK-PD simulation results, 200 to 400 mg of CKD-519 showing a 40% change in HDL-C and LDL-C from baselines was recommended for proof of concept studies in patients with dyslipidemia. Show less
We examined the effect of mild hyperglycemia on high-density lipoprotein (HDL) metabolism and kinetics in diet-controlled subjects with type 2 diabetes (T2D).
DLG2, also known as postsynaptic density protein-93 (PSD-93) or chapsyn-110, is an excitatory postsynaptic scaffolding protein that interacts with synaptic surface receptors and signaling molecules. A Show more
DLG2, also known as postsynaptic density protein-93 (PSD-93) or chapsyn-110, is an excitatory postsynaptic scaffolding protein that interacts with synaptic surface receptors and signaling molecules. A recent study has demonstrated that mutations in the DLG2 promoter region are significantly associated with autism spectrum disorder (ASD). Although DLG2 is well known as a schizophrenia-susceptibility gene, the mechanisms that link DLG2 gene disruption with ASD-like behaviors remain unclear. Mice lacking exon 14 of the Dlg2 gene (Dlg2 Dlg2 These results suggest that homozygous Dlg2 deletion in mice leads to ASD-like behavioral phenotypes, including social deficits and increased repetitive behaviors, as well as reductions in excitatory synaptic input onto dorsolateral spiny projection neurons, implying that the dorsal striatum is one of the brain regions vulnerable to the developmental dysregulation of DLG2. Show less
Yone Kawe Lin, Wei Wu, Rovingaile Kriska Ponce+2 more · 2020 · Proceedings of the National Academy of Sciences of the United States of America · National Academy of Sciences · added 2026-04-24
Transcription factor fusions (TFFs) are present in ∼30% of soft-tissue sarcomas. TFFs are not readily "druggable" in a direct pharmacologic manner and thus have proven difficult to target in the clini Show more
Transcription factor fusions (TFFs) are present in ∼30% of soft-tissue sarcomas. TFFs are not readily "druggable" in a direct pharmacologic manner and thus have proven difficult to target in the clinic. A prime example is the CIC-DUX4 oncoprotein, which fuses Capicua (CIC) to the double homeobox 4 gene, DUX4. CIC-DUX4 sarcoma is a highly aggressive and lethal subtype of small round cell sarcoma found predominantly in adolescents and young adults. To identify new therapeutic targets in CIC-DUX4 sarcoma, we performed chromatin immunoprecipitation sequencing analysis using patient-derived CIC-DUX4 cells. We uncovered multiple CIC-DUX4 targets that negatively regulate MAPK-ERK signaling. Mechanistically, CIC-DUX4 transcriptionally up-regulates these negative regulators of MAPK to dampen ERK activity, leading to sustained CIC-DUX4 expression. Genetic and pharmacologic MAPK-ERK activation through DUSP6 inhibition leads to CIC-DUX4 degradation and apoptotic induction. Collectively, we reveal a mechanism-based approach to therapeutically degrade the CIC-DUX4 oncoprotein and provide a precision-based strategy to combat this lethal cancer. Show less
Assessment of differentiation potential is a basic requirement to obtain qualified human pluripotent stem cells (hPSCs). Here, we report a simple differentiation method using fetal bovine serum (FBS) Show more
Assessment of differentiation potential is a basic requirement to obtain qualified human pluripotent stem cells (hPSCs). Here, we report a simple differentiation method using fetal bovine serum (FBS) to estimate differentiation potential and propensity of hPSCs. PluriTest using RNA-sequencing showed that cells differentiated after treatment with 5% FBS. Expression patterns of three germ layer markers revealed that cells cultured in Knockout Serum Replacement-containing medium (KSR) with mouse feeder cells had higher differentiation potential than cells cultured in a chemically defined medium (E8) with recombinant matrix proteins, especially into the mesoderm and endoderm lineages. Analysis of differentially expressed genes between KSR and E8 identified DUSP6 as a marker for where cells had been cultured. Expression of DUSP6 correlated with FGF-ERK signaling activity. Fine-tuning of FGF-ERK signaling activity to a range that can shut down DUSP6 transcription but sustain NANOG transcription partially increased the differentiation potential. Our data suggest that differentiation with 5% FBS is good to estimate differentiation potential and propensity at the early stage, and that DUSP6 is an excellent marker to monitor ERK signaling activity. Show less