Citations

Clear

9 citation(s) found for "Gu, Yuna".

Amyloid PET Quantitation and Centiloid Thresholds in the Diagnosis of Alzheimer Disease
Soleimani‐Meigooni, David N. , Chiotis, Konstantinos, Allen, Isabel E., Rabinovici, Gil D., Joie, Renaud La , Group, Meta-Centiloid Study, Apostolova, Liana G. , Asken, Breton M., Benzinger, Th., Betthauser, Tobey J., Bluma, Marina, Bombois, Stephanie, Bourgeat, Pierrick, Bouteloup, Vincent , Braskie, Meredith N., Brendel, Matthias, Brickman, Adam M., Bryant, Natalie, Bullich, Santiago , Carrillo, Maria C., Casaletto, Kaitlin, Cash, David M., Chang, Chiung-Chih, CHANG, H L, Chao, Yishu , Collij, Lyduine E., Corrada, Maria M., Craft, Suzanne , Dickerson, Bradford C., Dubois, Bruno, Dufouil, Carole, Fajardo, Alfonso, Farrar, Gill , Fortea, Juan, Frings, Lars , Frisoni, Giovanni B., Gardner, Raquel C., Gnörich, Johannes , Gordon, Brian A., Gu, Yuna , Guan, Yihui, Guo, Tengfei, Hanseeuw, Bernard J., Hansson, Oskar, Harrison, Theresa M., Huang, Qi, Huang, ST , Iaccarino, Leonardo, Ishii, Kazunari, Ishi, Kenji, Jagust, William J., Johnson, Sterling C., Kato, Takashi, Katsumi, Yuta, Kaye, Jeffrey, Kolinger, Guilherme D., Kramer, Joel H. , Landau, Susan M., Landeau, Brigitte, Lao, Patrick J., Lee, Sangwon, Lopresti, Brian J., Lowe, Val J. , Luchsinger, José A., Mao, Xiaoxie, March, Andrew, Masters, Colin L., Meyer, Philipp T., Mezenge, Florence, Mormino, Elizabeth C., Franquesa‐Mullerat, María , Nakamura, Akinori, Nordberg, Agneta, O’Brien, John T., O’Bryant, Sid E., Pappas, Ioannis, Peretti, Debora E., Rowe, Christopher C., Rowe, James B., Schwartz, Daniel L., Seo, Sang Won , Shekari, Mahnaz, Smith, Ruben, Snyder, Heather M. , Sokolowski, Andrzej, Sperling, Reisa A., Sun, Pan, Taggett, Jacinda Z., Touroutoglou, Alexandra , Vaillancourt, David E., Giessen, Elsmarieke van de, Vijverberg, Jort, Villemagne, Victor L. , Villeneuve, Sylvia , Wang, Wei-en, Weiner, Michael, Woodworth, Davis, Xiao, Cally , Xie, F, Yoon, Yeojun, Yun, Mijin, Severanc, A4, ABIDE, ADNI*, ADNI-DoD, AgeWell, AIBL, AMYPAD, BACS, BATON, BIOCARD, BLSA, BioFINDER-2, BrANCH, CPAS, DETECT-AD, GEMS, GHABS, HABS, HABS-HD, IDEAS, IMAP, INSIGHT-preAD, Insight46, K-ROAD, LEADS, MCSA, MULNIAD, MEMENTO, SCAN, PREVENT-AD, SPIN,, Corrada, María M. , La Joie, Renaud , Blazhenets, Ganna , Chiotis, Konstantinos , Allen, Isabel Elaine , Rabinovici, Gil D. , Asken, Breton M. , Bejanin, Alexandre , Benzinger, Tammie L.S. , Betthauser, Tobey J. , Blūma, Marina , Bombois, Stéphanie , Bourgeat, Pierrick , Braskie, Meredith N. , Brendel, Matthias , Brickman, Adam M. , Carrillo, María C. , Casaletto, Kaitlin B. , Cash, David M. , Chang, Chiung‐Chih , Chang, Hsin‐I , Chêne, Geneviève , Chételat, Gaël , Coath, William , Collij, Lyduine , Colmant, Lise , Dickerson, Bradford Clark , Dubois, Bruno , Dufouil, Carole , Fortea, Juan , Garibotto, Valentina , Gordon, Brian A. , Guan, Yihui , Guo, Tengfei , Hanseeuw, Bernard , Hansson, Oskar , Harrison, Theresa M. , Iaccarino, Leonardo , Ishii, Kazunari , Ishii, Kenji, Jagust, William J. , Johnson, Sterling C. , Katsumi, Yuta , Kaye, Jeffrey , Koeppe, Robert A. , Kolinger, Guilherme Domingues , Landau, Susan , Landeau, Brigitte , Lao, Patrick , Lee, Sangwon, Lleó, Alberto , Lopresti, Brian J. , Malpetti, Maura , March, Andrew, Masters, Colin L. , Mézenge, Florence, Mormino, Elizabeth C. , Nakamura, Akinori , Nordberg, Agneta , O'Brien, John Tiernan , O’Bryant, Sid E. , Pappas, Ioannis , Quenon, Lisa , Rowe, Christopher Cleon , Rowe, James B. , Rudolph, Marc D. , Salvadó, Gemma , Schott, Jonathan M. , Schwarz, Christopher G. , Shekari, Mahnaz , Silbert, Lisa C. , Smith, Ruben, Sokolowski, Andrzej, Sperling, Reisa Anne , Sun, Pan , Taggett, Jacinda , Toga, Arthur W. , Vaillancourt, David E. , Giessen, Elsmarieke van de , Vemuri, Prashanthi , Villain, Nicolas , Wang, Wei‐en , Weiner, Michael W. , Xie, Fang , Young, Christina B. , Yun, M R

Mayo Clinic

JAMA | July 13, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1001/jama.2026.13116 | PMID 42441390 Get It

Importance Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I 2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I 2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I 2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I 2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I 2 = 80%). Conclusions and Relevance In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.
Every Centiloid, from Everywhere, All at Once
Snyder, Heather M. , Apostolova, Liana G., Asken, Breton M., Bombois, Stéphanie, Bourgeat, Pierrick, Braskie, Meredith N., Carrillo, Maria C., Casaletto, Kaitlin B, Cash, David M, Chang, Hsin‐I., Chao, Yishu , Chételat, Gael, Collij, Lyduine E., Dickerson, Brad C., Dubois, Bruno, Valdez, Alfonso Fajardo, Farrar, Gill , Fortea, Juan M., Frisoni, Giovanni B, Gu, Yuna , Guo, Tengfei, Hanseeuw, Bernard J, Hansson, Oskar H., Harrison, Theresa, Huang, Qi, Huang, Shu‐Hua , Ishii, K, Ishii, Kenji, Jagust, William J., Katou, Rikio, Koeppe, Robert A., Kramer, Joel H, Landau, Susan M., Landeau, Brigitte, Lee, Sangwon, Lopresti, Brian J, Lowe, Val J. , Mao, Xiaoxie, March, Andrew, Masters, Colin L., Mézenge, Florence, Mormino, Elizabeth C., Franquesa‐Mullerat, María , Nakamura, Akinori, O'Bryant, Sid E., Pappas, Ioannis, Rowe, Christopher C., Salvadó, Gemma, Schott, Jonathan M, Schwartz, Daniel, Schwarz, Christopher G, Seo, Sang Won, Shekari, Mahnaz , Silbert, Lisa C, Smith, Ruben, Sokolowski, Andrzej, Soleimani‐Meigooni, David, Sperling, Reisa A., Sun, Pan , Toga, Arthur W., Vaillancourt, D., Giessen, Elsmarieke van de, Flier, Wiesje M. van der, Vemuri, Prashanthi, Villemagne, Victor L., Villeneuve, Sylvia , Wang, Wei‐En, Weiner, Michael S. W., Xiao, Cally , Xie, Fang, Yoon, Yeojun, Yun, M R , Rabinovici, Gil D., Joie, Renaud La, Consortia, AMYPAD and LEADS, Blazhenets, Ganna , Apostolova, Liana G. , Asken, Breton M. , Bejanin, Alexandre , Bombois, Stéphanie , Bourgeat, Pierrick , Braskie, Meredith N. , Carrillo, María C. , Casaletto, Kaitlin B. , Cash, David M. , Chang, Chia‐Hsuin , Chang, Hsin‐I , Chételat, Gaël , Coath, William , Collij, Lyduine , Colmant, Lise , Dickerson, Bradford Clark , Dubois, Bruno , Fortea, Juan , Frisoni, Giovanni B. , Gardner, Raquel C. , Garibotto, Valentina , Guo, Tengfei , Hanseeuw, Bernard , Hansson, Oskar , Harrison, Theresa M. , Ishii, Kenji, Jagust, William J. , Koeppe, Robert A. , Kramer, Joel H. , Landau, Susan , Landeau, Brigitte , Lee, Sangwon, Lopresti, Brian J. , March, Andrew, Masters, Colin L. , Mézenge, Florence, Mormino, Elizabeth C. , Nakamura, Akinori , O’Bryant, Sid E. , Pappas, Ioannis , Peretti, Débora Elisa , Quenon, Lisa , Rowe, Christopher C., Salvadó, Gemma , Schott, Jonathan M. , Schwartz, Daniel L., Schwarz, Christopher G. , Seo, Sang Won , Shekari, Mahnaz , Silbert, Lisa C. , Smith, Ruben, Soleimani‐Meigooni, David N. , Sperling, Reisa Anne , Sun, Pan , Toga, Arthur W. , Vaillancourt, David E. , Giessen, Elsmarieke van de , Flier, Wiesje M. van der , Vemuri, Prashanthi , Villain, Nicolas , Villemagne, Victor L. , Weiner, Michael W. , Xie, Fang , Young, Christina B. , Rabinovici, Gil D. , Joie, Renaud La

Mayo Clinic

Alzheimer's & Dementia | January 9, 2026 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_107124 Get It

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen's kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure 1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure 1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure 2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure 2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.
Sex, education and race/ethnicity have distinct effects on amyloid and tau‐PET status
Groot, Colin , Rowe, Christopher C., Giessen, Elsmarieke van de, Flier, Wiesje M. van der, Pijnenburg, Yolande A.L., Visser, Pieter Jelle, Braber, Anouk den, Pontecorvo, Michael J. , Burnham, Samantha C., Lu, Ming , Jagust, William J., Baker, Suzanne L. , Harrison, Theresa, Gispert, Juan Domingo, Shekari, Mahnaz , Minguillón, Carolina, Smith, Ruben, Mattsson‐Carlgren, Niklas, Palmqvist, Sebastian, Strandberg, Olof, Stomrud, Erik, Brickman, Adam, Manly, Jennifer J., Lao, Patrick J., Kreisl, William Charles, Malpetti, Maura, O'Brien, John T, Jäger, Elena, Bischof, Gérard, Drzezga, Alexander, Xie, Fang, Mao, Xiaoxie, Guan, Yihui, Frisoni, Giovanni B, Peretti, Débora Elisa , Skoog, I., Kern, Silke, Sperling, Reisa A., Johnson, Keith A., Risacher, Shannon, Saykin, Andrew J., Carrillo, Maria C., Dickerson, Brad C., Apostolova, Liana G., Rabinovici, Gil D., Barthel, H, Messerschmidt, Konstantin, Vandenberghe, Rik, Laere, Koen J. Van, Spruyt, Laure , Petersen, Ronald, Jack, Clifford R., Franzmeier, Nicolai, Brendel, Matthias, Gnörich, Johannes, Benzinger, Tammie L.S., Lagarde, Julien, Sarazin, Marie , Villeneuve, Sylvia , Poirier, Judes, Seo, Sang Won, Gu, Yuna , Kim, Jun Pyo, Mormino, Beth C., Vossler, Hillary , Rosa‐Neto, Pedro, Therriault, Joseph, Rahmouni, Nesrine, Cash, David M, Schott, Jonathan M, Hanseeuw, Bernard J, Jansen, Willemijn J. , Joie, Renaud La, Rosen, Howard J., Johnson, Sterling C., Christian, Bradley T, Betthauser, Tobey J., Landau, Susan M., O'Bryant, Sid E., Hansson, Oskar H., Ossenkoppele, Rik, Prevent‐AD, ADNI, ADNI‐DOD, A‐Study, MCSA,, O’Brien, John T. , O'Brien, John Tiernan , Groot, Colin , Coomans, Emma M. , Rowe, Christopher C., Doré, Vincent , Feizpour, Azadeh , Giessen, Elsmarieke van de , Flier, Wiesje M. van der , Pijnenburg, Yolande A.L. , Visser, Pieter Jelle , Braber, Anouk den , Burnham, Samantha C. , Kennedy, Ian Andrew , Jagust, William J. , Harrison, Theresa M. , Gispert, Juan Domingo , Shekari, Mahnaz , Minguillón, Carolina , Smith, Ruben, Mattsson, Niklas , Palmqvist, Sebastian , Strandberg, Olof, Stomrud, Erik , Brickman, Adam M. , Luchsinger, Jose Alejandro , Manly, Jennifer J. , Lao, Patrick , Malpetti, Maura , Rowe, James B. , Bischof, Gérard N. , Drzezga, Alexander E. , Xie, Fang , Guan, Yihui , Garibotto, Valentina , Frisoni, Giovanni B. , Schöll, Michael , Kern, Silke , Sperling, Reisa Anne , Johnson, Keith A. , Risacher, Shannon L. , Saykin, Andrew J. , Carrillo, María C. , Dickerson, Bradford Clark , Apostolova, Liana G. , Rabinovici, Gil D. , Rullmann, Michael , Messerschmidt, Konstantin, Vandenberghe, Rik , Petersen, Ronald, Jack, Clifford R. , Franzmeier, Nicolai , Brendel, Matthias , Gnörich, Johannes , Benzinger, Tammie L.S. , Lagarde, Julien , Bottlaender, Michel , Poirier, Judes , Seo, Sang Won , Kim, Jun Pyo, Young, Christina B. , Rosa-Neto, Pedro , Therriault, Joseph , Rahmouni, Nesrine , Coath, William , Cash, David M. , Schott, Jonathan M. , Hanseeuw, Bernard , Salman, Yasmine , Malotaux, Vincent , Joie, Renaud La , Rosen, Howard J. , Johnson, Sterling C. , Christian, Bradley T. , Betthauser, Tobey J. , Landau, Susan , O’Bryant, Sid E. , Hansson, Oskar , Ossenkoppele, Rik

Mayo Clinic

Alzheimer's & Dementia | January 8, 2026 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_105387 Get It

Abstract Background Sex, education and race/ethnicity are all associated with risk of Alzheimer's disease dementia. Here, we assess the effects of self‐reported sex, educational attainment and race/ethnicity on amyloid‐positivity, and tau‐PET‐positivity in 12,048 (7,394 cognitively unimpaired [CU], 2,177 MCI, and 2,477 dementia) individuals from 42 cohorts worldwide. Method Logistic generalized estimating equations were used to estimate frequency of amyloid‐positivity (using cohort‐specific thresholds for amyloid‐PET [84%] or CSF) and tau‐PET‐positivity (cohort‐specific thresholds of 2SD above mean temporal uptake in amyloid‐negative controls). We assessed: i) sex and APOEε4 ( N = 10,098) associations, to complement earlier findings of a higher frequency of tau‐positivity in females, ii) effects of lower/higher education ( N = 10,970; cohort‐specific median‐split), and iii) effects of race/ethnicity (non‐Hispanic White [hereafter: White], N = 4880; Asian, N = 116; Black or African‐American [hereafter: Black], N = 353; Hispanic, N = 356, only from Northern‐American cohorts). Outcomes were frequency of amyloid‐positivity in CU individuals only, and tau‐PET‐positivity in both amyloid‐positive (AB+) CU and cognitively impaired (CI, i.e. MCI and dementia) individuals. Interaction effects on the relationship between age and amyloid/tau‐positivity were assessed and only retained in the models when significant. Result Female sex was associated with an APOEε4 ‐independent increased frequency of amyloid‐positivity (β=0.51[0.22], p = 0.02) in CU and increase of tau‐positivity in both AB+CU (β=0.27[0.08]) and AB+CI (β=0.37[0.08], both p <0.01). Remarkably, tau‐positivity frequencies of female APOEε4 non‐carriers were equivalent to male APOEε4 carriers in AB+CI (Figure 1). No significant sex* APOE interactions were observed. In CU, higher education was associated with lower amyloid‐positivity frequency (β=‐0.12[0.05], p = 0.02). In contrast, among AB+CU, there was an age*education interaction effect that indicated more pronounced age effects on tau‐positivity in individuals with higher education (age*education:β interaction =0.03[0.01], p <0.01). There were no education effects in AB+CI (Figure 2). In CU, an age*race/ethnicity interaction effect was observed across all non‐White groups compared to White (Hispanic:β interaction =‐0.05[0.01], p <0.01; Black:‐0.04[0.01], p <0.01; Asian:‐0.02[0.01], p = 0.04). This suggests that the impact of age on amyloid‐positivity was less pronounced in non‐White groups. Furthermore, in AB+CI, Hispanic ethnicity was related to higher tau‐positivity frequency than White (β=0.51[0.22], p = 0.02; Figure 3). Conclusion In this multi‐center initiative comprised of clinical and community‐based cohorts, we observed that self‐reported sex, educational attainment and race/ethnicity were related to positivity‐frequencies of Alzheimer's disease pathology.
Every Centiloid, from Everywhere, All at Once
Snyder, Heather M. , Apostolova, Liana G., Bombois, Stéphanie, Bourgeat, Pierrick, Braskie, Meredith N. , Carrillo, Maria, Casaletto, Kaitlin B, Chang, C. -C., Chang, Hsin‐I., Chao, Yishu , Chetelat, Gaël, Collij, Lyduine E., Dickerson, Brad C., Dubois, Bruno, Valdez, Alfonso Fajardo, Farrar, Gill , Fortea, Juan M., Frisoni, Giovanni B, Gu, Yuna , Guo, Tengfei, Hansson, Oskar H., Huang, Q., Huang, Shu‐Hua , Ishii, Kenji, Jagust, William J., Kato, Takashi , Koeppe, R. A., Kramer, Joel H, Landau, Susan M., Landeau, Brigitte, Lee, Sangwon, Lopresti, Brian J. , Lowe, Val J. , Mao, Xiaoxie, March, Andrew, Masters, Colin L., Mézenge, Florence, Mormino, Elizabeth C. , Franquesa‐Mullerat, María , Nakamura, Akinori, O'Bryant, Sid E., Pappas, Ioannis G., Rowe, C. C., Schott, Jonathan M, Schwartz, Daniel L. , Schwarz, Christopher G, Seo, Sang Won, Shekari, Mahnaz, Smith, Ruben, Sokołowski, Andrzej , Soleimani‐Meigooni, David, Sperling, Reisa A., Sun, Pan , Toga, Arthur W., Vaillancourt, David E. , Flier, Wiesje M. van der, Vemuri, Prashanthi, Villain, Nicolas , Villemagne, Victor L., Villeneuve, Sylvia , Wang, Wei‐En, Weiner, Michael S. W., Xiao, Cally , Xie, Fang, Yoon, Yeojun, Yun, M R , Rabinovici, Gil D., Wang, Wei‐en , Blazhenets, Ganna , Apostolova, Liana G. , Asken, Breton M. , Bejanin, Alexandre , Bombois, Stéphanie , Bourgeat, Pierrick , Casaletto, Kaitlin B. , Cash, David M. , Chang, Hsin‐I , Chételat, Gaël , Coath, William , Collij, Lyduine , Colmant, Lise , Dickerson, Brad C., Dubois, Bruno , Fortea, Juan , Frisoni, Giovanni B. , Gardner, Raquel C. , Garibotto, Valentina , Guo, Tengfei , Hanseeuw, Bernard , Hansson, Oskar , Harrison, Theresa M. , Ishii, Kazunari , Jagust, William J. , Kramer, Joel H. , Landau, Susan, Landeau, Brigitte , Masters, Colin L. , Mézenge, Florence, Nakamura, Akinori , O’Bryant, Sid E. , Peretti, Débora Elisa , Quenon, Lisa , Salvadó, Gemma , Schott, Jonathan M. , Schwarz, Christopher G. , Seo, Sang Won , Shekari, Mahnaz , Silbert, Lisa C. , Sokolowski, Andrzej, Soleimani‐Meigooni, David N. , Sperling, Reisa Anne , Sun, Pan , Toga, Arthur W. , Giessen, Elsmarieke van de , Flier, Wiesje M. van der , Vemuri, Prashanthi , Villemagne, Victor L. , Weiner, Michael W. , Xie, Fang , Young, Christina B. , Rabinovici, Gil D. , Joie, Renaud La

Mayo Clinic

Alzheimer's & Dementia | December 23, 2025 | Volume: 21 | Issue: S8 | Pages: No page available

10.1002/alz70862_110011 Get It

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen’s kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure‐1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure‐1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure‐2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure‐2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.
Cyclin D1 overexpression induces replication stress and microhomology-mediated end-joining dependence in mantle cell lymphoma
Abeykoon, Jithma P. , Zhu, Guangli, Hirohashi, Yuna, Moreau, Lisa A. , Mukkavalli, Sirisha , Parmar, Kalindi , Zambrano, Gabriella, Jiang, Lige, Gwin, Kimberly, King, Rebecca L. , Wu, Xiaosheng , Yi, Dongni , Asada, Shuhei , Zhu, Guangli, Iyer, Divya , Zambrano, Gabriella, Manske, Michelle K. , Cerhan, James R. , Lou, Zhenkun , Shapiro, Geoffrey I. , Witzig, Thomas E. , D’Andrea, Alan D.

Mayo Clinic

Journal of Clinical Investigation | July 3, 2025 | Volume: 135 | Issue: 17 | Pages: No page available

10.1172/jci193006 | PMID 40608419 Get It

Oncogene expression can cause replication stress (RS), leading to DNA double-strand breaks (DSBs) that require repair through pathways such as homologous recombination, nonhomologous end-joining, and microhomology-mediated end-joining (MMEJ). Cyclin D1 (encoded by CCND1 ) is a well-known oncoprotein overexpressed in cancer; however, its role in RS is unknown. Using mantle cell lymphoma (MCL) as a naturally occurring model of cyclin D1 overexpression, we examined the impact of cyclin D1 on RS and DSB repair mechanisms. Cyclin D1 overexpression elevated RS, increased DNA damage, especially during mitosis, and caused specific upregulation of MMEJ. Furthermore, cyclin D1 activated polymerase theta ( POLQ ) transcription by binding its promoter loci, driving POLΘ-mediated MMEJ that is essential to withstand cyclin D1–induced RS. Moreover, concurrent ATM deficiency further intensified RS, enhanced POLQ expression, and heightened reliance on MMEJ-mediated DNA damage repair. Consequently, inhibition of POLΘ in cyclin D1–overexpressed settings further exacerbated RS, causing single-strand DNA gap accumulations and chromosomal instability, ultimately leading to apoptosis, an effect amplified in ATM-deficient cells. Targeting MMEJ via POLΘ inhibition is therefore an effective strategy in the context of cyclin D1 overexpression and ATM deficiency and may provide a unique therapeutic approach for treating MCL and other malignancies characterized by similar alterations.
Frequency and Clinical Outcomes Associated With Tau Positron Emission Tomography Positivity
Raghavan, Sheelakumari, Costoya‐Sánchez, Alejandro , Mainta, Ismini , Rodríguez-Fonseca, Omar Darío, Perissinotti, Andrés , Gu, Yuna , Yun, Jihwan, Peretti, Débora Elisa , Aguiar, Pablo , Bischof, Gérard N. , Seo, Sang Won , Villeneuve, Sylvia , O’Brien, John T. , Jagust, William, Frisoni, Giovanni B. , Soleimani‐Meigooni, David N. , Carrillo, Marı́a C., Joie, Renaud La , Rabinovici, Gil D. , Apostolova, Liana G. , Pontecorvo, Michael J. , Johnson, Keith A. , Weiner, Michael W. , Petersen, Ronald C., Jack, Clifford R. , Schöll, Michael , Labonté, Anne , Faubert, Anne‐Marie, Mathieu, Axel, Madjar, Cécile , Carrier, Charles Edouard, Kazazian, Christina, Lepage, Claude, Maillet, David , Michaud, Diane, Couture, Doris, Dea, Doris, Courcot, Blandine, Debacker, Clément , Fontaine, David, Knopman, David S. , Multhaup, Gerhard, Maltais, Jean‐Robert, Breitner, John C.S. , Poirier, Judes, Cheewakriengkrai, Laksanun, Sager, Mark A., Dauar‐Tedeschi, Marina, Rajah, Natasha, Aisen, Paul, Toussaint, Paule‐Joanne , Pierre, Bellec, Kostopoulos, Penelope, Étienne, Pierre , Tariot, Pierre N. , Orban, Pierre , Hoge, Rick, Thomas, Ronald J. , Gauthier, Serge , Craft, Suzanne , Montine, Thomas J. , Nair, Vasavan, Bohbot, Véronique D. , Venugopalan, Vinod, Ituria‐Medina, Yasser, Khachaturian, Zaven S., Teigner, Eduard, Anthal, Elena, Yu, Elsa, Ferdinand, Fabiola, Pogossova, Galina, Mayrand, Ginette, Duclair, Guerda, Gagné, Guylaine, Newbold‐Fox, Holly, Leppert, Illana, Tremblay‐Mercier, Jennifer , Frenette, Joanne, Frappier, Josée, Kat, Justin, Miron, Justin , Wan, Karen, Mahar, Laura, Carmo, Leopoldina, Théroux, Louise, Dufour, Marianne, Lafaille‐Magnan, Marie‐Élyse, Savard, Mélissa, Tuwaig, Miranda, Petkova, Mirela, Rioux, Pierre, Meyer, P.T., El‐Khoury, Rana, Gordon, Renee, Giles, Renuka, Das, Samir, Wang, Seqian, Tabrizi, Shirin , Mathotaarachchi, Sulantha , Dubuc, Sylvie, Lee, Tanya , Beaudry, Thomas, Gervais, Valérie, Pagé, Véronique, Desautels, René, Benbouhoud, Fatiha, Saint‐Fort, Eunice Farah, Verfaillie, Sander C.J. , Farzin, Sarah , Salaciak, Alyssa , Tullo, Stéphanie , Daoust, Leslie‐Ann, Köbe, Theresa , McSweeney, Melissa, Nilsson, Nathalie , Pishnamazi, Morteza, Bedetti, Christophe , Hudon, Louise, Greco, Claudia, Chapleau, Marianne , St‐Onge, Frédéric , Boutin, Sophie , Geddes, Maiya R. , Ducharme, Simon , Jean, Gabriel, Sylvain, Elisabeth, Élie, Marie‐Josee, Leblond‐Baccichet, Gloria, Soucy, Jean‐Paul , Ozlen, Hazal , Bailly, Julie, Mohammediyan, Béry, Chen, Yalin , Remz, Jordana, Rentz, Dorene M., Amariglio, Rebecca E. , Blacker, Deborah , Chhatwal, Jasmeer P. , Dickerson, Brad C., Donovan, Nancy J. , Farrell, Michelle E. , Gómez, Cristina Lois, Marshall, Gad A. , Oaoo, Kate, Price, Julie, Prokopiou, Prokopis C. , Reynolds, Gretchen , Skylar-Scott, Irina A., Vila‐Castelar, Clara , Yang, Hyun‐Sik , Trojanowki, John Q., Green, Robert C, Perrin, Richard J. , Shaw, Leslie M. , Potter, William Z. , Bernard, Marie , Jackson, Jonathan, Masliah, Eliezer , Masterman, Donna, Okonkwo, Ozioma, Ryan, Laurie, Silverberg, Nina, Fleisher, Adam , Fockler, Juliet , Conti, Cat, Jin, Chengshi , Nosheny, Rachel L. , Ashford, Mariam, Flenniken, Derek , Kormos, Adrienne, Montine, Tom, Rafii, Michael, Raman, Rema , Gessert, Devon, Salazar, Jennifer, Zimmerman, Caileigh, Cabrera, Yuliana, Walter, Sarah , Miller, Garrett, Coker, Godfrey, Clanton, Taylor, Hergesheimer, Lindsey, Smith, Stephanie , Adegoke, Olusegun, Mahboubi, Payam, Moore, Shelley, Pizzola, Jeremy, Shaffer, Elizabeth , Harvey, Danielle, Forghanian-Arani, Arvin, Borowski, Bret, Ward, Chad, Gunter, Jeff, Kantarci, Kejal, Thompson, Paul , Jahanshad, Neda , DeCarli, Charles , Knaack, Alexander , Fletcher, Evan, Chen, Stephanie R, Choe, Mark, Crawford, Karen , Yuschkevich, Paul A, Reiman, Eric M. , Mathis, Chet, Landau, Susan , Cairns, Nigel J. , Householder, Erin, Franklin, Erin , Bernhardt, Haley, Taylor‐Reinwald, Lisa, Korecka, Magdalena , Figurski, Michal, Neu, Scott, Nho, Kwangsik, Foroud, Tatiana M., Faber, Kelley , Wilmes, Kristi, Thal, Leon J., Dage, Jeffrey L. , Eloyan, Ani , Hammers, Dustin B. , Kirby, Kala, Kramer, Joel, Legarde, Julien, Murray, Melissa E., Newell, Kathy L. , Taurone, Alexander, Thangarajah, Maryanne, Touroutoglou, Alexandra , Clark, David , Day, Gregory S, Duara, Ranjan , Graff-Radford, Neill R, Grant, Ian , Masdeu, Joseph C. , Mendez, Mario F. , Onyike, Chiadi U. , Riddle, Meghan , Rogalskı, Emily , Salloway, Steven, Sha, Sharon J. , Carrillo, María C. , O'Brien, John Tiernan , Jack, Clifford R , Schöll, Michael , La Joie, Renaud , Rabinovici, Gil D , Dage, Jeffrey L , Rial, Alexis Moscoso , Heeman, Fiona , Raghavan, Sheelakumari , Essen, Martijn van , Camacho, Valle , Silva‐Rodríguez, Jesús , Ribaldi, Federica , Coomans, Emma M. , Brum, Wagner Scheeren , Grothe, Michel J. , Drzezga, Alexander E. , Malpetti, Maura , Rowe, James B. , Giessen, Elsmarieke van de , Ossenkoppele, Rik , Smith, Ruben , Hansson, Oskar , Garibotto, Valentina , Dickerson, Bradford Clark , LaMontagne, Pamela , Sperling, Reisa Anne , Vemuri, Prashanthi , Tam, Angela , Binette, Alexa Pichet , Dansereau, Christian , Picard, Cynthia , Michaud, Diane, Couture, Doris, Cuello, A. Claudio , Barkun, Alan , Evans, Alan Charles , Tardif, Christine Lucas , Knopman, David S. , Near, Jamie , Leoutsakos, Jeannie‐Marie , Brandt, Jason , Pruessner, Jens C. , Morris, John C. , Collins, D. Louis , Chakravarty, M. Mallar , Eisenberg, Mark Jeffrey , Rajah, Maria Natasha , Rosa-Neto, Pedro , Bellec, Pierre , Thomas, Ronald, Fonov, Vladimir , Vallee, Isabelle, Vogel, Jacob W. , Dadar, Mahsa , Appleby, Melissa , Meyer, Pierre‐François, Gonneaud, Julie , Pascoal, Tharick Ali , Vachon‐Presseau, Étienne , Spreng, R. Nathan , Rentz, Dorene M. , Buckley, Rachel F. , Gagliardi, Geoffroy Pierre , Gatchel, Jennifer R. , Guzmán‐Vélez, Edmarie , Jacobs, Heidi I.L. , Jutten, Roos J. , Pardilla‐Delgado, Enmanuelle , Price, Julie C. , Quiroz, Yakeel T. , Schultz, Aaron P. , Schultz, Stephanie A. , Sepulcre, Jorge , Vannini, Patrizia , Toga, Arthur W. , Beckett, Laurel , Saykin, Andrew J. , Potter, William, Barnes, Lisa L. , Gonzalez, Hector, Ho, Carole , Hsiao, John , Jackson, Jonathan , Veitch, Dallas P. , Neuhaus, John M , Rafii, Michael S. , Jimenez‐Maggiora, Gustavo Adolfo , Donohue, Michael , Arani, Arvin , Schwarz, Christopher G. , Jones, David T. , Kantarci, Kejal , Senjem, Matthew L. , Reid, Robert I. , Fox, Nick C. , Malone, Ian B. , Thomopoulos, Sophia I. , Nir, Talia M. , Tosun, Duygu , Das, Sandhitsu R. , Koeppe, Robert A. , Chen, Kewei , Risacher, Shannon L. , Shen, Li , Nudelman, Kelly , Ghetti, Bernardino , Grinberg, Lea T. , Hammers, Dustin B , Kirby, Kala, Kukull, Walter A. , Murray, Melissa E. , Polsinelli, Angelina J. , Atri, Alireza , Duara, Ranjan , Graff‐Radford, Neill R. , Honig, Lawrence S. , Johnson, Erik C. B. , Masdeu, Joseph C , Musiek, Erik , Salloway, Steve , Turner, Raymond Scott , Wingo, Thomas S , Wolk, S. J. , Womack, Kyle

Mayo Clinic

JAMA | June 16, 2025 | Volume: 334 | Issue: 3 | Pages: 229

10.1001/jama.2025.7817 | PMID 40522652 Get It

Importance Tau positron emission tomography (PET) allows in vivo detection of neurofibrillary tangles, a core neuropathologic feature of Alzheimer disease (AD). Objective To provide estimates of the frequency of tau PET positivity and its associated risk of clinical outcomes. Design, Setting, and Participants Longitudinal study using data pooled from 21 cohorts, comprising a convenience sample of 6514 participants from 13 countries, collected between January 2013 and June 2024. Cognitively unimpaired individuals and patients with a clinical diagnosis of mild cognitive impairment (MCI), AD dementia, or other neurodegenerative disorders were included. Exposures Tau PET with flortaucipir F 18, amyloid-β (Aβ) PET, and clinical examinations. Tau PET scans were visually rated as positive according to a US Food and Drug Administration– and European Medicines Agency–approved method, designed to indicate the presence of advanced neurofibrillary tangle pathology (Braak stages V-VI). Main Outcomes and Measures Frequency of tau PET positivity and absolute risk of clinical progression (eg, progression to MCI or dementia). Results Among the 6514 participants (mean age, 69.5 years; 50.5% female), median follow-up time ranged from 1.5 to 4.0 years. Of 3487 cognitively unimpaired participants, 349 (9.8%) were tau PET positive; the estimated frequency of tau PET positivity was less than 1% in those aged younger than 50 years, and increased from 3% (95% CI, 2%-4%) at 60 years to 19% (95% CI, 16%-24%) at 90 years. Tau PET positivity frequency estimates increased across MCI and AD dementia clinical diagnoses (43% [95% CI, 41%-46%] and 79% [95% CI, 77%-82%] at 75 years, respectively). Most tau PET–positive individuals (92%) were also Aβ PET positive. Cognitively unimpaired participants who were positive for both Aβ PET and tau PET had a higher absolute risk of progression to MCI or dementia over the following 5 years (57% [95% CI, 45%-71%]) compared with both Aβ PET–positive/tau PET–negative (17% [95% CI, 13%-22%]) and Aβ PET–negative/tau PET–negative (6% [95% CI, 5%-8%]) individuals. Among participants with MCI at the time of the tau PET scan, an Aβ PET–positive/tau PET–positive profile was associated with a 5-year absolute risk of progression to dementia of 70% (95% CI, 59%-81%). Conclusions and Relevance In a large convenience sample, a positive tau PET scan occurred at a nonnegligible rate among cognitively unimpaired individuals, and the combination of Aβ PET positivity and tau PET positivity was associated with a high risk of clinical progression in both preclinical and symptomatic stages of AD. These findings underscore the potential of tau PET as a biomarker for staging AD pathology.
Disruption of Microhomology-mediated End-joining in Ewing Sarcoma
Asada, Shuhei , Tanaka, Yutaro , Abeykoon, Jithma Prasad, Tanaka, Yutaro , Mukkavalli, Sirisha , Busso, Miles Del, Thangaiah, Judith Jebastin, Van Allen, Eliezer M , Shapiro, Geoffrey I , D'Andrea, Alan , Zhu, Guangli, Abeykoon, Jithma P. , Nguyen, Huy, Hirohashi, Yuna, Iyer, Divya , Ashton, Nicholas William , Mukkavalli, Sirisha , Velazquez, Martha, Jiang, Lige, Robinson, Steven I. , Parmar, Kalindi , Gillani, Riaz , Shapiro, Geoffrey I.

Mayo Clinic

No container title available | May 10, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1101/2025.05.06.651696 | PMID 40568108 Get It

SUMMARY Ewing sarcoma (EwS) is a group of bone and soft tissue cancers in children and young adults. Since EwS cells have pronounced sensitivity to radiation and chemotherapy-induced DNA damage, the role of the oncoprotein, EWS-FLI1, in DNA repair is likely. Here, we demonstrate that EWS-FLI1 causes a defect in microhomology-mediated end-joining (MMEJ) repair. EWSR1 is a splicing factor that promotes the faithful splicing of the POLQ pre-mRNA, required for the expression of POLΘ, a critical protein in the MMEJ pathway. Expression of EWS-FLI1, or loss of EWSR1, causes exon 25 skipping of the POLQ transcript, decreased POLΘ expression, impaired MMEJ, and cellular sensitivity to inhibitors of the Fanconi Anemia (FA), NHEJ, or HR pathways, through the mechanism of synthetic lethality. Knockdown of EWS-FLI1 expression restores POL0 mitotic foci and increases MMEJ activity. Inhibitors of the FA, NHEJ, or HR therefore may provide a targeted therapy for patients with EwS. Highlights - Ewing sarcoma tumors have a deficiency in POLθ expression and a corresponding loss of MMEJ activity - EWSR1 is a splicing factor that interacts with other splicing factors such as FUBP1 and KHSRP/FUBP2 to accurately splice the POLQ mRNA. - The EWS-FLI1 fusion oncoprotein, or loss of EWSR1, causes a splicing defect, leading to exon25 skipping of the POLQ pre-mRNA and loss of POLθ expression - The MMEJ deficiency of EwS cells results in cellular sensitivity to inhibitors of Fanconi Anemia, Homologous Recombination or Non-Homologous End-Joining - Exon 25 skipping of POLQ mRNA is a predictive biomarker for HR inhibitors in human cancers
Cyclin D1 Overexpression in Mantle Cell Lymphoma Causes Cellular Dependence on Microhomology-Mediated End-Joining
Abeykoon, Jithma P. , Zu, Guangli, Hirohashi, Yuna, Parmar, Kalindi , Jiang, Lige, Mukkavalli, Sirisha , Wu, Xiaosheng , Gwin, Kimberly, D’Andrea, Alan D. , D'Andrea, Alan , Asada, Shuhei , Iyer, Divya , Yi, Dongni , Manske, Michelle K. , Witzig, Thomas E. , Shapiro, Geoffrey I.

Mayo Clinic

Blood | December 6, 2024 | Volume: 144 | Issue: Supplement 1 | Pages: 2747-2747

10.1182/blood-2024-205197 Get It

Oncoprotein-driven human cancers exhibit replication stress (RS), leading to an increase in DNA double-strand breaks (DSB). These DSBs are repaired by one of the three main pathways - homologous recombination repair (HR), non-homologous end-joining (NHEJ), and microhomology-mediated end joining (MMEJ). Cyclin D1 (CCND1) is one of the most overexpressed oncoproteins and is universally overexpressed in mantle cell lymphoma (MCL). While CCND1 overexpression drives cells into the S-phase, its specific effects on RS and DSB repair pathways are poorly understood. Here, we investigated the impact of CCND1 overexpression on RS and DSB repair mechanisms in MCL. First, the expression level of CCND1 positively correlated with heightened RS, as indicated by elevated p-RPA-S33 and p-RPA S8 levels, and increased DNA damage, assessed by g-H2AX, especially in the mitotic phase, across diverse cell models, including MCL. Since CCND1-overexpressed cells proliferate rapidly, we hypothesized that some DNA repair pathways might be upregulated to meet the demand for repairing the excess RS-driven DSBs. Reporter assays demonstrated that the MMEJ pathway was specifically upregulated upon CCND1 overexpression, whereas no significant changes were observed in the HR and NHEJ pathways. Furthermore, CRISPR interference (CRISPRi)-mediated knockdown of CCND1 in MCL cells led to a significant reduction in MMEJ activity. This finding suggests the specificity of CCND1 in mediating the upregulation of the MMEJ pathway. Consistent with this, increased MMEJ activity, assessed via foci formation and immunoblotting of DNA polymerase theta expression (POLQ, encoded by POLQ gene), the primary polymerase for the MMEJ pathway, correlated with CCND1 overexpression, suggesting the crucial role of MMEJ in DSB repair processes under CCND1-overexpressed conditions. Sincethe MMEJ pathwayplays a pivotal role in repairing DSB during mitosis, we assessed the dependency of MCL cells on MMEJ-mediated DSB repair for cell survival. As expected, genetic deletion or pharmacological inhibition (ART558 and novobiocin) of POLQ in MCL cells led to increased RS and increased unrepaired DNA damage during mitosis, ultimately leading to chromosomal instability, mitotic catastrophe, and apoptosis. Additionally, the deficiency of POLQ in MCL cells resulted in increased levels of single-strand DNA, another critical biomarker for RS. Second, we found that ATM deficiency, the second most common genetic alteration after CCND1 overexpression in MCL, further increased the cellular dependence on MMEJ. Interestingly, the accumulation of unrepaired DNA damage during mitosis was notably increased in ATM-deficient CCND1-overexpressed cells. When POLQ was inhibited, a significant antitumor effect was evident in MCL cells, including ibrutinib-resistant MCL, both in vitro and in vivo, and this effect was enhanced by ATM deficiency. Further, simultaneous inhibition of both ATM (AZD0156) and POLQ was synthetic lethal in MCL cell lines and primary tumor cells from patients with MCL. Mechanistically, we observed the direct binding of CCND1 to the POLQ promoter and a corresponding upregulation of POLQ mRNA in CCND1-overexpressing cells. Consistently, a significant overexpression of POLQ mRNA was observed in primary MCL cells, compared to other non-Hodgkin lymphoma cells without CCND1 overexpression. Moreover, the positive correlation between POLQ and CCND1 expression was further validated using syngeneic B-lymphoma cells with and without CCND1 overexpression. Importantly, CRISPRi-mediated CCND1 knockdown reduced POLQ mRNA expression and the dependency of MCL cells on the MMEJ pathway for survival. In addition, ATM deficiency showed a further increase of endogenous POLQ expression and foci formation in cells with CCND1 overexpression, suggesting ATM negatively regulates the MMEJ pathway, especially in the CCND1 overexpressed background. In summary, CCND1 overexpression leads to a substantial increase in RS, intensifying the reliance on MMEJ-mediated mitotic DSB repair. Within MCL, POLQ is crucial in mitigating the adversities of CCND1-driven RS. Our data suggest that targeting the MMEJ pathway via POLQ inhibition, particularly in the presence of CCND1 overexpression and ATM deficiency, emerges as a promising therapeutic approach in oncoprotein-driven hematologic malignancies such as MCL.
Abstract 4396: Multiomics assessment of the cancer and stromal compartments of patient-derived pancreatic xenografts reveals clinically-relevant subtypes and novel targeted therapies
Marisa, Laëtitia , Loncle, Céline, Gayet, Odile , Moutardier, Vincent, Giovannini, Marc, Bian, Benjamin , Bigonnet, Martin , Rubis, Marion , Elarouci, Nabila , Armenoult, Lucile, Duconseil, Pauline , Ouaïssi, Mehdi , Maignan, Aurélie, Lomberk, Gwen , Ewald, Jacques , Bories, Erwan, Gonçalves, Anthony , Secq, Véronique, Garcia, Stéphane, Grandval, Philippe , Barraud-Blanc, Marine, Norguet, Emmanuelle, Gilabert, Marine , Roques, Julie, Calvo, Ézéquiel, Vasseur, Sophie , Reyniès, Aurélien de , Nicolle, Rémy , Blum, Yuna , Turrini, Olivıer , Ayadi, Mira , Gasmi, Mohamed , Boher, Jean‐Marie , Garnier, Jonathan , Poizat, Flora , Raoul, Jean‐Luc , Delpéro, Jean‐Robert , Guillaumond, Fabienne , Urrutia, Raúl , Dusetti, Nelson , Iovanna, Juan , Lomberk, Gwen L , de Reynies, Aurélien

Mayo Clinic

Cancer Research | July 31, 2017 | Volume: 77 | Issue: 13_Supplement | Pages: 4396-4396

10.1158/1538-7445.am2017-4396 Get It

Abstract Patient-derived xenografts (PDX) are appearing as a prime approach for preclinical studies despite being insufficiently characterized as a model of the human disease and its diversity. In this work, 29 PDX were obtained from either surgery or endoscopic ultrasound-guided fine needle aspirate of pancreatic adenocarcinoma. The extensive genomic profiling of these pancreatic PDX, revealed two clinically-relevant subtypes having broad similarities with human primary tumors. These subtypes are defined by highly specific DNA methylation and transcriptomic profiles (mRNA, miRNA or lncRNA) but are not distinguishable by exonic mutations or copy number aberrations. Moreover, by specifically analyzing the stroma transcriptome, as defined by the expression of murine transcripts, we found that it is able to stratify the patients with the same efficiency than the analysis of grafted human tumor cells. This finding suggest that transformed pancreatic cells drive the composition of their own stroma. Finally, the multiomics analysis pinpoints novel therapeutic targets, one of which we demonstrate to be an efficient method for treating pancreatic cancer. Overall, we show that PDX are trustworthy pre-clinical models of pancreatic adenocarcinoma including of unresectable tumors. Their multiomics profiling allow the independent analysis of the uncontaminated cancer or stromal compartments and discloses several original therapeutics targets. Citation Format: Remy Nicolle, Yuna Blum, Laetitia Marisa, Celine Loncle, Odile Gayet, Vincent Moutardier, Olivier Turrini, Marc Giovannini, Benjamin Bian, Martin Bigonnet, Marion Rubis, Nabila Elarouci, Lucile Armenoult, Mira Ayadi, Pauline Duconseil, Mohamed Gasmi, Mehdi Ouaissi, Aurélie Maignan, Gwen Lomberk, Jean-Marie Boher, Jacques Ewald, Erwan Bories, Jonathan Garnier, Anthony Goncalves, Flora Poizat, Jean-Luc Raoul, Veronique Secq, Stephane Garcia, Philippe Grandval, Marine Barraud-Blanc, Emmanuelle Norguet, Marine Gilabert, Jean-Robert Delpero, Julie Roques, Ezequiel Calvo, Fabienne Guillaumond, Sophie Vasseur, Raul Urrutia, Aurélien de Reyniès, Nelson Dusetti, Juan Iovanna. Multiomics assessment of the cancer and stromal compartments of patient-derived pancreatic xenografts reveals clinically-relevant subtypes and novel targeted therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4396. doi:10.1158/1538-7445.AM2017-4396