1
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Capp JP, Catania F, Thomas F. From genetic mosaicism to tumorigenesis through indirect genetic effects. Bioessays 2024:e2300238. [PMID: 38736323 DOI: 10.1002/bies.202300238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 04/19/2024] [Accepted: 04/22/2024] [Indexed: 05/14/2024]
Abstract
Genetic mosaicism has long been linked to aging, and several hypotheses have been proposed to explain the potential connections between mosaicism and susceptibility to cancer. It has been proposed that mosaicism may disrupt tissue homeostasis by affecting intercellular communications and releasing microenvironmental constraints within tissues. The underlying mechanisms driving these tissue-level influences remain unidentified, however. Here, we present an evolutionary perspective on the interplay between mosaicism and cancer, suggesting that the tissue-level impacts of genetic mosaicism can be attributed to Indirect Genetic Effects (IGEs). IGEs can increase the level of cellular stochasticity and phenotypic instability among adjacent cells, thereby elevating the risk of cancer development within the tissue. Moreover, as cells experience phenotypic changes in response to challenging microenvironmental conditions, these changes can initiate a cascade of nongenetic alterations, referred to as Indirect non-Genetic Effects (InGEs), which in turn catalyze IGEs among surrounding cells. We argue that incorporating both InGEs and IGEs into our understanding of the process of oncogenic transformation could trigger a major paradigm shift in cancer research with far-reaching implications for practical applications.
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Affiliation(s)
- Jean-Pascal Capp
- Toulouse Biotechnology Institute, INSA/University of Toulouse, CNRS, INRAE, Toulouse, France
| | - Francesco Catania
- Institute of Environmental Radioactivity, Fukushima University, Kanayagawa, Fukushima, Japan
| | - Frédéric Thomas
- CREEC, UMR IRD 224-CNRS 5290-University of Montpellier, Montpellier, France
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2
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Zhang W, Zhang K, Shi J, Qiu H, Kan C, Ma Y, Hou N, Han F, Sun X. The impact of the senescent microenvironment on tumorigenesis: Insights for cancer therapy. Aging Cell 2024; 23:e14182. [PMID: 38650467 PMCID: PMC11113271 DOI: 10.1111/acel.14182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 04/11/2024] [Accepted: 04/15/2024] [Indexed: 04/25/2024] Open
Abstract
The growing global burden of cancer, especially among people aged 60 years and over, has become a key public health issue. This trend suggests the need for a deeper understanding of the various cancer types in order to develop universally effective treatments. A prospective area of research involves elucidating the interplay between the senescent microenvironment and tumor genesis. Currently, most oncology research focuses on adulthood and tends to ignore the potential role of senescent individuals on tumor progression. Senescent cells produce a senescence-associated secretory phenotype (SASP) that has a dual role in the tumor microenvironment (TME). While SASP components can remodel the TME and thus hinder tumor cell proliferation, they can also promote tumorigenesis and progression via pro-inflammatory and pro-proliferative mechanisms. To address this gap, our review seeks to investigate the influence of senescent microenvironment changes on tumor development and their potential implications for cancer therapies.
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Affiliation(s)
- Wenqiang Zhang
- Department of Endocrinology and Metabolism, Clinical Research Center, Shandong Provincial Key Medical and Health Discipline of EndocrinologyAffiliated Hospital of Shandong Second Medical UniversityWeifangChina
- Department of PathologyAffiliated Hospital of Shandong Second Medical UniversityWeifangChina
| | - Kexin Zhang
- Department of Endocrinology and Metabolism, Clinical Research Center, Shandong Provincial Key Medical and Health Discipline of EndocrinologyAffiliated Hospital of Shandong Second Medical UniversityWeifangChina
| | - Junfeng Shi
- Department of Endocrinology and Metabolism, Clinical Research Center, Shandong Provincial Key Medical and Health Discipline of EndocrinologyAffiliated Hospital of Shandong Second Medical UniversityWeifangChina
| | - Hongyan Qiu
- Department of Endocrinology and Metabolism, Clinical Research Center, Shandong Provincial Key Medical and Health Discipline of EndocrinologyAffiliated Hospital of Shandong Second Medical UniversityWeifangChina
| | - Chengxia Kan
- Department of Endocrinology and Metabolism, Clinical Research Center, Shandong Provincial Key Medical and Health Discipline of EndocrinologyAffiliated Hospital of Shandong Second Medical UniversityWeifangChina
| | - Yujie Ma
- Department of Endocrinology and Metabolism, Clinical Research Center, Shandong Provincial Key Medical and Health Discipline of EndocrinologyAffiliated Hospital of Shandong Second Medical UniversityWeifangChina
| | - Ningning Hou
- Department of Endocrinology and Metabolism, Clinical Research Center, Shandong Provincial Key Medical and Health Discipline of EndocrinologyAffiliated Hospital of Shandong Second Medical UniversityWeifangChina
| | - Fang Han
- Department of Endocrinology and Metabolism, Clinical Research Center, Shandong Provincial Key Medical and Health Discipline of EndocrinologyAffiliated Hospital of Shandong Second Medical UniversityWeifangChina
- Department of PathologyAffiliated Hospital of Shandong Second Medical UniversityWeifangChina
| | - Xiaodong Sun
- Department of Endocrinology and Metabolism, Clinical Research Center, Shandong Provincial Key Medical and Health Discipline of EndocrinologyAffiliated Hospital of Shandong Second Medical UniversityWeifangChina
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3
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Zhang L, Deeb G, Deeb KK, Vale C, Peker Barclift D, Papadantonakis N. Measurable (Minimal) Residual Disease in Myelodysplastic Neoplasms (MDS): Current State and Perspectives. Cancers (Basel) 2024; 16:1503. [PMID: 38672585 PMCID: PMC11048433 DOI: 10.3390/cancers16081503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Revised: 04/08/2024] [Accepted: 04/10/2024] [Indexed: 04/28/2024] Open
Abstract
Myelodysplastic Neoplasms (MDS) have been traditionally studied through the assessment of blood counts, cytogenetics, and morphology. In recent years, the introduction of molecular assays has improved our ability to diagnose MDS. The role of Measurable (minimal) Residual Disease (MRD) in MDS is evolving, and molecular and flow cytometry techniques have been used in several studies. In this review, we will highlight the evolving concept of MRD in MDS, outline the various techniques utilized, and provide an overview of the studies reporting MRD and the correlation with outcomes.
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Affiliation(s)
- Linsheng Zhang
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - George Deeb
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Kristin K. Deeb
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Colin Vale
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory University, Atlanta, GA 30322, USA
| | - Deniz Peker Barclift
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Nikolaos Papadantonakis
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory University, Atlanta, GA 30322, USA
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4
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Zand H, Pourvali K. The Function of the Immune System, Beyond Strategies Based on Cell-Autonomous Mechanisms, Determines Cancer Development: Immune Response and Cancer Development. Adv Biol (Weinh) 2024; 8:e2300528. [PMID: 38221702 DOI: 10.1002/adbi.202300528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 12/09/2023] [Indexed: 01/16/2024]
Abstract
Although cancer remains a challenging disease to treat, early detection and removal of primary tumors through surgery or chemotherapy/radiotherapy can offer hope for patients. The privilege paradigm in cancer biology suggests that cell-autonomous mechanisms play a central role in tumorigenesis. According to this paradigm, these cellular mechanisms are the primary focus for the prevention and treatment of cancers. However, this point of view does not present a comprehensive theory for the initiation of cancer and an effective therapeutic strategy. Having an incomplete understanding of the etiology of cancer, it is essential to re-examine previous assumptions about carcinogenesis and develop new, practical theories that can account for all available clinical and experimental evidence. This will not only help to gain a better understanding of the disease, but also offer new avenues for treatment. This review provides evidence suggesting a shift in focus from a cell-autonomous mechanism to systemic mechanisms, particularly the immune system, that are involved in cancer formation.
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Affiliation(s)
- Hamid Zand
- Department of Cellular and Molecular Nutrition, Faculty of Nutrition Science and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, 1981619573, Iran
| | - Katayoun Pourvali
- Department of Cellular and Molecular Nutrition, Faculty of Nutrition Science and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, 1981619573, Iran
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5
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Alejandre C, Calle-Espinosa J, Iranzo J. Synergistic epistasis among cancer drivers can rescue early tumors from the accumulation of deleterious passengers. PLoS Comput Biol 2024; 20:e1012081. [PMID: 38687804 PMCID: PMC11087069 DOI: 10.1371/journal.pcbi.1012081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 05/10/2024] [Accepted: 04/16/2024] [Indexed: 05/02/2024] Open
Abstract
Epistasis among driver mutations is pervasive and explains relevant features of cancer, such as differential therapy response and convergence towards well-characterized molecular subtypes. Furthermore, a growing body of evidence suggests that tumor development could be hampered by the accumulation of slightly deleterious passenger mutations. In this work, we combined empirical epistasis networks, computer simulations, and mathematical models to explore how synergistic interactions among driver mutations affect cancer progression under the burden of slightly deleterious passengers. We found that epistasis plays a crucial role in tumor development by promoting the transformation of precancerous clones into rapidly growing tumors through a process that is analogous to evolutionary rescue. The triggering of epistasis-driven rescue is strongly dependent on the intensity of epistasis and could be a key rate-limiting step in many tumors, contributing to their unpredictability. As a result, central genes in cancer epistasis networks appear as key intervention targets for cancer therapy.
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Affiliation(s)
- Carla Alejandre
- Centro de Astrobiología (CAB) CSIC-INTA, Torrejón de Ardoz, Madrid, Spain
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM)—Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), Madrid, Spain
| | - Jorge Calle-Espinosa
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM)—Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), Madrid, Spain
| | - Jaime Iranzo
- Centro de Astrobiología (CAB) CSIC-INTA, Torrejón de Ardoz, Madrid, Spain
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM)—Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), Madrid, Spain
- Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, Zaragoza, Spain
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6
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Deng S, Gong H, Zhang D, Zhang M, He X. A statistical method for quantifying progenitor cells reveals incipient cell fate commitments. Nat Methods 2024; 21:597-608. [PMID: 38379073 DOI: 10.1038/s41592-024-02189-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 01/19/2024] [Indexed: 02/22/2024]
Abstract
Quantifying the number of progenitor cells that found an organ, tissue or cell population is of fundamental importance for understanding the development and homeostasis of a multicellular organism. Previous efforts rely on marker genes that are specifically expressed in progenitors. This strategy is, however, often hindered by the lack of ideal markers. Here we propose a general statistical method to quantify the progenitors of any tissues or cell populations in an organism, even in the absence of progenitor-specific markers, by exploring the cell phylogenetic tree that records the cell division history during development. The method, termed targeting coalescent analysis (TarCA), computes the probability that two randomly sampled cells of a tissue coalesce within the tissue-specific monophyletic clades. The inverse of this probability then serves as a measure of the progenitor number of the tissue. Both mathematic modeling and computer simulations demonstrated the high accuracy of TarCA, which was then validated using real data from nematode, fruit fly and mouse, all with related cell phylogenetic trees. We further showed that TarCA can be used to identify lineage-specific upregulated genes during embryogenesis, revealing incipient cell fate commitments in mouse embryos.
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Affiliation(s)
- Shanjun Deng
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China
| | - Han Gong
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China
| | - Di Zhang
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China
| | - Mengdong Zhang
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China
| | - Xionglei He
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China.
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7
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Ohno M, Takano N, Hidaka K, Sasaki F, Yamauchi K, Aoki Y, Nohmi T, Nakabeppu Y, Nakatsu Y, Tsuzuki T. Oxidative stress accelerates intestinal tumorigenesis by enhancing 8-oxoguanine-mediated mutagenesis in MUTYH-deficient mice. Genome Res 2024; 34:47-56. [PMID: 38290979 PMCID: PMC10904009 DOI: 10.1101/gr.278326.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 01/02/2024] [Indexed: 02/01/2024]
Abstract
Oxidative stress-induced DNA damage and its repair systems are related to cancer etiology; however, the molecular basis triggering tumorigenesis is not well understood. Here, we aimed to explore the causal relationship between oxidative stress, somatic mutations in pre-tumor-initiated normal tissues, and tumor incidence in the small intestines of MUTYH-proficient and MUTYH-deficient mice. MUTYH is a base excision repair enzyme associated with human colorectal cancer. Mice were administered different concentrations of potassium bromate (KBrO3; an oxidizing agent)-containing water for 4 wk for mutagenesis studies or 16 wk for tumorigenesis studies. All Mutyh -/- mice treated with >0.1% KBrO3 developed multiple tumors, and the average tumor number increased dose dependently. Somatic mutation analysis of Mutyh -/-/rpsL transgenic mice revealed that G:C > T:A transversion was the only mutation type correlated positively with KBrO3 dose and tumor incidence. These mutations preferentially occurred at 5'G in GG and GAA sequences in rpsL This characteristic mutation pattern was also observed in the genomic region of Mutyh -/- tumors using whole-exome sequencing. It closely corresponded to signature 18 and SBS36, typically caused by 8-oxo-guanine (8-oxoG). 8-oxoG-induced mutations were sequence context dependent, yielding a biased amino acid change leading to missense and stop-gain mutations. These mutations frequently occurred in critical amino acid codons of known cancer drivers, Apc or Ctnnb1, known for activating Wnt signal pathway. Our results indicate that oxidative stress contributes to increased tumor incidence by elevating the likelihood of gaining driver mutations by increasing 8-oxoG-mediated mutagenesis, particularly under MUTYH-deficient conditions.
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Affiliation(s)
- Mizuki Ohno
- Department of Medical Biophysics and Radiation Biology, Faculty of Medical Sciences, Kyushu University, Fukuoka, Fukuoka 812-8582, Japan;
| | - Noriko Takano
- Department of Medical Biophysics and Radiation Biology, Faculty of Medical Sciences, Kyushu University, Fukuoka, Fukuoka 812-8582, Japan
| | - Kyoko Hidaka
- Department of Medical Biophysics and Radiation Biology, Faculty of Medical Sciences, Kyushu University, Fukuoka, Fukuoka 812-8582, Japan
- Center for Fundamental Education, The University of Kitakyushu, Kitakyushu, Fukuoka 802-8577, Japan
| | - Fumiko Sasaki
- Department of Medical Biophysics and Radiation Biology, Faculty of Medical Sciences, Kyushu University, Fukuoka, Fukuoka 812-8582, Japan
| | - Kazumi Yamauchi
- Department of Medical Biophysics and Radiation Biology, Faculty of Medical Sciences, Kyushu University, Fukuoka, Fukuoka 812-8582, Japan
- Department of Radiobiology, Institute for Environmental Sciences, Kamikita, Aomori 039-3212, Japan
| | - Yasunobu Aoki
- Health and Environmental Risk Division, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan
| | - Takehiko Nohmi
- Division of Genetics and Mutagenesis, National Institute of Health Sciences, Kawasaki, Kanagawa 210-9501, Japan
| | - Yusaku Nakabeppu
- Division of Neurofunctional Genomics, Department of Immunobiology and Neuroscience, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Fukuoka 812-8582, Japan
- Japan Society for the Promotion of Science, San Francisco Office, Berkeley, California 94704, USA
| | - Yoshimichi Nakatsu
- Department of Medical Biophysics and Radiation Biology, Faculty of Medical Sciences, Kyushu University, Fukuoka, Fukuoka 812-8582, Japan
| | - Teruhisa Tsuzuki
- Department of Medical Biophysics and Radiation Biology, Faculty of Medical Sciences, Kyushu University, Fukuoka, Fukuoka 812-8582, Japan
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8
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Pagliuca S, Ferraro F. Immune-driven clonal cell selection at the intersection among cancer, infections, autoimmunity and senescence. Semin Hematol 2024; 61:22-34. [PMID: 38341340 DOI: 10.1053/j.seminhematol.2024.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Revised: 12/14/2023] [Accepted: 01/02/2024] [Indexed: 02/12/2024]
Abstract
Immune surveillance mechanisms play a crucial role in maintaining lifelong immune homeostasis in response to pathologic stimuli and aberrant cell states. However, their persistence, especially in the context of chronic antigenic exposure, can create a fertile ground for immune evasion. These escaping cell phenotypes, harboring a variety of genomic and transcriptomic aberrances, chiefly in human leukocyte antigen (HLA) and antigen presentation machinery genes, may survive and proliferate, featuring a scenario of clonal cell expansion with immune failure characteristics. While well characterized in solid and, to some extent, hematological malignancies, little is known about their occurrence and significance in other disease contexts. Historical literature highlights the role for escaping HLA-mediated recognition as a strategy adopted by virus to evade from the immune system, hinting at the potential for immune aberrant cell expansion in the context of chronic infections. Additionally, unmasked in idiopathic aplastic anemia as a mechanism able to rescue failing hematopoiesis, HLA clonal escape may operate in autoimmune disorders, particularly in tissues targeted by aberrant immune responses. Furthermore, senescent cell status emerging as immunogenic phenotypes stimulating T cell responses, may act as a bottleneck for the selection of such immune escaping clones, blurring the boundaries between neoplastic transformation, aging and inflammation. Here we provide a fresh overview and perspective on this immune-driven clonal cell expansion, linking pathophysiological features of neoplastic, autoimmune, infectious and senescence processes exposed to immune surveillance.
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Affiliation(s)
- Simona Pagliuca
- Hematology Department, Nancy University Hospital and UMR7365, IMoPA, University of Lorraine, Vandoeuvre-lès-Nancy, France.
| | - Francesca Ferraro
- Division of Oncology, Department of Internal Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO
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Abudahab S, Slattum PW, Price ET, McClay JL. Epigenetic regulation of drug metabolism in aging: utilizing epigenetics to optimize geriatric pharmacotherapy. Pharmacogenomics 2024; 25:41-54. [PMID: 38126340 PMCID: PMC10794944 DOI: 10.2217/pgs-2023-0199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023] Open
Abstract
We explore the relationship between epigenetic aging and drug metabolism. We review current evidence for changes in drug metabolism in normal aging, followed by a description of how epigenetic modifications associated with age can regulate the expression and functionality of genes. In particular, we focus on the role of epigenome-wide studies of human and mouse liver in understanding these age-related processes with respect to xenobiotic processing. We highlight genes encoding drug metabolizing enzymes and transporters revealed to be affected by epigenetic aging in these studies. We conclude that substantial evidence exists for epigenetic aging impacting drug metabolism and transport genes, but more work is needed. We further highlight the promise of pharmacoepigenetics applied to enhancing drug safety in older adults.
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Affiliation(s)
- Sara Abudahab
- Department of Pharmacotherapy & Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Patricia W Slattum
- Department of Pharmacotherapy & Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA
- Virginia Center on Aging, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Elvin T Price
- Department of Pharmacotherapy & Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Joseph L McClay
- Department of Pharmacotherapy & Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA
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10
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Porter HL, Ansere VA, Undi RB, Hoolehan W, Giles CB, Brown CA, Stanford D, Huycke MM, Freeman WM, Wren JD. Methylation Array Signals are Predictive of Chronological Age Without Bisulfite Conversion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.20.572465. [PMID: 38187520 PMCID: PMC10769286 DOI: 10.1101/2023.12.20.572465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
DNA methylation data has been used to make "epigenetic clocks" which attempt to measure chronological and biological aging. These models rely on data derived from bisulfite-based measurements, which exploit a semi-selective deamination and a genomic reference to determine methylation states. Here, we demonstrate how another hallmark of aging, genomic instability, influences methylation measurements in both bisulfite sequencing and methylation arrays. We found that non-methylation factors lead to "pseudomethylation" signals that are both confounding of epigenetic clocks and uniquely age predictive. Quantifying these covariates in aging studies will be critical to building better clocks and designing appropriate studies of epigenetic aging.
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Affiliation(s)
- Hunter L Porter
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
- Oklahoma Nathan Shock Center
| | - Victor A Ansere
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
| | | | - Walker Hoolehan
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
| | | | - Chase A Brown
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
| | | | | | - Willard M Freeman
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
- Oklahoma Nathan Shock Center
| | - Jonathan D Wren
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
- Oklahoma Nathan Shock Center
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11
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Nishida J, Cristea S, Bodapati S, Puleo J, Bai G, Patel A, Hughes M, Snow C, Borges V, Ruddy KJ, Collins LC, Feeney AM, Slowik K, Bossuyt V, Dillon D, Lin NU, Partridge AH, Michor F, Polyak K. Peripheral blood TCR clonotype diversity as an age-associated marker of breast cancer progression. Proc Natl Acad Sci U S A 2023; 120:e2316763120. [PMID: 38011567 DOI: 10.1073/pnas.2316763120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 10/27/2023] [Indexed: 11/29/2023] Open
Abstract
Immune escape is a prerequisite for tumor growth. We previously described a decline in intratumor activated cytotoxic T cells and T cell receptor (TCR) clonotype diversity in invasive breast carcinomas compared to ductal carcinoma in situ (DCIS), implying a central role of decreasing T cell responses in tumor progression. To determine potential associations between peripheral immunity and breast tumor progression, here, we assessed the peripheral blood TCR clonotype of 485 breast cancer patients diagnosed with either DCIS or de novo stage IV disease at younger (<45) or older (≥45) age. TCR clonotype diversity was significantly lower in older compared to younger breast cancer patients regardless of tumor stage at diagnosis. In the younger age group, TCR-α clonotype diversity was lower in patients diagnosed with de novo stage IV breast cancer compared to those diagnosed with DCIS. In the older age group, DCIS patients with higher TCR-α clonotype diversity were more likely to have a recurrence compared to those with lower diversity. Whole blood transcriptome profiles were distinct depending on the TCR-α Chao1 diversity score. There were more CD8+ T cells and a more active immune environment in DCIS tumors of young patients with higher peripheral blood TCR-α Chao1 diversity than in those with lower diversity. These results provide insights into the role that host immunity plays in breast cancer development across different age groups.
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MESH Headings
- Humans
- Aged
- Female
- Breast Neoplasms/pathology
- Carcinoma, Intraductal, Noninfiltrating/genetics
- Carcinoma, Intraductal, Noninfiltrating/pathology
- CD8-Positive T-Lymphocytes/pathology
- Biomarkers, Tumor/genetics
- Receptors, Antigen, T-Cell/genetics
- Neoplastic Processes
- Receptors, Antigen, T-Cell, alpha-beta/genetics
- Carcinoma, Ductal, Breast/pathology
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Affiliation(s)
- Jun Nishida
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115
| | - Simona Cristea
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| | - Sudheshna Bodapati
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
| | - Julieann Puleo
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115
| | - Gali Bai
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| | - Ashka Patel
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
| | - Melissa Hughes
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
| | - Craig Snow
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
| | - Virginia Borges
- Medicine-Medical Oncology, University of Colorado Comprehensive Cancer Center, Aurora, CO 80045
| | - Kathryn J Ruddy
- Division of Medical Oncology, Department of Oncology, Mayo Clinic, Rochester, MN 55905
| | - Laura C Collins
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115
| | - Anne-Marie Feeney
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
| | - Kara Slowik
- The Broad Institute of MIT and Harvard, Cambridge, MA 02138
| | - Veerle Bossuyt
- Mass General Pathology, Massachusetts General Hospital, Boston, MA 02114
| | - Deborah Dillon
- Department of Pathology, Brigham and Women's Hospital, Boston, MA 02115
| | - Nancy U Lin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115
| | - Ann H Partridge
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115
| | - Franziska Michor
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
- The Broad Institute of MIT and Harvard, Cambridge, MA 02138
- The Ludwig Center at Harvard, Boston, MA 02115
- Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA 02215
| | - Kornelia Polyak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115
- Mass General Pathology, Massachusetts General Hospital, Boston, MA 02114
- The Ludwig Center at Harvard, Boston, MA 02115
- Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA 02215
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12
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Kiemen AL, Wu PH, Braxton AM, Cornish TC, Hruban RH, Wood L, Wirtz D, Zwicker D. Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic findings. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.01.569633. [PMID: 38105957 PMCID: PMC10723372 DOI: 10.1101/2023.12.01.569633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Pancreatic ductal adenocarcinoma is a rare but lethal cancer. Recent evidence reveals that pancreatic intraepithelial neoplasms (PanINs), the microscopic precursor lesions in the pancreatic ducts that can give rise to invasive pancreatic cancer, are significantly larger and more prevalent than previously believed. Better understanding of the growth law dynamics of PanINs may improve our ability to understand how a miniscule fraction of these lesions makes the transition to invasive cancer. Here, using artificial intelligence (AI)-based three-dimensional (3D) tissue mapping method, we measured the volumes of >1,000 PanIN and found that lesion size is distributed according to a power law with a fitted exponent of -1.7 over > 3 orders of magnitude. Our data also suggest that PanIN growth is not very sensitive to the pancreatic microenvironment or an individual's age, family history, and lifestyle, and is rather shaped by general growth behavior. We analyze several models of PanIN growth and fit the predicted size distributions to the observed data. The best fitting models suggest that both intraductal spread of PanIN lesions and fusing of multiple lesions into large, highly branched structures drive PanIN growth patterns. This work lays the groundwork for future mathematical modeling efforts integrating PanIN incidence, morphology, genomic, and transcriptomic features to understand pancreas tumorigenesis, and demonstrates the utility of combining experimental measurement of human tissues with dynamic modeling for understanding cancer tumorigenesis.
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Affiliation(s)
- Ashley L. Kiemen
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Oncology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Pei-Hsun Wu
- Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Alicia M. Braxton
- Department of Comparative Medicine, Medical University of South Carolina, Charleston, SC
| | - Toby C. Cornish
- Department of Pathology, University of Colorado School of Medicine, Aurora, CO
| | - Ralph H. Hruban
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Oncology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Laura Wood
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Oncology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Denis Wirtz
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Oncology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - David Zwicker
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
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13
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Chen L, Chang D, Tandukar B, Deivendran D, Pozniak J, Cruz-Pacheco N, Cho RJ, Cheng J, Yeh I, Marine C, Bastian BC, Ji AL, Shain AH. STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer. Genome Biol 2023; 24:273. [PMID: 38037084 PMCID: PMC10688493 DOI: 10.1186/s13059-023-03121-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 11/22/2023] [Indexed: 12/02/2023] Open
Abstract
Spatial transcriptomic technologies, such as the Visium platform, measure gene expression in different regions of tissues. Here, we describe new software, STmut, to visualize somatic point mutations, allelic imbalance, and copy number alterations in Visium data. STmut is tested on fresh-frozen Visium data, formalin-fixed paraffin-embedded (FFPE) Visium data, and tumors with and without matching DNA sequencing data. Copy number is inferred on all conditions, but the chemistry of the FFPE platform does not permit analyses of single nucleotide variants. Taken together, we propose solutions to add the genetic dimension to spatial transcriptomic data and describe the limitations of different datatypes.
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Affiliation(s)
- Limin Chen
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Darwin Chang
- Department of Immunology, H. Lee Moffitt Cancer Center, Tampa, USA
| | - Bishal Tandukar
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Delahny Deivendran
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Joanna Pozniak
- Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Louvain, Belgium
- Laboratory for Molecular Cancer Biology, Department of Oncology, KU Leuven, Louvain, Belgium
| | - Noel Cruz-Pacheco
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Raymond J Cho
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Jeffrey Cheng
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Iwei Yeh
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
- Department of Pathology, University of California, San Francisco, San Francisco, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, USA
| | - Chris Marine
- Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Louvain, Belgium
- Laboratory for Molecular Cancer Biology, Department of Oncology, KU Leuven, Louvain, Belgium
| | - Boris C Bastian
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
- Department of Pathology, University of California, San Francisco, San Francisco, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, USA
| | - Andrew L Ji
- Department of Dermatology, Department of Oncological Sciences, Black Family Stem Cell Institute, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York City, USA
| | - A Hunter Shain
- Department of Dermatology, University of California, San Francisco, San Francisco, USA.
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, USA.
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14
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Zhang FM, Wu HF, Shi HP, Yu Z, Zhuang CL. Sarcopenia and malignancies: epidemiology, clinical classification and implications. Ageing Res Rev 2023; 91:102057. [PMID: 37666432 DOI: 10.1016/j.arr.2023.102057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/15/2023] [Accepted: 08/31/2023] [Indexed: 09/06/2023]
Abstract
Sarcopenia is a progressive systemic skeletal muscle disorder characterized by a pathological decline in muscle strength, quantity, and quality, which frequently affects the elderly population. The majority of cancer patients are of advanced age. Patients may already have sarcopenia prior to cancer development, and those with cancer are prone to developing sarcopenia due to hypercatabolism, inflammation, reduced physical fitness, anorexia, adverse effects, and stress associated with anticancer therapy. Based on the timing, sarcopenia in patients with cancer can be categorized into three: pre-existing sarcopenia before the onset of cancer, sarcopenia related to cancer, and sarcopenia related to cancer treatment. Sarcopenia not only changes the body composition of patients with cancer but also increases the incidence of postoperative complications, reduces therapeutic efficacy, impairs quality of life, and results in shortened survival. Different therapeutic strategies are required to match the cancer status and physical condition of patients with different etiologies and stages of sarcopenia. Here, we present a comprehensive review of the epidemiology and diagnosis of sarcopenia in patients with cancer, elucidate the complex interactions between cancer and sarcopenia, and provide evidence-based strategies for sarcopenia management in these patients.
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Affiliation(s)
- Feng-Min Zhang
- Colorectal Cancer Center/Department of Gastrointestinal Surgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Hao-Fan Wu
- Colorectal Cancer Center/Department of Gastrointestinal Surgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Han-Ping Shi
- Department of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University/ Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, China
| | - Zhen Yu
- Colorectal Cancer Center/Department of Gastrointestinal Surgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Cheng-Le Zhuang
- Colorectal Cancer Center/Department of Gastrointestinal Surgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
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15
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López-Gil L, Pascual-Ahuir A, Proft M. Genomic Instability and Epigenetic Changes during Aging. Int J Mol Sci 2023; 24:14279. [PMID: 37762580 PMCID: PMC10531692 DOI: 10.3390/ijms241814279] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 09/15/2023] [Accepted: 09/18/2023] [Indexed: 09/29/2023] Open
Abstract
Aging is considered the deterioration of physiological functions along with an increased mortality rate. This scientific review focuses on the central importance of genomic instability during the aging process, encompassing a range of cellular and molecular changes that occur with advancing age. In particular, this revision addresses the genetic and epigenetic alterations that contribute to genomic instability, such as telomere shortening, DNA damage accumulation, and decreased DNA repair capacity. Furthermore, the review explores the epigenetic changes that occur with aging, including modifications to histones, DNA methylation patterns, and the role of non-coding RNAs. Finally, the review discusses the organization of chromatin and its contribution to genomic instability, including heterochromatin loss, chromatin remodeling, and changes in nucleosome and histone abundance. In conclusion, this review highlights the fundamental role that genomic instability plays in the aging process and underscores the need for continued research into these complex biological mechanisms.
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Affiliation(s)
- Lucía López-Gil
- Department of Biotechnology, Instituto de Biología Molecular y Celular de Plantas, Universitat Politècnica de València, Ingeniero Fausto Elio s/n, 46022 Valencia, Spain;
- Department of Molecular and Cellular Pathology and Therapy, Instituto de Biomedicina de Valencia IBV-CSIC, Consejo Superior de Investigaciones Científicas CSIC, Jaime Roig 11, 46010 Valencia, Spain
| | - Amparo Pascual-Ahuir
- Department of Biotechnology, Instituto de Biología Molecular y Celular de Plantas, Universitat Politècnica de València, Ingeniero Fausto Elio s/n, 46022 Valencia, Spain;
| | - Markus Proft
- Department of Molecular and Cellular Pathology and Therapy, Instituto de Biomedicina de Valencia IBV-CSIC, Consejo Superior de Investigaciones Científicas CSIC, Jaime Roig 11, 46010 Valencia, Spain
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16
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Marongiu F, Cheri S, Laconi E. Clones of aging: When better fitness can be dangerous. Eur J Cell Biol 2023; 102:151340. [PMID: 37423036 DOI: 10.1016/j.ejcb.2023.151340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 05/29/2023] [Accepted: 07/05/2023] [Indexed: 07/11/2023] Open
Abstract
The biological and clinical significance of aberrant clonal expansions in aged tissues is being intensely discussed. Evidence is accruing that these clones often result from the normal dynamics of cell turnover in our tissues. The aged tissue microenvironment is prone to favour the emergence of specific clones with higher fitness partly because of an overall decline in cell intrinsic regenerative potential of surrounding counterparts. Thus, expanding clones in aged tissues need not to be mechanistically associated with the development of cancer, albeit this is a possibility. We suggest that growth pattern is a critical phenotypic attribute that impacts on the fate of such clonal proliferations. The acquisition of a better proliferative fitness, coupled with a defect in tissue pattern formation, could represent a dangerous mix setting the stage for their evolution towards neoplasia.
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Affiliation(s)
- Fabio Marongiu
- Department of Biomedical Sciences, University of Cagliari, Italy
| | - Samuele Cheri
- Department of Biomedical Sciences, University of Cagliari, Italy
| | - Ezio Laconi
- Department of Biomedical Sciences, University of Cagliari, Italy.
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17
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Santoso D, Thaha M, Empitu MA, Kadariswantiningsih IN, Suryantoro SD, Haryati MR, Hertanto DM, Pramudya D, Bintoro SUY, Nasronudin N, Alsagaff MY, Susilo H, Wungu CDK, Budhiparama NC, Hogendoorn PCW. Brown Tumour in Chronic Kidney Disease: Revisiting an Old Disease with a New Perspective. Cancers (Basel) 2023; 15:4107. [PMID: 37627135 PMCID: PMC10452999 DOI: 10.3390/cancers15164107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 08/10/2023] [Accepted: 08/12/2023] [Indexed: 08/27/2023] Open
Abstract
Osteitis fibrosa cystica (OFC) and Brown Tumours are two related but distinct types of bone lesions that result from the overactivity of osteoclasts and are most often associated with chronic kidney disease (CKD). Despite their potential consequences, these conditions are poorly understood because of their rare prevalence and variability in their clinical manifestation. Canonically, OFC and Brown Tumours are caused by secondary hyperparathyroidism in CKD. Recent literature showed that multiple factors, such as hyperactivation of the renin-angiotensin-aldosterone system and chronic inflammation, may also contribute to the occurrence of these diseases through osteoclast activation. Moreover, hotspot KRAS mutations were identified in these lesions, placing them in the spectrum of RAS-MAPK-driven neoplasms, which were until recently thought to be reactive lesions. Some risk factors contributed to the occurrence of OFC and Brown Tumours, such as age, gender, comorbidities, and certain medications. The diagnosis of OFC and Brown Tumours includes clinical symptoms involving chronic bone pain and laboratory findings of hyperparathyroidism. In radiological imaging, the X-ray and Computed tomography (CT) scan could show lytic or multi-lobular cystic alterations. Histologically, both lesions are characterized by clustered osteoclasts in a fibrotic hemorrhagic background. Based on the latest understanding of the mechanism of OFC, this review elaborates on the manifestation, diagnosis, and available therapies that can be leveraged to prevent the occurrence of OFC and Brown Tumours.
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Affiliation(s)
- Djoko Santoso
- Department of Internal Medicine, Dr. Soetomo Hospital, Surabaya 60286, Indonesia; (D.S.); (D.M.H.); (D.P.); (S.U.Y.B.); (N.N.)
- Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga Hospital, Universitas Airlangga, Surabaya 60115, Indonesia; (S.D.S.); (M.R.H.)
| | - Mochammad Thaha
- Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga Hospital, Universitas Airlangga, Surabaya 60115, Indonesia; (S.D.S.); (M.R.H.)
| | - Maulana A. Empitu
- Department of Anatomy, Histology, and Pharmacology, Faculty of Medicine, Universitas Airlangga, Surabaya 60132, Indonesia;
| | | | - Satriyo Dwi Suryantoro
- Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga Hospital, Universitas Airlangga, Surabaya 60115, Indonesia; (S.D.S.); (M.R.H.)
| | - Mutiara Rizki Haryati
- Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga Hospital, Universitas Airlangga, Surabaya 60115, Indonesia; (S.D.S.); (M.R.H.)
| | - Decsa Medika Hertanto
- Department of Internal Medicine, Dr. Soetomo Hospital, Surabaya 60286, Indonesia; (D.S.); (D.M.H.); (D.P.); (S.U.Y.B.); (N.N.)
| | - Dana Pramudya
- Department of Internal Medicine, Dr. Soetomo Hospital, Surabaya 60286, Indonesia; (D.S.); (D.M.H.); (D.P.); (S.U.Y.B.); (N.N.)
| | | | - Nasronudin Nasronudin
- Department of Internal Medicine, Dr. Soetomo Hospital, Surabaya 60286, Indonesia; (D.S.); (D.M.H.); (D.P.); (S.U.Y.B.); (N.N.)
- Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga Hospital, Universitas Airlangga, Surabaya 60115, Indonesia; (S.D.S.); (M.R.H.)
| | - Mochamad Yusuf Alsagaff
- Department of Cardiology and Vascular Medicine, Universitas Airlangga Hospital, Universitas Airlangga, Surabaya 60115, Indonesia; (M.Y.A.); (H.S.)
| | - Hendri Susilo
- Department of Cardiology and Vascular Medicine, Universitas Airlangga Hospital, Universitas Airlangga, Surabaya 60115, Indonesia; (M.Y.A.); (H.S.)
| | - Citrawati Dyah Kencono Wungu
- Department of Physiology and Medical Biochemistry, Faculty of Medicine, Universitas Airlangga, Surabaya 60132, Indonesia;
| | - Nicolaas C. Budhiparama
- Department of Orthopaedic Surgery, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands;
| | - Pancras C. W. Hogendoorn
- Department of Pathology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands
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18
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Passman AM, Haughey MJ, Carlotti E, Williams MJ, Cereser B, Lin ML, Devkumar S, Gabriel JP, Gringeri E, Cillo U, Russo FP, Hoare M, ChinAleong J, Jansen M, Wright NA, Kocher HM, Huang W, Alison MR, McDonald SAC. Hepatocytes undergo punctuated expansion dynamics from a periportal stem cell niche in normal human liver. J Hepatol 2023; 79:417-432. [PMID: 37088309 DOI: 10.1016/j.jhep.2023.03.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 03/29/2023] [Accepted: 03/30/2023] [Indexed: 04/25/2023]
Abstract
BACKGROUND & AIMS While normal human liver is thought to be generally quiescent, clonal hepatocyte expansions have been observed, though neither their cellular source nor their expansion dynamics have been determined. Knowing the hepatocyte cell of origin, and their subsequent dynamics and trajectory within the human liver will provide an important basis to understand disease-associated dysregulation. METHODS Herein, we use in vivo lineage tracing and methylation sequence analysis to demonstrate normal human hepatocyte ancestry. We exploit next-generation mitochondrial sequencing to determine hepatocyte clonal expansion dynamics across spatially distinct areas of laser-captured, microdissected, clones, in tandem with computational modelling in morphologically normal human liver. RESULTS Hepatocyte clones and rare SOX9+ hepatocyte progenitors commonly associate with portal tracts and we present evidence that clones can lineage-trace with cholangiocytes, indicating the presence of a bipotential common ancestor at this niche. Within clones, we demonstrate methylation CpG sequence diversity patterns indicative of periportal not pericentral ancestral origins, indicating a portal to central vein expansion trajectory. Using spatial analysis of mitochondrial DNA variants by next-generation sequencing coupled with mathematical modelling and Bayesian inference across the portal-central axis, we demonstrate that patterns of mitochondrial DNA variants reveal large numbers of spatially restricted mutations in conjunction with limited numbers of clonal mutations. CONCLUSIONS These datasets support the existence of a periportal progenitor niche and indicate that clonal patches exhibit punctuated but slow growth, then quiesce, likely due to acute environmental stimuli. These findings crucially contribute to our understanding of hepatocyte dynamics in the normal human liver. IMPACT AND IMPLICATIONS The liver is mainly composed of hepatocytes, but we know little regarding the source of these cells or how they multiply over time within the disease-free human liver. In this study, we determine a source of new hepatocytes by combining many different lab-based methods and computational predictions to show that hepatocytes share a common cell of origin with bile ducts. Both our experimental and computational data also demonstrate hepatocyte clones are likely to expand in slow waves across the liver in a specific trajectory, but often lie dormant for many years. These data show for the first time the expansion dynamics of hepatocytes in normal liver and their cell of origin enabling the accurate measurment of changes to their dynamics that may lead to liver disease. These findings are important for researchers determining cancer risk in human liver.
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Affiliation(s)
- Adam M Passman
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Magnus J Haughey
- School of Mathematical Sciences, Queen Mary University of London, London, UK
| | - Emanuela Carlotti
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Marc J Williams
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Bianca Cereser
- Centre for Tumour Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Meng-Lay Lin
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Shruthi Devkumar
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Jonathan P Gabriel
- Centre for Tumour Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Enrico Gringeri
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy
| | - Umberto Cillo
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy
| | - Francesco Paolo Russo
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy
| | - Matthew Hoare
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | | | - Marnix Jansen
- Department of Cellular Pathology, University College London, London, UK; UCL Cancer Centre, University College London, London, UK
| | - Nicholas A Wright
- Centre for Tumour Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Hermant M Kocher
- Centre for Tumour Biology, Barts Cancer Institute, Queen Mary University of London, London, UK; Cancer Tissue Bank, Barts Cancer Institute, Queen Mary University of London, London, UK; Barts and the London HPB Centre, The Royal London Hospital, Barts Health NHS Trust, London, UK
| | - Weini Huang
- School of Mathematical Sciences, Queen Mary University of London, London, UK; Group of Theoretical Biology, The State Key Laboratory of Biocontrol, School of Life Science, Sun Yat-sen University, Guangzhou, China
| | - Malcolm R Alison
- Centre for Tumour Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Stuart A C McDonald
- Centre for Cancer Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK.
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19
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Ma Y, Gan J, Bai Y, Cao D, Jiao Y. Minimal residual disease in solid tumors: an overview. Front Med 2023; 17:649-674. [PMID: 37707677 DOI: 10.1007/s11684-023-1018-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 06/24/2023] [Indexed: 09/15/2023]
Abstract
Minimal residual disease (MRD) is termed as the small numbers of remnant tumor cells in a subset of patients with tumors. Liquid biopsy is increasingly used for the detection of MRD, illustrating the potential of MRD detection to provide more accurate management for cancer patients. As new techniques and algorithms have enhanced the performance of MRD detection, the approach is becoming more widely and routinely used to predict the prognosis and monitor the relapse of cancer patients. In fact, MRD detection has been shown to achieve better performance than imaging methods. On this basis, rigorous investigation of MRD detection as an integral method for guiding clinical treatment has made important advances. This review summarizes the development of MRD biomarkers, techniques, and strategies for the detection of cancer, and emphasizes the application of MRD detection in solid tumors, particularly for the guidance of clinical treatment.
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Affiliation(s)
- Yarui Ma
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jingbo Gan
- Genetron Health (Beijing) Co. Ltd., Beijing, 102206, China
| | - Yinlei Bai
- Genetron Health (Beijing) Co. Ltd., Beijing, 102206, China
| | - Dandan Cao
- Genetron Health (Beijing) Co. Ltd., Beijing, 102206, China
| | - Yuchen Jiao
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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20
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Roškar L, Kokol M, Pavlič R, Roškar I, Smrkolj Š, Rižner TL. Decreased Gene Expression of Antiangiogenic Factors in Endometrial Cancer: qPCR Analysis and Machine Learning Modelling. Cancers (Basel) 2023; 15:3661. [PMID: 37509322 PMCID: PMC10378066 DOI: 10.3390/cancers15143661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 07/30/2023] Open
Abstract
Endometrial cancer (EC) is an increasing health concern, with its growth driven by an angiogenic switch that occurs early in cancer development. Our study used publicly available datasets to examine the expression of angiogenesis-related genes and proteins in EC tissues, and compared them with adjacent control tissues. We identified nine genes with significant differential expression and selected six additional antiangiogenic genes from prior research for validation on EC tissue in a cohort of 36 EC patients. Using machine learning, we built a prognostic model for EC, combining our data with The Cancer Genome Atlas (TCGA). Our results revealed a significant up-regulation of IL8 and LEP and down-regulation of eleven other genes in EC tissues. These genes showed differential expression in the early stages and lower grades of EC, and in patients without deep myometrial or lymphovascular invasion. Gene co-expressions were stronger in EC tissues, particularly those with lymphovascular invasion. We also found more extensive angiogenesis-related gene involvement in postmenopausal women. In conclusion, our findings suggest that angiogenesis in EC is predominantly driven by decreased antiangiogenic factor expression, particularly in EC with less favourable prognostic features. Our machine learning model effectively stratified EC based on gene expression, distinguishing between low and high-grade cases.
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Affiliation(s)
- Luka Roškar
- Department of Gynaecology and Obstetrics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
- Division of Gynaecology and Obstetrics, General Hospital Murska Sobota, 9000 Murska Sobota, Slovenia
| | - Marko Kokol
- Faculty of Electrical Engineering and Computer Science, University of Maribor, 2000 Maribor, Slovenia
- Semantika Research, Semantika d.o.o., 2000 Maribor, Slovenia
| | - Renata Pavlič
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Irena Roškar
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Špela Smrkolj
- Department of Gynaecology and Obstetrics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
- Division of Gynaecology and Obstetrics, University Medical Centre, 1000 Ljubljana, Slovenia
| | - Tea Lanišnik Rižner
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
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21
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Galloway-Peña JR, Jobin C. Microbiota Influences on Hematopoiesis and Blood Cancers: New Horizons? Blood Cancer Discov 2023; 4:267-275. [PMID: 37052501 PMCID: PMC10320642 DOI: 10.1158/2643-3230.bcd-22-0172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 03/10/2023] [Accepted: 03/10/2023] [Indexed: 04/14/2023] Open
Abstract
Hematopoiesis governs the generation of immune cells through the differentiation of hematopoietic stem cells (HSC) into various progenitor cells, a process controlled by intrinsic and extrinsic factors. Among extrinsic factors influencing hematopoiesis is the microbiota, or the collection of microorganisms present in various body sites. The microbiota has a profound impact on host homeostasis by virtue of its ability to release various molecules and structural components, which promote normal organ function. In this review, we will discuss the role of microbiota in influencing hematopoiesis and how disrupting the microbiota/host network could lead to hematologic malignancies, as well as highlight important knowledge gaps to move this field of research forward. SIGNIFICANCE Microbiota dysfunction is associated with many pathologic conditions, including hematologic malignancies. In this review, we discuss the role of microbiota in influencing hematopoiesis and how disrupting the microbiota/host network could lead to hematologic malignancies. Understanding how the microbiota influences hematologic malignancies could have an important therapeutic impact for patients.
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Affiliation(s)
- Jessica R. Galloway-Peña
- Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, Texas
- Department of Veterinary Pathobiology, Texas A&M University, College Station, Texas
| | - Christian Jobin
- Department of Medicine, University of Florida, Gainesville, Florida
- Department of Anatomy and Cell Biology, University of Florida, Gainesville, Florida
- Department of Infectious Diseases and Immunology, University of Florida, Gainesville, Florida
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22
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Marchetti F, Cardoso R, Chen CL, Douglas GR, Elloway J, Escobar PA, Harper T, Heflich RH, Kidd D, Lynch AM, Myers MB, Parsons BL, Salk JJ, Settivari RS, Smith-Roe SL, Witt KL, Yauk CL, Young R, Zhang S, Minocherhomji S. Error-corrected next generation sequencing - Promises and challenges for genotoxicity and cancer risk assessment. MUTATION RESEARCH. REVIEWS IN MUTATION RESEARCH 2023; 792:108466. [PMID: 37643677 DOI: 10.1016/j.mrrev.2023.108466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 07/12/2023] [Accepted: 08/23/2023] [Indexed: 08/31/2023]
Abstract
Error-corrected Next Generation Sequencing (ecNGS) is rapidly emerging as a valuable, highly sensitive and accurate method for detecting and characterizing mutations in any cell type, tissue or organism from which DNA can be isolated. Recent mutagenicity and carcinogenicity studies have used ecNGS to quantify drug-/chemical-induced mutations and mutational spectra associated with cancer risk. ecNGS has potential applications in genotoxicity assessment as a new readout for traditional models, for mutagenesis studies in 3D organotypic cultures, and for detecting off-target effects of gene editing tools. Additionally, early data suggest that ecNGS can measure clonal expansion of mutations as a mechanism-agnostic early marker of carcinogenic potential and can evaluate mutational load directly in human biomonitoring studies. In this review, we discuss promising applications, challenges, limitations, and key data initiatives needed to enable regulatory testing and adoption of ecNGS - including for advancing safety assessment, augmenting weight-of-evidence for mutagenicity and carcinogenicity mechanisms, identifying early biomarkers of cancer risk, and managing human health risk from chemical exposures.
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Affiliation(s)
| | | | - Connie L Chen
- Health and Environmental Sciences Institute, Washington, DC, USA.
| | | | - Joanne Elloway
- Safety Sciences, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | | | - Tod Harper
- Amgen Research, Amgen Inc, Thousand Oaks, CA, USA
| | - Robert H Heflich
- US Food and Drug Administration/National Center for Toxicological Research, Jefferson, AR, USA
| | - Darren Kidd
- Labcorp Early Development Laboratories Limited, Harrogate, North Yorkshire, UK
| | | | - Meagan B Myers
- US Food and Drug Administration/National Center for Toxicological Research, Jefferson, AR, USA
| | - Barbara L Parsons
- US Food and Drug Administration/National Center for Toxicological Research, Jefferson, AR, USA
| | | | | | | | - Kristine L Witt
- NIEHS, Division of the National Toxicology Program, Research Triangle Park, NC, USA
| | | | - Robert Young
- MilliporeSigma, Rockville, MD, USA; Current: Consultant, Bethesda, MD, USA
| | | | - Sheroy Minocherhomji
- Amgen Research, Amgen Inc, Thousand Oaks, CA, USA; Current: Eli Lilly and Company, Indianapolis, IN, USA
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23
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Menon V, Brash DE. Next-generation sequencing methodologies to detect low-frequency mutations: "Catch me if you can". MUTATION RESEARCH. REVIEWS IN MUTATION RESEARCH 2023; 792:108471. [PMID: 37716438 PMCID: PMC10843083 DOI: 10.1016/j.mrrev.2023.108471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/06/2023] [Accepted: 09/07/2023] [Indexed: 09/18/2023]
Abstract
Mutations, the irreversible changes in an organism's DNA sequence, are present in tissues at a variant allele frequency (VAF) ranging from ∼10-8 per bp for a founder mutation to ∼10-3 for a histologically normal tissue sample containing several independent clones - compared to 1%- 50% for a heterozygous tumor mutation or a polymorphism. The rarity of these events poses a challenge for accurate clinical diagnosis and prognosis, toxicology, and discovering new disease etiologies. Standard Next-Generation Sequencing (NGS) technologies report VAFs as low as 0.5% per nt, but reliably observing rarer precursor events requires additional sophistication to measure ultralow-frequency mutations. We detail the challenge; define terms used to characterize the results, which vary between laboratories and sometimes conflict between biologists and bioinformaticists; and describe recent innovations to improve standard NGS methodologies including: single-strand consensus sequence methods such as Safe-SeqS and SiMSen-Seq; tandem-strand consensus sequence methods such as o2n-Seq and SMM-Seq; and ultrasensitive parent-strand consensus sequence methods such as DuplexSeq, PacBio HiFi, SinoDuplex, OPUSeq, EcoSeq, BotSeqS, Hawk-Seq, NanoSeq, SaferSeq, and CODEC. Practical applications are also noted. Several methods quantify VAF down to 10-5 at a nt and mutation frequency (MF) in a target region down to 10-7 per nt. By expanding to > 1 Mb of sites never observed twice, thus forgoing VAF, other methods quantify MF < 10-9 per nt or < 15 errors per haploid genome. Clonal expansion cannot be directly distinguished from independent mutations by sequencing, so it is essential for a paper to report whether its MF counted only different mutations - the minimum independent-mutation frequency MFminI - or all mutations observed including recurrences - the larger maximum independent-mutation frequency MFmaxI which may reflect clonal expansion. Ultrasensitive methods reveal that, without their use, even mutations with VAF 0.5-1% are usually spurious.
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Affiliation(s)
- Vijay Menon
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT 06520-8040, USA.
| | - Douglas E Brash
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT 06520-8040, USA; Department of Dermatology, Yale School of Medicine, New Haven, CT 06520-8059, USA; Yale Cancer Center, Yale School of Medicine, New Haven, CT 06520-8028, USA.
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24
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Zhu W, Liu S, Shi Y, Tang Q, Sun J, Bai R, Sun Z, Du Z. The epidemic of acute lymphoid leukemia in China: current trends and future prediction. Front Oncol 2023; 13:1195065. [PMID: 37397360 PMCID: PMC10313194 DOI: 10.3389/fonc.2023.1195065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 05/30/2023] [Indexed: 07/04/2023] Open
Abstract
Background China has experienced one of the fastest increases in the incidence of acute lymphoid leukemia (ALL). The aim of this study was to assess the long-term trends of the incidence and mortality of ALL in mainland China between 1990 and 2019 and to project these trends through 2028. Methods Data on ALL were extracted from the Global Burden of Disease Study 2019; population data were extracted from World Population Prospects 2019. An age-period-cohort framework was used in the analysis. Results The net drift for the incidence of ALL was 7.5% (95% confidence interval [CI]: 7.1%, 7.8%) per year in women and 7.1% (95% CI: 6.7%, 7.6%) in men, and local drift was found to be higher than 0 in every studied age group (p<0.05). The net drift for mortality was 1.2% (95% CI: 1.0%, 1.5%) in women and 2.0% (95% CI: 1.7%, 2.3%) in men. Local drift was lower than 0 in boys aged 0-4 years and girls aged 0-9 years and higher than 0 in men aged 10-84 years and women aged 15-84 years. The estimated period relative risks (RRs) for both incidence and mortality showed increasing trends in the recent period. The cohort RRs for incidence showed increasing trends in both sexes; however, the cohort RR for mortality was decreased in the recent birth cohort (women born after 1988-1992 and men born after 2003-2007). Compared with that in 2019, the incidence of ALL in 2028 is projected to increase by 64.1% in men and 75.0% in women, and the mortality is predicted to decrease by 11.1% in men and 14.3% in women. The proportion of older adult/adults individuals with incident ALL and ALL-related death was projected to increase. Conclusions Over the last three decades, the incidence and mortality rates of ALL have generally increased. It is projected that the incidence rate of ALL in mainland China will continue to increase in the future, but the associated mortality rate will decline. The proportion of older adult/adults individuals with incident ALL and ALL-related death was projected to increase gradually among both sexes. More efforts are needed, especially for older adult/adults individuals.
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Affiliation(s)
- Wenxuan Zhu
- Department of Hepatobiliary Surgery, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China
| | - Shixuan Liu
- Health Science Center, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Ying Shi
- Department of Chronic Disease, Xi'an Weiyang District Center for Disease Control and Prevention, Xi’an, Shaanxi, China
| | - Qingyu Tang
- Health Science Center, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Jianzhong Sun
- Health Science Center, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Ruhai Bai
- School of Public Affairs, Nanjing University of Science and Technology, Nanjing, Jiangsu, China
| | - Zhonghe Sun
- Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Zhaoqing Du
- Department of Hepatobiliary Surgery, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China
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25
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Dańczak‐Pazdrowska A, Gornowicz‐Porowska J, Polańska A, Krajka‐Kuźniak V, Stawny M, Gostyńska A, Rubiś B, Nourredine S, Ashiqueali S, Schneider A, Tchkonia T, Wyles SP, Kirkland JL, Masternak MM. Cellular senescence in skin-related research: Targeted signaling pathways and naturally occurring therapeutic agents. Aging Cell 2023; 22:e13845. [PMID: 37042069 PMCID: PMC10265178 DOI: 10.1111/acel.13845] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Revised: 03/25/2023] [Accepted: 03/27/2023] [Indexed: 04/13/2023] Open
Abstract
Despite the growing interest by researchers into cellular senescence, a hallmark of cellular aging, its role in human skin remains equivocal. The skin is the largest and most accessible human organ, reacting to the external and internal environment. Hence, it is an organ of choice to investigate cellular senescence and to target root-cause aging processes using senolytic and senomorphic agents, including naturally occurring plant-based derivatives. This review presents different aspects of skin cellular senescence, from physiology to pathology and signaling pathways. Cellular senescence can have both beneficial and detrimental effects on the skin, indicating that both prosenescent and antisenescent therapies may be desirable, based on the context. Knowledge of molecular mechanisms involved in skin cellular senescence may provide meaningful insights for developing effective therapeutics for senescence-related skin disorders, such as wound healing and cosmetic skin aging changes.
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Affiliation(s)
| | - Justyna Gornowicz‐Porowska
- Department and Division of Practical Cosmetology and Skin Diseases ProphylaxisPoznan University of Medical SciencesPoznanPoland
| | - Adriana Polańska
- Department of Dermatology and VenereologyPoznan University of Medical SciencesPoznanPoland
| | | | - Maciej Stawny
- Department of Pharmaceutical ChemistryPoznan University of Medical SciencesPoznanPoland
| | - Aleksandra Gostyńska
- Department of Pharmaceutical ChemistryPoznan University of Medical SciencesPoznanPoland
| | - Błażej Rubiś
- Department of Clinical Chemistry and Molecular DiagnosticsPoznan University of Medical SciencesPoznanPoland
| | - Sarah Nourredine
- Burnett School of Biomedical SciencesCollege of Medicine, University of Central FloridaOrlandoFloridaUSA
| | - Sarah Ashiqueali
- Burnett School of Biomedical SciencesCollege of Medicine, University of Central FloridaOrlandoFloridaUSA
| | | | - Tamara Tchkonia
- Department of Physiology and Biomedical EngineeringMayo ClinicRochesterMinnesotaUSA
| | | | - James L. Kirkland
- Department of Physiology and Biomedical EngineeringMayo ClinicRochesterMinnesotaUSA
| | - Michal M. Masternak
- Burnett School of Biomedical SciencesCollege of Medicine, University of Central FloridaOrlandoFloridaUSA
- Department of Head and Neck SurgeryPoznan University of Medical SciencesPoznanPoland
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26
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Pelizzola M, Laursen R, Hobolth A. Model selection and robust inference of mutational signatures using Negative Binomial non-negative matrix factorization. BMC Bioinformatics 2023; 24:187. [PMID: 37158829 PMCID: PMC10165836 DOI: 10.1186/s12859-023-05304-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 04/25/2023] [Indexed: 05/10/2023] Open
Abstract
BACKGROUND The spectrum of mutations in a collection of cancer genomes can be described by a mixture of a few mutational signatures. The mutational signatures can be found using non-negative matrix factorization (NMF). To extract the mutational signatures we have to assume a distribution for the observed mutational counts and a number of mutational signatures. In most applications, the mutational counts are assumed to be Poisson distributed, and the rank is chosen by comparing the fit of several models with the same underlying distribution and different values for the rank using classical model selection procedures. However, the counts are often overdispersed, and thus the Negative Binomial distribution is more appropriate. RESULTS We propose a Negative Binomial NMF with a patient specific dispersion parameter to capture the variation across patients and derive the corresponding update rules for parameter estimation. We also introduce a novel model selection procedure inspired by cross-validation to determine the number of signatures. Using simulations, we study the influence of the distributional assumption on our method together with other classical model selection procedures. We also present a simulation study with a method comparison where we show that state-of-the-art methods are highly overestimating the number of signatures when overdispersion is present. We apply our proposed analysis on a wide range of simulated data and on two real data sets from breast and prostate cancer patients. On the real data we describe a residual analysis to investigate and validate the model choice. CONCLUSIONS With our results on simulated and real data we show that our model selection procedure is more robust at determining the correct number of signatures under model misspecification. We also show that our model selection procedure is more accurate than the available methods in the literature for finding the true number of signatures. Lastly, the residual analysis clearly emphasizes the overdispersion in the mutational count data. The code for our model selection procedure and Negative Binomial NMF is available in the R package SigMoS and can be found at https://github.com/MartaPelizzola/SigMoS .
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Affiliation(s)
- Marta Pelizzola
- Department of Mathematics, Aarhus University, Aarhus, Denmark.
| | | | - Asger Hobolth
- Department of Mathematics, Aarhus University, Aarhus, Denmark
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27
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Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. SCIENCE CHINA. LIFE SCIENCES 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Citation(s) in RCA: 71] [Impact Index Per Article: 71.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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Affiliation(s)
- Hainan Bao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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Pitiyarachchi O, Lee YC, Sim HW, Srirangan S, Mapagu C, Kirk J, Harnett PR, Balleine RL, Bowtell DDL, Samimi G, Brand AH, Marsh DJ, Beale P, Anderson L, Bouantoun N, Provan P, Ramus SJ, DeFazio A, Friedlander M. Older age should not be a barrier to testing for somatic variants in homologous recombination DNA repair-related genes in patients with high-grade serous ovarian carcinoma. Transl Oncol 2023; 31:101638. [PMID: 36805919 PMCID: PMC9971549 DOI: 10.1016/j.tranon.2023.101638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 01/29/2023] [Accepted: 02/08/2023] [Indexed: 02/20/2023] Open
Abstract
BACKGROUND Somatic pathogenic variants (PVs) in homologous recombination DNA repair (HR)-related genes found in high-grade serous ovarian carcinomas (HGSC) are not well-characterised in older patients (≥70 years). This may reflect low testing rates in older patients. METHODS Data from 1210 HGSC patients in AACR Project GENIE and 324 patients in an independent dataset INOVATe were analysed. Cases where somatic variants could be distinguished from germline variants were included, and analysis was restricted to those with a somatic TP53 variant, to ensure cases were HGSC. RESULTS Of 1210 patients in GENIE, 27% (n = 325) were aged ≥70 years at testing. Patients with somatic-only PVs in BRCA2 were older compared with BRCA1 (median 71 vs 60 years, p = 0.002). Median age for 21 patients with somatic-only PVs in 11 other HR-related genes ranged from 40 to 67 years. In older patients, 7% (n = 22) had somatic BRCA1/2 PVs, and 1% (n = 2) had PVs other HR-related genes; this rate was not significantly different to younger patients (<70 years), 7% (n = 62) BRCA1/2 and 2% (n = 19) other HR-related genes (p = 0.36). The overall frequency of somatic BRCA1/2 PVs was similar in INOVATe (n = 25; 7.7%) and somatic-only BRCA2 PVs were again found in older patients compared with BRCA1 (median age: at testing, 70 vs 63 years; at diagnosis, 68 vs 60 years). CONCLUSIONS The overall frequency of somatic-only PVs in HR-related genes was similar in older and younger patients with HGSC, highlighting the importance of somatic testing irrespective of age. Limiting somatic testing by age may exclude patients who could benefit from maintenance poly(ADP-ribose) polymerase (PARP) inhibitors.
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Affiliation(s)
- Omali Pitiyarachchi
- School of Biomedical Sciences, Faculty of Medicine and Health, UNSW Sydney, Sydney, NSW, Australia.
| | - Yeh Chen Lee
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, NSW, Australia; Department of Medical Oncology, Prince of Wales and Royal Hospital for Women, Randwick, NSW, Australia
| | - Hao-Wen Sim
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, NSW, Australia; NHMRC Clinical Trials Centre, The University of Sydney, Camperdown, NSW, Australia; Department of Medical Oncology, The Kinghorn Cancer Centre, Darlinghurst, NSW, Australia; Department of Medical Oncology, Chris O'Brien Lifehouse, Camperdown, NSW, Australia; Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Sivatharsny Srirangan
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, NSW, Australia; Department of Gynaecological Oncology, Westmead Hospital, Westmead, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Cristina Mapagu
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Illawarra and Shoalhaven Cancer Care Centres, Wollongong and Nowra, NSW, Australia
| | - Judy Kirk
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; The Crown Princess Mary Cancer Centre, Westmead Hospital, Westmead, NSW, Australia
| | - Paul R Harnett
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; The Crown Princess Mary Cancer Centre, Westmead Hospital, Westmead, NSW, Australia
| | - Rosemary L Balleine
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - David D L Bowtell
- Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia; Sir Peter MacCallum Cancer Centre Department of Oncology, University of Melbourne, Parkville, Victoria, Australia
| | - Goli Samimi
- National Cancer Institute, Bethesda, Maryland, United States of America
| | - Alison H Brand
- Department of Gynaecological Oncology, Westmead Hospital, Westmead, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Deborah J Marsh
- Translational Oncology Group, School of Life Sciences, Faculty of Science, University of Technology Sydney, NSW, Australia; Northern Clinical School, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Philip Beale
- Department of Medical Oncology, Chris O'Brien Lifehouse, Camperdown, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Lyndal Anderson
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; NSW Health Pathology, NSW, Australia; Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - Natalie Bouantoun
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, NSW, Australia; Department of Gynaecological Oncology, Westmead Hospital, Westmead, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Pamela Provan
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, NSW, Australia; Department of Gynaecological Oncology, Westmead Hospital, Westmead, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | | | - Susan J Ramus
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, NSW, Australia; Adult Cancer Program, Lowy Cancer Research Centre, UNSW Sydney, Sydney, NSW, Australia
| | - Anna DeFazio
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, NSW, Australia; Department of Gynaecological Oncology, Westmead Hospital, Westmead, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia
| | - Michael Friedlander
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, NSW, Australia; Department of Medical Oncology, Prince of Wales and Royal Hospital for Women, Randwick, NSW, Australia
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29
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Grant SR, Tang L, Wei L, Foster BA, Paragh G, Huss WJ. Mutation Hotspots Found in Bladder Cancer Aid Prediction of Carcinogenic Risk in Normal Urothelium. Int J Mol Sci 2023; 24:ijms24097852. [PMID: 37175559 PMCID: PMC10177765 DOI: 10.3390/ijms24097852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 04/11/2023] [Accepted: 04/22/2023] [Indexed: 05/15/2023] Open
Abstract
More than 80,000 new cases of bladder cancer are estimated to be diagnosed in 2023. However, the 5-year survival rate for bladder cancer has not changed in decades, highlighting the need for prevention. Numerous cancer-causing mutations are present in the urothelium long before signs of cancer arise. Mutation hotspots in cancer-driving genes were identified in non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) tumor samples. Mutation burden within the hotspot regions was measured in normal urothelium with a low and high risk of cancer. A significant correlation was found between the mutation burden in normal urothelium and bladder cancer tissue within the hotspot regions. A combination of measured hotspot burden and personal risk factors was used to fit machine learning classification models. The efficacy of each model to differentiate between adjacent benign urothelium from bladder cancer patients and normal urothelium from healthy donors was measured. A random forest model using a combination of personal risk factors and mutations within MIBC hotspots yielded the highest AUC of 0.9286 for the prediction of high- vs. low-risk normal urothelium. Currently, there are no effective biomarkers to assess subclinical field disease and early carcinogenic progression in the bladder. Our findings demonstrate novel differences in mutation hotspots in NMIBC and MIBC and provide the first evidence for mutation hotspots to aid in the assessment of cancer risk in the normal urothelium. Early risk assessment and identification of patients at high risk of bladder cancer before the clinical presentation of the disease can pave the way for targeted personalized preventative therapy.
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Affiliation(s)
- Sydney R Grant
- Department of Dermatology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
- Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Li Tang
- Department of Cancer Prevention & Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Lei Wei
- Department of Biostatistics & Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Barbara A Foster
- Department of Pharmacology & Therapeutics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Gyorgy Paragh
- Department of Dermatology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
- Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
| | - Wendy J Huss
- Department of Dermatology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
- Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
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30
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Pereira QC, dos Santos TW, Fortunato IM, Ribeiro ML. The Molecular Mechanism of Polyphenols in the Regulation of Ageing Hallmarks. Int J Mol Sci 2023; 24:ijms24065508. [PMID: 36982583 PMCID: PMC10049696 DOI: 10.3390/ijms24065508] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 12/27/2022] [Accepted: 01/04/2023] [Indexed: 03/16/2023] Open
Abstract
Ageing is a complex process characterized mainly by a decline in the function of cells, tissues, and organs, resulting in an increased risk of mortality. This process involves several changes, described as hallmarks of ageing, which include genomic instability, telomere attrition, epigenetic changes, loss of proteostasis, dysregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell depletion, and altered intracellular communication. The determining role that environmental factors such as diet and lifestyle play on health, life expectancy, and susceptibility to diseases, including cancer and neurodegenerative diseases, is wellestablished. In view of the growing interest in the beneficial effects of phytochemicals in the prevention of chronic diseases, several studies have been conducted, and they strongly suggest that the intake of dietary polyphenols may bring numerous benefits due to their antioxidant and anti-inflammatory properties, and their intake has been associated with impaired ageing in humans. Polyphenol intake has been shown to be effective in ameliorating several age-related phenotypes, including oxidative stress, inflammatory processes, impaired proteostasis, and cellular senescence, among other features, which contribute to an increased risk of ageing-associated diseases. This review aims to address, in a general way, the main findings described in the literature about the benefits of polyphenols in each of the hallmarks of ageing, as well as the main regulatory mechanisms responsible for the observed antiageing effects.
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Affiliation(s)
- Quélita Cristina Pereira
- Laboratory of Immunopharmacology and Molecular Biology, Sao Francisco University Medical School, Braganca Paulista 12916-900, SP, Brazil
| | - Tanila Wood dos Santos
- Laboratory of Immunopharmacology and Molecular Biology, Sao Francisco University Medical School, Braganca Paulista 12916-900, SP, Brazil
| | - Isabela Monique Fortunato
- Laboratory of Immunopharmacology and Molecular Biology, Sao Francisco University Medical School, Braganca Paulista 12916-900, SP, Brazil
| | - Marcelo Lima Ribeiro
- Laboratory of Immunopharmacology and Molecular Biology, Sao Francisco University Medical School, Braganca Paulista 12916-900, SP, Brazil
- Lymphoma Translational Group, Josep Carreras Leukemia Research Institute, 08916 Badalona, Spain
- Correspondence:
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Pan-cancer clinical impact of latent drivers from double mutations. Commun Biol 2023; 6:202. [PMID: 36808143 PMCID: PMC9941481 DOI: 10.1038/s42003-023-04519-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 01/23/2023] [Indexed: 02/22/2023] Open
Abstract
Here, we discover potential 'latent driver' mutations in cancer genomes. Latent drivers have low frequencies and minor observable translational potential. As such, to date they have escaped identification. Their discovery is important, since when paired in cis, latent driver mutations can drive cancer. Our comprehensive statistical analysis of the pan-cancer mutation profiles of ~60,000 tumor sequences from the TCGA and AACR-GENIE cohorts identifies significantly co-occurring potential latent drivers. We observe 155 same gene double mutations of which 140 individual components are cataloged as latent drivers. Evaluation of cell lines and patient-derived xenograft response data to drug treatment indicate that in certain genes double mutations may have a prominent role in increasing oncogenic activity, hence obtaining a better drug response, as in PIK3CA. Taken together, our comprehensive analyses indicate that same-gene double mutations are exceedingly rare phenomena but are a signature for some cancer types, e.g., breast, and lung cancers. The relative rarity of doublets can be explained by the likelihood of strong signals resulting in oncogene-induced senescence, and by doublets consisting of non-identical single residue components populating the background mutational load, thus not identified.
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32
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Compounds in Indonesian Ginger Rhizome Extracts and Their Potential for Anti-Skin Aging Based on Molecular Docking. COSMETICS 2022. [DOI: 10.3390/cosmetics9060128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Skin aging is a condition caused by reactive oxygen species (ROS) and advanced glycation end products (AGEs). Indonesian gingers (Zingiber officinale), which consists of Gajah (GG), Red (MM), and Emprit (EE) ginger, are thought to produce anti-skin aging compounds through enzyme inhibition. The enzymes used in the molecular docking study were collagenase, hyaluronidase, elastase, and tyrosinase. This study aimed to determine the compounds contained in Indonesian ginger rhizome ethanolic extracts using liquid chromatography–mass spectrometry/mass spectrometry to differentiate metabolites contained in the different Indonesian ginger rhizome extracts. A principal component analysis (PCA) and a heat map analysis were used in order to determine which compounds and extracts contained potential anti-skin aging properties based on a molecular docking study. Ascorbic acid was used as a control ligand in the molecular docking study. Ninety-eight compounds were identified in three different ginger rhizomes extracts and were grouped into three separate quadrants. The most potent compound for anti-skin aging in the Indonesian ginger rhizome extracts was octinoxate. Octinoxate showed a high abundance in the EE ginger rhizome extract. Therefore, the EE ginger extract was the Indonesian ginger rhizome extract with the greatest potential for anti-skin aging.
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Turek D, Haefliger S, Ameline B, Alborelli I, Calgua B, Hartmann W, Harder D, Flanagan AM, Amary F, Baumhoer D. Brown Tumors Belong to the Spectrum of KRAS -driven Neoplasms. Am J Surg Pathol 2022; 46:1577-1582. [PMID: 36040039 PMCID: PMC9561227 DOI: 10.1097/pas.0000000000001963] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Brown tumors are rare and generally self-limiting mass lesions of bone occurring in the context of hyperparathyroidism. Although commonly regarded as endocrine-driven tumor-like lesions, we detected pathogenic hotspot KRAS mutations in 10/16 brown tumors (62%) with similar frequencies found in cases affecting the peripheral and axial skeleton. Pathogenic mutations in other driver genes of the RAS-MAPK pathway were not identified. Our findings suggest brown tumors to represent true neoplasms driven by the activation of the RAS-MAPK signaling pathway. The frequent regression of brown tumors after normalization of hyperparathyroidism points to a second hit mediated by endocrine stimulation to be required for tumor development. Our findings underline the pathogenic relation of brown tumors to nonossifying fibroma and giant cell granuloma of the jaws which both appear histologically similar to brown tumors and are also driven by RAS-MAPK signaling pathway activation.
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Affiliation(s)
- Daniel Turek
- Bone Tumor Reference Centre, Institute of Medical Genetics and Pathology
| | - Simon Haefliger
- Bone Tumor Reference Centre, Institute of Medical Genetics and Pathology
| | - Baptiste Ameline
- Bone Tumor Reference Centre, Institute of Medical Genetics and Pathology
| | | | | | - Wolfgang Hartmann
- Division of Translational Pathology, Gerhard-Domagk-Institut of Pathology, University Hospital Münster, Münster, Germany
| | - Dorothee Harder
- Department of Radiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Adrienne M. Flanagan
- Cellular and Molecular Pathology, Royal National Orthopaedic Hospital, Stanmore, Greater London
- Research Department of Pathology, University College London, UCL Cancer Institute, London, UK
| | - Fernanda Amary
- Cellular and Molecular Pathology, Royal National Orthopaedic Hospital, Stanmore, Greater London
- Research Department of Pathology, University College London, UCL Cancer Institute, London, UK
| | - Daniel Baumhoer
- Bone Tumor Reference Centre, Institute of Medical Genetics and Pathology
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Ghezelayagh TS, Kohrn BF, Fredrickson J, Manhardt E, Radke MR, Katz R, Gray HJ, Urban RR, Pennington KP, Liao JB, Doll KM, Simons EJ, Burzawa JK, Goff BA, Speiser P, Swisher EM, Norquist BM, Risques RA. Uterine lavage identifies cancer mutations and increased TP53 somatic mutation burden in individuals with ovarian cancer. CANCER RESEARCH COMMUNICATIONS 2022; 2:1282-1292. [PMID: 36311816 PMCID: PMC9615025 DOI: 10.1158/2767-9764.crc-22-0314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Current screening methods for ovarian cancer (OC) have failed to demonstrate a significant reduction in mortality. Uterine lavage combined with TP53 ultra-deep sequencing for the detection of disseminated OC cells has emerged as a promising tool, but this approach has not been tested for early-stage disease or non-serous histologies. In addition, lavages carry multiple background mutations, the significance of which is poorly understood. Uterine lavage was collected preoperatively in 34 patients undergoing surgery for suspected ovarian malignancy including 14 patients with benign disease and 20 patients with OC (6 non-serous and 14 high grade serous-like (serous)). Ultra-deep duplex sequencing (~3000x) with a panel of common OC genes identified the tumor mutation in 33% of non-serous (all early stage) and in 79% of serous cancers (including four early stage). In addition, all lavages carried multiple somatic mutations (average of 25 mutations per lavage), more than half of which corresponded to common cancer driver mutations. Driver mutations in KRAS, PIK3CA, PTEN, PPP2R1A and ARID1A presented as larger clones than non-driver mutations and with similar frequency in lavages from patients with and without OC, indicating prevalent somatic evolution in all patients. Driver TP53 mutations, however, presented as significantly larger clones and with higher frequency in lavages from individuals with OC, suggesting that TP53-specific clonal expansions are linked to ovarian cancer development. Our results demonstrate that lavages capture cancer cells, even from early-stage cancers, as well as other clonal expansions and support further exploration of TP53 mutation burden as a potential OC risk factor.
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Affiliation(s)
- Talayeh S. Ghezelayagh
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
| | - Brendan F. Kohrn
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
| | - Jeanne Fredrickson
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
| | - Enna Manhardt
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - Marc R. Radke
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - Ronit Katz
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - Heidi J. Gray
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - Renata R. Urban
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - Kathryn P. Pennington
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - John B. Liao
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - Kemi M. Doll
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - Elise J. Simons
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - Jennifer K. Burzawa
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - Barbara A. Goff
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | | | - Elizabeth M. Swisher
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - Barbara M. Norquist
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington
| | - Rosa Ana Risques
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
- Corresponding Author: Rosa Ana Risques, Laboratory Medicine and Pathology, University of Washington, HSB, E506, Seattle, WA 98195. Phone: 206-616-4976; E-mail:
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35
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Rahal Z, Sinjab A, Wistuba II, Kadara H. Game of clones: Battles in the field of carcinogenesis. Pharmacol Ther 2022; 237:108251. [PMID: 35850404 PMCID: PMC10249058 DOI: 10.1016/j.pharmthera.2022.108251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 07/10/2022] [Accepted: 07/12/2022] [Indexed: 11/22/2022]
Abstract
Recent advances in bulk sequencing approaches as well as genomic decoding at the single-cell level have revealed surprisingly high somatic mutational burdens in normal tissues, as well as increased our understanding of the landscape of "field cancerization", that is, molecular and immune alterations in mutagen-exposed normal-appearing tissues that recapitulated those present in tumors. Charting the somatic mutational landscapes in normal tissues can have strong implications on our understanding of how tumors arise from mutagenized epithelium. Making sense of those mutations to understand the progression along the pathologic continuum of normal epithelia, preneoplasias, up to malignant tissues will help pave way for identification of ideal targets that can guide new strategies for preventing or eliminating cancers at their earliest stages of development. In this review, we will provide a brief history of field cancerization and its implications on understanding early stages of cancer pathogenesis and deviation from the pathologically "normal" state. The review will provide an overview of how mutations accumulating in normal tissues can lead to a patchwork of mutated cell clones that compete while maintaining an overall state of functional homeostasis. The review also explores the role of clonal competition in directing the fate of normal tissues and summarizes multiple mechanisms elicited in this phenomenon and which have been linked to cancer development. Finally, we highlight the importance of understanding mutations in normal tissues, as well as clonal competition dynamics (in both the epithelium and the microenvironment) and their significance in exploring new approaches to combatting cancer.
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Affiliation(s)
- Zahraa Rahal
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, USA
| | - Ansam Sinjab
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, USA
| | - Ignacio I Wistuba
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, USA
| | - Humam Kadara
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, USA.
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36
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Wang M, Wu Y, He Y, Liu J, Chen Y, Huang J, Qi G, Li P. SIRT1 upregulation promotes epithelial-mesenchymal transition by inducing senescence escape in endometriosis. Sci Rep 2022; 12:12302. [PMID: 35853978 PMCID: PMC9296487 DOI: 10.1038/s41598-022-16629-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 07/13/2022] [Indexed: 02/06/2023] Open
Abstract
Endometrial epithelial cells carry distinct cancer-associated alterations that may be more susceptible to endometriosis. Mouse models have shown that overexpression of SIRT1 associated with oncogene activation contributes to the pathogenesis of endometriosis, but the underlying reason remains elusive. Here, we used integrated systems biology analysis and found that enrichment of endometrial stromal fibroblasts in endometriosis and their cellular abundance correlated negatively with epithelial cells in clinical specimens. Furthermore, endometrial epithelial cells were characterized by significant overexpression of SIRT1, which is involved in triggering the EMT switch by escaping damage or oncogene-induced induced senescence in clinical specimens and in vitro human cell line models. This observation supports that genetic and epigenetic incident favors endometrial epithelia cells escape from senescence and fuel EMT process in endometriosis, what could be overcome by downregulation of SIRT1.
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Affiliation(s)
- Minghua Wang
- Department of Pathology, Longgang District People's Hospital, Shenzhen, 518172, China.,Department of Pathology, Jinan University School of Medicine, Guangzhou, 510632, China
| | - Yongqi Wu
- Department of Pathology, Jinan University School of Medicine, Guangzhou, 510632, China
| | - Yunbiao He
- Department of Medical Statistics, Jinan University School of Medicine, Guangzhou, 510632, China
| | - Jing Liu
- Department of Pathology, Jinan University School of Medicine, Guangzhou, 510632, China
| | - Yingxing Chen
- Department of Gynecology and Obstetrics, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Jieqiong Huang
- Department of Pathology, Jinan University School of Medicine, Guangzhou, 510632, China
| | - Guolong Qi
- Department of Medical Statistics, Jinan University School of Medicine, Guangzhou, 510632, China.
| | - Ping Li
- Department of Pathology, Jinan University School of Medicine, Guangzhou, 510632, China.
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37
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Aguado J, Gómez-Inclán C, Leeson HC, Lavin MF, Shiloh Y, Wolvetang EJ. The hallmarks of aging in Ataxia-Telangiectasia. Ageing Res Rev 2022; 79:101653. [PMID: 35644374 DOI: 10.1016/j.arr.2022.101653] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 04/28/2022] [Accepted: 05/24/2022] [Indexed: 01/10/2023]
Abstract
Ataxia-telangiectasia (A-T) is caused by absence of the catalytic activity of ATM, a protein kinase that plays a central role in the DNA damage response, many branches of cellular metabolism, redox and mitochondrial homeostasis, and cell cycle regulation. A-T is a complex disorder characterized mainly by progressive cerebellar degeneration, immunodeficiency, radiation sensitivity, genome instability, and predisposition to cancer. It is increasingly recognized that the premature aging component of A-T is an important driver of this disease, and A-T is therefore an attractive model to study the aging process. This review outlines the current state of knowledge pertaining to the molecular and cellular signatures of aging in A-T and proposes how these new insights can guide novel therapeutic approaches for A-T.
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Affiliation(s)
- Julio Aguado
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Queensland 4072, Australia.
| | - Cecilia Gómez-Inclán
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Queensland 4072, Australia
| | - Hannah C Leeson
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Queensland 4072, Australia
| | - Martin F Lavin
- University of Queensland Centre for Clinical Research, The University of Queensland, Herston, Brisbane, Australia
| | - Yosef Shiloh
- The David and Inez Myers Laboratory of Cancer Genetics, Department of Human Molecular Genetics and Biochemistry, Tel Aviv University School of Medicine, Tel Aviv, Israel
| | - Ernst J Wolvetang
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Queensland 4072, Australia.
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38
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Matas J, Kohrn B, Fredrickson J, Carter K, Yu M, Wang T, Gui X, Soussi T, Moreno V, Grady WM, Peinado MA, Risques RA. Colorectal Cancer Is Associated with the Presence of Cancer Driver Mutations in Normal Colon. Cancer Res 2022; 82:1492-1502. [PMID: 35425963 PMCID: PMC9022358 DOI: 10.1158/0008-5472.can-21-3607] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 01/20/2022] [Accepted: 02/10/2022] [Indexed: 11/16/2022]
Abstract
Although somatic mutations in colorectal cancer are well characterized, little is known about the accumulation of cancer mutations in the normal colon before cancer. Here, we have developed and applied an ultrasensitive, single-molecule mutational test based on CRISPR-DS technology, which enables mutation detection at extremely low frequency (<0.001) in normal colon from patients with and without colorectal cancer. This testing platform revealed that normal colon from patients with and without colorectal cancer carries mutations in common colorectal cancer genes, but these mutations are more abundant in patients with cancer. Oncogenic KRAS mutations were observed in the normal colon of about one third of patients with colorectal cancer but in none of the patients without colorectal cancer. Patients with colorectal cancer also carried more TP53 mutations than patients without cancer and these mutations were more pathogenic and formed larger clones, especially in patients with early-onset colorectal cancer. Most mutations in the normal colon were different from the driver mutations in tumors, suggesting that the occurrence of independent clones with pathogenic KRAS and TP53 mutations is a common event in the colon of individuals who develop colorectal cancer. These results indicate that somatic evolution contributes to clonal expansions in the normal colon and that this process is enhanced in individuals with cancer, particularly in those with early-onset colorectal cancer. SIGNIFICANCE This work suggests prevalent somatic evolution in the normal colon of patients with colorectal cancer, highlighting the potential of using ultrasensitive gene sequencing to predict disease risk.
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Affiliation(s)
- Julia Matas
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
- Institut Germans Trias i Pujol, Badalona, Spain
| | - Brendan Kohrn
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
| | - Jeanne Fredrickson
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
| | - Kelly Carter
- Fred Hutchinson Cancer Research Center, Seattle, USA
| | - Ming Yu
- Fred Hutchinson Cancer Research Center, Seattle, USA
| | - Ting Wang
- Fred Hutchinson Cancer Research Center, Seattle, USA
| | - Xianyong Gui
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
| | - Thierry Soussi
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- Sorbonne Université, UPMC Univ Paris 06, F- 75005 Paris, France
- INSERM, U1138, Centre de Recherche des Cordeliers, Paris, France
| | - Victor Moreno
- Oncology Data Analytics Program, Catalan Institute of Oncology (ICO), Barcelona, Spain
- Colorectal Cancer Group, ONCOBELL Program, Institut de Recerca Biomedica de Bellvitge (IDIBELL), Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Barcelona, Spain
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain
| | | | | | - Rosa Ana Risques
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
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Valls PO, Esposito A. Signalling dynamics, cell decisions, and homeostatic control in health and disease. Curr Opin Cell Biol 2022; 75:102066. [PMID: 35245783 PMCID: PMC9097822 DOI: 10.1016/j.ceb.2022.01.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 01/27/2022] [Accepted: 01/28/2022] [Indexed: 11/13/2022]
Abstract
Cell signalling engenders cells with the capability to receive and process information from the intracellular and extracellular environments, trigger and execute biological responses, and communicate with each other. Ultimately, cell signalling is responsible for maintaining homeostasis at the cellular, tissue and systemic level. For this reason, cell signalling is a topic of intense research efforts aimed to elucidate how cells coordinate transitions between states in developing and adult organisms in physiological and pathological conditions. Here, we review current knowledge of how cell signalling operates at multiple spatial and temporal scales, focusing on how single-cell analytical techniques reveal mechanisms underpinning cell-to-cell variability, signalling plasticity, and collective cellular responses.
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Affiliation(s)
- Pablo Oriol Valls
- MRC Cancer Unit, University of Cambridge, Cambridge, CB2 0XZ, United Kingdom
| | - Alessandro Esposito
- MRC Cancer Unit, University of Cambridge, Cambridge, CB2 0XZ, United Kingdom; Centre for Genome Engineering and Maintenance, College of Health, Medicine and Life Sciences, Brunel University London, Uxbridge, UB8 3PH, United Kingdom.
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40
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Shared genetic and epigenetic changes link aging and cancer. Trends Cell Biol 2022; 32:338-350. [PMID: 35144882 DOI: 10.1016/j.tcb.2022.01.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 12/28/2021] [Accepted: 01/07/2022] [Indexed: 12/12/2022]
Abstract
Aging is a universal biological process that increases the risk of multiple diseases including cancer. Growing evidence shows that alterations in the genome and epigenome, driven by similar mechanisms, are found in both aged cells and cancer cells. In this review, we detail the genetic and epigenetic changes associated with normal aging and the mechanisms responsible for these changes. By highlighting genetic and epigenetic alterations in the context of tumorigenesis, cancer progression, and the aging tumor microenvironment, we examine the possible impacts of the normal aging process on malignant transformation. Finally, we examine the implications of age-related genetic and epigenetic alterations in both tumors and patients for the treatment of cancer.
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Cuadros M, Cano C, Garcia-Rodriguez S, Martín JL, Poyatos-Andujar A, Ruiz-Cabello F, Pedrinaci S, Durán G, Benavides M, Bautista-Ojeda MD, Pereda T, Benitez-Cantos MS, Medina P, Blanco A, Gonzalez A, Lizardi P. Acceleration of the DNA methylation clock among lynch syndrome-associated mutation carriers. BMC Med Genomics 2022; 15:45. [PMID: 35246124 PMCID: PMC8895826 DOI: 10.1186/s12920-022-01183-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 02/15/2022] [Indexed: 11/17/2022] Open
Abstract
Background DNA methylation (DNAm) age metrics have been widely accepted as an epigenetic biomarker for biological aging and disease. The purpose of this study is to assess whether or not individuals carrying Lynch Syndrome-associated mutations are affected in their rate of biological aging, as measured by the epigenetic clock. Methods Genome-wide bisulfite DNA sequencing data were generated using DNA from CD4 + T-cells obtained from peripheral blood using 27 patient samples from Lynch syndrome families. Horvath’s DNAm age model based on penalized linear regression was applied to estimate DNAm age from patient samples with distinct clinical and genetic characteristics to investigate cancer mutation-related aging effects. Results Both Lynch mutation carriers and controls exhibited high variability in their estimated DNAm age, but regression analysis showed steeper slope for the Lynch mutation carriers. Remarkably, six Lynch Syndrome-associated mutation carriers showed a strong correlation to the control group, and two sisters carrying Lynch Syndrome-associated mutations, with no significant difference in lifestyle and similar chronological age, were assigned very different DNAm age. Conclusions Future studies will be required to explore, in larger patient populations, whether specific epigenetic age acceleration is predictive of time-to-cancer development, treatment response, and survival. Epigenetic clock DNAm metrics may be affected by the presence of cancer mutations in the germline, and thus show promise of potential clinical utility for stratified surveillance strategies based on the relative risk for imminent emergence of tumor lesions in otherwise healthy Lynch Syndrome-associated mutation carriers.
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Affiliation(s)
- Marta Cuadros
- Department of Biochemistry and Molecular Biology III and Immunology, Faculty of Medicine, University of Granada, Av. de la Investigación 11, 18007, Granada, Spain. .,GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, Av. de la Ilustración 114, 18007, Granada, Spain. .,Health Research Institute of Granada (Ibis.Granada), Av. Fuerzas Armadas 2, 18014, Granada, Spain.
| | - Carlos Cano
- Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain.
| | - Sonia Garcia-Rodriguez
- Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain. .,GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, Av. de la Ilustración 114, 18007, Granada, Spain.
| | | | | | | | | | - Gema Durán
- Hospital Regional Universitario Carlos Haya, Málaga, Spain
| | | | | | | | - Maria Soledad Benitez-Cantos
- Department of Biochemistry and Molecular Biology III and Immunology, Faculty of Medicine, University of Granada, Av. de la Investigación 11, 18007, Granada, Spain.,GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, Av. de la Ilustración 114, 18007, Granada, Spain
| | - Pedro Medina
- GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, Av. de la Ilustración 114, 18007, Granada, Spain.,Health Research Institute of Granada (Ibis.Granada), Av. Fuerzas Armadas 2, 18014, Granada, Spain.,Department of Biochemistry and Molecular Biology I, Faculty of Sciences, University of Granada, Av. de Fuente Nueva S/N, 18071, Granada, Spain
| | - Armando Blanco
- Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
| | - Antonio Gonzalez
- Instituto de Parasitología y Biomedicina LopezNeyra - CSIC, Granada, Spain
| | - Paul Lizardi
- GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, Av. de la Ilustración 114, 18007, Granada, Spain
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Birkou M, Raptis V, Marousis KD, Tsevis A, Bourikas K, Bentrop D, Episkopou V, Spyroulias GA. Impact of a Single Nucleotide Polymorphism on the 3D Protein Structure and Ubiquitination Activity of E3 Ubiquitin Ligase Arkadia. Front Mol Biosci 2022; 9:844129. [PMID: 35281275 PMCID: PMC8905620 DOI: 10.3389/fmolb.2022.844129] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 01/31/2022] [Indexed: 11/16/2022] Open
Abstract
Single nucleotide polymorphisms (SNPs) are genetic variations which can play a vital role in the study of human health. SNP studies are often used to identify point mutations that are associated with diseases. Arkadia (RNF111) is an E3 ubiquitin ligase that enhances transforming growth factor-beta (TGF-β) signaling by targeting negative regulators for degradation. Dysregulation of the TGF-β pathway is implicated in cancer because it exhibits tumor suppressive activity in normal cells while in tumor cells it promotes invasiveness and metastasis. Τhe SNP CGT > TGT generated an amino-acid (aa) substitution of Arginine 957 to Cysteine on the enzymatic RING domain of Arkadia. This was more prevalent in a tumor than in a normal tissue sample of a patient with colorectal cancer. This prompted us to investigate the effect of this mutation in the structure and activity of Arkadia RING. We used nuclear magnetic resonance (NMR) to analyze at an atomic-level the structural and dynamic properties of the R957C Arkadia RING domain, while ubiquitination and luciferase assays provided information about its enzymatic functionality. Our study showed that the R957C mutation changed the electrostatic properties of the RING domain however, without significant effects on the structure of its core region. However, the functional studies revealed that the R957C Arkadia exhibits significantly increased enzymatic activity supporting literature data that Arkadia within tumor cells promotes aggressive and metastatic behavior.
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Affiliation(s)
- Maria Birkou
- Department of Pharmacy, University of Patras, Patras, Greece
| | - Vasilios Raptis
- Department of Pharmacy, University of Patras, Patras, Greece
| | | | - Athanasios Tsevis
- School of Science and Technology, Hellenic Open University, Patras, Greece
| | - Kyriakos Bourikas
- School of Science and Technology, Hellenic Open University, Patras, Greece
| | - Detlef Bentrop
- Institute of Physiology II, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Vasso Episkopou
- Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Burlington Danes, London, United Kingdom
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Jiang L, Yu H, Ness S, Mao P, Guo F, Tang J, Guo Y. Comprehensive Analysis of Co-Mutations Identifies Cooperating Mechanisms of Tumorigenesis. Cancers (Basel) 2022; 14:415. [PMID: 35053577 PMCID: PMC8774165 DOI: 10.3390/cancers14020415] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 01/07/2022] [Accepted: 01/11/2022] [Indexed: 12/16/2022] Open
Abstract
Somatic mutations are one of the most important factors in tumorigenesis and are the focus of most cancer-sequencing efforts. The co-occurrence of multiple mutations in one tumor has gained increasing attention as a means of identifying cooperating mutations or pathways that contribute to cancer. Using multi-omics, phenotypical, and clinical data from 29,559 cancer subjects and 1747 cancer cell lines covering 78 distinct cancer types, we show that co-mutations are associated with prognosis, drug sensitivity, and disparities in sex, age, and race. Some co-mutation combinations displayed stronger effects than their corresponding single mutations. For example, co-mutation TP53:KRAS in pancreatic adenocarcinoma is significantly associated with disease specific survival (hazard ratio = 2.87, adjusted p-value = 0.0003) and its prognostic predictive power is greater than either TP53 or KRAS as individually mutated genes. Functional analyses revealed that co-mutations with higher prognostic values have higher potential impact and cause greater dysregulation of gene expression. Furthermore, many of the prognostically significant co-mutations caused gains or losses of binding sequences of RNA binding proteins or micro RNAs with known cancer associations. Thus, detailed analyses of co-mutations can identify mechanisms that cooperate in tumorigenesis.
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Affiliation(s)
- Limin Jiang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China;
- School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
| | - Hui Yu
- Department of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87131, USA; (H.Y.); (S.N.); (P.M.)
| | - Scott Ness
- Department of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87131, USA; (H.Y.); (S.N.); (P.M.)
| | - Peng Mao
- Department of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87131, USA; (H.Y.); (S.N.); (P.M.)
| | - Fei Guo
- School of Computer Science and Engineering, Central South University, Changsha 410083, China;
| | - Jijun Tang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China;
| | - Yan Guo
- Department of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87131, USA; (H.Y.); (S.N.); (P.M.)
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Taniguchi N, Takahara T, Ito T, Yamamoto Y, Satou A, Ohashi A, Takahashi E, Maeda N, Tsuzuki T. Clinicopathologic analysis of malignant or premalignant cutaneous neoplasms in Japanese kidney transplant recipients. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY 2021; 14:1138-1147. [PMID: 35027994 PMCID: PMC8748015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Accepted: 11/12/2021] [Indexed: 06/14/2023]
Abstract
It is well known that recipients of kidney transplants are at an increased risk of developing malignant or premalignant cutaneous neoplasms (MPCNs) after transplantation. However, the pathogenesis of MPCNs after kidney transplant has not been well-studied in Asian populations. This study aimed to describe the clinicopathologiccharacteristics of MPCNs in an Asian population. We retrospectively reviewed the medical records of 1956 patients who received kidney transplants at two hospitals in Japan, between 2003 and 2019. Among these patients, 24 developed 50 MPCN lesions, including 14 squamous cell carcinoma (SCC, 28%), 23 Bowen's disease (BD, 46%), 11 actinic keratosis (AK, 22%), and two basal cell carcinoma (BCC, 4%). No patient had malignant melanoma. The duration from transplantation to the diagnosis was significantly longer for SCC than for BD or AK (P=0.021, 0.036, respectively). Seven patients had multiple MPCNs in sun-exposed areas of skin. Among the 50 MPCNs, 40 (80%) were located in sun-exposed areas, and 10 (20%) were located in sun-protected areas. MPCNs in sun-exposed skin were frequently accompanied by dermal solar elastosis (90%, 36/40). We found high-risk human papillomavirus (HR-HPV) infections in two anogenital lesions (100%, 2/2). In contrast, HR-HPV infections were not detected in any extragenital lesions (0%, 0/30). Our results suggested that, among Japanese recipients of kidney transplant, MPCNs in sun-exposed skin areas may be associated with immunosuppression and ultraviolet exposure.
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Affiliation(s)
- Natsuki Taniguchi
- Department of Surgical Pathology, Aichi Medical University HospitalNagakute, Japan
| | - Taishi Takahara
- Department of Surgical Pathology, Aichi Medical University HospitalNagakute, Japan
| | - Takanori Ito
- Department of Surgical Pathology, Aichi Medical University HospitalNagakute, Japan
| | - Yuki Yamamoto
- Department of Surgical Pathology, Aichi Medical University HospitalNagakute, Japan
| | - Akira Satou
- Department of Surgical Pathology, Aichi Medical University HospitalNagakute, Japan
| | - Akiko Ohashi
- Department of Surgical Pathology, Aichi Medical University HospitalNagakute, Japan
| | - Emiko Takahashi
- Department of Surgical Pathology, Aichi Medical University HospitalNagakute, Japan
| | - Nagako Maeda
- Department of Surgical Pathology, Japanese Red Cross Aichi Medical Center Nagoya Daini HospitalJapan
| | - Toyonori Tsuzuki
- Department of Surgical Pathology, Aichi Medical University HospitalNagakute, Japan
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Gondek LP. CHIP: is clonal hematopoiesis a surrogate for aging and other disease? HEMATOLOGY. AMERICAN SOCIETY OF HEMATOLOGY. EDUCATION PROGRAM 2021; 2021:384-389. [PMID: 34889429 PMCID: PMC8791098 DOI: 10.1182/hematology.2021000270] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Somatic mutations are an unavoidable consequence of aging tissues. Even though most mutations are functionally silent, some may affect genes critical to proper tissue self-renewal and differentiation, resulting in the outgrowth of affected cells, also known as clonal expansion. In hematopoietic tissue such clonal dominance is known as clonal hematopoiesis (CH). Sporadic CH is frequent in aging and affects over 10% of individuals beyond the fifth decade of life. It has been associated with an increased risk of hematologic malignancies and cardiovascular disease. In addition to aging, CH has been observed in other hematologic conditions and confers an adaptation of hematopoietic stem cells (HSCs) to various environmental stressors and cell-intrinsic defects. In the presence of extrinsic stressors such as genotoxic therapies, T-cell-mediated immune attack, or inflammation, somatic mutations may result in augmentation of HSC fitness. Such attuned HSCs can evade the environmental insults and outcompete their unadapted counterparts. Similarly, in inherited bone marrow failures, somatic mutations in HSCs frequently lead to the reversion of inherited defects. This may occur via the direct correction of germline mutations or indirect compensatory mechanisms. Occasionally, such adaptation may involve oncogenes or tumor suppressors, resulting in malignant transformation. In this brief article, we focus on the mechanisms of clonal dominance in various clinical and biological contexts.
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Affiliation(s)
- Lukasz P. Gondek
- Correspondence Lukasz P. Gondek, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, 1650 Orleans St, CRB1-290, Baltimore, MD 21287; e-mail:
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Duijster JW, Franz E, Neefjes J, Mughini-Gras L. Bacterial and Parasitic Pathogens as Risk Factors for Cancers in the Gastrointestinal Tract: A Review of Current Epidemiological Knowledge. Front Microbiol 2021; 12:790256. [PMID: 34956157 PMCID: PMC8692736 DOI: 10.3389/fmicb.2021.790256] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 11/11/2021] [Indexed: 12/12/2022] Open
Abstract
The oncogenic potential of viral infections is well established and documented for many years already. However, the contribution of (commensal) bacteria and parasites to the development and progression of cancers has only recently gained momentum, resulting in a rapid growth of publications on the topic. Indeed, various bacteria and parasites have been suggested to play a role in the development of gastrointestinal cancer in particular. Therefore, an overview of the current epidemiological knowledge on the association between infections with bacteria and parasites and cancers of the gastrointestinal tract is needed. In this review, we summarized the methodological characteristics and main results of epidemiological studies investigating the association of 10 different bacteria (Bacteroides fragilis, Campylobacter spp., Clostridium spp., Enterococcus faecalis, Escherichia coli, Fusobacterium nucleatum, Porphyromonas gingivalis, non-typhoidal Salmonella, Salmonella Typhi, and Streptococcus spp.) and three parasites (Cryptosporidium spp., Schistosoma spp., and Strongyloides stercoralis) with gastrointestinal cancer. While the large body of studies based on microbiome sequencing provides valuable insights into the relative abundance of different bacterial taxa in cancer patients as compared to individuals with pre-malignant conditions or healthy controls, more research is needed to fulfill Koch's postulates, possibly making use of follow-up data, to assess the complex role of bacterial and parasitic infections in cancer epidemiology. Studies incorporating follow-up time between detection of the bacterium or parasite and cancer diagnosis remain valuable as these allow for estimation of cause-effect relationships.
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Affiliation(s)
- Janneke W. Duijster
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
- Department of Cell and Chemical Biology, Oncode Institute, Leiden University Medical Center, Leiden, Netherlands
| | - Eelco Franz
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Jacques Neefjes
- Department of Cell and Chemical Biology, Oncode Institute, Leiden University Medical Center, Leiden, Netherlands
| | - Lapo Mughini-Gras
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands
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47
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Lee W, Wang Z, Saffern M, Jun T, Huang KL. Genomic and molecular features distinguish young adult cancer from later-onset cancer. Cell Rep 2021; 37:110005. [PMID: 34788626 PMCID: PMC8631509 DOI: 10.1016/j.celrep.2021.110005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 08/20/2021] [Accepted: 10/25/2021] [Indexed: 02/07/2023] Open
Abstract
Young adult cancer has increased in incidence worldwide, but its molecular etiologies remain unclear. We systematically characterize genomic profiles of young adult tumors with ages of onset ≤50 years and compare them to later-onset tumors using over 6,000 cases across 14 cancer types. While young adult tumors generally show lower mutation burdens and comparable copy-number variation rates compared to later-onset cases, they are enriched for multiple driver mutations and copy-number alterations in subtype-specific contexts. Characterization of tumor immune microenvironments reveals pan-cancer patterns of elevated TGF-β response/dendritic cells and lower IFN-γ response/macrophages relative to later-onset tumors, corresponding to age-related responses to immunotherapy in several cancer types. Finally, we identify prevalent clinically actionable events that disproportionally affect young adult or later-onset cases. The resulting catalog of age-related molecular drivers can guide precision diagnostics and treatments for young adult cancer.
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Affiliation(s)
- William Lee
- Department of Genetics and Genomic Sciences, Center for Transformative Disease Modeling, Tisch Cancer Institute, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Zishan Wang
- Department of Genetics and Genomic Sciences, Center for Transformative Disease Modeling, Tisch Cancer Institute, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Miriam Saffern
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Tomi Jun
- Division of Hematology and Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kuan-Lin Huang
- Department of Genetics and Genomic Sciences, Center for Transformative Disease Modeling, Tisch Cancer Institute, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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48
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Mutational patterns and their correlation to CHIP-related mutations and age in hematological malignancies. Blood Adv 2021; 5:4426-4434. [PMID: 34570179 PMCID: PMC8579257 DOI: 10.1182/bloodadvances.2021004668] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 08/03/2021] [Indexed: 01/17/2023] Open
Abstract
Comparison of the mutation frequencies and numbers of 122 genes in 3096 cases enables identification of “mutation-driven” entities. Differences in mutation patterns in cases with or without CHIP-associated mutations across entities suggest differences in pathophysiology.
Acquired somatic mutations are crucial for the development of most cancers. We performed a comprehensive comparative analysis of the mutational landscapes and their correlation with CHIP-related (clonal hematopoiesis of indeterminate potential) mutations and patient age of 122 genes in 3096 cases of 28 different hematological malignancies. Differences were observed regarding (1) the median number of mutations (highest, median n = 4; lowest, n = 0); (2) specificity of certain mutations (high frequencies in atypical chronic myeloid leukemia [aCML; ASXL1, 86%], follicular lymphoma [FL; KMT2D, 87%; CREBBP, 73%], hairy cell lymphoma [BRAF, 100%], lymphoplasmacytic lymphoma [MYD88, 98%; CXCR4, 51%], myeloproliferative neoplasm [MPN; AK2, 68%]); (3) distribution of mutations (broad distribution within/across the myeloid/lymphoid lineage for TET2, ASXL1, DNMT3A, TP53, BCOR, and ETV6); (4) correlation of mutations with patient’s age (correlated with older age across entities: TET2, DNMT3A, ASXL1, TP53, EZH2, BCOR, GATA2, and IDH2; younger age: KIT, POT1, RAD21, U2AF2, and WT1); (5) correlation of mutation number per patient with age. Moreover, we observed high frequencies of mutations in RUNX1, SRSF2, IDH2, NRAS, and EZH2 in cases comprising at least 1 DTA (DNMT3A, TET2, ASXL1) mutation, whereas in cases without DTA mutations, TP53, KRAS, WT1, and SF3B1 were more frequent across entities, suggesting differences in pathophysiology. These results give further insight into the complex genetic landscape and the role of DTA mutations in hematological neoplasms and define mutation-driven entities (myelodysplastic syndrome/MPN overlap; secondary acute myeloid) in comparison with entities defined by chromosomal fusions (chronic myeloid leukemia; myeloid/lymphoid neoplasm with eosinophilia).
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49
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Rodak O, Peris-Díaz MD, Olbromski M, Podhorska-Okołów M, Dzięgiel P. Current Landscape of Non-Small Cell Lung Cancer: Epidemiology, Histological Classification, Targeted Therapies, and Immunotherapy. Cancers (Basel) 2021; 13:4705. [PMID: 34572931 PMCID: PMC8470525 DOI: 10.3390/cancers13184705] [Citation(s) in RCA: 82] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Revised: 09/13/2021] [Accepted: 09/16/2021] [Indexed: 02/07/2023] Open
Abstract
Non-small cell lung cancer (NSCLC) is a subtype of the most frequently diagnosed cancer in the world. Its epidemiology depends not only on tobacco exposition but also air quality. While the global trends in NSCLC incidence have started to decline, we can observe region-dependent differences related to the education and the economic level of the patients. Due to an increasing understanding of NSCLC biology, new diagnostic and therapeutic strategies have been developed, such as the reorganization of histopathological classification or tumor genotyping. Precision medicine is focused on the recognition of a genetic mutation in lung cancer cells called "driver mutation" to provide a variety of specific inhibitors of improperly functioning proteins. A rapidly growing group of approved drugs for targeted therapy in NSCLC currently allows the following mutated proteins to be treated: EGFR family (ERBB-1, ERBB-2), ALK, ROS1, MET, RET, NTRK, and RAF. Nevertheless, one of the most frequent NSCLC molecular sub-types remains without successful treatment: the K-Ras protein. In this review, we discuss the current NSCLC landscape treatment focusing on targeted therapy and immunotherapy, including first- and second-line monotherapies, immune checkpoint inhibitors with chemotherapy treatment, and approved predictive biomarkers.
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Affiliation(s)
- Olga Rodak
- Department of Histology and Embryology, Department of Human Morphology and Embryology, Wroclaw Medical University, 50-368 Wroclaw, Poland; (M.O.); (P.D.)
| | - Manuel David Peris-Díaz
- Department of Chemical Biology, Faculty of Biotechnology, University of Wroclaw, F. Joliot-Curie 14a, 50-383 Wroclaw, Poland;
| | - Mateusz Olbromski
- Department of Histology and Embryology, Department of Human Morphology and Embryology, Wroclaw Medical University, 50-368 Wroclaw, Poland; (M.O.); (P.D.)
| | - Marzenna Podhorska-Okołów
- Department of Ultrastructural Research, Department of Human Morphology and Embryology, Wroclaw Medical University, 50-368 Wroclaw, Poland;
| | - Piotr Dzięgiel
- Department of Histology and Embryology, Department of Human Morphology and Embryology, Wroclaw Medical University, 50-368 Wroclaw, Poland; (M.O.); (P.D.)
- Department of Physiotherapy, University School of Physical Education, 51-612 Wroclaw, Poland
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50
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Jiang P, Ollodart AR, Sudhesh V, Herr AJ, Dunham MJ, Harris K. A modified fluctuation assay reveals a natural mutator phenotype that drives mutation spectrum variation within Saccharomyces cerevisiae. eLife 2021; 10:68285. [PMID: 34523420 PMCID: PMC8497059 DOI: 10.7554/elife.68285] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 09/14/2021] [Indexed: 12/23/2022] Open
Abstract
Although studies of Saccharomyces cerevisiae have provided many insights into mutagenesis and DNA repair, most of this work has focused on a few laboratory strains. Much less is known about the phenotypic effects of natural variation within S. cerevisiae’s DNA repair pathways. Here, we use natural polymorphisms to detect historical mutation spectrum differences among several wild and domesticated S. cerevisiae strains. To determine whether these differences are likely caused by genetic mutation rate modifiers, we use a modified fluctuation assay with a CAN1 reporter to measure de novo mutation rates and spectra in 16 of the analyzed strains. We measure a 10-fold range of mutation rates and identify two strains with distinctive mutation spectra. These strains, known as AEQ and AAR, come from the panel’s ‘Mosaic beer’ clade and share an enrichment for C > A mutations that is also observed in rare variation segregating throughout the genomes of several Mosaic beer and Mixed origin strains. Both AEQ and AAR are haploid derivatives of the diploid natural isolate CBS 1782, whose rare polymorphisms are enriched for C > A as well, suggesting that the underlying mutator allele is likely active in nature. We use a plasmid complementation test to show that AAR and AEQ share a mutator allele in the DNA repair gene OGG1, which excises 8-oxoguanine lesions that can cause C > A mutations if left unrepaired.
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Affiliation(s)
- Pengyao Jiang
- Department of Genome Sciences, University of Washington, Seattle, United States
| | - Anja R Ollodart
- Department of Genome Sciences, University of Washington, Seattle, United States.,Molecular and Cellular Biology Program, University of Washington, Seattle, United States
| | - Vidha Sudhesh
- Department of Genome Sciences, University of Washington, Seattle, United States
| | - Alan J Herr
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, United States
| | - Maitreya J Dunham
- Department of Genome Sciences, University of Washington, Seattle, United States
| | - Kelley Harris
- Department of Genome Sciences, University of Washington, Seattle, United States.,Department of Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, United States
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