1
|
Cheng Z, Ennis DP, Lu B, Mirza HB, Sokota C, Kaur B, Singh N, Le Saux O, Russo G, Giannone G, Tookman LA, Krell J, Barnes C, McDermott J, McNeish IA. The genomic trajectory of ovarian high-grade serous carcinoma can be observed in STIC lesions. J Pathol 2024; 264:42-54. [PMID: 38956451 DOI: 10.1002/path.6322] [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: 02/23/2024] [Revised: 04/18/2024] [Accepted: 05/22/2024] [Indexed: 07/04/2024]
Abstract
Ovarian high-grade serous carcinoma (HGSC) originates in the fallopian tube, with secretory cells carrying a TP53 mutation, known as p53 signatures, identified as potential precursors. p53 signatures evolve into serous tubal intraepithelial carcinoma (STIC) lesions, which in turn progress into invasive HGSC, which readily spreads to the ovary and disseminates around the peritoneal cavity. We recently investigated the genomic landscape of early- and late-stage HGSC and found higher ploidy in late-stage (median 3.1) than early-stage (median 2.0) samples. Here, to explore whether the high ploidy and possible whole-genome duplication (WGD) observed in late-stage disease were determined early in the evolution of HGSC, we analysed archival formalin-fixed paraffin-embedded (FFPE) samples from five HGSC patients. p53 signatures and STIC lesions were laser-capture microdissected and sequenced using shallow whole-genome sequencing (sWGS), while invasive ovarian/fallopian tube and metastatic carcinoma samples underwent macrodissection and were profiled using both sWGS and targeted next-generation sequencing. Results showed highly similar patterns of global copy number change between STIC lesions and invasive carcinoma samples within each patient. Ploidy changes were evident in STIC lesions, but not p53 signatures, and there was a strong correlation between ploidy in STIC lesions and invasive ovarian/fallopian tube and metastatic samples in each patient. The reconstruction of sample phylogeny for each patient from relative copy number indicated that high ploidy, when present, occurred early in the evolution of HGSC, which was further validated by copy number signatures in ovarian and metastatic tumours. These findings suggest that aberrant ploidy, suggestive of WGD, arises early in HGSC and is detected in STIC lesions, implying that the trajectory of HGSC may be determined at the earliest stages of tumour development. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Collapse
Affiliation(s)
- Zhao Cheng
- Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College London, London, UK
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK
| | - Darren P Ennis
- Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Bingxin Lu
- Department of Cell and Developmental Biology, University College London, London, UK
| | - Hasan B Mirza
- Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Chishimba Sokota
- Department of Cellular Pathology, Imperial College Healthcare NHS Trust, London, UK
| | - Baljeet Kaur
- Department of Cellular Pathology, Imperial College Healthcare NHS Trust, London, UK
| | - Naveena Singh
- Department of Pathology, Barts Healthcare NHS Trust, London, UK
| | - Olivia Le Saux
- Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Giorgia Russo
- Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Gaia Giannone
- Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Laura A Tookman
- Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Jonathan Krell
- Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College London, London, UK
| | - Chris Barnes
- Department of Cell and Developmental Biology, University College London, London, UK
| | - Jackie McDermott
- Department of Cellular Pathology, Imperial College Healthcare NHS Trust, London, UK
| | - Iain A McNeish
- Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College London, London, UK
| |
Collapse
|
2
|
Xiao F, Wang Z, Qiao L, Zhang X, Wu N, Wang J, Yu X. Application of PARP inhibitors combined with immune checkpoint inhibitors in ovarian cancer. J Transl Med 2024; 22:778. [PMID: 39169400 PMCID: PMC11337781 DOI: 10.1186/s12967-024-05583-z] [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: 06/02/2024] [Accepted: 08/04/2024] [Indexed: 08/23/2024] Open
Abstract
The advent of polyadenosine diphosphate ribose polymerase inhibitors (PARPi) has brought about significant changes in the field of ovarian cancer treatment. However, in 2022, Rucaparib, Olaparib, and Niraparib, had their marketing approval revoked for third-line and subsequent therapies due to an increased potential for adverse events. Consequently, the exploration of new treatment modalities remains imperative. Recently, the integration of PARPi with immune checkpoint inhibitors (ICIs) has emerged as a potential remedy option within the context of ovarian cancer. This article offers a comprehensive examination of the mechanisms and applications of PARPi and ICIs in the treatment of ovarian cancer. It synthesizes the existing evidence supporting their combined use and discusses key considerations that merit attention in ongoing development efforts.
Collapse
Affiliation(s)
- Fen Xiao
- Department of Basic Medical Sciences, School of Medicine, Hunan Normal University, Changsha, China
- Hunan Gynecological Tumor Clinical Research Center; Hunan Key Laboratory of Cancer Metabolism; Hunan Cancer Hospital, and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - ZhiBin Wang
- Hunan Gynecological Tumor Clinical Research Center; Hunan Key Laboratory of Cancer Metabolism; Hunan Cancer Hospital, and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Liu Qiao
- Department of Basic Medical Sciences, School of Medicine, Hunan Normal University, Changsha, China
- Hunan Gynecological Tumor Clinical Research Center; Hunan Key Laboratory of Cancer Metabolism; Hunan Cancer Hospital, and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Xiu Zhang
- Hunan Gynecological Tumor Clinical Research Center; Hunan Key Laboratory of Cancer Metabolism; Hunan Cancer Hospital, and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - NaYiYuan Wu
- Hunan Gynecological Tumor Clinical Research Center; Hunan Key Laboratory of Cancer Metabolism; Hunan Cancer Hospital, and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China.
| | - Jing Wang
- Hunan Gynecological Tumor Clinical Research Center; Hunan Key Laboratory of Cancer Metabolism; Hunan Cancer Hospital, and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China.
| | - Xing Yu
- Department of Basic Medical Sciences, School of Medicine, Hunan Normal University, Changsha, China.
- Key Laboratory of Model Animals and Stem Cell Biology of Hunan Province, School of Medicine, Hunan Normal University, Changsha, China.
- Research Center of Reproduction and Translational Medicine of Hunan Province, School of Medicine, Hunan Normal University, Changsha, China.
- Hunan Provincial Key Laboratory of Regional Hereditary Birth Defects Prevention and Control, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal University, Changsha, China.
| |
Collapse
|
3
|
Kandoussi I, El Haddoumi G, Mansouri M, Belyamani L, Ibrahimi A, Eljaoudi R. Overcoming Resistance in Cancer Therapy: Computational Exploration of PIK3CA Mutations, Unveiling Novel Non-Toxic Inhibitors, and Molecular Insights Into Targeting PI3Kα. Bioinform Biol Insights 2024; 18:11779322241269386. [PMID: 39176270 PMCID: PMC11339747 DOI: 10.1177/11779322241269386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 06/21/2024] [Indexed: 08/24/2024] Open
Abstract
Phosphoinositide-3-kinases (PI3 K) are pivotal regulators of cell signaling implicated in various cancers. Particularly, mutations in the PIK3CA gene encoding the p110α catalytic subunit drive oncogenic signaling, making it an attractive therapeutic target. Our study conducted in silico exploration of 31 PIK3CA mutations across breast, endometrial, colon, and ovarian cancers, assessing their impacts on response to PI3Kα inhibitors and identifying potential non-toxic inhibitors and also elucidating their effects on protein stability and flexibility. Specifically, we observed significant alterations in the stability and flexibility of the PI3 K protein induced by these mutations. Through molecular docking analysis, we evaluated the binding interactions between the selected inhibitors and the PI3 K protein. The filtration of ligands involved calculating chemical descriptors, incorporating Veber and Lipinski rules, as well as IC50 values and toxicity predictions. This process reduced the initial dataset of 1394 ligands to 12 potential non-toxic inhibitors, and four reference inhibitors with significant biological activity in clinical trials were then chosen based on their physico-chemical properties. This analysis revealed Lig5's exceptional performance, exhibiting superior affinity and specificity compared to established reference inhibitors such as pictilisib. Lig5 formed robust binding interactions with the PI3 K protein, suggesting its potential as a highly effective therapeutic agent against PI3 K-driven cancers. Furthermore, molecular dynamics simulations provided valuable insights into Lig5's stability and its interactions with PI3 K over 100 ns. These simulations supported Lig5's potential as a versatile inhibitor capable of effectively targeting various mutational profiles of PI3 K, thereby mitigating issues related to resistance and toxicity commonly associated with current inhibitors.
Collapse
Affiliation(s)
- Ilham Kandoussi
- Biotechnology Lab (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed V University in Rabat, Rabat, Morocco
| | - Ghyzlane El Haddoumi
- Biotechnology Lab (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed V University in Rabat, Rabat, Morocco
| | - Mariam Mansouri
- Biotechnology Lab (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed V University in Rabat, Rabat, Morocco
| | - Lahcen Belyamani
- Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco
- Emergency Department, Military Hospital Mohammed V, Medical and Pharmacy School, Mohammed V University in Rabat, Rabat, Morocco
| | - Azeddine Ibrahimi
- Biotechnology Lab (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed V University in Rabat, Rabat, Morocco
| | - Rachid Eljaoudi
- Biotechnology Lab (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed V University in Rabat, Rabat, Morocco
- Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco
- Emergency Department, Military Hospital Mohammed V, Medical and Pharmacy School, Mohammed V University in Rabat, Rabat, Morocco
- Department of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, Mohammed V University in Rabat, Rabat, Morocco
| |
Collapse
|
4
|
Diaz JEL, Barcessat V, Bahamon C, Hecht C, Das TK, Cagan RL. Functional exploration of copy number alterations in a Drosophila model of triple-negative breast cancer. Dis Model Mech 2024; 17:dmm050191. [PMID: 38721669 PMCID: PMC11247506 DOI: 10.1242/dmm.050191] [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: 03/14/2023] [Accepted: 04/30/2024] [Indexed: 07/04/2024] Open
Abstract
Accounting for 10-20% of breast cancer cases, triple-negative breast cancer (TNBC) is associated with a disproportionate number of breast cancer deaths. One challenge in studying TNBC is its genomic profile: with the exception of TP53 loss, most breast cancer tumors are characterized by a high number of copy number alterations (CNAs), making modeling the disease in whole animals challenging. We computationally analyzed 186 CNA regions previously identified in breast cancer tumors to rank genes within each region by likelihood of acting as a tumor driver. We then used a Drosophila p53-Myc TNBC model to identify 48 genes as functional drivers. To demonstrate the utility of this functional database, we established six 3-hit models; altering candidate genes led to increased aspects of transformation as well as resistance to the chemotherapeutic drug fluorouracil. Our work provides a functional database of CNA-associated TNBC drivers, and a template for an integrated computational/whole-animal approach to identify functional drivers of transformation and drug resistance within CNAs in other tumor types.
Collapse
Affiliation(s)
- Jennifer E L Diaz
- Department of Cell, Development, and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Internal Medicine, UCLA David Geffen School of Medicine, CA 90095, USA
| | - Vanessa Barcessat
- Department of Cell, Development, and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Christian Bahamon
- Department of Cell, Development, and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Chana Hecht
- Department of Cell, Development, and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Tirtha K Das
- Department of Cell, Development, and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ross L Cagan
- Department of Cell, Development, and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- School of Cancer Sciences and Wolfson Wohl Cancer Research Centre, University of Glasgow, Glasgow G61 1BD, UK
| |
Collapse
|
5
|
Carels N. Assessing RNA-Seq Workflow Methodologies Using Shannon Entropy. BIOLOGY 2024; 13:482. [PMID: 39056677 PMCID: PMC11274087 DOI: 10.3390/biology13070482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 06/20/2024] [Accepted: 06/27/2024] [Indexed: 07/28/2024]
Abstract
RNA-seq faces persistent challenges due to the ongoing, expanding array of data processing workflows, none of which have yet achieved standardization to date. It is imperative to determine which method most effectively preserves biological facts. Here, we used Shannon entropy as a tool for depicting the biological status of a system. Thus, we assessed the measurement of Shannon entropy by several RNA-seq workflow approaches, such as DESeq2 and edgeR, but also by combining nine normalization methods with log2 fold change on paired samples of TCGA RNA-seq representing datasets of 515 patients and spanning 12 different cancer types with 5-year overall survival rates ranging from 20% to 98%. Our analysis revealed that TPM, RLE, and TMM normalization, coupled with a threshold of log2 fold change ≥1, for identifying differentially expressed genes, yielded the best results. We propose that Shannon entropy can serve as an objective metric for refining the optimization of RNA-seq workflows and mRNA sequencing technologies.
Collapse
Affiliation(s)
- Nicolas Carels
- Laboratory of Biological System Modeling, Center of Technological Development in Health (CDTS), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro 21040-900, RJ, Brazil
| |
Collapse
|
6
|
Klockner TC, Campbell CS. Selection forces underlying aneuploidy patterns in cancer. Mol Cell Oncol 2024; 11:2369388. [PMID: 38919375 PMCID: PMC11197905 DOI: 10.1080/23723556.2024.2369388] [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: 02/21/2024] [Accepted: 06/13/2024] [Indexed: 06/27/2024]
Abstract
Aneuploidy, the presence of an aberrant number of chromosomes, has been associated with tumorigenesis for over a century. More recently, advances in karyotyping techniques have revealed its high prevalence in cancer: About 90% of solid tumors and 50-70% of hematopoietic cancers exhibit chromosome gains or losses. When analyzed at the level of specific chromosomes, there are strong patterns that are observed in cancer karyotypes both pan-cancer and for specific cancer types. These specific aneuploidy patterns correlate strongly with outcomes for tumor initiation, progression, metastasis formation, immune evasion and resistance to therapeutic treatment. Despite their prominence, understanding the basis underlying aneuploidy patterns in cancer has been challenging. Advances in genetic engineering and bioinformatic analyses now offer insights into the genetic determinants of aneuploidy pattern selection. Overall, there is substantial evidence that expression changes of particular genes can act as the positive selective forces for adaptation through aneuploidy. Recent findings suggest that multiple genes contribute to the selection of specific aneuploid chromosomes in cancer; however, further research is necessary to identify the most impactful driver genes. Determining the genetic basis and accompanying vulnerabilities of specific aneuploidy patterns is an essential step in selectively targeting these hallmarks of tumors.
Collapse
Affiliation(s)
- Tamara C. Klockner
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Vienna, Austria
- Center for Molecular Biology, Department of Chromosome Biology, University of Vienna, Vienna, Austria
- A Doctoral School of the University of Vienna and the Medical University of Vienna, Vienna, Austria
| | - Christopher S. Campbell
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Vienna, Austria
- Center for Molecular Biology, Department of Chromosome Biology, University of Vienna, Vienna, Austria
| |
Collapse
|
7
|
El-Sayed MM, Bianco JR, Li Y, Fabian Z. Tumor-Agnostic Therapy-The Final Step Forward in the Cure for Human Neoplasms? Cells 2024; 13:1071. [PMID: 38920700 PMCID: PMC11201516 DOI: 10.3390/cells13121071] [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: 05/01/2024] [Revised: 06/17/2024] [Accepted: 06/18/2024] [Indexed: 06/27/2024] Open
Abstract
Cancer accounted for 10 million deaths in 2020, nearly one in every six deaths annually. Despite advancements, the contemporary clinical management of human neoplasms faces a number of challenges. Surgical removal of tumor tissues is often not possible technically, while radiation and chemotherapy pose the risk of damaging healthy cells, tissues, and organs, presenting complex clinical challenges. These require a paradigm shift in developing new therapeutic modalities moving towards a more personalized and targeted approach. The tumor-agnostic philosophy, one of these new modalities, focuses on characteristic molecular signatures of transformed cells independently of their traditional histopathological classification. These include commonly occurring DNA aberrations in cancer cells, shared metabolic features of their homeostasis or immune evasion measures of the tumor tissues. The first dedicated, FDA-approved tumor-agnostic agent's profound progression-free survival of 78% in mismatch repair-deficient colorectal cancer paved the way for the accelerated FDA approvals of novel tumor-agnostic therapeutic compounds. Here, we review the historical background, current status, and future perspectives of this new era of clinical oncology.
Collapse
Affiliation(s)
| | | | | | - Zsolt Fabian
- School of Medicine and Dentistry, Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK; (M.M.E.-S.); (J.R.B.); (Y.L.)
| |
Collapse
|
8
|
Miao Y, Bai Y, Miao J, Murray AA, Lin J, Dong J, Qu Z, Zhang RY, Nguyen QD, Wang S, Yu J, Nguele Meke F, Zhang ZY. Off-target autophagy inhibition by SHP2 allosteric inhibitors contributes to their antitumor activity in RAS-driven cancers. J Clin Invest 2024; 134:e177142. [PMID: 38842946 PMCID: PMC11291269 DOI: 10.1172/jci177142] [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: 10/31/2023] [Accepted: 06/04/2024] [Indexed: 08/02/2024] Open
Abstract
Aberrant activation of RAS/MAPK signaling is common in cancer, and efforts to inhibit pathway components have yielded drugs with promising clinical activities. Unfortunately, treatment-provoked adaptive resistance mechanisms inevitably develop, limiting their therapeutic potential. As a central node essential for receptor tyrosine kinase-mediated RAS activation, SHP2 has emerged as an attractive cancer target. Consequently, many SHP2 allosteric inhibitors are now in clinical testing. Here we discovered a previously unrecognized off-target effect associated with SHP2 allosteric inhibitors. We found that these inhibitors accumulate in the lysosome and block autophagic flux in an SHP2-independent manner. We showed that off-target autophagy inhibition by SHP2 allosteric inhibitors contributes to their antitumor activity. We also demonstrated that SHP2 allosteric inhibitors harboring this off-target activity not only suppress oncogenic RAS signaling but also overcome drug resistance such as MAPK rebound and protective autophagy in response to RAS/MAPK pathway blockage. Finally, we exemplified a therapeutic framework that harnesses both the on- and off-target activities of SHP2 allosteric inhibitors for improved treatment of mutant RAS-driven and drug-resistant malignancies such as pancreatic and colorectal cancers.
Collapse
Affiliation(s)
- Yiming Miao
- Department of Medicinal Chemistry and Molecular Pharmacology and
| | - Yunpeng Bai
- Department of Medicinal Chemistry and Molecular Pharmacology and
| | - Jinmin Miao
- Department of Medicinal Chemistry and Molecular Pharmacology and
| | | | - Jianping Lin
- Department of Medicinal Chemistry and Molecular Pharmacology and
| | - Jiajun Dong
- Department of Medicinal Chemistry and Molecular Pharmacology and
| | - Zihan Qu
- Department of Chemistry, Purdue University, West Lafayette, Indiana, USA
| | - Ruo-Yu Zhang
- Department of Medicinal Chemistry and Molecular Pharmacology and
| | - Quyen D. Nguyen
- Department of Chemistry, Purdue University, West Lafayette, Indiana, USA
| | - Shaomeng Wang
- Departments of Internal Medicine, Pharmacology, and Medicinal Chemistry, University of Michigan, Ann Arbor, Michigan, USA
| | - Jingmei Yu
- Department of Medicinal Chemistry and Molecular Pharmacology and
| | | | - Zhong-Yin Zhang
- Department of Medicinal Chemistry and Molecular Pharmacology and
- Department of Chemistry, Purdue University, West Lafayette, Indiana, USA
- Institute for Cancer Research and
- Institute for Drug Discovery, Purdue University, West Lafayette, Indiana, USA
| |
Collapse
|
9
|
Carceles-Cordon M, Orme JJ, Domingo-Domenech J, Rodriguez-Bravo V. The yin and yang of chromosomal instability in prostate cancer. Nat Rev Urol 2024; 21:357-372. [PMID: 38307951 PMCID: PMC11156566 DOI: 10.1038/s41585-023-00845-9] [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] [Accepted: 12/13/2023] [Indexed: 02/04/2024]
Abstract
Metastatic prostate cancer remains an incurable lethal disease. Studies indicate that prostate cancer accumulates genomic changes during disease progression and displays the highest levels of chromosomal instability (CIN) across all types of metastatic tumours. CIN, which refers to ongoing chromosomal DNA gain or loss during mitosis, and derived aneuploidy, are known to be associated with increased tumour heterogeneity, metastasis and therapy resistance in many tumour types. Paradoxically, high CIN levels are also proposed to be detrimental to tumour cell survival, suggesting that cancer cells must develop adaptive mechanisms to ensure their survival. In the context of prostate cancer, studies indicate that CIN has a key role in disease progression and might also offer a therapeutic vulnerability that can be pharmacologically targeted. Thus, a comprehensive evaluation of the causes and consequences of CIN in prostate cancer, its contribution to aggressive advanced disease and a better understanding of the acquired CIN tolerance mechanisms can translate into new tumour classifications, biomarker development and therapeutic strategies.
Collapse
Affiliation(s)
| | - Jacob J Orme
- Department of Oncology, Mayo Clinic, Rochester, MN, USA
| | - Josep Domingo-Domenech
- Department of Urology, Mayo Clinic, Rochester, MN, USA.
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, USA.
| | - Veronica Rodriguez-Bravo
- Department of Urology, Mayo Clinic, Rochester, MN, USA.
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, USA.
| |
Collapse
|
10
|
Sun T, Zhang P, Zhang Q, Wang B, Zhao Q, Liu F, Ma X, Zhao C, Zhou X, Chen R, Ouyang S. Transcriptome analysis reveals PRKCA as a potential therapeutic target for overcoming cisplatin resistance in lung cancer through ferroptosis. Heliyon 2024; 10:e30780. [PMID: 38765024 PMCID: PMC11096979 DOI: 10.1016/j.heliyon.2024.e30780] [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: 10/30/2023] [Revised: 05/03/2024] [Accepted: 05/06/2024] [Indexed: 05/21/2024] Open
Abstract
Cisplatin-based chemotherapy is the current standard care for lung cancer patients; however, drug resistance frequently develops during treatment, thereby limiting therapeutic efficacy.The molecular mechanisms underlying cisplatin resistance remain elusive. In this study, we conducted an analysis of microarray data from the Gene Expression Omnibus (GEO) database under the accession numbers GSE21656, which encompassed expression profiling of cisplatin-resistant H460 (DDP-H460)and the parental cells (H460). Subsequently, we calculated the differentially expressed genes (DEGs) between DDP-H460 and H460. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs demonstrated significant impact on the Rap1, PI3K/AKT and MAPK signaling pathways. Moreover, protein and protein interaction (PPI) network analysis identified PRKCA, DET1, and UBE2N as hub genes that potentially contribute predominantly to cisplatin resistance. Ultimately, PRKCA was selected for validation due to its significant prognostic effect, which predicts unfavorable overall survival and disease-free survival in patients with lung cancer. Network analysis conducted on The Cancer Genome Atlas (TCGA) database revealed a strong gene-level correlation between PRKCA and TP53, CDKN2A, BYR2, TTN, KRAS, and PIK3CA; whereas at the protein level, it exhibited a high correlation with EGFR, Lck, Bcl2, and Syk. The in vitro experiments revealed that PRKCA was upregulated in the cisplatin-resistant A549 cells (DDP-A549), while knockdown of PRKCA increased DDP-A549 apoptosis upon cisplatin treatment. Moreover, we observed that PRKCA knockdown attenuated DDP-A549 proliferation, migration and invasion ability. Western blot analysis demonstrated that PRKCA knockdown downregulated phosphorylation of PI3K expression while upregulated the genes involved in ferroptosis signaling. In summary, our results elucidate the role of PRKCA in acquiring resistance to cisplatin and underscore its potential as a therapeutic target for cisplatin-resistant lung cancer.
Collapse
Affiliation(s)
- Ting Sun
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Penghua Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qingyi Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Binhui Wang
- Biotherapy Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China
- Cancer Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China
| | - Qitai Zhao
- Biotherapy Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China
- Cancer Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China
| | - Fenghui Liu
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Xiaohua Ma
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Chunling Zhao
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Xiaolei Zhou
- Department of Respiratory medicine, Henan Province Chest Hospital, Zhengzhou 450052, Henan, China
| | - Ruiying Chen
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Songyun Ouyang
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| |
Collapse
|
11
|
Xi Y, Zheng K, Deng F, Liu Y, Sun H, Zheng Y, Tong HHY, Ji Y, Zhang Y, Chen W, Zhang Y, Zou X, Hao J. Themis: advancing precision oncology through comprehensive molecular subtyping and optimization. Brief Bioinform 2024; 25:bbae261. [PMID: 38833322 PMCID: PMC11149663 DOI: 10.1093/bib/bbae261] [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: 01/30/2024] [Revised: 04/30/2024] [Accepted: 05/21/2024] [Indexed: 06/06/2024] Open
Abstract
Recent advances in tumor molecular subtyping have revolutionized precision oncology, offering novel avenues for patient-specific treatment strategies. However, a comprehensive and independent comparison of these subtyping methodologies remains unexplored. This study introduces 'Themis' (Tumor HEterogeneity analysis on Molecular subtypIng System), an evaluation platform that encapsulates a few representative tumor molecular subtyping methods, including Stemness, Anoikis, Metabolism, and pathway-based classifications, utilizing 38 test datasets curated from The Cancer Genome Atlas (TCGA) and significant studies. Our self-designed quantitative analysis uncovers the relative strengths, limitations, and applicability of each method in different clinical contexts. Crucially, Themis serves as a vital tool in identifying the most appropriate subtyping methods for specific clinical scenarios. It also guides fine-tuning existing subtyping methods to achieve more accurate phenotype-associated results. To demonstrate the practical utility, we apply Themis to a breast cancer dataset, showcasing its efficacy in selecting the most suitable subtyping methods for personalized medicine in various clinical scenarios. This study bridges a crucial gap in cancer research and lays a foundation for future advancements in individualized cancer therapy and patient management.
Collapse
Affiliation(s)
- Yue Xi
- Department of Reproductive Medicine, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Province, 250013, China
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Kun Zheng
- Department of Urology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
| | - Fulan Deng
- School of Materials Science and Engineering, Shanghai Institute of Technology, Shanghai 201418, China
| | - Yujun Liu
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Hourong Sun
- Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Department of Cardiovascular Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Yingxia Zheng
- Department of Laboratory Medicine, Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Henry H Y Tong
- Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China
| | - Yuan Ji
- Molecular Pathology center, Dept. Pathology, Zhongshan Hospital, Fudan University
| | - Yingchun Zhang
- Department of Reproductive Medicine, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Province, 250013, China
| | - Wantao Chen
- Ninth People's Hospital, Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, National Clinical Research Center of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Yiming Zhang
- Department of Reproductive Medicine, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Province, 250013, China
| | - Xin Zou
- National Engineering Center for Biochip at Shanghai, China
| | - Jie Hao
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
| |
Collapse
|
12
|
Jiang L, Jia L, Wang Y, Wu Y, Yue J. Adap-BDCM: Adaptive Bilinear Dynamic Cascade Model for Classification Tasks on CNV Datasets. Interdiscip Sci 2024:10.1007/s12539-024-00635-w. [PMID: 38758306 DOI: 10.1007/s12539-024-00635-w] [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: 12/21/2023] [Revised: 04/18/2024] [Accepted: 04/23/2024] [Indexed: 05/18/2024]
Abstract
Copy number variation (CNV) is an essential genetic driving factor of cancer formation and progression, making intelligent classification based on CNV feasible. However, there are a few challenges in the current machine learning and deep learning methods, such as the design of base classifier combination schemes in ensemble methods and the selection of layers of neural networks, which often result in low accuracy. Therefore, an adaptive bilinear dynamic cascade model (Adap-BDCM) is developed to further enhance the accuracy and applicability of these methods for intelligent classification on CNV datasets. In this model, a feature selection module is introduced to mitigate the interference of redundant information, and a bilinear model based on the gated attention mechanism is proposed to extract more beneficial deep fusion features. Furthermore, an adaptive base classifier selection scheme is designed to overcome the difficulty of manually designing base classifier combinations and enhance the applicability of the model. Lastly, a novel feature fusion scheme with an attribute recall submodule is constructed, effectively avoiding getting stuck in local solutions and missing some valuable information. Numerous experiments have demonstrated that our Adap-BDCM model exhibits optimal performance in cancer classification, stage prediction, and recurrence on CNV datasets. This study can assist physicians in making diagnoses faster and better.
Collapse
Affiliation(s)
- Liancheng Jiang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030600, China
| | - Liye Jia
- College of Computer Science and Technology, Taiyuan Normal University, Taiyuan, 030619, China
| | - Yizhen Wang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030600, China
| | - Yongfei Wu
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030600, China
| | - Junhong Yue
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030600, China.
| |
Collapse
|
13
|
Wickland DP, McNinch C, Jessen E, Necela B, Shreeder B, Lin Y, Knutson KL, Asmann YW. Comprehensive profiling of cancer neoantigens from aberrant RNA splicing. J Immunother Cancer 2024; 12:e008988. [PMID: 38754917 PMCID: PMC11097882 DOI: 10.1136/jitc-2024-008988] [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] [Accepted: 04/29/2024] [Indexed: 05/18/2024] Open
Abstract
BACKGROUND Cancer neoantigens arise from protein-altering somatic mutations in tumor and rank among the most promising next-generation immuno-oncology agents when used in combination with immune checkpoint inhibitors. We previously developed a computational framework, REAL-neo, for identification, quality control, and prioritization of both class-I and class-II human leucocyte antigen (HLA)-presented neoantigens resulting from somatic single-nucleotide mutations, small insertions and deletions, and gene fusions. In this study, we developed a new module, SPLICE-neo, to identify neoantigens from aberrant RNA transcripts from two distinct sources: (1) DNA mutations within splice sites and (2) de novo RNA aberrant splicings. METHODS First, SPLICE-neo was used to profile all DNA splice-site mutations in 11,892 tumors from The Cancer Genome Atlas (TCGA) and identified 11 profiles of splicing donor or acceptor site gains or losses. Transcript isoforms resulting from the top seven most frequent profiles were computed using novel logic models. Second, SPLICE-neo identified de novo RNA splicing events using RNA sequencing reads mapped to novel exon junctions from either single, double, or multiple exon-skipping events. The aberrant transcripts from both sources were then ranked based on isoform expression levels and z-scores assuming that individual aberrant splicing events are rare. Finally, top-ranked novel isoforms were translated into protein, and the resulting neoepitopes were evaluated for neoantigen potential using REAL-neo. The top splicing neoantigen candidates binding to HLA-A*02:01 were validated using in vitro T2 binding assays. RESULTS We identified abundant splicing neoantigens in four representative TCGA cancers: BRCA, LUAD, LUSC, and LIHC. In addition to their substantial contribution to neoantigen load, several splicing neoantigens were potent tumor antigens with stronger bindings to HLA compared with the positive control of antigens from influenza virus. CONCLUSIONS SPLICE-neo is the first tool to comprehensively identify and prioritize splicing neoantigens from both DNA splice-site mutations and de novo RNA aberrant splicings. There are two major advances of SPLICE-neo. First, we developed novel logic models that assemble and prioritize full-length aberrant transcripts from DNA splice-site mutations. Second, SPLICE-neo can identify exon-skipping events involving more than two exons, which account for a quarter to one-third of all skipping events.
Collapse
Affiliation(s)
- Daniel P Wickland
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida, USA
| | - Colton McNinch
- National Institute of Allergy and Infectious Diseases, Bethesda, Maryland, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Erik Jessen
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Brian Necela
- Department of Immunology, Mayo Clinic, Jacksonville, Florida, USA
| | - Barath Shreeder
- Department of Immunology, Mayo Clinic, Jacksonville, Florida, USA
| | - Yi Lin
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Keith L Knutson
- Department of Immunology, Mayo Clinic, Jacksonville, Florida, USA
| | - Yan W Asmann
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida, USA
| |
Collapse
|
14
|
Gaillard DHK, Lof P, Sistermans EA, Mokveld T, Horlings HM, Mom CH, Reinders MJT, Amant F, van den Broek D, Wessels LFA, Lok CAR. Evaluating the effectiveness of pre-operative diagnosis of ovarian cancer using minimally invasive liquid biopsies by combining serum human epididymis protein 4 and cell-free DNA in patients with an ovarian mass. Int J Gynecol Cancer 2024; 34:713-721. [PMID: 38388177 DOI: 10.1136/ijgc-2023-005073] [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] [Indexed: 02/24/2024] Open
Abstract
OBJECTIVE To assess the feasibility of scalable, objective, and minimally invasive liquid biopsy-derived biomarkers such as cell-free DNA copy number profiles, human epididymis protein 4 (HE4), and cancer antigen 125 (CA125) for pre-operative risk assessment of early-stage ovarian cancer in a clinically representative and diagnostically challenging population and to compare the performance of these biomarkers with the Risk of Malignancy Index (RMI). METHODS In this case-control study, we included 100 patients with an ovarian mass clinically suspected to be early-stage ovarian cancer. Of these 100 patients, 50 were confirmed to have a malignant mass (cases) and 50 had a benign mass (controls). Using WisecondorX, an algorithm used extensively in non-invasive prenatal testing, we calculated the benign-calibrated copy number profile abnormality score. This score represents how different a sample is from benign controls based on copy number profiles. We combined this score with HE4 serum concentration to separate cases and controls. RESULTS Combining the benign-calibrated copy number profile abnormality score with HE4, we obtained a model with a significantly higher sensitivity (42% vs 0%; p<0.002) at 99% specificity as compared with the RMI that is currently employed in clinical practice. Investigating performance in subgroups, we observed especially large differences in the advanced stage and non-high-grade serous ovarian cancer groups. CONCLUSION This study demonstrates that cell-free DNA can be successfully employed to perform pre-operative risk of malignancy assessment for ovarian masses; however, results warrant validation in a more extensive clinical study.
Collapse
Affiliation(s)
- Duco H K Gaillard
- Division of Molecular Carcinogenesis, Netherlands Cancer Institute, Amsterdam, The Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, Netherlands
| | - Pien Lof
- Department of Gynecological Oncology, Center for Gynecologic Oncology Amsterdam, Amsterdam, Netherlands
| | - Erik A Sistermans
- Department of Human Genetics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Amsterdam Reproduction & Development, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
| | - Tom Mokveld
- Delft Bioinformatics Lab, Delft University of Technology, Delft, Netherlands
| | - Hugo Mark Horlings
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Constantijne H Mom
- Department of Gynecological Oncology, Center for Gynecologic Oncology Amsterdam, Amsterdam, Netherlands
| | - Marcel J T Reinders
- Delft Bioinformatics Lab, Delft University of Technology, Delft, Netherlands
| | - Frédéric Amant
- Department of Gynecological Oncology, Center for Gynecologic Oncology Amsterdam, Amsterdam, Netherlands
- Division of Gynecologic Oncology, UZ Leuven, Leuven, Belgium
| | - Daan van den Broek
- Department of Laboratory Medicine, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Lodewyk F A Wessels
- Division of Molecular Carcinogenesis, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Christianne A R Lok
- Department of Gynecological Oncology, Center for Gynecologic Oncology Amsterdam, Amsterdam, Netherlands
| |
Collapse
|
15
|
Luan W, Cheng H, Xie H, Liu H, Wang Y, Wang S, Ye X, Zhu H, Tang F, Li Y, Chang X. PRKDC-Mediated NHEJ May Play a Crucial Role in Aneuploidy of Chromosome 8-Driven Progression of Ovarian Cancer. Int J Mol Sci 2024; 25:4825. [PMID: 38732044 PMCID: PMC11084440 DOI: 10.3390/ijms25094825] [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: 02/08/2024] [Revised: 04/15/2024] [Accepted: 04/20/2024] [Indexed: 05/13/2024] Open
Abstract
High malignancy is a prominent characteristic of epithelial ovarian cancer (EOC), emphasizing the necessity for further elucidation of the potential mechanisms underlying cancer progression. Aneuploidy and copy number variation (CNV) partially contribute to the heightened malignancy observed in EOC; however, the precise features of aneuploidy and their underlying molecular patterns, as well as the relationship between CNV and aneuploidy in EOC, remain unclear. In this study, we employed single-cell sequencing data along with The Cancer Genome Atlas (TCGA) to investigate aneuploidy and CNV in EOC. The technique of fluorescence in situ hybridization (FISH) was employed using specific probes. The copy number variation within the genomic region of chromosome 8 (42754568-47889815) was assessed and utilized as a representative measure for the ploidy status of individual cells in chromosome 8. Differential expression analysis was performed between different subgroups based on chromosome 8 ploidy. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI), and hub-gene analyses were subsequently utilized to identify crucial genes involved. By classifying enriched tumor cells into distinct subtypes based on chromosome 8 ploidy combined with TCGA data integration, we identified key genes driving chromosome 8 aneuploidy in EOC, revealing that PRKDC gene involvement through the mediated non-homologous end-joining pathway may play a pivotal role in disease progression. Further validation through analysis of the GEO and TCGA database and survival assessment, considering both mRNA expression levels and CNV status of PRKDC, has confirmed its involvement in the progression of EOC. Further functional analysis revealed an upregulation of PRKDC in both ovarian EOC cells and tissues, with its expression showing a significant correlation with the extent of copy number variation (CNV) on chromosome 8. Taken together, CNV amplification and aneuploidy of chromosome 8 are important characteristics of EOC. PRKDC and the mediated NHEJ pathway may play a crucial role in driving aneuploidy on chromosome 8 during the progression of EOC.
Collapse
Affiliation(s)
- Wenqing Luan
- Department of Obstetrics and Gynecology, Peking University People’s Hospital, School of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing 100044, China; (W.L.); (H.C.); (H.X.); (H.L.); (Y.W.); (S.W.); (X.Y.); (H.Z.); (F.T.)
- Center of Gynecologic Oncology, Peking University People’s Hospital, Beijing 100044, China
| | - Hongyan Cheng
- Department of Obstetrics and Gynecology, Peking University People’s Hospital, School of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing 100044, China; (W.L.); (H.C.); (H.X.); (H.L.); (Y.W.); (S.W.); (X.Y.); (H.Z.); (F.T.)
- Center of Gynecologic Oncology, Peking University People’s Hospital, Beijing 100044, China
| | - Haoling Xie
- Department of Obstetrics and Gynecology, Peking University People’s Hospital, School of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing 100044, China; (W.L.); (H.C.); (H.X.); (H.L.); (Y.W.); (S.W.); (X.Y.); (H.Z.); (F.T.)
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing 100871, China
| | - Huiping Liu
- Department of Obstetrics and Gynecology, Peking University People’s Hospital, School of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing 100044, China; (W.L.); (H.C.); (H.X.); (H.L.); (Y.W.); (S.W.); (X.Y.); (H.Z.); (F.T.)
- Center of Gynecologic Oncology, Peking University People’s Hospital, Beijing 100044, China
| | - Yicheng Wang
- Department of Obstetrics and Gynecology, Peking University People’s Hospital, School of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing 100044, China; (W.L.); (H.C.); (H.X.); (H.L.); (Y.W.); (S.W.); (X.Y.); (H.Z.); (F.T.)
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing 100871, China
| | - Shang Wang
- Department of Obstetrics and Gynecology, Peking University People’s Hospital, School of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing 100044, China; (W.L.); (H.C.); (H.X.); (H.L.); (Y.W.); (S.W.); (X.Y.); (H.Z.); (F.T.)
- Center of Gynecologic Oncology, Peking University People’s Hospital, Beijing 100044, China
| | - Xue Ye
- Department of Obstetrics and Gynecology, Peking University People’s Hospital, School of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing 100044, China; (W.L.); (H.C.); (H.X.); (H.L.); (Y.W.); (S.W.); (X.Y.); (H.Z.); (F.T.)
- Center of Gynecologic Oncology, Peking University People’s Hospital, Beijing 100044, China
| | - Honglan Zhu
- Department of Obstetrics and Gynecology, Peking University People’s Hospital, School of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing 100044, China; (W.L.); (H.C.); (H.X.); (H.L.); (Y.W.); (S.W.); (X.Y.); (H.Z.); (F.T.)
- Center of Gynecologic Oncology, Peking University People’s Hospital, Beijing 100044, China
| | - Fuchou Tang
- Department of Obstetrics and Gynecology, Peking University People’s Hospital, School of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing 100044, China; (W.L.); (H.C.); (H.X.); (H.L.); (Y.W.); (S.W.); (X.Y.); (H.Z.); (F.T.)
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing 100871, China
| | - Yi Li
- Department of Obstetrics and Gynecology, Peking University People’s Hospital, School of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing 100044, China; (W.L.); (H.C.); (H.X.); (H.L.); (Y.W.); (S.W.); (X.Y.); (H.Z.); (F.T.)
- Center of Gynecologic Oncology, Peking University People’s Hospital, Beijing 100044, China
| | - Xiaohong Chang
- Department of Obstetrics and Gynecology, Peking University People’s Hospital, School of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing 100044, China; (W.L.); (H.C.); (H.X.); (H.L.); (Y.W.); (S.W.); (X.Y.); (H.Z.); (F.T.)
- Center of Gynecologic Oncology, Peking University People’s Hospital, Beijing 100044, China
| |
Collapse
|
16
|
Lin CJ, Jin X, Ma D, Chen C, Ou-Yang Y, Pei YC, Zhou CZ, Qu FL, Wang YJ, Liu CL, Fan L, Hu X, Shao ZM, Jiang YZ. Genetic interactions reveal distinct biological and therapeutic implications in breast cancer. Cancer Cell 2024; 42:701-719.e12. [PMID: 38593782 DOI: 10.1016/j.ccell.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 01/16/2024] [Accepted: 03/13/2024] [Indexed: 04/11/2024]
Abstract
Co-occurrence and mutual exclusivity of genomic alterations may reflect the existence of genetic interactions, potentially shaping distinct biological phenotypes and impacting therapeutic response in breast cancer. However, our understanding of them remains limited. Herein, we investigate a large-scale multi-omics cohort (n = 873) and a real-world clinical sequencing cohort (n = 4,405) including several clinical trials with detailed treatment outcomes and perform functional validation in patient-derived organoids, tumor fragments, and in vivo models. Through this comprehensive approach, we construct a network comprising co-alterations and mutually exclusive events and characterize their therapeutic potential and underlying biological basis. Notably, we identify associations between TP53mut-AURKAamp and endocrine therapy resistance, germline BRCA1mut-MYCamp and improved sensitivity to PARP inhibitors, and TP53mut-MYBamp and immunotherapy resistance. Furthermore, we reveal that precision treatment strategies informed by co-alterations hold promise to improve patient outcomes. Our study highlights the significance of genetic interactions in guiding genome-informed treatment decisions beyond single driver alterations.
Collapse
Affiliation(s)
- Cai-Jin Lin
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Xi Jin
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Ding Ma
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Chao Chen
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Yang Ou-Yang
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Yu-Chen Pei
- Precision Cancer Medical Center, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Chao-Zheng Zhou
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Fei-Lin Qu
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Yun-Jin Wang
- Precision Cancer Medical Center, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Cheng-Lin Liu
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Lei Fan
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Xin Hu
- Precision Cancer Medical Center, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
| | - Zhi-Ming Shao
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.
| | - Yi-Zhou Jiang
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.
| |
Collapse
|
17
|
Denisenko E, de Kock L, Tan A, Beasley AB, Beilin M, Jones ME, Hou R, Muirí DÓ, Bilic S, Mohan GRKA, Salfinger S, Fox S, Hmon KPW, Yeow Y, Kim Y, John R, Gilderman TS, Killingbeck E, Gray ES, Cohen PA, Yu Y, Forrest ARR. Spatial transcriptomics reveals discrete tumour microenvironments and autocrine loops within ovarian cancer subclones. Nat Commun 2024; 15:2860. [PMID: 38570491 PMCID: PMC10991508 DOI: 10.1038/s41467-024-47271-y] [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: 10/05/2022] [Accepted: 03/26/2024] [Indexed: 04/05/2024] Open
Abstract
High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment.
Collapse
Affiliation(s)
- Elena Denisenko
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia.
| | - Leanne de Kock
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada
| | - Adeline Tan
- Anatomical Pathology Department, Clinipath, Sonic Healthcare, Perth, WA, 6017, Australia
| | - Aaron B Beasley
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, 6027, Australia
| | - Maria Beilin
- Department of Gynaecological Oncology, Bendat Family Comprehensive Cancer Centre, St John of God Subiaco Hospital, 12 Salvado Rd, Subiaco, WA, 6008, Australia
| | - Matthew E Jones
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | - Rui Hou
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | - Dáithí Ó Muirí
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | - Sanela Bilic
- Department of Gynaecological Oncology, Bendat Family Comprehensive Cancer Centre, St John of God Subiaco Hospital, 12 Salvado Rd, Subiaco, WA, 6008, Australia
| | - G Raj K A Mohan
- Department of Gynaecological Oncology, Bendat Family Comprehensive Cancer Centre, St John of God Subiaco Hospital, 12 Salvado Rd, Subiaco, WA, 6008, Australia
- School of Medicine, University of Notre Dame, Fremantle, WA, 6160, Australia
| | | | - Simon Fox
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | - Khaing P W Hmon
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | - Yen Yeow
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia
| | | | - Rhea John
- NanoString Technologies, Seattle, WA, USA
| | | | | | - Elin S Gray
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, 6027, Australia
| | - Paul A Cohen
- Division of Obstetrics and Gynaecology, Medical School, University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia.
- Institute for Health Research, The University of Notre Dame Australia, 32 Mouat Street Fremantle, Fremantle, WA, 6160, Australia.
| | - Yu Yu
- Division of Obstetrics and Gynaecology, Medical School, University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia.
- Curtin Medical School, Curtin University, 410 Koorliny Way, Bentley, WA, 6102, Australia.
- Curtin Health Innovation Research Institute, Curtin University B305, Bentley, WA, 6102, Australia.
| | - Alistair R R Forrest
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Nedlands, Perth, WA, 6009, Australia.
| |
Collapse
|
18
|
Dinh KN, Vázquez-García I, Chan A, Malhotra R, Weiner A, McPherson AW, Tavaré S. CINner: modeling and simulation of chromosomal instability in cancer at single-cell resolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.03.587939. [PMID: 38617259 PMCID: PMC11014621 DOI: 10.1101/2024.04.03.587939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Cancer development is characterized by chromosomal instability, manifesting in frequent occurrences of different genomic alteration mechanisms ranging in extent and impact. Mathematical modeling can help evaluate the role of each mutational process during tumor progression, however existing frameworks can only capture certain aspects of chromosomal instability (CIN). We present CINner, a mathematical framework for modeling genomic diversity and selection during tumor evolution. The main advantage of CINner is its flexibility to incorporate many genomic events that directly impact cellular fitness, from driver gene mutations to copy number alterations (CNAs), including focal amplifications and deletions, missegregations and whole-genome duplication (WGD). We apply CINner to find chromosome-arm selection parameters that drive tumorigenesis in the absence of WGD in chromosomally stable cancer types. We found that the selection parameters predict WGD prevalence among different chromosomally unstable tumors, hinting that the selective advantage of WGD cells hinges on their tolerance for aneuploidy and escape from nullisomy. Direct application of CINner to model the WGD proportion and fraction of genome altered (FGA) further uncovers the increase in CNA probabilities associated with WGD in each cancer type. CINner can also be utilized to study chromosomally stable cancer types, by applying a selection model based on driver gene mutations and focal amplifications or deletions. Finally, we used CINner to analyze the impact of CNA probabilities, chromosome selection parameters, tumor growth dynamics and population size on cancer fitness and heterogeneity. We expect that CINner will provide a powerful modeling tool for the oncology community to quantify the impact of newly uncovered genomic alteration mechanisms on shaping tumor progression and adaptation.
Collapse
Affiliation(s)
- Khanh N. Dinh
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA
- Department of Statistics, Columbia University, New York, NY, USA
| | - Ignacio Vázquez-García
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrew Chan
- Case Western Reserve University, Cleveland, OH, USA
| | - Rhea Malhotra
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Stanford University, Palo Alto, CA, USA
| | - Adam Weiner
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Andrew W. McPherson
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Simon Tavaré
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA
- Department of Statistics, Columbia University, New York, NY, USA
| |
Collapse
|
19
|
Jiang YZ, Ma D, Jin X, Xiao Y, Yu Y, Shi J, Zhou YF, Fu T, Lin CJ, Dai LJ, Liu CL, Zhao S, Su GH, Hou W, Liu Y, Chen Q, Yang J, Zhang N, Zhang WJ, Liu W, Ge W, Yang WT, You C, Gu Y, Kaklamani V, Bertucci F, Verschraegen C, Daemen A, Shah NM, Wang T, Guo T, Shi L, Perou CM, Zheng Y, Huang W, Shao ZM. Integrated multiomic profiling of breast cancer in the Chinese population reveals patient stratification and therapeutic vulnerabilities. NATURE CANCER 2024; 5:673-690. [PMID: 38347143 DOI: 10.1038/s43018-024-00725-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 01/04/2024] [Indexed: 04/30/2024]
Abstract
Molecular profiling guides precision treatment of breast cancer; however, Asian patients are underrepresented in publicly available large-scale studies. We established a comprehensive multiomics cohort of 773 Chinese patients with breast cancer and systematically analyzed their genomic, transcriptomic, proteomic, metabolomic, radiomic and digital pathology characteristics. Here we show that compared to breast cancers in white individuals, Asian individuals had more targetable AKT1 mutations. Integrated analysis revealed a higher proportion of HER2-enriched subtype and correspondingly more frequent ERBB2 amplification and higher HER2 protein abundance in the Chinese HR+HER2+ cohort, stressing anti-HER2 therapy for these individuals. Furthermore, comprehensive metabolomic and proteomic analyses revealed ferroptosis as a potential therapeutic target for basal-like tumors. The integration of clinical, transcriptomic, metabolomic, radiomic and pathological features allowed for efficient stratification of patients into groups with varying recurrence risks. Our study provides a public resource and new insights into the biology and ancestry specificity of breast cancer in the Asian population, offering potential for further precision treatment approaches.
Collapse
Affiliation(s)
- Yi-Zhou Jiang
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Ding Ma
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xi Jin
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi Xiao
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ying Yu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Jinxiu Shi
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), Shanghai, China
| | - Yi-Fan Zhou
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Tong Fu
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Cai-Jin Lin
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lei-Jie Dai
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Cheng-Lin Liu
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shen Zhao
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Guan-Hua Su
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wanwan Hou
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Yaqing Liu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Qingwang Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Jingcheng Yang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
- Greater Bay Area Institute of Precision Medicine, Guangzhou, China
| | - Naixin Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Wen-Juan Zhang
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei Liu
- Westlake Omics (Hangzhou) Biotechnology, Hangzhou, China
| | - Weigang Ge
- Westlake Omics (Hangzhou) Biotechnology, Hangzhou, China
| | - Wen-Tao Yang
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Chao You
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yajia Gu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Virginia Kaklamani
- Division Haematology/Oncology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - François Bertucci
- Predictive Oncology Laboratory and Department of Medical Oncology, CRCM, Institut Paoli-Calmettes, Inserm UMR1068, CNRS UMR7258, Aix-Marseille Université, Marseille, France
| | | | - Anneleen Daemen
- Department of Bioinformatics and Computational Biology, Genentech, South San Francisco, CA, USA
| | - Nakul M Shah
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - Ting Wang
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Tiannan Guo
- Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- School of Medicine, School of Life Sciences, Westlake University, Hangzhou, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, China
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China
- International Human Phenome Institutes (Shanghai), Shanghai, China
| | - Charles M Perou
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Shanghai Cancer Center, Fudan University, Shanghai, China.
| | - Wei Huang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), Shanghai, China.
| | - Zhi-Ming Shao
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
| |
Collapse
|
20
|
Fan P, Tao P, Wang Z, Wang J, Hou Y, Lu W, Ma L, Zhang Y, Tong H. Evaluation of AJCC staging system and proposal of a novel stage grouping system in retroperitoneal liposarcoma: the Fudan Zhongshan experience. Front Oncol 2024; 14:1373762. [PMID: 38601763 PMCID: PMC11004455 DOI: 10.3389/fonc.2024.1373762] [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: 01/20/2024] [Accepted: 03/18/2024] [Indexed: 04/12/2024] Open
Abstract
Background Overall survival (OS) varies significantly among individuals with heterogeneous retroperitoneal liposarcoma (RPLS), even among those with the same clinical stage. Improved staging of RPLS is a critical unmet need, given the disappointing results of external validations of the 8th American Joint Committee on Cancer (AJCC) TNM staging system. Methods The cohort study included 220 consecutive patients who underwent surgical resection for primary RPLS at the largest sarcoma centre of Fudan University in China from September 2009 to August 2021, combined with 277 adult patients with RPLS in the SEER database from 1975 to 2020. Data analysis was performed from December 2021 to December 2022. Patients were retrospectively restaged according to the 8th and 7th editions of the TNM staging system as well as the new TNM (nTNM) staging system. The primary endpoint was overall survival (OS). Comparative analysis of postoperative survival was performed using the Kaplan-Meier method, and differences between subgroups were tested using the log-rank test. The OS prediction nomogram was generated based on baseline variables and tumour characteristics. Harrell's consistency index (C-index), area under the curve (AUC) of receiver operating characteristic curves (ROC), and calibration curves were used to evaluate the performance of the nomogram. Results A total of 497 patients were enrolled in the study, including 282 (56.7%) male patients. The median follow-up was 51 months (interquartile range, IQR, 23-83), and the OS rates at 1, 3, and 5 years were 87.9%, 75.3%, and 64.9%, respectively. According to the staging distribution of the AJCC 7th edition, 6 patients were stage IA (1.2%), 189 patients were stage IB (38%), 12 patients were stage IIA (2.4%), 150 patients were stage IIB (30.1%), 131 patients were stage III (26.3%), and 9 patients were stage IV (1.8%). With the 8th edition staging, this distribution changed: 6 patients (1.2%) were stage IA, 189 patients (38%) were stage IB, 12 patients (2.4%) were stage II, 24 patients (4.8%) were stage IIIA, 257 patients (51.7%) were stage IIIB, and 9 patients (1.8%) were stage IV. 182 patients (36.6%) were reclassified according to the nTNM staging system with the new T stage classification. The C-index and log-rank score improved after implementation of nTNM implementation. The nTNM system was associated with improved identification of high-risk patients compared with the AJCC 7th and 8th TNM. The FNCLCC stage proved to be highly prognostic with significant intergroup differences in OS. The calibration curve shows a high degree of agreement between the actual OS rate and the nomogram estimated OS rate. Conclusion Compared with 8th AJCC TNM, 7th AJCC TNM staging system showed a more homogeneous staging distribution and a slight improvement in the prognostic accuracy of RPLS. The revised T-stage and nTNM systems showed better risk stratification performance. The FNCLCC stage was found to have high prognostic value, further emphasising histological grade is the least negligible prognostic factor in predicting patient survival. The constructed nomogram model enables individualized prognostic analysis and helps to develop risk-adapted therapy for RPLS patients.
Collapse
Affiliation(s)
- Peidang Fan
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
- First Affiliated Hospital, Anhui University of Science and Technology, Huainan, China
| | - Ping Tao
- Department of Laboratory Medicine, Shanghai Traditional Chinese Medicine-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhenyu Wang
- Department of General Surgery, Jinshan Hospital, Fudan University, Shanghai, China
| | - Jiongyuan Wang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yingyong Hou
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Weiqi Lu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Lijie Ma
- Department of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Yong Zhang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of General Surgery, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China
- Xiamen Clinical Research Center for Cancer Therapy, Xiamen, China
| | - Hanxing Tong
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| |
Collapse
|
21
|
Treekitkarnmongkol W, Solis LM, Sankaran D, Gagea M, Singh PK, Mistry R, Nguyen T, Kai K, Liu J, Sasai K, Jitsumori Y, Liu J, Nagao N, Stossi F, Mancini MA, Wistuba II, Thompson AM, Lee JM, Cadiñanos J, Wong KK, Abbott CM, Sahin AA, Liu S, Katayama H, Sen S. eEF1A2 promotes PTEN-GSK3β-SCF complex-dependent degradation of Aurora kinase A and is inactivated in breast cancer. Sci Signal 2024; 17:eadh4475. [PMID: 38442201 DOI: 10.1126/scisignal.adh4475] [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: 03/03/2023] [Accepted: 02/15/2024] [Indexed: 03/07/2024]
Abstract
The translation elongation factor eEF1A promotes protein synthesis. Its methylation by METTL13 increases its activity, supporting tumor growth. However, in some cancers, a high abundance of eEF1A isoforms is associated with a good prognosis. Here, we found that eEF1A2 exhibited oncogenic or tumor-suppressor functions depending on its interaction with METTL13 or the phosphatase PTEN, respectively. METTL13 and PTEN competed for interaction with eEF1A2 in the same structural domain. PTEN-bound eEF1A2 promoted the ubiquitination and degradation of the mitosis-promoting Aurora kinase A in the S and G2 phases of the cell cycle. eEF1A2 bridged the interactions between the SKP1-CUL1-FBXW7 (SCF) ubiquitin ligase complex, the kinase GSK3β, and Aurora-A, thereby facilitating the phosphorylation of Aurora-A in a degron site that was recognized by FBXW7. Genetic ablation of Eef1a2 or Pten in mice resulted in a greater abundance of Aurora-A and increased cell cycling in mammary tumors, which was corroborated in breast cancer tissues from patients. Reactivating this pathway using fimepinostat, which relieves inhibitory signaling directed at PTEN and increases FBXW7 expression, combined with inhibiting Aurora-A with alisertib, suppressed breast cancer cell proliferation in culture and tumor growth in vivo. The findings demonstrate a therapeutically exploitable, tumor-suppressive role for eEF1A2 in breast cancer.
Collapse
Affiliation(s)
- Warapen Treekitkarnmongkol
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Luisa M Solis
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Deivendran Sankaran
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Mihai Gagea
- Department of Veterinary Medicine and Surgery, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Pankaj K Singh
- Center for Translational Cancer Research, Texas A&M Health Science Center, Institute of Biosciences and Technology, Houston, TX 77030, USA
| | - Ragini Mistry
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Tristian Nguyen
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Kazuharu Kai
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jiajun Liu
- State Key Laboratory of Bioreactor Engineering, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, PR China
| | - Kaori Sasai
- Department of Molecular Oncology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama 700-8558, Japan
| | - Yoshimi Jitsumori
- Department of Molecular Oncology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama 700-8558, Japan
| | - Jianwen Liu
- State Key Laboratory of Bioreactor Engineering, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, PR China
| | - Norio Nagao
- Department of Life and Environmental Sciences, Prefectural University of Hiroshima, Shobara, 727-0023, Japan
| | - Fabio Stossi
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Michael A Mancini
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ignacio I Wistuba
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | | | - Jonathan M Lee
- Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Juan Cadiñanos
- Fundación Centro Médico de Asturias, 33193 Oviedo, Spain
- Instituto de Medicina Oncológica y Molecular de Asturias (IMOMA), 33193 Oviedo, Spain
| | - Kwong-Kwok Wong
- Department of Gynecologic Oncology and Reproductive Medicine, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Catherine M Abbott
- Centre for Genomic & Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK
| | - Aysegul A Sahin
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Suyu Liu
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Hiroshi Katayama
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of Molecular Oncology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama 700-8558, Japan
| | - Subrata Sen
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| |
Collapse
|
22
|
Wang Y, Chen Y, Gao J, Xie H, Guo Y, Yang J, Liu J, Chen Z, Li Q, Li M, Ren J, Wen L, Tang F. Mapping crossover events of mouse meiotic recombination by restriction fragment ligation-based Refresh-seq. Cell Discov 2024; 10:26. [PMID: 38443370 PMCID: PMC10915157 DOI: 10.1038/s41421-023-00638-9] [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: 06/02/2023] [Accepted: 12/11/2023] [Indexed: 03/07/2024] Open
Abstract
Single-cell whole-genome sequencing methods have undergone great improvements over the past decade. However, allele dropout, which means the inability to detect both alleles simultaneously in an individual diploid cell, largely restricts the application of these methods particularly for medical applications. Here, we develop a new single-cell whole-genome sequencing method based on third-generation sequencing (TGS) platform named Refresh-seq (restriction fragment ligation-based genome amplification and TGS). It is based on restriction endonuclease cutting and ligation strategy in which two alleles in an individual cell can be cut into equal fragments and tend to be amplified simultaneously. As a new single-cell long-read genome sequencing method, Refresh-seq features much lower allele dropout rate compared with SMOOTH-seq. Furthermore, we apply Refresh-seq to 688 sperm cells and 272 female haploid cells (secondary polar bodies and parthenogenetic oocytes) from F1 hybrid mice. We acquire high-resolution genetic map of mouse meiosis recombination at low sequencing depth and reveal the sexual dimorphism in meiotic crossovers. We also phase the structure variations (deletions and insertions) in sperm cells and female haploid cells with high precision. Refresh-seq shows great performance in screening aneuploid sperm cells and oocytes due to the low allele dropout rate and has great potential for medical applications such as preimplantation genetic diagnosis.
Collapse
Affiliation(s)
- Yan Wang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Yijun Chen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Junpeng Gao
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
- Emergency Center, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Haoling Xie
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Yuqing Guo
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Jingwei Yang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Jun'e Liu
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Zonggui Chen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
- Changping Laboratory, Beijing, China
| | - Qingqing Li
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Mengyao Li
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Jie Ren
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Lu Wen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
| | - Fuchou Tang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
- Changping Laboratory, Beijing, China.
| |
Collapse
|
23
|
Schneider MP, Cullen AE, Pangonyte J, Skelton J, Major H, Van Oudenhove E, Garcia MJ, Chaves Urbano B, Piskorz AM, Brenton JD, Macintyre G, Markowetz F. scAbsolute: measuring single-cell ploidy and replication status. Genome Biol 2024; 25:62. [PMID: 38438920 PMCID: PMC10910719 DOI: 10.1186/s13059-024-03204-y] [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: 06/15/2023] [Accepted: 02/22/2024] [Indexed: 03/06/2024] Open
Abstract
Cancer cells often exhibit DNA copy number aberrations and can vary widely in their ploidy. Correct estimation of the ploidy of single-cell genomes is paramount for downstream analysis. Based only on single-cell DNA sequencing information, scAbsolute achieves accurate and unbiased measurement of single-cell ploidy and replication status, including whole-genome duplications. We demonstrate scAbsolute's capabilities using experimental cell multiplets, a FUCCI cell cycle expression system, and a benchmark against state-of-the-art methods. scAbsolute provides a robust foundation for single-cell DNA sequencing analysis across different technologies and has the potential to enable improvements in a number of downstream analyses.
Collapse
Affiliation(s)
- Michael P Schneider
- University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
| | - Amy E Cullen
- University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
| | - Justina Pangonyte
- University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
| | - Jason Skelton
- University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
| | - Harvey Major
- University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
| | - Elke Van Oudenhove
- University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
| | - Maria J Garcia
- Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | | | - Anna M Piskorz
- University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
| | - James D Brenton
- University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK
| | - Geoff Macintyre
- Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Florian Markowetz
- University of Cambridge, Cambridge, UK.
- Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK.
| |
Collapse
|
24
|
Sun C, Zhang Y, Wang Z, Chen J, Zhang J, Gu Y. TMED2 promotes glioma tumorigenesis by being involved in EGFR recycling transport. Int J Biol Macromol 2024; 262:130055. [PMID: 38354922 DOI: 10.1016/j.ijbiomac.2024.130055] [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: 11/02/2023] [Revised: 01/22/2024] [Accepted: 02/06/2024] [Indexed: 02/16/2024]
Abstract
Aberrant epidermal growth factor receptor (EGFR) signaling is the core signaling commonly activated in glioma. The transmembrane emp24 protein transport domain protein 2 (TMED2) interacts with cargo proteins involved in protein sorting and transport between endoplasmic reticulum (ER) and Golgi apparatus. In this study, we found the correlation between TMED2 with glioma progression and EGFR signaling through database analysis. Moreover, we demonstrated that TMED2 is essential for glioma cell proliferation, migration, and invasion at the cellular levels, as well as tumor formation in mouse models, underscoring its significance in the pathobiology of gliomas. Mechanistically, TMED2 was found to enhance EGFR-AKT signaling by facilitating EGFR recycling, thereby providing the initial evidence of TMED2's involvement in the membrane protein recycling process. In summary, our findings shed light on the roles and underlying mechanisms of TMED2 in the regulation of glioma tumorigenesis and EGFR signaling, suggesting that targeting TMED2 could emerge as a promising therapeutic strategy for gliomas and other tumors associated with aberrant EGFR signaling.
Collapse
Affiliation(s)
- Changning Sun
- Key Laboratory of Marine Drugs, Ministry of Education, School of Medicine and Pharmacy, Ocean University of China, 5 Yushan Road, Qingdao 266003, China; College of Marine Science and Biological Engineering, Qingdao University of Science and Technology, Qingdao 266042, China; Laboratory for Marine Drugs and Bioproducts of Laoshan Laboratory, Qingdao 266200, China
| | - Yihan Zhang
- Key Laboratory of Marine Drugs, Ministry of Education, School of Medicine and Pharmacy, Ocean University of China, 5 Yushan Road, Qingdao 266003, China; Laboratory for Marine Drugs and Bioproducts of Laoshan Laboratory, Qingdao 266200, China
| | - Zhuangzhi Wang
- Key Laboratory of Marine Drugs, Ministry of Education, School of Medicine and Pharmacy, Ocean University of China, 5 Yushan Road, Qingdao 266003, China; College of Marine Science and Biological Engineering, Qingdao University of Science and Technology, Qingdao 266042, China; Laboratory for Marine Drugs and Bioproducts of Laoshan Laboratory, Qingdao 266200, China
| | - Jin Chen
- College of Marine Science and Biological Engineering, Qingdao University of Science and Technology, Qingdao 266042, China
| | - Junhua Zhang
- College of Marine Science and Biological Engineering, Qingdao University of Science and Technology, Qingdao 266042, China
| | - Yuchao Gu
- College of Marine Science and Biological Engineering, Qingdao University of Science and Technology, Qingdao 266042, China; Laboratory for Marine Drugs and Bioproducts of Laoshan Laboratory, Qingdao 266200, China.
| |
Collapse
|
25
|
Dai J, Zheng S, Falco MM, Bao J, Eriksson J, Pikkusaari S, Forstén S, Jiang J, Wang W, Gao L, Perez-Villatoro F, Dufva O, Saeed K, Wang Y, Amiryousefi A, Färkkilä A, Mustjoki S, Kauppi L, Tang J, Vähärautio A. Tracing back primed resistance in cancer via sister cells. Nat Commun 2024; 15:1158. [PMID: 38326354 PMCID: PMC10850087 DOI: 10.1038/s41467-024-45478-7] [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: 04/25/2023] [Accepted: 01/24/2024] [Indexed: 02/09/2024] Open
Abstract
Exploring non-genetic evolution of cell states during cancer treatments has become attainable by recent advances in lineage-tracing methods. However, transcriptional changes that drive cells into resistant fates may be subtle, necessitating high resolution analysis. Here, we present ReSisTrace that uses shared transcriptomic features of sister cells to predict the states priming treatment resistance. Applying ReSisTrace in ovarian cancer cells perturbed with olaparib, carboplatin or natural killer (NK) cells reveals pre-resistant phenotypes defined by proteostatic and mRNA surveillance features, reflecting traits enriched in the upcoming subclonal selection. Furthermore, we show that DNA repair deficiency renders cells susceptible to both DNA damaging agents and NK killing in a context-dependent manner. Finally, we leverage the obtained pre-resistance profiles to predict and validate small molecules driving cells to sensitive states prior to treatment. In summary, ReSisTrace resolves pre-existing transcriptional features of treatment vulnerability, facilitating both molecular patient stratification and discovery of synergistic pre-sensitizing therapies.
Collapse
Affiliation(s)
- Jun Dai
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Shuyu Zheng
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Matías M Falco
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jie Bao
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Johanna Eriksson
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Sanna Pikkusaari
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Sofia Forstén
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jing Jiang
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Wenyu Wang
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Luping Gao
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Fernando Perez-Villatoro
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine, Helsinki, Finland
| | - Olli Dufva
- Research Program in Translational Immunology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Khalid Saeed
- Research Program in Translational Immunology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Yinyin Wang
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Ali Amiryousefi
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Anniina Färkkilä
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine, Helsinki, Finland
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
- Department of Obstetrics and Gynecology, and Clinical Trial Unit, Comprehensive Cancer Centre, Helsinki University Hospital, Helsinki, Finland
| | - Satu Mustjoki
- Research Program in Translational Immunology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Liisa Kauppi
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jing Tang
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
| | - Anna Vähärautio
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- Foundation for the Finnish Cancer Institute, Helsinki, Finland.
| |
Collapse
|
26
|
Jamalzadeh S, Dai J, Lavikka K, Li Y, Jiang J, Huhtinen K, Virtanen A, Oikkonen J, Hietanen S, Hynninen J, Vähärautio A, Häkkinen A, Hautaniemi S. Genome-wide quantification of copy-number aberration impact on gene expression in ovarian high-grade serous carcinoma. BMC Cancer 2024; 24:173. [PMID: 38317080 PMCID: PMC10840274 DOI: 10.1186/s12885-024-11895-6] [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: 10/25/2023] [Accepted: 01/17/2024] [Indexed: 02/07/2024] Open
Abstract
Copy-number alterations (CNAs) are a hallmark of cancer and can regulate cancer cell states via altered gene expression values. Herein, we have developed a copy-number impact (CNI) analysis method that quantifies the degree to which a gene expression value is impacted by CNAs and leveraged this analysis at the pathway level. Our results show that a high CNA is not necessarily reflected at the gene expression level, and our method is capable of detecting genes and pathways whose activity is strongly influenced by CNAs. Furthermore, the CNI analysis enables unbiased categorization of CNA categories, such as deletions and amplifications. We identified six CNI-driven pathways associated with poor treatment response in ovarian high-grade serous carcinoma (HGSC), which we found to be the most CNA-driven cancer across 14 cancer types. The key driver in most of these pathways was amplified wild-type KRAS, which we validated functionally using CRISPR modulation. Our results suggest that wild-type KRAS amplification is a driver of chemotherapy resistance in HGSC and may serve as a potential treatment target.
Collapse
Affiliation(s)
- Sanaz Jamalzadeh
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jun Dai
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Kari Lavikka
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Yilin Li
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jing Jiang
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Kaisa Huhtinen
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Institute of Biomedicine and FICAN West Cancer Centre, University of Turku and Turku University Hospital, Turku, Finland
| | - Anni Virtanen
- Department of Pathology, University of Helsinki and HUS Diagnostic Center, Helsinki University Hospital, Helsinki, Finland
| | - Jaana Oikkonen
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Sakari Hietanen
- Department of Obstetrics and Gynecology, University of Turku and Turku University Hospital, Turku, Finland
| | - Johanna Hynninen
- Department of Obstetrics and Gynecology, University of Turku and Turku University Hospital, Turku, Finland
| | - Anna Vähärautio
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Foundation for the Finnish Cancer Institute, Helsinki, Finland
| | - Antti Häkkinen
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- Computational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Sampsa Hautaniemi
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
| |
Collapse
|
27
|
Du M, Cai Q, Sun J, Zhang M, Zhang S, Liu X, Zhang M, Zhang X. Aneuploid serves as a prognostic marker and favors immunosuppressive microenvironment in ovarian cancer. J Ovarian Res 2024; 17:30. [PMID: 38308314 PMCID: PMC10836026 DOI: 10.1186/s13048-024-01356-w] [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: 09/11/2023] [Accepted: 01/18/2024] [Indexed: 02/04/2024] Open
Abstract
Ovarian cancer is the most lethal gynecologic neoplasm, and most patients experience recurrence and chemoresistance. Even the promising immunotherapy showed limited efficacy in ovarian cancer, probably due to the immunosuppressive microenvironment. However, the behind mechanisms of the immune exclusion or cold phenotype in ovarian cancer still remain to be explored. As a cancer dominated by copy number variations instead of mutations, ovarian cancer contains a high fraction of aneuploid, which might correlate with immune inhibition. Nevertheless, whether or how aneuploid affects ovarian cancer is still unclear. For exploring the role of aneuploid cancer cells and the potential ploidy-immune relationship, herein, the ploidy information was first comprehensively analyzed combining the karyotype data and copy number variation data obtained from Mitelman and cBioPortal databases, respectively. Ovarian cancer showed strong ploidy heterogeneity, with high fraction of aneuploid and recurrent arm-level and whole chromosome changes. Furthermore, clinical parameters were compared between the highly-aneuploid and the near-diploid ovarian cancers. Aneuploid indicated high grade, poor overall survival and poor disease-free survival in ovarian cancer. To understand the biofunction affected by aneuploid, the differentially expressed genes between the highly-aneuploid and the near-diploid groups were analyzed. Transcription data suggested that aneuploid cancer correlated with deregulated MHC expression, abnormal antigen presentation, and less infiltration of macrophages and activated T cells and higher level of T cell exclusion. Furthermore, the ploidy-MHC association was verified using the Human Protein Atlas database. All these data supported that aneuploid might be promising for cancer management and immune surveillance in ovarian cancer.
Collapse
Affiliation(s)
- Ming Du
- Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, China
| | - Qingqing Cai
- Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, China
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai, 200011, China
| | - Jiaan Sun
- Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, China
| | - Mingxing Zhang
- Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, China
| | - Shuo Zhang
- Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, China
| | - Xiaoxia Liu
- Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, China
| | - Mengyu Zhang
- Center for Reproductive Medicine, Naval Medical Center, Naval Medical University, Shanghai, 200052, China.
| | - Xiaoyan Zhang
- Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, China.
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai, 200011, China.
- Department of Obstetrics and Gynecology of Shanghai Medical School, Fudan University, Shanghai, 200032, China.
| |
Collapse
|
28
|
Lorkowski SW, Dermawan JK, Rubin BP. The practical utility of AI-assisted molecular profiling in the diagnosis and management of cancer of unknown primary: an updated review. Virchows Arch 2024; 484:369-375. [PMID: 37999736 DOI: 10.1007/s00428-023-03708-1] [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: 10/12/2023] [Revised: 11/07/2023] [Accepted: 11/14/2023] [Indexed: 11/25/2023]
Abstract
Cancer of unknown primary (CUP) presents a complex diagnostic challenge, characterized by metastatic tumors of unknown tissue origin and a dismal prognosis. This review delves into the emerging significance of artificial intelligence (AI) and machine learning (ML) in transforming the landscape of CUP diagnosis, classification, and treatment. ML approaches, trained on extensive molecular profiling data, have shown promise in accurately predicting tissue of origin. Genomic profiling, encompassing driver mutations and copy number variations, plays a pivotal role in CUP diagnosis by providing insights into tumor type-specific oncogenic alterations. Mutational signatures (MS), reflecting somatic mutation patterns, offer further insights into CUP diagnosis. Known MS with established etiology, such as ultraviolet (UV) light-induced DNA damage and tobacco exposure, have been identified in cases of dedifferentiated/transdifferentiated melanoma and carcinoma. Deep learning models that integrate gene expression data and DNA methylation patterns offer insights into tissue lineage and tumor classification. In digital pathology, machine learning algorithms analyze whole-slide images to aid in CUP classification. Finally, precision oncology, guided by molecular profiling, offers targeted therapies independent of primary tissue identification. Clinical trials assigning CUP patients to molecularly guided therapies, including targetable alterations and tumor mutation burden as an immunotherapy biomarker, have resulted in improved overall survival in a subset of patients. In conclusion, AI- and ML-driven approaches are revolutionizing CUP management by enhancing diagnostic accuracy. Precision oncology utilizing enhanced molecular profiling facilitates the identification of targeted therapies that transcend the need to identify the tissue of origin, ultimately improving patient outcomes.
Collapse
Affiliation(s)
- Shuhui Wang Lorkowski
- Department of Cardiovascular and Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA
| | - Josephine K Dermawan
- Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, 44195, USA
| | - Brian P Rubin
- Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.
| |
Collapse
|
29
|
Baker TM, Waise S, Tarabichi M, Van Loo P. Aneuploidy and complex genomic rearrangements in cancer evolution. NATURE CANCER 2024; 5:228-239. [PMID: 38286829 PMCID: PMC7616040 DOI: 10.1038/s43018-023-00711-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 12/14/2023] [Indexed: 01/31/2024]
Abstract
Mutational processes that alter large genomic regions occur frequently in developing tumors. They range from simple copy number gains and losses to the shattering and reassembly of entire chromosomes. These catastrophic events, such as chromothripsis, chromoplexy and the formation of extrachromosomal DNA, affect the expression of many genes and therefore have a substantial effect on the fitness of the cells in which they arise. In this review, we cover large genomic alterations, the mechanisms that cause them and their effect on tumor development and evolution.
Collapse
Affiliation(s)
- Toby M Baker
- The Francis Crick Institute, London, UK
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sara Waise
- The Francis Crick Institute, London, UK
- Cancer Sciences Unit, University of Southampton, Southampton, UK
| | - Maxime Tarabichi
- The Francis Crick Institute, London, UK
- Institute for Interdisciplinary Research (IRIBHM), Université Libre de Bruxelles, Brussels, Belgium
| | - Peter Van Loo
- The Francis Crick Institute, London, UK.
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| |
Collapse
|
30
|
Kauffmann J, Esders M, Ruff L, Montavon G, Samek W, Muller KR. From Clustering to Cluster Explanations via Neural Networks. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024; 35:1926-1940. [PMID: 35797317 DOI: 10.1109/tnnls.2022.3185901] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
A recent trend in machine learning has been to enrich learned models with the ability to explain their own predictions. The emerging field of explainable AI (XAI) has so far mainly focused on supervised learning, in particular, deep neural network classifiers. In many practical problems, however, the label information is not given and the goal is instead to discover the underlying structure of the data, for example, its clusters. While powerful methods exist for extracting the cluster structure in data, they typically do not answer the question why a certain data point has been assigned to a given cluster. We propose a new framework that can, for the first time, explain cluster assignments in terms of input features in an efficient and reliable manner. It is based on the novel insight that clustering models can be rewritten as neural networks-or "neuralized." Cluster predictions of the obtained networks can then be quickly and accurately attributed to the input features. Several showcases demonstrate the ability of our method to assess the quality of learned clusters and to extract novel insights from the analyzed data and representations.
Collapse
|
31
|
Leibold J, Tsanov KM, Amor C, Ho YJ, Sánchez-Rivera FJ, Feucht J, Baslan T, Chen HA, Tian S, Simon J, Wuest A, Wilkinson JE, Lowe SW. Somatic mouse models of gastric cancer reveal genotype-specific features of metastatic disease. NATURE CANCER 2024; 5:315-329. [PMID: 38177458 PMCID: PMC10899107 DOI: 10.1038/s43018-023-00686-w] [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: 03/22/2022] [Accepted: 11/10/2023] [Indexed: 01/06/2024]
Abstract
Metastatic gastric carcinoma is a highly lethal cancer that responds poorly to conventional and molecularly targeted therapies. Despite its clinical relevance, the mechanisms underlying the behavior and therapeutic response of this disease are poorly understood owing, in part, to a paucity of tractable models. Here we developed methods to somatically introduce different oncogenic lesions directly into the murine gastric epithelium. Genotypic configurations observed in patients produced metastatic gastric cancers that recapitulated the histological, molecular and clinical features of all nonviral molecular subtypes of the human disease. Applying this platform to both wild-type and immunodeficient mice revealed previously unappreciated links between the genotype, organotropism and immune surveillance of metastatic cells, which produced distinct patterns of metastasis that were mirrored in patients. Our results establish a highly portable platform for generating autochthonous cancer models with flexible genotypes and host backgrounds, which can unravel mechanisms of gastric tumorigenesis or test new therapeutic concepts.
Collapse
Affiliation(s)
- Josef Leibold
- Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Department of Medical Oncology and Pneumology, University Hospital Tuebingen, Tuebingen, Germany.
- iFIT Cluster of Excellence EXC 2180 'Image-Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany.
| | - Kaloyan M Tsanov
- Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Corina Amor
- Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, NY, USA
| | - Yu-Jui Ho
- Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Francisco J Sánchez-Rivera
- Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Judith Feucht
- iFIT Cluster of Excellence EXC 2180 'Image-Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
- Department I-General Paediatrics, Haematology/Oncology, University Children's Hospital Tuebingen, Tuebingen, Germany
| | - Timour Baslan
- Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Biomedical Sciences, School of Veterinary Medicine, The University of Pennsylvania, Philadelphia, PA, USA
| | - Hsuan-An Chen
- Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sha Tian
- Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Janelle Simon
- Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Alexandra Wuest
- Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - John E Wilkinson
- Department of Pathology, University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Scott W Lowe
- Cancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Howard Hughes Medical Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| |
Collapse
|
32
|
Mayol del Valle M, Morales B, Philbrick B, Adeagbo S, Goyal S, Newman S, Frontera NL, Nduom E, Olson J, Neill S, Hoang K. Intramedullary Spinal Cord Tumors: Whole-Genome Sequencing to Assist Management and Prognosis. Cancers (Basel) 2024; 16:404. [PMID: 38254893 PMCID: PMC10814932 DOI: 10.3390/cancers16020404] [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: 11/06/2023] [Revised: 12/12/2023] [Accepted: 01/02/2024] [Indexed: 01/24/2024] Open
Abstract
Intramedullary spinal cord tumors (IMSCTs) harbor unique genetic mutations which may play a role in prognostication and management. To this end, we present the largest cohort of IMSCTs with genetic characterization in the literature from our multi-site institutional registry. A total of 93 IMSCT patient records were reviewed from the years 1999 to 2020. Out of these, 61 complied with all inclusion criteria, 14 of these patients had undergone genetic studies with 8 undergoing whole-genomic sequencing. Univariate analyses were used to assess any factors associated with progression-free survival (PFS) using the Cox proportional hazards model. Firth's penalized likelihood approach was used to account for the low event rates. Fisher's exact test was performed to compare whole-genome analyses and specific gene mutations with progression. PFS (months) was given as a hazard ratio. Only the absence of copy neutral loss of heterozygosity (LOH) was shown to be significant (0.05, p = 0.008). Additionally, higher risk of recurrence/progression was associated with LOH (p = 0.0179). Our results suggest LOH as a genetic predictor of shorter progression-free survival, particularly within ependymoma and glioblastoma tumor types. Further genomic research with larger multi-institutional datasets should focus on these mutations as possible prognostic factors.
Collapse
Affiliation(s)
- Miguel Mayol del Valle
- Department of Neurosurgery, Emory University Hospital, 1365 Clifton Road NE, Suite B6200, Atlanta, GA 30322, USA; (S.N.); (E.N.); (J.O.); (K.H.)
| | - Bryan Morales
- Department of Neuropathology, Emory University Hospital, 1364 Clifton Road, NE Room H-184, Atlanta, GA 30322, USA; (B.M.); (S.N.)
| | - Brandon Philbrick
- Department of Neurosurgery, Emory University School of Medicine, 100 Woodruff Circle, Atlanta, GA 30322, USA (S.A.)
| | - Segun Adeagbo
- Department of Neurosurgery, Emory University School of Medicine, 100 Woodruff Circle, Atlanta, GA 30322, USA (S.A.)
| | - Subir Goyal
- Biostatistics Shared Resource Department, Winship Cancer Institute, Emory University, 1365-C Clifton Road, NE, Atlanta, GA 30322, USA;
| | - Sarah Newman
- Department of Neurosurgery, Emory University Hospital, 1365 Clifton Road NE, Suite B6200, Atlanta, GA 30322, USA; (S.N.); (E.N.); (J.O.); (K.H.)
| | - Natasha L. Frontera
- School of Medicine, University of Puerto Rico Medical Sciences Campus, P.O. Box 365067, San Juan 00936-5067, Puerto Rico;
| | - Edjah Nduom
- Department of Neurosurgery, Emory University Hospital, 1365 Clifton Road NE, Suite B6200, Atlanta, GA 30322, USA; (S.N.); (E.N.); (J.O.); (K.H.)
| | - Jeffrey Olson
- Department of Neurosurgery, Emory University Hospital, 1365 Clifton Road NE, Suite B6200, Atlanta, GA 30322, USA; (S.N.); (E.N.); (J.O.); (K.H.)
| | - Stewart Neill
- Department of Neuropathology, Emory University Hospital, 1364 Clifton Road, NE Room H-184, Atlanta, GA 30322, USA; (B.M.); (S.N.)
| | - Kimberly Hoang
- Department of Neurosurgery, Emory University Hospital, 1365 Clifton Road NE, Suite B6200, Atlanta, GA 30322, USA; (S.N.); (E.N.); (J.O.); (K.H.)
| |
Collapse
|
33
|
Ciriello G, Magnani L, Aitken SJ, Akkari L, Behjati S, Hanahan D, Landau DA, Lopez-Bigas N, Lupiáñez DG, Marine JC, Martin-Villalba A, Natoli G, Obenauf AC, Oricchio E, Scaffidi P, Sottoriva A, Swarbrick A, Tonon G, Vanharanta S, Zuber J. Cancer Evolution: A Multifaceted Affair. Cancer Discov 2024; 14:36-48. [PMID: 38047596 PMCID: PMC10784746 DOI: 10.1158/2159-8290.cd-23-0530] [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: 05/04/2023] [Revised: 08/29/2023] [Accepted: 10/23/2023] [Indexed: 12/05/2023]
Abstract
Cancer cells adapt and survive through the acquisition and selection of molecular modifications. This process defines cancer evolution. Building on a theoretical framework based on heritable genetic changes has provided insights into the mechanisms supporting cancer evolution. However, cancer hallmarks also emerge via heritable nongenetic mechanisms, including epigenetic and chromatin topological changes, and interactions between tumor cells and the tumor microenvironment. Recent findings on tumor evolutionary mechanisms draw a multifaceted picture where heterogeneous forces interact and influence each other while shaping tumor progression. A comprehensive characterization of the cancer evolutionary toolkit is required to improve personalized medicine and biomarker discovery. SIGNIFICANCE Tumor evolution is fueled by multiple enabling mechanisms. Importantly, genetic instability, epigenetic reprogramming, and interactions with the tumor microenvironment are neither alternative nor independent evolutionary mechanisms. As demonstrated by findings highlighted in this perspective, experimental and theoretical approaches must account for multiple evolutionary mechanisms and their interactions to ultimately understand, predict, and steer tumor evolution.
Collapse
Affiliation(s)
- Giovanni Ciriello
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Luca Magnani
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, United Kingdom
- Breast Epigenetic Plasticity and Evolution Laboratory, Division of Breast Cancer Research, The Institute of Cancer Research, London, United Kingdom
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Sarah J. Aitken
- Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, United Kingdom
- Department of Histopathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Leila Akkari
- Division of Tumor Biology and Immunology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Sam Behjati
- Wellcome Sanger Institute, Hinxton, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom
| | - Douglas Hanahan
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Ludwig Institute for Cancer Research, Lausanne, Switzerland
| | - Dan A. Landau
- New York Genome Center, New York, New York
- Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, New York
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, New York
| | - Nuria Lopez-Bigas
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Darío G. Lupiáñez
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Jean-Christophe Marine
- Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Leuven, Belgium
- Laboratory for Molecular Cancer Biology, Department of Oncology, KULeuven, Leuven, Belgium
| | - Ana Martin-Villalba
- Department of Molecular Neurobiology, German Cancer Research Center (DFKZ), Heidelberg, Germany
| | - Gioacchino Natoli
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Milan, Italy
| | - Anna C. Obenauf
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna, Austria
| | - Elisa Oricchio
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
| | - Paola Scaffidi
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Milan, Italy
- Cancer Epigenetic Laboratory, The Francis Crick Institute, London, United Kingdom
| | - Andrea Sottoriva
- Computational Biology Research Centre, Human Technopole, Milan, Italy
| | - Alexander Swarbrick
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Darlinghurst, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
| | - Giovanni Tonon
- Vita-Salute San Raffaele University, Milan, Italy
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Sakari Vanharanta
- Translational Cancer Medicine Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Biochemistry and Developmental Biology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Johannes Zuber
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna, Austria
- Medical University of Vienna, Vienna BioCenter (VBC), Vienna, Austria
| |
Collapse
|
34
|
Dai Y, Xu J, Gong X, Wei J, Gao Y, Chai R, Lu C, Zhao B, Kang Y. Human Fallopian Tube-Derived Organoids with TP53 and RAD51D Mutations Recapitulate an Early Stage High-Grade Serous Ovarian Cancer Phenotype In Vitro. Int J Mol Sci 2024; 25:886. [PMID: 38255960 PMCID: PMC10815309 DOI: 10.3390/ijms25020886] [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: 11/19/2023] [Revised: 12/15/2023] [Accepted: 01/03/2024] [Indexed: 01/24/2024] Open
Abstract
RAD51D mutations have been implicated in the transformation of normal fallopian tube epithelial (FTE) cells into high-grade serous ovarian cancer (HGSOC), one of the most prevalent and aggressive gynecologic malignancies. Currently, no suitable model exists to elucidate the role of RAD51D in disease initiation and progression. Here, we established organoids from primary human FTE and introduced TP53 as well as RAD51D knockdown to enable the exploration of their mutational impact on FTE lesion generation. We observed that TP53 deletion rescued the adverse effects of RAD51D deletion on the proliferation, stemness, senescence, and apoptosis of FTE organoids. RAD51D deletion impaired the homologous recombination (HR) function and induced G2/M phase arrest, whereas concurrent TP53 deletion mitigated G0/G1 phase arrest and boosted DNA replication when combined with RAD51D mutation. The co-deletion of TP53 and RAD51D downregulated cilia assembly, development, and motility, but upregulated multiple HGSOC-associated pathways, including the IL-17 signaling pathway. IL-17A treatment significantly improved cell viability. TP53 and RAD51D co-deleted organoids exhibited heightened sensitivity to platinum, poly-ADP ribose polymerase inhibitors (PARPi), and cell cycle-related medication. In summary, our research highlighted the use of FTE organoids with RAD51D mutations as an invaluable in vitro platform for the early detection of carcinogenesis, mechanistic exploration, and drug screening.
Collapse
Affiliation(s)
- Yilin Dai
- Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai 200011, China
| | - Jing Xu
- Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai 200011, China
| | - Xiaofeng Gong
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai 200438, China
| | - Jinsong Wei
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai 200438, China
| | - Yi Gao
- Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai 200011, China
| | - Ranran Chai
- Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai 200011, China
| | - Chong Lu
- Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai 200011, China
| | - Bing Zhao
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai 200438, China
| | - Yu Kang
- Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China
- Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Shanghai 200011, China
| |
Collapse
|
35
|
Zhang W, Xiao Y, Zhou Q, Zhu X, Zhang Y, Xiang Q, Wu S, Song X, Zhao J, Yuan R, Xiao B, Li L. KNSTRN Is a Prognostic Biomarker That Is Correlated with Immune Infiltration in Breast Cancer and Promotes Cell Cycle and Proliferation. Biochem Genet 2024:10.1007/s10528-023-10615-2. [PMID: 38198023 DOI: 10.1007/s10528-023-10615-2] [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: 09/25/2023] [Accepted: 11/29/2023] [Indexed: 01/11/2024]
Abstract
Kinetochore-localized astrin/SPAG5-binding protein (KNSTRN) promotes the progression of bladder cancer and lung adenocarcinoma. However, its expression and biological function in breast cancer remain largely unknown. Therefore, this study aimed to analyze KNSTRN expression, prognoses, correlation with immune infiltration, expression-associated genes, and regulated signaling pathways to characterize its role in regulating the cell cycle using both bioinformatics and in vitro functional experiments. Analyses of The Cancer Genome Atlas, Gene Expression Omnibus, TIMER, and The Human Protein Atlas databases revealed a significant upregulation of KNSTRN transcript and protein levels in breast cancer. Kaplan-Meier survival analyses demonstrated a significant association between high expression of KNSTRN and poor overall survival, relapse-free survival, post-progression survival, and distant metastases-free survival in patients with breast cancer. Furthermore, multivariate Cox regression analyses confirmed that KNSTRN is an independent prognostic factor for breast cancer. Immune infiltration analysis indicated a positive correlation between KNSTRN expression and T regulatory cell infiltration while showing a negative correlation with Tgd and natural killer cell infiltration. Gene set enrichment analysis along with single-cell transcriptome data analysis suggested that KNSTRN promoted cell cycle progression by regulating the expression of key cell cycle proteins. The overexpression and silencing of KNSTRN in vitro, respectively, promoted and inhibited the proliferation of breast cancer cells. The overexpression of KNSTRN enhanced the expression of key cell cycle regulators, including CDK4, CDK6, and cyclin D3, thereby accelerating the G1/S phase transition and leading to aberrant proliferation of breast cancer cells. In conclusion, our study demonstrates that KNSTRN functions as an oncogene in breast cancer by regulating immune response, promoting G1/S transition, and facilitating breast cancer cell proliferation. Moreover, KNSTRN has potential as a molecular biomarker for diagnostic and prognostic prediction in breast cancer.
Collapse
Affiliation(s)
- Wenwu Zhang
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
- Department of Laboratory Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215008, China
| | - Yuhan Xiao
- School of Public Health, Dali University, Dali, 671000, China
| | - Quan Zhou
- Department of Laboratory Medicine, General Hospital of Southern Theater Command of People's Liberation Army (PLA), Guangzhou, 510010, China
| | - Xin Zhu
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Yanxia Zhang
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Qin Xiang
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Shunhong Wu
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Xiaoyu Song
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Junxiu Zhao
- School of Public Health, Dali University, Dali, 671000, China
| | - Ruanfei Yuan
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China
| | - Bin Xiao
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China.
| | - Linhai Li
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, 511518, China.
- Department of Laboratory Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215008, China.
| |
Collapse
|
36
|
Wang Y, Duval AJ, Adli M, Matei D. Biology-driven therapy advances in high-grade serous ovarian cancer. J Clin Invest 2024; 134:e174013. [PMID: 38165032 PMCID: PMC10760962 DOI: 10.1172/jci174013] [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] [Indexed: 01/03/2024] Open
Abstract
Following a period of slow progress, the completion of genome sequencing and the paradigm shift relative to the cell of origin for high grade serous ovarian cancer (HGSOC) led to a new perspective on the biology and therapeutic solutions for this deadly cancer. Experimental models were revisited to address old questions, and improved tools were generated. Additional pathways emerging as drivers of ovarian tumorigenesis and key dependencies for therapeutic targeting, in particular, VEGF-driven angiogenesis and homologous recombination deficiency, were discovered. Molecular profiling of histological subtypes of ovarian cancer defined distinct genetic events for each entity, enabling the first attempts toward personalized treatment. Armed with this knowledge, HGSOC treatment was revised to include new agents. Among them, PARP inhibitors (PARPis) were shown to induce unprecedented improvement in clinical benefit for selected subsets of patients. Research on mechanisms of resistance to PARPis is beginning to discover vulnerabilities and point to new treatment possibilities. This Review highlights these advances, the remaining challenges, and unsolved problems in the field.
Collapse
Affiliation(s)
- Yinu Wang
- Department of Obstetrics and Gynecology and
| | - Alexander James Duval
- Department of Obstetrics and Gynecology and
- Driskill Graduate Program, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Mazhar Adli
- Department of Obstetrics and Gynecology and
- Robert H. Lurie Comprehensive Cancer Center, Chicago, Illinois, USA
| | - Daniela Matei
- Department of Obstetrics and Gynecology and
- Robert H. Lurie Comprehensive Cancer Center, Chicago, Illinois, USA
- Jesse Brown Veteran Affairs Medical Center, Chicago, Illinois, USA
| |
Collapse
|
37
|
Selves J, de Castro E Gloria H, Brunac AC, Saffi J, Guimbaud R, Brousset P, Hoffmann JS. Exploring the basis of heterogeneity of cancer aggressiveness among the mutated POLE variants. Life Sci Alliance 2024; 7:e202302290. [PMID: 37891003 PMCID: PMC10610022 DOI: 10.26508/lsa.202302290] [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] [Revised: 10/04/2023] [Accepted: 10/18/2023] [Indexed: 10/29/2023] Open
Abstract
Germline pathogenic variants in the exonuclease domain of the replicative DNA polymerase Pol ε encoded by the POLE gene, predispose essentially to colorectal and endometrial tumors by inducing an ultramutator phenotype. It is still unclear whether all the POLE alterations influence similar strength tumorigenesis, immune microenvironment, and treatment response. In this review, we summarize the current understanding of the mechanisms and consequences of POLE mutations in human malignancies; we highlight the heterogeneity of mutation rate and cancer aggressiveness among POLE variants, propose some mechanistic basis underlining such heterogeneity, and discuss novel considerations for the choice and efficacy of therapies of POLE tumors.
Collapse
Affiliation(s)
- Janick Selves
- Department of Pathology, Institut Universitaire du Cancer-Oncopole de Toulouse; Centre Hospitalier Universitaire (CHU), Toulouse, France
- Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse III Paul Sabatier, INSERM, CRCT, Toulouse, France
| | - Helena de Castro E Gloria
- Laboratory of Genetic Toxicology, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil
| | - Anne-Cécile Brunac
- Department of Pathology, Institut Universitaire du Cancer-Oncopole de Toulouse; Centre Hospitalier Universitaire (CHU), Toulouse, France
| | - Jenifer Saffi
- Laboratory of Genetic Toxicology, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil
| | - Rosine Guimbaud
- Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse III Paul Sabatier, INSERM, CRCT, Toulouse, France
- Department of Digestive Oncology, Centre Hospitalier Universitaire (CHU), Toulouse, France
- Department of Digestive Surgery, Centre Hospitalier Universitaire (CHU), Toulouse, France
| | - Pierre Brousset
- Department of Pathology, Institut Universitaire du Cancer-Oncopole de Toulouse; Centre Hospitalier Universitaire (CHU), Toulouse, France
- Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse III Paul Sabatier, INSERM, CRCT, Toulouse, France
- Laboratoire d'Excellence Toulouse Cancer (TOUCAN), Toulouse, France
| | - Jean-Sébastien Hoffmann
- Department of Pathology, Institut Universitaire du Cancer-Oncopole de Toulouse; Centre Hospitalier Universitaire (CHU), Toulouse, France
- Laboratoire d'Excellence Toulouse Cancer (TOUCAN), Toulouse, France
| |
Collapse
|
38
|
Derbal Y. Adaptive Control of Tumor Growth. Cancer Control 2024; 31:10732748241230869. [PMID: 38294947 PMCID: PMC10832444 DOI: 10.1177/10732748241230869] [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: 09/25/2023] [Revised: 12/04/2023] [Accepted: 01/15/2024] [Indexed: 02/02/2024] Open
Abstract
Cancer treatment optimizations select the most optimum combinations of drugs, sequencing schedules, and appropriate doses that would limit toxicity and yield an improved patient quality of life. However, these optimizations often lack an adequate consideration of cancer's near-infinite potential for evolutionary adaptation to therapeutic interventions. Adapting cancer therapy based on monitored tumor burden and clonal composition is an intuitively sound approach to the treatment of cancer as an inherently complex and adaptive system. The adaptation would be driven by clinical outcome setpoints embodying the aims to thwart therapeutic resistance and maintain a long-term management of the disease or even a cure. However, given the nonlinear, stochastic dynamics of tumor response to therapeutic interventions, adaptive therapeutic strategies may at least need a one-step-ahead prediction of tumor burden to maintain their control over tumor growth dynamics. The article explores the feasibility of adaptive cancer treatment driven by tumor state feedback assuming cell adaptive fitness to be the underlying source of phenotypic plasticity and pathway entropy as a biomarker of tumor growth trajectory. The exploration is undertaken using deterministic and stochastic models of tumor growth dynamics.
Collapse
Affiliation(s)
- Youcef Derbal
- Ted Rogers School of Information Technology Management, Toronto Metropolitan University, Toronto, ON, Canada
| |
Collapse
|
39
|
Chang J, Zhao X, Wang Y, Liu T, Zhong C, Lao Y, Zhang S, Liao H, Bai F, Lin D, Wu C. Genomic alterations driving precancerous to cancerous lesions in esophageal cancer development. Cancer Cell 2023; 41:2038-2050.e5. [PMID: 38039962 DOI: 10.1016/j.ccell.2023.11.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 07/26/2023] [Accepted: 11/04/2023] [Indexed: 12/03/2023]
Abstract
Esophageal squamous cell carcinoma (ESCC) develops through a series of increasingly abnormal precancerous lesions. Previous studies have revealed the striking differences between normal esophageal epithelium and ESCC in copy number alterations (CNAs) and mutations in genes driving clonal expansion. However, due to limited data on early precancerous lesions, the timing of these transitions and which among them are prerequisites for malignant transformation remained unclear. Here, we analyze 1,275 micro-biopsies from normal esophagus, early and late precancerous lesions, and esophageal cancers to decipher the genomic alterations at each stage. We show that the frequency of TP53 biallelic inactivation increases dramatically in early precancerous lesion stage while CNAs and APOBEC mutagenesis substantially increase at late stages. TP53 biallelic loss is the prerequisite for the development of CNAs of genes in cell cycle, DNA repair, and apoptosis pathways, suggesting it might be one of the earliest steps initiating malignant transformation.
Collapse
Affiliation(s)
- Jiang Chang
- Department of Health Toxicology, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
| | - Xuan Zhao
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Yichen Wang
- Cancer, Ageing and Somatic Mutation, Wellcome Sanger Institute, Hinxton, UK
| | - Tianyuan Liu
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Ce Zhong
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Yueqiong Lao
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Shaosen Zhang
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Han Liao
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Fan Bai
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing 100871, China; Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing 100871, China; Center for Translational Cancer Research, Peking University First Hospital, Beijing 100034, China.
| | - Dongxin Lin
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China; Key Laboratory of Cancer Genomic Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou 510060, China.
| | - Chen Wu
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China; Key Laboratory of Cancer Genomic Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China; CAMS Oxford Institute, Chinese Academy of Medical Sciences, Beijing 100006, China.
| |
Collapse
|
40
|
Zimmer N, Trzeciak ER, Müller A, Licht P, Sprang B, Leukel P, Mailänder V, Sommer C, Ringel F, Tuettenberg J, Kim E, Tuettenberg A. Nuclear Glycoprotein A Repetitions Predominant (GARP) Is a Common Trait of Glioblastoma Stem-like Cells and Correlates with Poor Survival in Glioblastoma Patients. Cancers (Basel) 2023; 15:5711. [PMID: 38136258 PMCID: PMC10741777 DOI: 10.3390/cancers15245711] [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: 10/20/2023] [Revised: 11/17/2023] [Accepted: 12/01/2023] [Indexed: 12/24/2023] Open
Abstract
Glioblastoma (GB) is notoriously resistant to therapy. GB genesis and progression are driven by glioblastoma stem-like cells (GSCs). One goal for improving treatment efficacy and patient outcomes is targeting GSCs. Currently, there are no universal markers for GSCs. Glycoprotein A repetitions predominant (GARP), an anti-inflammatory protein expressed by activated regulatory T cells, was identified as a possible marker for GSCs. This study evaluated GARP for the detection of human GSCs utilizing a multidimensional experimental design that replicated several features of GB: (1) intratumoral heterogeneity, (2) cellular hierarchy (GSCs with varied degrees of self-renewal and differentiation), and (3) longitudinal GSC evolution during GB recurrence (GSCs from patient-matched newly diagnosed and recurrent GB). Our results indicate that GARP is expressed by GSCs across various cellular states and disease stages. GSCs with an increased GARP expression had reduced self-renewal but no alterations in proliferative capacity or differentiation commitment. Rather, GARP correlated inversely with the expression of GFAP and PDGFR-α, markers of astrocyte or oligodendrocyte differentiation. GARP had an abnormal nuclear localization (GARPNU+) in GSCs and was negatively associated with patient survival. The uniformity of GARP/GARPNU+ expression across different types of GSCs suggests a potential use of GARP as a marker to identify GSCs.
Collapse
Affiliation(s)
- Niklas Zimmer
- Department of Dermatology, University Medical Center Mainz, 55131 Mainz, Germany (P.L.)
| | - Emily R. Trzeciak
- Department of Dermatology, University Medical Center Mainz, 55131 Mainz, Germany (P.L.)
| | - Andreas Müller
- Department of Neurosurgery, University Medical Center Mainz, 55131 Mainz, Germany
- Laboratory of Experimental Neurooncology, University Medical Center Mainz, 55131 Mainz, Germany
| | - Philipp Licht
- Department of Dermatology, University Medical Center Mainz, 55131 Mainz, Germany (P.L.)
| | - Bettina Sprang
- Department of Neurosurgery, University Medical Center Mainz, 55131 Mainz, Germany
- Laboratory of Experimental Neurooncology, University Medical Center Mainz, 55131 Mainz, Germany
| | - Petra Leukel
- Institute of Neuropathology, University Medical Center Mainz, 55131 Mainz, Germany
| | - Volker Mailänder
- Department of Dermatology, University Medical Center Mainz, 55131 Mainz, Germany (P.L.)
- Research Center for Immunotherapy, University Medical Center Mainz, 55131 Mainz, Germany
| | - Clemens Sommer
- Institute of Neuropathology, University Medical Center Mainz, 55131 Mainz, Germany
| | - Florian Ringel
- Department of Neurosurgery, University Medical Center Mainz, 55131 Mainz, Germany
| | - Jochen Tuettenberg
- Department of Neurosurgery, SHG-Klinikum Idar-Oberstein, 55743 Idar-Oberstein, Germany;
| | - Ella Kim
- Department of Neurosurgery, University Medical Center Mainz, 55131 Mainz, Germany
- Laboratory of Experimental Neurooncology, University Medical Center Mainz, 55131 Mainz, Germany
| | - Andrea Tuettenberg
- Department of Dermatology, University Medical Center Mainz, 55131 Mainz, Germany (P.L.)
- Research Center for Immunotherapy, University Medical Center Mainz, 55131 Mainz, Germany
| |
Collapse
|
41
|
Gram SB, Alosi D, Bagger FO, Østrup O, von Buchwald C, Friborg J, Wessel I, Vogelius IR, Rohrberg K, Rasmussen JH. Clinical implication of genetic intratumor heterogeneity for targeted therapy in head and neck cancer. Acta Oncol 2023; 62:1831-1839. [PMID: 37902999 DOI: 10.1080/0284186x.2023.2272293] [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: 07/24/2023] [Accepted: 10/15/2023] [Indexed: 11/01/2023]
Abstract
BACKGROUND Genomic profiling is increasingly used both in therapeutic decision-making and as inclusion criteria for trials testing targeted therapies. However, the mutational landscape may vary across different areas of a tumor and intratumor heterogeneity will challenge treatments or clinical decisions based on single tumor biopsies. The purpose of this study was to assess the clinical relevance of genetic intratumor heterogeneity in head and neck squamous cell carcinomas (HNSCC) using the ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT). MATERIALS AND METHODS This prospective study included 33 whole tumor specimens from 28 patients with primary or recurrent HNSCC referred for surgery. Three tumor blocks were selected from central, semi-peripheral, and peripheral positions, mimicking biopsies in three different locations. Genetic analysis of somatic copy number alterations (SCNAs) was performed on the three biopsies using Oncoscan, focusing on 45 preselected HNSCC genes of interest. Clinical relevance was assessed using the ESCAT score to investigate whether and how treatment decisions would change based on the three biopsies from the same tumor. RESULTS The SCNAs identified among 45 preselected genes within the three tumor biopsies derived from the same tumor revealed distinct variations. The detected discrepancies could potentially influence treatment approaches or clinical decisions in 36% of the patients if only one tumor biopsy was used. Recurrent tumors exhibited significantly higher variation in SCNAs than primary tumors (p = .024). No significant correlation between tumor size and heterogeneity (p = .7) was observed. CONCLUSION In 36% of patients diagnosed with HNSCC, clinically significant intratumor heterogeneity was observed which may have implications for patient management. This finding substantiates the need for future studies that specifically investigate the clinical implications associated with intratumor heterogeneity.
Collapse
Affiliation(s)
- Signe Buhl Gram
- Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Daniela Alosi
- Center for Genomic Medicine, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Frederik Otzen Bagger
- Center for Genomic Medicine, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Olga Østrup
- Center for Genomic Medicine, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Christian von Buchwald
- Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Jeppe Friborg
- Department of Oncology, Section of Radiotherapy, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Irene Wessel
- Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Ivan Richter Vogelius
- Department of Oncology, Section of Radiotherapy, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Kristoffer Rohrberg
- Department of Oncology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Jacob Høygaard Rasmussen
- Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| |
Collapse
|
42
|
Zelli V, Manno A, Compagnoni C, Ibraheem RO, Zazzeroni F, Alesse E, Rossi F, Arbib C, Tessitore A. Classification of tumor types using XGBoost machine learning model: a vector space transformation of genomic alterations. J Transl Med 2023; 21:836. [PMID: 37990214 PMCID: PMC10664515 DOI: 10.1186/s12967-023-04720-4] [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: 05/16/2023] [Accepted: 11/10/2023] [Indexed: 11/23/2023] Open
Abstract
BACKGROUND Machine learning (ML) represents a powerful tool to capture relationships between molecular alterations and cancer types and to extract biological information. Here, we developed a plain ML model aimed at distinguishing cancer types based on genetic lesions, providing an additional tool to improve cancer diagnosis, particularly for tumors of unknown origin. METHODS TCGA data from 9,927 samples spanning 32 different cancer types were downloaded from cBioportal. A vector space model type data transformation technique was designed to build consistently homogeneous new datasets containing, as predictive features, calls for somatic point mutations and copy number variations at chromosome arm-level, thus allowing the use of the XGBoost classifier models. Considering the imbalance in the dataset, due to large difference in the number of cases for each tumor, two preprocessing strategies were considered: i) setting a percentage cut-off threshold to remove less represented cancer types, ii) dividing cancer types into different groups based on biological criteria and training a specific XGBoost model for each of them. The performance of all trained models was mainly assessed by the out-of-sample balanced accuracy (BACC) and the AUC scores. RESULTS The XGBoost classifier achieved the best performance (BACC 77%; AUC 97%) on a dataset containing the 10 most represented tumor types. Moreover, dividing the 18 most represented cancers into three different groups (endocrine-related carcinomas, other carcinomas and other cancers),such analysis models achieved 78%, 71% and 86% BACC, respectively, with AUC scores greater than 96%. In addition, the model capable of linking each group to a specific cancer type reached 81% BACC and 94% AUC. Overall, the diagnostic potential of our model was comparable/higher with respect to others already described in literature and based on similar molecular data and ML approaches. CONCLUSIONS A boosted ML approach able to accurately discriminate different cancer types was developed. The methodology builds datasets simpler and more interpretable than the original data, while keeping enough information to accurately train standard ML models without resorting to sophisticated Deep Learning architectures. In combination with histopathological examinations, this approach could improve cancer diagnosis by using specific DNA alterations, processed by a replicable and easy-to-use automated technology. The study encourages new investigations which could further increase the classifier's performance, for example by considering more features and dividing tumors into their main molecular subtypes.
Collapse
Affiliation(s)
- Veronica Zelli
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, 67100, L'Aquila, Italy
- Center for Molecular Diagnostics and Advanced Therapies, University of L'Aquila, Via Petrini, 67100, L'Aquila, Italy
| | - Andrea Manno
- Department of Information Engineering, Computer Science and Mathematics, Center of Excellence DEWS, University of L'Aquila, 67100, L'Aquila, Italy
| | - Chiara Compagnoni
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, 67100, L'Aquila, Italy
| | - Rasheed Oyewole Ibraheem
- Department of Information Engineering, Computer Science and Mathematics, Center of Excellence DEWS, University of L'Aquila, 67100, L'Aquila, Italy
| | - Francesca Zazzeroni
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, 67100, L'Aquila, Italy
| | - Edoardo Alesse
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, 67100, L'Aquila, Italy
| | - Fabrizio Rossi
- Department of Information Engineering, Computer Science and Mathematics, Center of Excellence DEWS, University of L'Aquila, 67100, L'Aquila, Italy
| | - Claudio Arbib
- Department of Information Engineering, Computer Science and Mathematics, Center of Excellence DEWS, University of L'Aquila, 67100, L'Aquila, Italy
| | - Alessandra Tessitore
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, 67100, L'Aquila, Italy.
- Center for Molecular Diagnostics and Advanced Therapies, University of L'Aquila, Via Petrini, 67100, L'Aquila, Italy.
| |
Collapse
|
43
|
Hatano Y. The Pathology according to p53 Pathway. Pathobiology 2023; 91:230-243. [PMID: 37963443 PMCID: PMC11313058 DOI: 10.1159/000535203] [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: 08/05/2023] [Accepted: 11/12/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Observations play a pivotal role in the progress of science, including in pathology. The cause of a disease such as cancer is analyzed by breaking it down into smaller organs, tissues, cells, and molecules. The current standard cancer diagnostic procedure, microscopic observation, relies on preserved morphological characteristics. In contrast, molecular analyses explore oncogenic pathway activation that leads to genetic mutations and aberrant protein expression. Such molecular analyses could potentially identify therapeutic targets and has gained considerable attention in clinical oncology. SUMMARY This review summarizes the cardinal biomarkers of the p53 pathway, p53, p16, and mouse double minute 2 (MDM2), in the context of traditional surgical pathology and emerging genomic oncology. The p53 pathway, which is dysregulated in more than a half of all cancers, can be applied in several diagnostic settings. A four-classification model of immunophenotype for p53 pathway gene status, tumor types with a high frequency of abnormalities for each p53 pathway gene, and a minimal p53 pathway immunohistochemical panel is also described. KEY MESSAGES Immunohistochemistry of oncogenic signals should be interpreted according to molecular findings based on genomic oncology, in addition to the microscopic findings of diagnostic pathology.
Collapse
Affiliation(s)
- Yuichiro Hatano
- Department of Pathology, Faculty of Medicine, Osaka Medical and Pharmaceutical University, Takatsuki, Osaka, Japan
| |
Collapse
|
44
|
Zhang Y, Liu Z, Li J, Wu B, Li X, Duo M, Xu H, Liu L, Su X, Duan X, Luo P, Zhang J, Li Z. Oncogenic pathways refine a new perspective on the classification of hepatocellular carcinoma. Cell Signal 2023; 111:110890. [PMID: 37714446 DOI: 10.1016/j.cellsig.2023.110890] [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: 07/07/2023] [Revised: 09/03/2023] [Accepted: 09/12/2023] [Indexed: 09/17/2023]
Abstract
BACKGROUND Genetic alterations in oncogenic pathways are critical for cancer initiation, development, and treatment resistance. However, studies are limited regarding pathways correlated with prognosis, sorafenib, and transcatheter arterial chemoembolization (TACE) in hepatocellular carcinoma (HCC). METHODS In this study, 1928 patients from 11 independent datasets and a clinical in-house cohort were screened to explore the relationships among canonical pathway alterations in HCC patients. The molecular mechanisms, biological functions, immune landscape, and clinical outcomes among three heterogeneous phenotypes were further explored. RESULTS We charted the detailed landscape of pathway alterations in the TCGA-LIHC cohort, screened three pivotal pathways (p53, PI3K, and WNT), identified co-occurrence patterns and mutual exclusively, and stratified patients into three altered-pathway dominant phenotypes (ADPs). P53|PI3K ADP characterized by genomic instability (e.g., highest TMB, FGA, FGG, and FGL) indicated an unfavorable prognosis. While, patients in WNT ADP suggested a median prognosis, enhanced immune activation, and sensitivity to PD-L1 therapy. Remarkably, sorafenib and TACE exhibited efficacy for patients in WNT ADP and low frequent alteration phenotype (LFP). Additionally, ADP could work independently of common clinical traits (e.g., AJCC stage) and previous molecular classifications (e.g., iCluster, serum biomarkers). CONCLUSIONS ADP provides a new perspective for identifying patients at high risk of recurrence and could optimize precision treatment to improve the clinical outcomes in HCC.
Collapse
Affiliation(s)
- Yuyuan Zhang
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China
| | - Zaoqu Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China; State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Department of Pathophysiology, Peking Union Medical College, Beijing 100730, China
| | - Jie Li
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China
| | - Bailu Wu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China
| | - Xin Li
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China
| | - Mengjie Duo
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Hui Xu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China
| | - Long Liu
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | | | - Xuhua Duan
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China
| | - Peng Luo
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Jian Zhang
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Zhen Li
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China.
| |
Collapse
|
45
|
Marques JF, Kops GJPL. Permission to pass: on the role of p53 as a gatekeeper for aneuploidy. Chromosome Res 2023; 31:31. [PMID: 37864038 PMCID: PMC10589155 DOI: 10.1007/s10577-023-09741-9] [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: 05/30/2023] [Revised: 09/25/2023] [Accepted: 10/03/2023] [Indexed: 10/22/2023]
Abstract
Aneuploidy-the karyotype state in which the number of chromosomes deviates from a multiple of the haploid chromosome set-is common in cancer, where it is thought to facilitate tumor initiation and progression. However, it is poorly tolerated in healthy cells: during development and tissue homeostasis, aneuploid cells are efficiently cleared from the population. It is still largely unknown how cancer cells become, and adapt to being, aneuploid. P53, the gatekeeper of the genome, has been proposed to guard against aneuploidy. Aneuploidy in cancer genomes strongly correlates with mutations in TP53, and p53 is thought to prevent the propagation of aneuploid cells. Whether p53 also participates in preventing the mistakes in cell division that lead to aneuploidy is still under debate. In this review, we summarize the current understanding of the role of p53 in protecting cells from aneuploidy, and we explore the consequences of functional p53 loss for the propagation of aneuploidy in cancer.
Collapse
Affiliation(s)
- Joana F Marques
- Royal Netherlands Academy of Arts and Sciences (KNAW), Hubrecht Institute, Uppsalalaan 8, 3584CT, Utrecht, the Netherlands
- University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, the Netherlands
- Oncode Institute, Jaarbeursplein 6, 3521AL, Utrecht, the Netherlands
| | - Geert J P L Kops
- Royal Netherlands Academy of Arts and Sciences (KNAW), Hubrecht Institute, Uppsalalaan 8, 3584CT, Utrecht, the Netherlands.
- University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, the Netherlands.
- Oncode Institute, Jaarbeursplein 6, 3521AL, Utrecht, the Netherlands.
| |
Collapse
|
46
|
Hippen AA, Omran DK, Weber LM, Jung E, Drapkin R, Doherty JA, Hicks SC, Greene CS. Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors. Genome Biol 2023; 24:239. [PMID: 37864274 PMCID: PMC10588129 DOI: 10.1186/s13059-023-03077-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 09/29/2023] [Indexed: 10/22/2023] Open
Abstract
BACKGROUND Single-cell gene expression profiling provides unique opportunities to understand tumor heterogeneity and the tumor microenvironment. Because of cost and feasibility, profiling bulk tumors remains the primary population-scale analytical strategy. Many algorithms can deconvolve these tumors using single-cell profiles to infer their composition. While experimental choices do not change the true underlying composition of the tumor, they can affect the measurements produced by the assay. RESULTS We generated a dataset of high-grade serous ovarian tumors with paired expression profiles from using multiple strategies to examine the extent to which experimental factors impact the results of downstream tumor deconvolution methods. We find that pooling samples for single-cell sequencing and subsequent demultiplexing has a minimal effect. We identify dissociation-induced differences that affect cell composition, leading to changes that may compromise the assumptions underlying some deconvolution algorithms. We also observe differences across mRNA enrichment methods that introduce additional discrepancies between the two data types. We also find that experimental factors change cell composition estimates and that the impact differs by method. CONCLUSIONS Previous benchmarks of deconvolution methods have largely ignored experimental factors. We find that methods vary in their robustness to experimental factors. We provide recommendations for methods developers seeking to produce the next generation of deconvolution approaches and for scientists designing experiments using deconvolution to study tumor heterogeneity.
Collapse
Affiliation(s)
- Ariel A Hippen
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Dalia K Omran
- Penn Ovarian Cancer Research Center, Department of Obstetrics and Gynecology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Lukas M Weber
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Euihye Jung
- Penn Ovarian Cancer Research Center, Department of Obstetrics and Gynecology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ronny Drapkin
- Penn Ovarian Cancer Research Center, Department of Obstetrics and Gynecology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Stephanie C Hicks
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Casey S Greene
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| |
Collapse
|
47
|
Sauer CM, Hall JA, Couturier DL, Bradley T, Piskorz AM, Griffiths J, Sawle A, Eldridge MD, Smith P, Hosking K, Reinius MAV, Morrill Gavarró L, Mes-Masson AM, Ennis D, Millan D, Hoyle A, McNeish IA, Jimenez-Linan M, Martins FC, Tischer J, Vias M, Brenton JD. Molecular landscape and functional characterization of centrosome amplification in ovarian cancer. Nat Commun 2023; 14:6505. [PMID: 37845213 PMCID: PMC10579337 DOI: 10.1038/s41467-023-41840-3] [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: 02/16/2023] [Accepted: 09/21/2023] [Indexed: 10/18/2023] Open
Abstract
High-grade serous ovarian carcinoma (HGSOC) is characterised by poor outcome and extreme chromosome instability (CIN). Therapies targeting centrosome amplification (CA), a key mediator of chromosome missegregation, may have significant clinical utility in HGSOC. However, the prevalence of CA in HGSOC, its relationship to genomic biomarkers of CIN and its potential impact on therapeutic response have not been defined. Using high-throughput multi-regional microscopy on 287 clinical HGSOC tissues and 73 cell lines models, here we show that CA through centriole overduplication is a highly recurrent and heterogeneous feature of HGSOC and strongly associated with CIN and genome subclonality. Cell-based studies showed that high-prevalence CA is phenocopied in ovarian cancer cell lines, and that high CA is associated with increased multi-treatment resistance; most notably to paclitaxel, the commonest treatment used in HGSOC. CA in HGSOC may therefore present a potential driver of tumour evolution and a powerful biomarker for response to standard-of-care treatment.
Collapse
Affiliation(s)
- Carolin M Sauer
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK.
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK.
| | - James A Hall
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
| | - Dominique-Laurent Couturier
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, CB2 0SR, UK
| | - Thomas Bradley
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
| | - Anna M Piskorz
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
| | - Jacob Griffiths
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
| | - Ashley Sawle
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
| | - Matthew D Eldridge
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
| | - Philip Smith
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
| | - Karen Hosking
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
| | - Marika A V Reinius
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
- Cambridge University Hospital NHS Foundation Trust and National Institute for Health Research Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge, UK
| | - Lena Morrill Gavarró
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
| | - Anne-Marie Mes-Masson
- Department of Medicine, Université de Montréal and Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montreal, QC, Canada
| | - Darren Ennis
- Department of Surgery and Cancer, Ovarian Cancer Action Research Centre, Imperial College London, London, UK
| | - David Millan
- Department of Pathology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Aoisha Hoyle
- Department of Pathology, University Hospital Monklands. NHS Lanarkshire, Airdrie, UK
| | - Iain A McNeish
- Department of Surgery and Cancer, Ovarian Cancer Action Research Centre, Imperial College London, London, UK
| | - Mercedes Jimenez-Linan
- Cambridge University Hospital NHS Foundation Trust and National Institute for Health Research Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge, UK
| | - Filipe Correia Martins
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
- Cambridge University Hospital NHS Foundation Trust and National Institute for Health Research Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge, UK
| | - Julia Tischer
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
| | - Maria Vias
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK
| | - James D Brenton
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK.
- Cancer Research UK Major Centre-Cambridge, University of Cambridge, Cambridge, CB2 0RE, UK.
- Cambridge University Hospital NHS Foundation Trust and National Institute for Health Research Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge, UK.
| |
Collapse
|
48
|
Islam SS, Karakas B, Aboussekhra A, Noman ASM. KEAP1/NRF2 Mutations in Stem Cells Define an Aggressive Subset of Head and Neck Cancer Patients Who Have a Poor Prognosis, Lung Metastasis, and Therapeutic Failure. Cancers (Basel) 2023; 15:5006. [PMID: 37894373 PMCID: PMC10605399 DOI: 10.3390/cancers15205006] [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: 08/23/2023] [Revised: 10/05/2023] [Accepted: 10/09/2023] [Indexed: 10/29/2023] Open
Abstract
Mutations in Keap1/Nrf2 in head and neck cancer result in abnormal cell growth. Progenitor cells, bulk tumor cells, and head and neck cancer stem cells (HN-CSCs) may all harbor these mutations. Nevertheless, whether Keap1/Nrf2 mutations in HN-CSCs have an impact on clinical outcomes is unknown. Cancerous HN-CSCs and benign stem cells were obtained from freshly resected head and neck cancer patients (n = 50) via flow cytometry cell sorting and tested for Keap1/Nrf2 mutations. The existence of Keap1/Nrf2 mutations in HN-CSCs, as well as their correlations with tumor mutations, pathologic tumor stage, tumor histologic grades, lung metastasis, treatment outcomes, and the patient's age and conditions, are assessed at the last follow-up visit. Thirteen tumors were found to have Keap1/Nrf2 mutations in their HN-CSCs. More than half of the lung metastases and disease progression occurred in HN-CSCs with mutations. Patients whose tumors carried Keap1/Nrf2 mutations in their HN-CSCs had significantly shorter progression-free survival, overall survival, and time of treatment failure than their non-HN-CSC counterparts. These associations were partly driven by HN-CSCs, in which Keap1/Nrf2 mutations were overrepresented in fast progressors and associated with an increased risk of disease progression. Our findings suggest that molecular genotyping of HN-CSCs may facilitate personalized treatment strategies and assist in identifying patients who are likely to benefit from chemotherapy.
Collapse
Affiliation(s)
- Syed S. Islam
- Department Molecular Oncology, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia
- Faculty of Medicine, Al-Faisal University, Riyadh 11533, Saudi Arabia
| | - Bedri Karakas
- 3 B & B Bio, 4 Professional Drive, Gaithersburg, MD 20879, USA;
| | - Abdelilah Aboussekhra
- Department Molecular Oncology, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia
| | - Abu Shadat M. Noman
- Department Biochemistry and Molecular Biology, The University of Chittagong, Chittagong 4331, Bangladesh
| |
Collapse
|
49
|
Khella CA, Franciosa L, Rodirguez-Rodriguez L, Rajkarnikar R, Mythreye K, Gatza ML. HCK Promotes High-Grade Serous Ovarian Cancer Tumorigenesis through CD44 and NOTCH3 Signaling. Mol Cancer Res 2023; 21:1037-1049. [PMID: 37342066 DOI: 10.1158/1541-7786.mcr-22-0496] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 10/05/2022] [Accepted: 06/15/2023] [Indexed: 06/22/2023]
Abstract
High-grade serous ovarian cancer (HGSOC) is a highly aggressive and lethal subtype of ovarian cancer. While most patients initially respond to standard-of-care treatment, the majority will eventually relapse and succumb to their disease. Despite significant advances in our understanding of this disease, the mechanisms that govern the distinctions between HGSOC with good and poor prognosis remain unclear. In this study, we implemented a proteogenomic approach to analyze gene expression, proteomic and phosphoproteomic profiles of HGSOC tumor samples to identify molecular pathways that distinguish HGSOC tumors relative to clinical outcome. Our analyses identify significant upregulation of hematopoietic cell kinase (HCK) expression and signaling in poor prognostic HGSOC patient samples. Analyses of independent gene expression datasets and IHC of patient samples confirmed increased HCK signaling in tumors relative to normal fallopian or ovarian samples and demonstrated aberrant expression in tumor epithelial cells. Consistent with the association between HCK expression and tumor aggressiveness in patient samples, in vitro phenotypic studies showed that HCK can, in part, promote cell proliferation, colony formation, and invasive capacity of cell lines. Mechanistically, HCK mediates these phenotypes, partly through CD44 and NOTCH3-dependent signaling, and inhibiting CD44 or NOTCH3 activity, either genetically or through gamma-secretase inhibitors, can revert HCK-driven phenotypes. IMPLICATIONS Collectively, these studies establish that HCK acts as an oncogenic driver of HGSOC through aberrant activation of CD44 and NOTCH3 signaling and identifies this network as a potential therapeutic opportunity in a subset of patients with aggressive and recurrent HGSOC.
Collapse
Affiliation(s)
- Christen A Khella
- Department of Radiation Oncology, Robert Wood Johnson Medical School, New Brunswick, New Jersey
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey
- School of Graduate Studies, Rutgers University, New Brunswick, New Jersey
| | | | | | - Resha Rajkarnikar
- Department of Pathology and O'Neal Comprehensive Cancer Center, Heersink School of Medicine, University of Alabama, Birmingham, Alabama
| | - Karthikeyan Mythreye
- Department of Pathology and O'Neal Comprehensive Cancer Center, Heersink School of Medicine, University of Alabama, Birmingham, Alabama
| | - Michael L Gatza
- Department of Radiation Oncology, Robert Wood Johnson Medical School, New Brunswick, New Jersey
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey
| |
Collapse
|
50
|
Morgan RD, Burghel GJ, Flaum N, Bulman M, Smith P, Clamp AR, Hasan J, Mitchell C, Salih Z, Woodward ER, Lalloo F, Shaw J, Desai S, Crosbie EJ, Edmondson RJ, Schlecht H, Wallace AJ, Jayson GC, Evans DGR. Predicting the likelihood of a BRCA1/2 pathogenic variant being somatic by testing only tumour DNA in non-mucinous high-grade epithelial ovarian cancer. J Clin Pathol 2023; 76:684-689. [PMID: 35738887 DOI: 10.1136/jcp-2022-208369] [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: 05/02/2022] [Accepted: 06/09/2022] [Indexed: 11/04/2022]
Abstract
AIMS Clinical guidelines recommend testing both germline and tumour DNA for BRCA1/2 pathogenic variants (PVs) in non-mucinous high-grade epithelial ovarian cancer (NMEOC). In this study, we show that some tumour BRCA1/2 PVs are highly likely to be somatic based on certain clinical and variant characteristics, meaning it may not be necessary to test all NMEOC cases for germline BRCA1/2 PVs. METHODS An observational study that included all tumour BRCA1/2 PVs detected in cases of NMEOC in the Northwest of England between July 2017 and February 2022. All tumour BRCA1/2 PVs were compared with PVs recorded in a prospectively gathered pan-cancer germline BRCA1/2 (gBRCA) testing database for the same geographical region (gBRCA1 PVs=910 and gBRCA2 PVs=922). Tumour BRCA1/2 PVs were categorised as common (≥1%), uncommon (<1%) or absent from the germline database. RESULTS One hundred and thirteen tumour BRCA1/2 PVs were detected in 111 NMEOC cases. There were 69 germline and 44 somatic variants. The mean age at diagnosis for gBRCA and somatic BRCA1/2 (sBRCA) PVs was 56.9 and 68.5 years, respectively (Student's t-test p<0.0001). All sBRCA PVs were detected in non-familial cases. All tumour BRCA1/2 PVs with a variant allele frequency (VAF) <35% in non-familial cases were somatic variants. Eighty-one per cent of germline-tumour BRCA1/2 PVs were present (common=31, uncommon=25) in the gBRCA testing database, while 89% of somatic-tumour BRCA1/2 PVs were absent (n=39). CONCLUSIONS We predict the likelihood of a tumour BRCA1/2 PV being somatic is 99.8% in non-familial cases of NMEOC diagnosed aged ≥75, where the VAF is ≤30% and there is no regional germline commonality.
Collapse
Affiliation(s)
- Robert D Morgan
- Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK
| | - George J Burghel
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, UK
| | - Nicola Flaum
- Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Evolution, Infection and Genomics, University of Manchester, Manchester, UK
| | - Michael Bulman
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, UK
| | - Philip Smith
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, UK
| | - Andrew R Clamp
- Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - Jurjees Hasan
- Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK
| | - Claire Mitchell
- Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK
| | - Zena Salih
- Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK
| | - Emma R Woodward
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, UK
- Department of Clinical Genetics, Manchester University NHS Foundation Trust, Manchester, UK
| | - Fiona Lalloo
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, UK
- Department of Clinical Genetics, Manchester University NHS Foundation Trust, Manchester, UK
| | - Joseph Shaw
- Department of Histopathology, Manchester University NHS Foundation Trust, Manchester, UK
| | - Sudha Desai
- Department of Histopathology, The Christie NHS Foundation Trust, Manchester, UK
| | - Emma J Crosbie
- Division of Cancer Sciences, University of Manchester, Manchester, UK
- Department of Gynaecological Surgery, Manchester University NHS Foundation Trust, Manchester, UK
| | - Richard J Edmondson
- Division of Cancer Sciences, University of Manchester, Manchester, UK
- Department of Gynaecological Surgery, Manchester University NHS Foundation Trust, Manchester, UK
| | - Helene Schlecht
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, UK
| | - Andrew J Wallace
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, UK
| | - Gordon C Jayson
- Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - D Gareth R Evans
- North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Evolution, Infection and Genomics, University of Manchester, Manchester, UK
- Department of Clinical Genetics, Manchester University NHS Foundation Trust, Manchester, UK
| |
Collapse
|