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Holder AM, Dedeilia A, Sierra-Davidson K, Cohen S, Liu D, Parikh A, Boland GM. Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours. Nat Rev Cancer 2024:10.1038/s41568-024-00705-7. [PMID: 38867074 DOI: 10.1038/s41568-024-00705-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/08/2024] [Indexed: 06/14/2024]
Abstract
Although more than a decade has passed since the approval of immune checkpoint inhibitors (ICIs) for the treatment of melanoma and non-small-cell lung, breast and gastrointestinal cancers, many patients still show limited response. US Food and Drug Administration (FDA)-approved biomarkers include programmed cell death 1 ligand 1 (PDL1) expression, microsatellite status (that is, microsatellite instability-high (MSI-H)) and tumour mutational burden (TMB), but these have limited utility and/or lack standardized testing approaches for pan-cancer applications. Tissue-based analytes (such as tumour gene signatures, tumour antigen presentation or tumour microenvironment profiles) show a correlation with immune response, but equally, these demonstrate limited efficacy, as they represent a single time point and a single spatial assessment. Patient heterogeneity as well as inter- and intra-tumoural differences across different tissue sites and time points represent substantial challenges for static biomarkers. However, dynamic biomarkers such as longitudinal biopsies or novel, less-invasive markers such as blood-based biomarkers, radiomics and the gut microbiome show increasing potential for the dynamic identification of ICI response, and patient-tailored predictors identified through neoadjuvant trials or novel ex vivo tumour models can help to personalize treatment. In this Perspective, we critically assess the multiple new static, dynamic and patient-specific biomarkers, highlight the newest consortia and trial efforts, and provide recommendations for future clinical trials to make meaningful steps forwards in the field.
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Affiliation(s)
- Ashley M Holder
- Department of Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | | | - Sonia Cohen
- Department of Surgery, Massachusetts General Hospital, Boston, MA, USA
| | - David Liu
- Dana Farber Cancer Institute, Boston, MA, USA
| | - Aparna Parikh
- Cancer Center, Massachusetts General Hospital, Boston, MA, USA
| | - Genevieve M Boland
- Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
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2
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Prathipati P, Pathania AS, Chaturvedi NK, Gupta SC, Byrareddy SN, Coulter DW, Challagundla KB. SAP30, an oncogenic driver of progression, poor survival, and drug resistance in neuroblastoma. MOLECULAR THERAPY. NUCLEIC ACIDS 2024; 35:101543. [PMID: 38817681 PMCID: PMC11137595 DOI: 10.1016/j.omtn.2022.03.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 03/18/2022] [Indexed: 06/01/2024]
Abstract
Neuroblastoma is the most devastating extracranial solid malignancy in children. Despite an intense treatment regimen, the prognosis for high-risk neuroblastoma patients remains poor, with less than 40% survival. So far, MYCN amplification status is considered the most prognostic factor but corresponds to only ∼25% of neuroblastoma patients. Therefore, it is essential to identify a better prognosis and therapy response marker in neuroblastoma patients. We applied robust bioinformatic data mining tools, such as weighted gene co-expression network analysis, cisTarget, and single-cell regulatory network inference and clustering on two neuroblastoma patient datasets. We found Sin3A-associated protein 30 (SAP30), a driver transcription factor positively associated with high-risk, progression, stage 4, and poor survival in neuroblastoma patient cohorts. Tumors of high-risk neuroblastoma patients and relapse-specific patient-derived xenografts showed higher SAP30 levels. The advanced pharmacogenomic analysis and CRISPR-Cas9 screens indicated that SAP30 essentiality is associated with cisplatin resistance and further showed higher levels in cisplatin-resistant patient-derived xenograft tumor cell lines. Silencing of SAP30 induced cell death in vitro and led to a reduced tumor burden and size in vivo. Altogether, these results indicate that SAP30 is a better prognostic and cisplatin-resistance marker and thus a potential drug target in high-risk neuroblastoma.
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Affiliation(s)
- Philip Prathipati
- Laboratory of Bioinformatics, National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8 Saito-Asagi, Ibaraki City, Osaka 567-0085, Japan
| | - Anup S. Pathania
- Department of Biochemistry and Molecular Biology & Fred and Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Nagendra K. Chaturvedi
- Department of Pediatrics, Division of Hematology/Oncology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Subash C. Gupta
- Department of Biochemistry, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India
| | - Siddappa N. Byrareddy
- Department of Biochemistry and Molecular Biology & Fred and Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE 68198, USA
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Don W. Coulter
- Department of Pediatrics, Division of Hematology/Oncology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Kishore B. Challagundla
- Department of Biochemistry and Molecular Biology & Fred and Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE 68198, USA
- The Child Health Research Institute, University of Nebraska Medical Center, Omaha, NE 68198, USA
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3
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Colussi DM, Stathopulos PB. The mitochondrial calcium uniporter: Balancing tumourigenic and anti-tumourigenic responses. J Physiol 2024. [PMID: 38857425 DOI: 10.1113/jp285515] [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: 12/26/2023] [Accepted: 05/20/2024] [Indexed: 06/12/2024] Open
Abstract
Increased malignancy and poor treatability associated with solid tumour cancers have commonly been attributed to mitochondrial calcium (Ca2+) dysregulation. The mitochondrial Ca2+ uniporter complex (mtCU) is the predominant mode of Ca2+ uptake into the mitochondrial matrix. The main components of mtCU are the pore-forming mitochondrial Ca2+ uniporter (MCU) subunit, MCU dominant-negative beta (MCUb) subunit, essential MCU regulator (EMRE) and the gatekeeping mitochondrial Ca2+ uptake 1 and 2 (MICU1 and MICU2) proteins. In this review, we describe mtCU-mediated mitochondrial Ca2+ dysregulation in solid tumour cancer types, finding enhanced mtCU activity observed in colorectal cancer, breast cancer, oral squamous cell carcinoma, pancreatic cancer, hepatocellular carcinoma and embryonal rhabdomyosarcoma. By contrast, decreased mtCU activity is associated with melanoma, whereas the nature of mtCU dysregulation remains unclear in glioblastoma. Furthermore, we show that numerous polymorphisms associated with cancer may alter phosphorylation sites on the pore forming MCU and MCUb subunits, which cluster at interfaces with EMRE. We highlight downstream/upstream biomolecular modulators of MCU and MCUb that alter mtCU-mediated mitochondrial Ca2+ uptake and may be used as biomarkers or to aid in the development of novel cancer therapeutics. Additionally, we provide an overview of the current small molecule inhibitors of mtCU that interact with the Asp residue of the critical Asp-Ile-Met-Glu motif or through other allosteric regulatory mechanisms to block Ca2+ permeation. Finally, we describe the relationship between MCU- and MCUb-mediating microRNAs and mitochondrial Ca2+ uptake that should be considered in the discovery of new treatment approaches for cancer.
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Affiliation(s)
- Danielle M Colussi
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Peter B Stathopulos
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
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4
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Yang K, Lu R, Mei J, Cao K, Zeng T, Hua Y, Huang X, Li W, Yin Y. The war between the immune system and the tumor - using immune biomarkers as tracers. Biomark Res 2024; 12:51. [PMID: 38816871 PMCID: PMC11137916 DOI: 10.1186/s40364-024-00599-5] [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: 12/06/2023] [Accepted: 05/10/2024] [Indexed: 06/01/2024] Open
Abstract
Nowadays, immunotherapy is one of the most promising anti-tumor therapeutic strategy. Specifically, immune-related targets can be used to predict the efficacy and side effects of immunotherapy and monitor the tumor immune response. In the past few decades, increasing numbers of novel immune biomarkers have been found to participate in certain links of the tumor immunity to contribute to the formation of immunosuppression and have entered clinical trials. Here, we systematically reviewed the oncogenesis and progression of cancer in the view of anti-tumor immunity, particularly in terms of tumor antigen expression (related to tumor immunogenicity) and tumor innate immunity to complement the cancer-immune cycle. From the perspective of integrated management of chronic cancer, we also appraised emerging factors affecting tumor immunity (including metabolic, microbial, and exercise-related markers). We finally summarized the clinical studies and applications based on immune biomarkers. Overall, immune biomarkers participate in promoting the development of more precise and individualized immunotherapy by predicting, monitoring, and regulating tumor immune response. Therefore, targeting immune biomarkers may lead to the development of innovative clinical applications.
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Affiliation(s)
- Kai Yang
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
| | - Rongrong Lu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
| | - Jie Mei
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
| | - Kai Cao
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
| | - Tianyu Zeng
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
| | - Yijia Hua
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
- Gusu School, Nanjing Medical University, Nanjing, China
| | - Xiang Huang
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China.
| | - Wei Li
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China.
| | - Yongmei Yin
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China.
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5
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Nakauma-González JA, Rijnders M, Noordsij MTW, Martens JWM, van der Veldt AAM, Lolkema MPJ, Boormans JL, van de Werken HJG. Whole-genome mapping of APOBEC mutagenesis in metastatic urothelial carcinoma identifies driver hotspot mutations and a novel mutational signature. CELL GENOMICS 2024; 4:100528. [PMID: 38552621 PMCID: PMC11019362 DOI: 10.1016/j.xgen.2024.100528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 12/22/2023] [Accepted: 03/06/2024] [Indexed: 04/13/2024]
Abstract
Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like (APOBEC) enzymes mutate specific DNA sequences and hairpin-loop structures, challenging the distinction between passenger and driver hotspot mutations. Here, we characterized 115 whole genomes of metastatic urothelial carcinoma (mUC) to identify APOBEC mutagenic hotspot drivers. APOBEC-associated mutations were detected in 92% of mUCs and were equally distributed across the genome, while APOBEC hotspot mutations (ApoHMs) were enriched in open chromatin. Hairpin loops were frequent targets of didymi (twins in Greek), two hotspot mutations characterized by the APOBEC SBS2 signature, in conjunction with an uncharacterized mutational context (Ap[C>T]). Next, we developed a statistical framework that identified ApoHMs as drivers in coding and non-coding genomic regions of mUCs. Our results and statistical framework were validated in independent cohorts of 23 non-metastatic UCs and 3,744 samples of 17 metastatic cancers, identifying cancer-type-specific drivers. Our study highlights the role of APOBEC in cancer development and may contribute to developing novel targeted therapy options for APOBEC-driven cancers.
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Affiliation(s)
- J Alberto Nakauma-González
- Cancer Computational Biology Center, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands; Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands; Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands.
| | - Maud Rijnders
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - Minouk T W Noordsij
- Cancer Computational Biology Center, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - John W M Martens
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - Astrid A M van der Veldt
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands; Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - Martijn P J Lolkema
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - Joost L Boormans
- Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - Harmen J G van de Werken
- Cancer Computational Biology Center, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands; Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands; Department of Immunology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands.
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6
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Chen F, Zhang Y, Sedlazeck FJ, Creighton CJ. Germline structural variation globally impacts the cancer transcriptome including disease-relevant genes. Cell Rep Med 2024; 5:101446. [PMID: 38442712 PMCID: PMC10983041 DOI: 10.1016/j.xcrm.2024.101446] [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: 09/26/2023] [Revised: 01/01/2024] [Accepted: 02/06/2024] [Indexed: 03/07/2024]
Abstract
Germline variation and somatic alterations contribute to the molecular profile of cancers. We combine RNA with whole genome sequencing across 1,218 cancer patients to determine the extent germline structural variants (SVs) impact expression of nearby genes. For hundreds of genes, recurrent and common germline SV breakpoints within 100 kb associate with increased or decreased expression in tumors spanning various tissues of origin. A significant fraction of germline SV expression associations involves duplication of intergenic enhancers or 3' UTR disruption. Genes altered by both somatic and germline SVs include ATRX and CEBPA. Genes essential in cancer cell lines include BARD1 and IRS2. Genes with both expression and germline SV breakpoint patterns associated with patient survival include GCLM. Our results capture a class of phenotypic variation at work in the disease setting, including genes with cancer roles. Specific germline SVs represent potential cancer risk variants for genetic testing, including those involving genes with targeting implications.
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Affiliation(s)
- Fengju Chen
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yiqun Zhang
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Computer Science, Rice University, Houston, TX 77005, USA
| | - Chad J Creighton
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA.
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7
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Warrell J, Salichos L, Gancz M, Gerstein MB. Latent evolutionary signatures: a general framework for analysing music and cultural evolution. J R Soc Interface 2024; 21:20230647. [PMID: 38503341 PMCID: PMC10950459 DOI: 10.1098/rsif.2023.0647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 02/14/2024] [Indexed: 03/21/2024] Open
Abstract
Cultural processes of change bear many resemblances to biological evolution. The underlying units of non-biological evolution have, however, remained elusive, especially in the domain of music. Here, we introduce a general framework to jointly identify underlying units and their associated evolutionary processes. We model musical styles and principles of organization in dimensions such as harmony and form as following an evolutionary process. Furthermore, we propose that such processes can be identified by extracting latent evolutionary signatures from musical corpora, analogously to identifying mutational signatures in genomics. These signatures provide a latent embedding for each song or musical piece. We develop a deep generative architecture for our model, which can be viewed as a type of variational autoencoder with an evolutionary prior constraining the latent space; specifically, the embeddings for each song are tied together via an energy-based prior, which encourages songs close in evolutionary space to share similar representations. As illustration, we analyse songs from the McGill Billboard dataset. We find frequent chord transitions and formal repetition schemes and identify latent evolutionary signatures related to these features. Finally, we show that the latent evolutionary representations learned by our model outperform non-evolutionary representations in such tasks as period and genre prediction.
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Affiliation(s)
- Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Leonidas Salichos
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Biological and Chemical Sciences, New York Institute of Technology, New York, NY 10023, USA
- Biomedical Data Science Center, New York Institute of Technology, New York, NY 10023, USA
| | - Michael Gancz
- Department of Music, Yale University, New Haven, CT 06520, USA
| | - Mark B. Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
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8
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Galant N, Nicoś M, Kuźnar-Kamińska B, Krawczyk P. Variant Allele Frequency Analysis of Circulating Tumor DNA as a Promising Tool in Assessing the Effectiveness of Treatment in Non-Small Cell Lung Carcinoma Patients. Cancers (Basel) 2024; 16:782. [PMID: 38398173 PMCID: PMC10887123 DOI: 10.3390/cancers16040782] [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: 01/22/2024] [Revised: 02/06/2024] [Accepted: 02/07/2024] [Indexed: 02/25/2024] Open
Abstract
Despite the different possible paths of treatment, lung cancer remains one of the leading causes of death in oncological patients. New tools guiding the therapeutic process are under scientific investigation, and one of the promising indicators of the effectiveness of therapy in patients with NSCLC is variant allele frequency (VAF) analysis. VAF is a metric characterized as the measurement of the specific variant allele proportion within a genomic locus, and it can be determined using methods based on NGS or PCR. It can be assessed using not only tissue samples but also ctDNA (circulating tumor DNA) isolated from liquid biopsy. The non-invasive characteristic of liquid biopsy enables a more frequent collection of material and increases the potential of VAF analysis in monitoring therapy. Several studies have been performed on patients with NSCLC to evaluate the possibility of VAF usage. The research carried out so far demonstrates that the evaluation of VAF dynamics may be useful in monitoring tumor progression, remission, and recurrence during or after treatment. Moreover, the use of VAF analysis appears to be beneficial in making treatment decisions. However, several issues require better understanding and standardization before VAF testing can be implemented in clinical practice. In this review, we discuss the difficulties in the application of ctDNA VAF analysis in clinical routine, discussing the diagnostic and methodological challenges in VAF measurement in liquid biopsy. We highlight the possible applications of VAF-based measurements that are under consideration in clinical trials in the monitoring of personalized treatments for patients with NSCLC.
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Affiliation(s)
- Natalia Galant
- Department of Pneumonology, Oncology and Allergology, Medical University of Lublin, 20-059 Lublin, Poland
| | - Marcin Nicoś
- Department of Pneumonology, Oncology and Allergology, Medical University of Lublin, 20-059 Lublin, Poland
| | - Barbara Kuźnar-Kamińska
- Department of Pulmonology, Allergology and Respiratory Oncology, Poznan University of Medical Sciences, 61-710 Poznan, Poland;
| | - Paweł Krawczyk
- Department of Pneumonology, Oncology and Allergology, Medical University of Lublin, 20-059 Lublin, Poland
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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.
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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.
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10
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Matkarimov BT, Saparbaev MK. Chargaff's second parity rule lies at the origin of additive genetic interactions in quantitative traits to make omnigenic selection possible. PeerJ 2023; 11:e16671. [PMID: 38107580 PMCID: PMC10725672 DOI: 10.7717/peerj.16671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 11/22/2023] [Indexed: 12/19/2023] Open
Abstract
Background Francis Crick's central dogma provides a residue-by-residue mechanistic explanation of the flow of genetic information in living systems. However, this principle may not be sufficient for explaining how random mutations cause continuous variation of quantitative highly polygenic complex traits. Chargaff's second parity rule (CSPR), also referred to as intrastrand DNA symmetry, defined as near-exact equalities G ≈ C and A ≈ T within a single DNA strand, is a statistical property of cellular genomes. The phenomenon of intrastrand DNA symmetry was discovered more than 50 years ago; at present, it remains unclear what its biological role is, what the mechanisms are that force cellular genomes to comply strictly with CSPR, and why genomes of certain noncellular organisms have broken intrastrand DNA symmetry. The present work is aimed at studying a possible link between intrastrand DNA symmetry and the origin of genetic interactions in quantitative traits. Methods Computational analysis of single-nucleotide polymorphisms in human and mouse populations and of nucleotide composition biases at different codon positions in bacterial and human proteomes. Results The analysis of mutation spectra inferred from single-nucleotide polymorphisms observed in murine and human populations revealed near-exact equalities of numbers of reverse complementary mutations, indicating that random genetic variations obey CSPR. Furthermore, nucleotide compositions of coding sequences proved to be statistically interwoven via CSPR because pyrimidine bias at the 3rd codon position compensates purine bias at the 1st and 2nd positions. Conclusions According to Fisher's infinitesimal model, we propose that accumulation of reverse complementary mutations results in a continuous phenotypic variation due to small additive effects of statistically interwoven genetic variations. Therefore, additive genetic interactions can be inferred as a statistical entanglement of nucleotide compositions of separate genetic loci. CSPR challenges the neutral theory of molecular evolution-because all random mutations participate in variation of a trait-and provides an alternative solution to Haldane's dilemma by making a gene function diffuse. We propose that CSPR is symmetry of Fisher's infinitesimal model and that genetic information can be transferred in an implicit contactless manner.
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Affiliation(s)
- Bakhyt T. Matkarimov
- National Laboratory Astana, Nazarbayev University, Astana, Kazakhstan
- L.N.Gumilev Eurasian National University, Astana, Kazakhstan
| | - Murat K. Saparbaev
- Groupe «Mechanisms of DNA Repair and Carcinogenesis», CNRS UMR9019, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
- Al-Farabi Kazakh National University, Almaty, Kazakhstan
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11
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Rao Y, Ahmed N, Pritchard J, O'Brien EP. Incorporating mutational heterogeneity to identify genes that are enriched for synonymous mutations in cancer. BMC Bioinformatics 2023; 24:462. [PMID: 38062391 PMCID: PMC10704839 DOI: 10.1186/s12859-023-05521-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 10/05/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Synonymous mutations, which change the DNA sequence but not the encoded protein sequence, can affect protein structure and function, mRNA maturation, and mRNA half-lives. The possibility that synonymous mutations might be enriched in cancer has been explored in several recent studies. However, none of these studies control for all three types of mutational heterogeneity (patient, histology, and gene) that are known to affect the accurate identification of non-synonymous cancer-associated genes. Our goal is to adopt the current standard for non-synonymous mutations in an investigation of synonymous mutations. RESULTS Here, we create an algorithm, MutSigCVsyn, an adaptation of MutSigCV, to identify cancer-associated genes that are enriched for synonymous mutations based on a non-coding background model that takes into account the mutational heterogeneity across these levels. Using MutSigCVsyn, we first analyzed 2572 cancer whole-genome samples from the Pan-cancer Analysis of Whole Genomes (PCAWG) to identify non-synonymous cancer drivers as a quality control. Indicative of the algorithm accuracy we find that 58.6% of these candidate genes were also found in Cancer Census Gene (CGC) list, and 66.2% were found within the PCAWG cancer driver list. We then applied it to identify 30 putative cancer-associated genes that are enriched for synonymous mutations within the same samples. One of the promising gene candidates is the B cell lymphoma 2 (BCL-2) gene. BCL-2 regulates apoptosis by antagonizing the action of proapoptotic BCL-2 family member proteins. The synonymous mutations in BCL2 are enriched in its anti-apoptotic domain and likely play a role in cancer cell proliferation. CONCLUSION Our study introduces MutSigCVsyn, an algorithm that accounts for mutational heterogeneity at patient, histology, and gene levels, to identify cancer-associated genes that are enriched for synonymous mutations using whole genome sequencing data. We identified 30 putative candidate genes that will benefit from future experimental studies on the role of synonymous mutations in cancer biology.
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Affiliation(s)
- Yiyun Rao
- Huck Institute of the Life Sciences, Pennsylvania State University, University Park, State College, PA, 16802, USA
| | - Nabeel Ahmed
- Huck Institute of the Life Sciences, Pennsylvania State University, University Park, State College, PA, 16802, USA
- Moderna, Inc., Cambridge, USA
| | - Justin Pritchard
- Department of Biomedical Engineering, Pennsylvania State University, University Park, State College, PA, 16802, USA.
| | - Edward P O'Brien
- Department of Chemistry, Pennsylvania State University, University Park, State College, PA, 16802, USA.
- Institute for Computational and Data Sciences, Pennsylvania State University, University Park, State College, PA, 16802, USA.
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12
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Kang W, Mo Z, Li W, Ma H, Zhang Q. Heterogeneity and individualized treatment of microenvironment in glioblastoma (Review). Oncol Rep 2023; 50:217. [PMID: 37888767 PMCID: PMC10636722 DOI: 10.3892/or.2023.8654] [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: 05/12/2023] [Accepted: 10/12/2023] [Indexed: 10/28/2023] Open
Abstract
The heterogeneity of glioblastoma can suppress immune cell function and lead to immune evasion, which presents a challenge in developing effective molecular therapies for tumor cells. However, the study of tumor immune heterogeneity holds great potential for clinical immunotherapy. Liquid biopsy is a useful tool for accurately monitoring dynamic changes in tumor immune heterogeneity and the tumor microenvironment. This paper explores the heterogeneity of glioblastoma and the immune microenvironment, providing a therapeutic basis for individualized treatment. Using liquid biopsy technology as a new diagnostic method, innovative treatment strategies may be implemented for patients with glioblastoma to improve their outcomes.
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Affiliation(s)
- Wei Kang
- Department of Neurosurgery, Qinghai Provincial People's Hospital, Xining, Qinghai 810001, P.R. China
| | - Zhixiao Mo
- Department of Neurosurgery, Qinghai Cardio-Cerebrovascular Hospital, Xining, Qinghai 810099, P.R. China
| | - Wenshan Li
- Department of Neurosurgery, Qinghai Provincial People's Hospital, Xining, Qinghai 810001, P.R. China
- Key Laboratory of Neurology of Gansu Province, Department of Neurosurgery, Lanzhou University Second Hospital, Lanzhou, Gansu 730030, P.R. China
| | - Haifeng Ma
- Department of Neurosurgery, Qinghai Provincial People's Hospital, Xining, Qinghai 810001, P.R. China
| | - Qiang Zhang
- Department of Neurosurgery, Qinghai Provincial People's Hospital, Xining, Qinghai 810001, P.R. China
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13
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Yoon SH, Nam JW. Clustering malignant cell states using universally variable genes. Brief Bioinform 2023; 25:bbad460. [PMID: 38084922 PMCID: PMC10783859 DOI: 10.1093/bib/bbad460] [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: 08/09/2023] [Revised: 11/20/2023] [Accepted: 11/22/2023] [Indexed: 12/18/2023] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) has revealed important insights into the heterogeneity of malignant cells. However, sample-specific genomic alterations often confound such analysis, resulting in patient-specific clusters that are difficult to interpret. Here, we present a novel approach to address the issue. By normalizing gene expression variances to identify universally variable genes (UVGs), we were able to reduce the formation of sample-specific clusters and identify underlying molecular hallmarks in malignant cells. In contrast to highly variable genes vulnerable to a specific sample bias, UVGs led to better detection of clusters corresponding to distinct malignant cell states. Our results demonstrate the utility of this approach for analyzing scRNA-seq data and suggest avenues for further exploration of malignant cell heterogeneity.
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Affiliation(s)
- Sang-Ho Yoon
- Department of Life Science, College of Natural Sciences, Hanyang University, Seoul 04763, Republic of Korea
- Hanyang Institute of Advanced BioConvergence, Hanyang University, Seoul 04763, Republic of Korea
- Hanyang Institute of Bioscience and Biotechnology, Bio-BigData Research Center, Hanyang University, Seoul 04763, Republic of Korea
| | - Jin-Wu Nam
- Department of Life Science, College of Natural Sciences, Hanyang University, Seoul 04763, Republic of Korea
- Hanyang Institute of Advanced BioConvergence, Hanyang University, Seoul 04763, Republic of Korea
- Research Institute for Convergence of Basic Sciences, Hanyang University, Seoul 04763, Republic of Korea
- Hanyang Institute of Bioscience and Biotechnology, Bio-BigData Research Center, Hanyang University, Seoul 04763, Republic of Korea
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14
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Xu X, Li Y, Chen T, Hou C, Yang L, Zhu P, Zhang Y, Li T. VIPpred: a novel model for predicting variant impact on phosphorylation events driving carcinogenesis. Brief Bioinform 2023; 25:bbad480. [PMID: 38156562 PMCID: PMC10782907 DOI: 10.1093/bib/bbad480] [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: 04/11/2023] [Revised: 11/14/2023] [Accepted: 12/03/2023] [Indexed: 12/30/2023] Open
Abstract
Disrupted protein phosphorylation due to genetic variation is a widespread phenomenon that triggers oncogenic transformation of healthy cells. However, few relevant phosphorylation disruption events have been verified due to limited biological experimental methods. Because of the lack of reliable benchmark datasets, current bioinformatics methods primarily use sequence-based traits to study variant impact on phosphorylation (VIP). Here, we increased the number of experimentally supported VIP events from less than 30 to 740 by manually curating and reanalyzing multi-omics data from 916 patients provided by the Clinical Proteomic Tumor Analysis Consortium. To predict VIP events in cancer cells, we developed VIPpred, a machine learning method characterized by multidimensional features that exhibits robust performance across different cancer types. Our method provided a pan-cancer landscape of VIP events, which are enriched in cancer-related pathways and cancer driver genes. We found that variant-induced increases in phosphorylation events tend to inhibit the protein degradation of oncogenes and promote tumor suppressor protein degradation. Our work provides new insights into phosphorylation-related cancer biology as well as novel avenues for precision therapy.
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Affiliation(s)
- Xiaofeng Xu
- Department of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Ying Li
- Department of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, Shanxi 030024, China
| | - Taoyu Chen
- Department of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Chao Hou
- Department of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Liang Yang
- Department of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Peiyu Zhu
- Department of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Yi Zhang
- Department of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Tingting Li
- Department of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
- Key Laboratory for Neuroscience, Ministry of Education/National Health Commission of China, Peking University, Beijing 100191, China
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15
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Ünlü B, Pons C, Ho UL, Batté A, Aloy P, van Leeuwen J. Global analysis of suppressor mutations that rescue human genetic defects. Genome Med 2023; 15:78. [PMID: 37821946 PMCID: PMC10568808 DOI: 10.1186/s13073-023-01232-0] [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: 04/07/2023] [Accepted: 09/12/2023] [Indexed: 10/13/2023] Open
Abstract
BACKGROUND Genetic suppression occurs when the deleterious effects of a primary "query" mutation, such as a disease-causing mutation, are rescued by a suppressor mutation elsewhere in the genome. METHODS To capture existing knowledge on suppression relationships between human genes, we examined 2,400 published papers for potential interactions identified through either genetic modification of cultured human cells or through association studies in patients. RESULTS The resulting network encompassed 476 unique suppression interactions covering a wide spectrum of diseases and biological functions. The interactions frequently linked genes that operate in the same biological process. Suppressors were strongly enriched for genes with a role in stress response or signaling, suggesting that deleterious mutations can often be buffered by modulating signaling cascades or immune responses. Suppressor mutations tended to be deleterious when they occurred in absence of the query mutation, in apparent contrast with their protective role in the presence of the query. We formulated and quantified mechanisms of genetic suppression that could explain 71% of interactions and provided mechanistic insight into disease pathology. Finally, we used these observations to predict suppressor genes in the human genome. CONCLUSIONS The global suppression network allowed us to define principles of genetic suppression that were conserved across diseases, model systems, and species. The emerging frequency of suppression interactions among human genes and range of underlying mechanisms, together with the prevalence of suppression in model organisms, suggest that compensatory mutations may exist for most genetic diseases.
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Affiliation(s)
- Betül Ünlü
- Center for Integrative Genomics, University of Lausanne, Génopode Building, 1015, Lausanne, Switzerland
| | - Carles Pons
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology, Barcelona, Spain
| | - Uyen Linh Ho
- Center for Integrative Genomics, University of Lausanne, Génopode Building, 1015, Lausanne, Switzerland
| | - Amandine Batté
- Center for Integrative Genomics, University of Lausanne, Génopode Building, 1015, Lausanne, Switzerland
| | - Patrick Aloy
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology, Barcelona, Spain
- Institucio Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Jolanda van Leeuwen
- Center for Integrative Genomics, University of Lausanne, Génopode Building, 1015, Lausanne, Switzerland.
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16
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Aldea M, Friboulet L, Apcher S, Jaulin F, Mosele F, Sourisseau T, Soria JC, Nikolaev S, André F. Precision medicine in the era of multi-omics: can the data tsunami guide rational treatment decision? ESMO Open 2023; 8:101642. [PMID: 37769400 PMCID: PMC10539962 DOI: 10.1016/j.esmoop.2023.101642] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 08/14/2023] [Indexed: 09/30/2023] Open
Abstract
Precision medicine for cancer is rapidly moving to an approach that integrates multiple dimensions of the biology in order to model mechanisms of cancer progression in each patient. The discovery of multiple drivers per tumor challenges medical decision that faces several treatment options. Drug sensitivity depends on the actionability of the target, its clonal or subclonal origin and coexisting genomic alterations. Sequencing has revealed a large diversity of drivers emerging at treatment failure, which are potential targets for clinical trials or drug repurposing. To effectively prioritize therapies, it is essential to rank genomic alterations based on their proven actionability. Moving beyond primary drivers, the future of precision medicine necessitates acknowledging the intricate spatial and temporal heterogeneity inherent in cancer. The advent of abundant complex biological data will make artificial intelligence algorithms indispensable for thorough analysis. Here, we will discuss the advancements brought by the use of high-throughput genomics, the advantages and limitations of precision medicine studies and future perspectives in this field.
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Affiliation(s)
- M Aldea
- Department of Medical Oncology, Gustave Roussy, Villejuif; PRISM, INSERM, Gustave Roussy, Villejuif.
| | | | - S Apcher
- PRISM, INSERM, Gustave Roussy, Villejuif
| | - F Jaulin
- PRISM, INSERM, Gustave Roussy, Villejuif
| | - F Mosele
- Department of Medical Oncology, Gustave Roussy, Villejuif; PRISM, INSERM, Gustave Roussy, Villejuif
| | | | - J-C Soria
- Paris Saclay University, Orsay; Drug Development Department, Gustave Roussy, Villejuif, France
| | - S Nikolaev
- PRISM, INSERM, Gustave Roussy, Villejuif
| | - F André
- Department of Medical Oncology, Gustave Roussy, Villejuif; PRISM, INSERM, Gustave Roussy, Villejuif; Paris Saclay University, Orsay
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17
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Chen F, Zhang Y, Chandrashekar DS, Varambally S, Creighton CJ. Global impact of somatic structural variation on the cancer proteome. Nat Commun 2023; 14:5637. [PMID: 37704602 PMCID: PMC10499989 DOI: 10.1038/s41467-023-41374-8] [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: 04/20/2023] [Accepted: 09/01/2023] [Indexed: 09/15/2023] Open
Abstract
Both proteome and transcriptome data can help assess the relevance of non-coding somatic mutations in cancer. Here, we combine mass spectrometry-based proteomics data with whole genome sequencing data across 1307 human tumors spanning various tissues to determine the extent somatic structural variant (SV) breakpoint patterns impact protein expression of nearby genes. We find that about 25% of the hundreds of genes with SV-associated cis-regulatory alterations at the mRNA level are similarly associated at the protein level. SVs associated with enhancer hijacking, retrotransposon translocation, altered DNA methylation, or fusion transcripts are implicated in protein over-expression. SVs combined with altered protein levels considerably extend the numbers of patients with tumors somatically altered for critical pathways. We catalog both SV breakpoint patterns involving patient survival and genes with nearby SV breakpoints associated with increased cell dependency in cancer cell lines. Pan-cancer proteogenomics identifies targetable non-coding alterations, by virtue of the associated deregulated genes.
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Affiliation(s)
- Fengju Chen
- Dan L. Duncan Comprehensive Cancer Center Division of Biostatistics, Baylor College of Medicine, Houston, TX, USA
| | - Yiqun Zhang
- Dan L. Duncan Comprehensive Cancer Center Division of Biostatistics, Baylor College of Medicine, Houston, TX, USA
| | - Darshan S Chandrashekar
- Molecular and Cellular Pathology, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, 35233, USA
- O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL, 35233, USA
- Genomic Diagnostics and Bioinformatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, 35233, USA
| | - Sooryanarayana Varambally
- Molecular and Cellular Pathology, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, 35233, USA
- O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL, 35233, USA
- The Informatics Institute, University of Alabama at Birmingham, Birmingham, AL, 35233, USA
| | - Chad J Creighton
- Dan L. Duncan Comprehensive Cancer Center Division of Biostatistics, Baylor College of Medicine, Houston, TX, USA.
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
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18
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Janssen K, Duran-Romaña R, Bottu G, Guharoy M, Botzki A, Rousseau F, Schymkowitz J. SNPeffect 5.0: large-scale structural phenotyping of protein coding variants extracted from next-generation sequencing data using AlphaFold models. BMC Bioinformatics 2023; 24:287. [PMID: 37464277 DOI: 10.1186/s12859-023-05407-9] [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: 07/05/2022] [Accepted: 07/10/2023] [Indexed: 07/20/2023] Open
Abstract
BACKGROUND Next-generation sequencing technologies yield large numbers of genetic alterations, of which a subset are missense variants that alter an amino acid in the protein product. These variants can have a potentially destabilizing effect leading to an increased risk of misfolding and aggregation. Multiple software tools exist to predict the effect of single-nucleotide variants on proteins, however, a pipeline integrating these tools while starting from an NGS data output list of variants is lacking. RESULTS The previous version SNPeffect 4.0 (De Baets in Nucleic Acids Res 40(D1):D935-D939, 2011) provided an online database containing pre-calculated variant effects and low-throughput custom variant analysis. Here, we built an automated and parallelized pipeline that analyzes the impact of missense variants on the aggregation propensity and structural stability of proteins starting from the Variant Call Format as input. The pipeline incorporates the AlphaFold Protein Structure Database to achieve high coverage for structural stability analyses using the FoldX force field. The effect on aggregation-propensity is analyzed using the established predictors TANGO and WALTZ. The pipeline focuses solely on the human proteome and can be used to analyze proteome stability/damage in a given sample based on sequencing results. CONCLUSION We provide a bioinformatics pipeline that allows structural phenotyping from sequencing data using established stability and aggregation predictors including FoldX, TANGO, and WALTZ; and structural proteome coverage provided by the AlphaFold database. The pipeline and installation guide are freely available for academic users on https://github.com/vibbits/snpeffect and requires a computer cluster.
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Affiliation(s)
- Kobe Janssen
- Switch Laboratory, VIB-KU Leuven Center for Brain and Disease Research, Herestraat 49, 3000, Leuven, Belgium
- Switch Laboratory, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Ramon Duran-Romaña
- Switch Laboratory, VIB-KU Leuven Center for Brain and Disease Research, Herestraat 49, 3000, Leuven, Belgium
- Switch Laboratory, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Guy Bottu
- VIB Bioinformatics Core, VIB, Rijvisschestraat 120, 9052, Ghent, Belgium
| | - Mainak Guharoy
- VIB Bioinformatics Core, VIB, Rijvisschestraat 120, 9052, Ghent, Belgium
| | - Alexander Botzki
- VIB Bioinformatics Core, VIB, Rijvisschestraat 120, 9052, Ghent, Belgium
| | - Frederic Rousseau
- Switch Laboratory, VIB-KU Leuven Center for Brain and Disease Research, Herestraat 49, 3000, Leuven, Belgium.
- Switch Laboratory, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
| | - Joost Schymkowitz
- Switch Laboratory, VIB-KU Leuven Center for Brain and Disease Research, Herestraat 49, 3000, Leuven, Belgium.
- Switch Laboratory, Department of Cellular and Molecular Medicine, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
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19
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Coleman JC, Hallett SR, Grigoriadis AE, Conte MR. LARP4A and LARP4B in cancer: The new kids on the block. Int J Biochem Cell Biol 2023; 161:106441. [PMID: 37356415 DOI: 10.1016/j.biocel.2023.106441] [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: 05/03/2023] [Revised: 06/09/2023] [Accepted: 06/17/2023] [Indexed: 06/27/2023]
Abstract
Recent developments have mounted a stunning body of evidence underlying the importance of RNA binding proteins (RBPs) in cancer research. In this minireview we focus on LARP4A and LARP4B, two paralogs belonging to the superfamily of La-related proteins, and provide a critical overview of current research, including their roles in cancer pathogenesis and cell proliferation, migration, cell cycle and apoptosis. We highlight current controversies surrounding LARP4A and LARP4B and conclude that their complex roles in tumorigenesis are cell-, tissue- and context-dependent, warning that caution must be exercised before categorising either protein as an oncoprotein or tumour-suppressor. We also reveal that LARP4A and LARP4B have often been confused with one another, adding uncertainty in delineating their functions. We suggest that further functional and mechanistic studies of LARP4 proteins present significant challenges for future investigations to recognise the vital contributions of these RBPs in cancer research.
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Affiliation(s)
- Jennifer C Coleman
- Centre for Craniofacial & Regenerative Biology, King's College London, London SE1 9RT, UK
| | - Sadie R Hallett
- Randall Centre for Cell and Molecular Biophysics, King's College London, London SE1 1UL, UK
| | | | - Maria R Conte
- Randall Centre for Cell and Molecular Biophysics, King's College London, London SE1 1UL, UK.
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20
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Esposito R, Lanzós A, Uroda T, Ramnarayanan S, Büchi I, Polidori T, Guillen-Ramirez H, Mihaljevic A, Merlin BM, Mela L, Zoni E, Hovhannisyan L, McCluggage F, Medo M, Basile G, Meise DF, Zwyssig S, Wenger C, Schwarz K, Vancura A, Bosch-Guiteras N, Andrades Á, Tham AM, Roemmele M, Medina PP, Ochsenbein AF, Riether C, Kruithof-de Julio M, Zimmer Y, Medová M, Stroka D, Fox A, Johnson R. Tumour mutations in long noncoding RNAs enhance cell fitness. Nat Commun 2023; 14:3342. [PMID: 37291246 PMCID: PMC10250536 DOI: 10.1038/s41467-023-39160-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 06/01/2023] [Indexed: 06/10/2023] Open
Abstract
Long noncoding RNAs (lncRNAs) are linked to cancer via pathogenic changes in their expression levels. Yet, it remains unclear whether lncRNAs can also impact tumour cell fitness via function-altering somatic "driver" mutations. To search for such driver-lncRNAs, we here perform a genome-wide analysis of fitness-altering single nucleotide variants (SNVs) across a cohort of 2583 primary and 3527 metastatic tumours. The resulting 54 mutated and positively-selected lncRNAs are significantly enriched for previously-reported cancer genes and a range of clinical and genomic features. A number of these lncRNAs promote tumour cell proliferation when overexpressed in in vitro models. Our results also highlight a dense SNV hotspot in the widely-studied NEAT1 oncogene. To directly evaluate the functional significance of NEAT1 SNVs, we use in cellulo mutagenesis to introduce tumour-like mutations in the gene and observe a significant and reproducible increase in cell fitness, both in vitro and in a mouse model. Mechanistic studies reveal that SNVs remodel the NEAT1 ribonucleoprotein and boost subnuclear paraspeckles. In summary, this work demonstrates the utility of driver analysis for mapping cancer-promoting lncRNAs, and provides experimental evidence that somatic mutations can act through lncRNAs to enhance pathological cancer cell fitness.
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Affiliation(s)
- Roberta Esposito
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland.
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland.
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso", CNR, 80131, Naples, Italy.
| | - Andrés Lanzós
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Graduate School of Cellular and Biomedical Sciences, University of Bern, 3012, Bern, Switzerland
| | - Tina Uroda
- School of Biology and Environmental Science, University College Dublin, Dublin, D04 V1W8, Ireland
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Sunandini Ramnarayanan
- School of Biology and Environmental Science, University College Dublin, Dublin, D04 V1W8, Ireland
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- The SFI Centre for Research Training in Genomics Data Science, Dublin, Ireland
| | - Isabel Büchi
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Taisia Polidori
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Hugo Guillen-Ramirez
- School of Biology and Environmental Science, University College Dublin, Dublin, D04 V1W8, Ireland
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Ante Mihaljevic
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Bernard Mefi Merlin
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Lia Mela
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Eugenio Zoni
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Urology, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Lusine Hovhannisyan
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Finn McCluggage
- School of Molecular Sciences, University of Western Australia, Crawley, WA, Australia
- School of Human Sciences, University of Western Australia, Crawley, WA, Australia
| | - Matúš Medo
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Giulia Basile
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Dominik F Meise
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Sandra Zwyssig
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Corina Wenger
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Kyriakos Schwarz
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Adrienne Vancura
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Núria Bosch-Guiteras
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Graduate School of Cellular and Biomedical Sciences, University of Bern, 3012, Bern, Switzerland
| | - Álvaro Andrades
- GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, Granada, 18016, Spain
- Instituto de Investigación Biosanitaria, Granada, 18014, Spain
- Department of Biochemistry and Molecular Biology I, University of Granada, Granada, 18071, Spain
| | - Ai Ming Tham
- School of Biology and Environmental Science, University College Dublin, Dublin, D04 V1W8, Ireland
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Michaela Roemmele
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Pedro P Medina
- GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, Granada, 18016, Spain
- Instituto de Investigación Biosanitaria, Granada, 18014, Spain
- Department of Biochemistry and Molecular Biology I, University of Granada, Granada, 18071, Spain
| | - Adrian F Ochsenbein
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Carsten Riether
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Marianna Kruithof-de Julio
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Urology, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Yitzhak Zimmer
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Michaela Medová
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Deborah Stroka
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Archa Fox
- School of Molecular Sciences, University of Western Australia, Crawley, WA, Australia
- School of Human Sciences, University of Western Australia, Crawley, WA, Australia
| | - Rory Johnson
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland.
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland.
- School of Biology and Environmental Science, University College Dublin, Dublin, D04 V1W8, Ireland.
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland.
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21
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Kumar S, Gerstein M. Unified views on variant impact across many diseases. Trends Genet 2023; 39:442-450. [PMID: 36858880 PMCID: PMC10192142 DOI: 10.1016/j.tig.2023.02.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 02/02/2023] [Accepted: 02/02/2023] [Indexed: 03/03/2023]
Abstract
Genomic studies of human disorders are often performed by distinct research communities (i.e., focused on rare diseases, common diseases, or cancer). Despite underlying differences in the mechanistic origin of different disease categories, these studies share the goal of identifying causal genomic events that are critical for the clinical manifestation of the disease phenotype. Moreover, these studies face common challenges, including understanding the complex genetic architecture of the disease, deciphering the impact of variants on multiple scales, and interpreting noncoding mutations. Here, we highlight these challenges in depth and argue that properly addressing them will require a more unified vocabulary and approach across disease communities. Toward this goal, we present a unified perspective on relating variant impact to various genomic disorders.
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Affiliation(s)
- Sushant Kumar
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Department of Computer Science, Yale University, New Haven, CT 06520, USA; Department of Statistics & Data Science, Yale University, New Haven, CT 06520, USA.
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22
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Zhu X, Zhao W, Zhou Z, Gu X. Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools. J Mol Evol 2023:10.1007/s00239-023-10117-0. [PMID: 37246992 DOI: 10.1007/s00239-023-10117-0] [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: 12/30/2022] [Accepted: 05/09/2023] [Indexed: 05/30/2023]
Abstract
Cancer originates from somatic cells that have accumulated mutations. These mutations alter the phenotype of the cells, allowing them to escape homeostatic regulation that maintains normal cell numbers. The emergence of malignancies is an evolutionary process in which the random accumulation of somatic mutations and sequential selection of dominant clones cause cancer cells to proliferate. The development of technologies such as high-throughput sequencing has provided a powerful means to measure subclonal evolutionary dynamics across space and time. Here, we review the patterns that may be observed in cancer evolution and the methods available for quantifying the evolutionary dynamics of cancer. An improved understanding of the evolutionary trajectories of cancer will enable us to explore the molecular mechanism of tumorigenesis and to design tailored treatment strategies.
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Affiliation(s)
- Xunuo Zhu
- Innovation Institute for Artificial Intelligence in Medicine, Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Wenyi Zhao
- Innovation Institute for Artificial Intelligence in Medicine, Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Zhan Zhou
- Innovation Institute for Artificial Intelligence in Medicine, Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322000, China.
- Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, 310058, China.
| | - Xun Gu
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA, 50011, USA.
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23
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Pezzuto F, Hofman V, Bontoux C, Fortarezza F, Lunardi F, Calabrese F, Hofman P. The significance of co-mutations in EGFR-mutated non-small cell lung cancer: Optimizing the efficacy of targeted therapies? Lung Cancer 2023; 181:107249. [PMID: 37244040 DOI: 10.1016/j.lungcan.2023.107249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 05/03/2023] [Accepted: 05/11/2023] [Indexed: 05/29/2023]
Abstract
Non-small cell lung cancer (NSCLC) is the most common cause of cancer death worldwide. In non-squamous NSCLC, the identification of oncogenic drivers and the development of target-specific molecules led to remarkable progress in therapeutic strategies and overall survival over the last decade. Nevertheless, responses are limited by systematically acquired mechanisms of resistance early on after starting a targeted therapy. Moreover, mounting evidence has demonstrated that each oncogenic-driven cluster is actually heterogeneous in terms of molecular features, clinical behaviour, and sensitivity to targeted therapy. In this review, we aimed to examine the prognostic and predictive significance of oncogene-driven co-mutations, focusing mainly on EGFR and TP53. A narrative review was performed by searching MEDLINE databases for English articles published over the last decade (from January 2012 until November 2022). The bibliographies of key references were manually reviewed to select those eligible for the topic. The genetic landscape of EGFR-mutated NSCLC is more complicated than what is known so far. In particular, the occurrence of TP53 co-mutations stratify patients carrying EGFR mutations in terms of treatment response. The study provides a deeper understanding of the mechanisms underlying the variability of the genetic landscape of EGFR-mutated NSCLC and summarizes notably the clinical importance of TP53 co-mutations for an open avenue to more properly addressing the clinical decision-making in the near future.
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Affiliation(s)
- Federica Pezzuto
- University Côte d'Azur, Laboratory of Clinical and Experimental Pathology, FHU OncoAge, BB-0033-00025, Pasteur Hospital, 30 voie romaine, 06001 Nice, France; Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova Medical School, Via A. Gabelli 61, 35121 Padova, Italy.
| | - Véronique Hofman
- University Côte d'Azur, Laboratory of Clinical and Experimental Pathology, FHU OncoAge, BB-0033-00025, Pasteur Hospital, 30 voie romaine, 06001 Nice, France
| | - Christophe Bontoux
- University Côte d'Azur, Laboratory of Clinical and Experimental Pathology, FHU OncoAge, BB-0033-00025, Pasteur Hospital, 30 voie romaine, 06001 Nice, France
| | - Francesco Fortarezza
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova Medical School, Via A. Gabelli 61, 35121 Padova, Italy
| | - Francesca Lunardi
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova Medical School, Via A. Gabelli 61, 35121 Padova, Italy
| | - Fiorella Calabrese
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova Medical School, Via A. Gabelli 61, 35121 Padova, Italy
| | - Paul Hofman
- University Côte d'Azur, Laboratory of Clinical and Experimental Pathology, FHU OncoAge, BB-0033-00025, Pasteur Hospital, 30 voie romaine, 06001 Nice, France.
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24
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Derbal Y. Cell Adaptive Fitness and Cancer Evolutionary Dynamics. Cancer Inform 2023; 22:11769351231154679. [PMID: 36860424 PMCID: PMC9969436 DOI: 10.1177/11769351231154679] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 01/17/2023] [Indexed: 02/26/2023] Open
Abstract
Genome instability of cancer cells translates into increased entropy and lower information processing capacity, leading to metabolic reprograming toward higher energy states, presumed to be aligned with a cancer growth imperative. Dubbed as the cell adaptive fitness, the proposition postulates that the coupling between cell signaling and metabolism constrains cancer evolutionary dynamics along trajectories privileged by the maintenance of metabolic sufficiency for survival. In particular, the conjecture postulates that clonal expansion becomes restricted when genetic alterations induce a sufficiently high level of disorder, that is, high entropy, in the regulatory signaling network, abrogating as a result the ability of cancer cells to successfully replicate, leading to a stage of clonal stagnation. The proposition is analyzed in the context of an in-silico model of tumor evolutionary dynamics to illustrate how cell-inherent adaptive fitness may predictably constrain clonal evolution of tumors, which would have significant implications for the design of adaptive cancer therapies.
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Affiliation(s)
- Youcef Derbal
- Youcef Derbal, Ted Rogers School of
Information Technology Management, Toronto Metropolitan University, 350 Victoria
Street, Toronto, ON M5B 2K3, Canada.
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25
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Mandell JD, Cannataro VL, Townsend JP. Estimation of Neutral Mutation Rates and Quantification of Somatic Variant Selection Using cancereffectsizeR. Cancer Res 2023; 83:500-505. [PMID: 36469362 PMCID: PMC9929515 DOI: 10.1158/0008-5472.can-22-1508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 10/11/2022] [Accepted: 11/30/2022] [Indexed: 12/12/2022]
Abstract
Somatic nucleotide mutations can contribute to cancer cell survival, proliferation, and pathogenesis. Although research has focused on identifying which mutations are "drivers" versus "passengers," quantifying the proliferative effects of specific variants within clinically relevant contexts could reveal novel aspects of cancer biology. To enable researchers to estimate these cancer effects, we developed cancereffectsizeR, an R package that organizes somatic variant data, facilitates mutational signature analysis, calculates site-specific mutation rates, and tests models of selection. Built-in models support effect estimation from single nucleotides to genes. Users can also estimate epistatic effects between paired sets of variants, or design and test custom models. The utility of cancer effect was validated by showing in a pan-cancer dataset that somatic variants classified as likely pathogenic or pathogenic in ClinVar exhibit substantially higher effects than most other variants. Indeed, cancer effect was a better predictor of pathogenic status than variant prevalence or functional impact scores. In addition, the application of this approach toward pairwise epistasis in lung adenocarcinoma showed that driver mutations in BRAF, EGFR, or KRAS typically reduce selection for alterations in the other two genes. Companion reference data packages support analyses using the hg19 or hg38 human genome builds, and a reference data builder enables use with any species or custom genome build with available genomic and transcriptomic data. A reference manual, tutorial, and public source code repository are available at https://townsend-lab-yale.github.io/cancereffectsizeR. Comprehensive estimation of cancer effects of somatic mutations can provide insights into oncogenic trajectories, with implications for cancer prognosis and treatment. SIGNIFICANCE An R package provides streamlined, customizable estimation of underlying nucleotide mutation rates and of the oncogenic and epistatic effects of mutations in cancer cohorts.
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Affiliation(s)
- Jeffrey D. Mandell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut
| | | | - Jeffrey P. Townsend
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
- Genetics, Genomics, and Epigenetics Research Program, Yale Cancer Center, New Haven, Connecticut
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut
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26
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Sarkar E, Chielle E, Gursoy G, Chen L, Gerstein M, Maniatakos M. Privacy-preserving cancer type prediction with homomorphic encryption. Sci Rep 2023; 13:1661. [PMID: 36717667 PMCID: PMC9886900 DOI: 10.1038/s41598-023-28481-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 01/19/2023] [Indexed: 01/31/2023] Open
Abstract
Cancer genomics tailors diagnosis and treatment based on an individual's genetic information and is the crux of precision medicine. However, analysis and maintenance of high volume of genetic mutation data to build a machine learning (ML) model to predict the cancer type is a computationally expensive task and is often outsourced to powerful cloud servers, raising critical privacy concerns for patients' data. Homomorphic encryption (HE) enables computation on encrypted data, thus, providing cryptographic guarantees to protect privacy. But restrictive overheads of encrypted computation deter its usage. In this work, we explore the challenges of privacy preserving cancer type prediction using a dataset consisting of more than 2 million genetic mutations from 2713 patients for several cancer types by building a highly accurate ML model and then implementing its privacy preserving version in HE. Our solution for cancer type inference encodes somatic mutations based on their impact on the cancer genomes into the feature space and then uses statistical tests for feature selection. We propose a fast matrix multiplication algorithm for HE-based model. Our final model achieves 0.98 micro-average area under curve improving accuracy from 70.08 to 83.61% , being 550 times faster than the standard matrix multiplication-based privacy-preserving models. Our tool can be found at https://github.com/momalab/octal-candet .
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Affiliation(s)
- Esha Sarkar
- Tandon School of Engineering, New York University, Brooklyn, NY, 11201, USA.
| | - Eduardo Chielle
- Center for Cyber Security, New York University Abu Dhabi, Abu Dhabi, 129188, UAE
| | - Gamze Gursoy
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Leo Chen
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Michail Maniatakos
- Center for Cyber Security, New York University Abu Dhabi, Abu Dhabi, 129188, UAE
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27
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Landau J, Tsaban L, Yaacov A, Ben Cohen G, Rosenberg S. Shared Cancer Dataset Analysis Identifies and Predicts the Quantitative Effects of Pan-Cancer Somatic Driver Variants. Cancer Res 2023; 83:74-88. [PMID: 36264175 DOI: 10.1158/0008-5472.can-22-1038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 08/02/2022] [Accepted: 10/18/2022] [Indexed: 02/03/2023]
Abstract
Driver mutations endow tumors with selective advantages and produce an array of pathogenic effects. Determining the function of somatic variants is important for understanding cancer biology and identifying optimal therapies. Here, we compiled a shared dataset from several cancer genomic databases. Two measures were applied to 535 cancer genes based on observed and expected frequencies of driver variants as derived from cancer-specific rates of somatic mutagenesis. The first measure comprised a binary classifier based on a binomial test; the second was tumor variant amplitude (TVA), a continuous measure representing the selective advantage of individual variants. TVA outperformed all other computational tools in terms of its correlation with experimentally derived functional scores of cancer mutations. TVA also highly correlated with drug response, overall survival, and other clinical implications in relevant cancer genes. This study demonstrates how a selective advantage measure based on a large cancer dataset significantly impacts our understanding of the spectral effect of driver variants in cancer. The impact of this information will increase as cancer treatment becomes more precise and personalized to tumor-specific mutations. SIGNIFICANCE A new selective advantage estimation assists in oncogenic driver identification and relative effect measurements, enabling better prognostication, therapy selection, and prioritization.
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Affiliation(s)
- Jakob Landau
- Gaffin Center for Neuro-Oncology, Sharett Institute for Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.,The Wohl Institute for Translational Medicine, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Linoy Tsaban
- Gaffin Center for Neuro-Oncology, Sharett Institute for Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.,The Wohl Institute for Translational Medicine, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Adar Yaacov
- Gaffin Center for Neuro-Oncology, Sharett Institute for Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.,The Wohl Institute for Translational Medicine, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.,Department of Microbiology and Molecular Genetics, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Gil Ben Cohen
- Gaffin Center for Neuro-Oncology, Sharett Institute for Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.,The Wohl Institute for Translational Medicine, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Shai Rosenberg
- Gaffin Center for Neuro-Oncology, Sharett Institute for Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.,The Wohl Institute for Translational Medicine, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
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28
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Shen M, Kang Y. Cancer fitness genes: emerging therapeutic targets for metastasis. Trends Cancer 2023; 9:69-82. [PMID: 36184492 DOI: 10.1016/j.trecan.2022.08.007] [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: 07/07/2022] [Revised: 08/25/2022] [Accepted: 08/30/2022] [Indexed: 12/31/2022]
Abstract
Development of cancer therapeutics has traditionally focused on targeting driver oncogenes. Such an approach is limited by toxicity to normal tissues and treatment resistance. A class of 'cancer fitness genes' with crucial roles in metastasis have been identified. Elevated or altered activities of these genes do not directly cause cancer; instead, they relieve the stresses that tumor cells encounter and help them adapt to a changing microenvironment, thus facilitating tumor progression and metastasis. Importantly, as normal cells do not experience high levels of stress under physiological conditions, targeting cancer fitness genes is less likely to cause toxicity to noncancerous tissues. Here, we summarize the key features and function of cancer fitness genes and discuss their therapeutic potential.
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Affiliation(s)
- Minhong Shen
- Department of Pharmacology, Wayne State University School of Medicine, Michigan, MI, USA; Department of Oncology, Wayne State University School of Medicine and Tumor Biology and Microenvironment Research Program, Barbara Ann Karmanos Cancer Institute, Michigan, MI, USA.
| | - Yibin Kang
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA; Ludwig Institute for Cancer Research Princeton Branch, Princeton, NJ, USA.
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29
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Freischel AR, Teer JK, Luddy K, Cunningham J, Artzy-Randrup Y, Epstein T, Tsai KY, Berglund A, Cleveland JL, Gillies RJ, Brown JS, Gatenby RA. Evolutionary Analysis of TCGA Data Using Over- and Under- Mutated Genes Identify Key Molecular Pathways and Cellular Functions in Lung Cancer Subtypes. Cancers (Basel) 2022; 15:18. [PMID: 36612014 PMCID: PMC9817988 DOI: 10.3390/cancers15010018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 11/30/2022] [Accepted: 12/08/2022] [Indexed: 12/24/2022] Open
Abstract
We identify critical conserved and mutated genes through a theoretical model linking a gene’s fitness contribution to its observed mutational frequency in a clinical cohort. “Passenger” gene mutations do not alter fitness and have mutational frequencies determined by gene size and the mutation rate. Driver mutations, which increase fitness (and proliferation), are observed more frequently than expected. Non-synonymous mutations in essential genes reduce fitness and are eliminated by natural selection resulting in lower prevalence than expected. We apply this “evolutionary triage” principle to TCGA data from EGFR-mutant, KRAS-mutant, and NEK (non-EGFR/KRAS) lung adenocarcinomas. We find frequent overlap of evolutionarily selected non-synonymous gene mutations among the subtypes suggesting enrichment for adaptations to common local tissue selection forces. Overlap of conserved genes in the LUAD subtypes is rare suggesting negative evolutionary selection is strongly dependent on initiating mutational events during carcinogenesis. Highly expressed genes are more likely to be conserved and significant changes in expression (>20% increased/decreased) are common in genes with evolutionarily selected mutations but not in conserved genes. EGFR-mut cancers have fewer average mutations (89) than KRAS-mut (228) and NEK (313). Subtype-specific variation in conserved and mutated genes identify critical molecular components in cell signaling, extracellular matrix remodeling, and membrane transporters. These findings demonstrate subtype-specific patterns of co-adaptations between the defining driver mutation and somatically conserved genes as well as novel insights into epigenetic versus genetic contributions to cancer evolution.
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Affiliation(s)
- Audrey R. Freischel
- Departments of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
- Cancer Biology and Evolution Program, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
| | - Jamie K. Teer
- Cancer Biology and Evolution Program, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
- Departments of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
| | - Kimberly Luddy
- Departments of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Jessica Cunningham
- Departments of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
| | - Yael Artzy-Randrup
- Departments of Cancer Physiology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
| | - Tamir Epstein
- Departments of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
| | - Kenneth Y. Tsai
- Departments of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
- Departments of Cancer Physiology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
| | - Anders Berglund
- Departments of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - John L. Cleveland
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Robert J. Gillies
- Departments of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
- Departments of Pathology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
- Department of Diagnostic Imaging & Interventional Radiology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
| | - Joel S. Brown
- Departments of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
- Cancer Biology and Evolution Program, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
| | - Robert A. Gatenby
- Departments of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
- Cancer Biology and Evolution Program, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
- Department of Diagnostic Imaging & Interventional Radiology, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA
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30
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Castro-Mondragon JA, Aure M, Lingjærde O, Langerød A, Martens JWM, Børresen-Dale AL, Kristensen V, Mathelier A. Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of gene regulatory programs in cancers. Nucleic Acids Res 2022; 50:12131-12148. [PMID: 36477895 PMCID: PMC9757053 DOI: 10.1093/nar/gkac1143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 11/03/2022] [Accepted: 11/17/2022] [Indexed: 12/13/2022] Open
Abstract
Most cancer alterations occur in the noncoding portion of the human genome, where regulatory regions control gene expression. The discovery of noncoding mutations altering the cells' regulatory programs has been limited to few examples with high recurrence or high functional impact. Here, we show that transcription factor binding sites (TFBSs) have similar mutation loads to those in protein-coding exons. By combining cancer somatic mutations in TFBSs and expression data for protein-coding and miRNA genes, we evaluate the combined effects of transcriptional and post-transcriptional alterations on the regulatory programs in cancers. The analysis of seven TCGA cohorts culminates with the identification of protein-coding and miRNA genes linked to mutations at TFBSs that are associated with a cascading trans-effect deregulation on the cells' regulatory programs. Our analyses of cis-regulatory mutations associated with miRNAs recurrently predict 12 mature miRNAs (derived from 7 precursors) associated with the deregulation of their target gene networks. The predictions are enriched for cancer-associated protein-coding and miRNA genes and highlight cis-regulatory mutations associated with the dysregulation of key pathways associated with carcinogenesis. By combining transcriptional and post-transcriptional regulation of gene expression, our method predicts cis-regulatory mutations related to the dysregulation of key gene regulatory networks in cancer patients.
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Affiliation(s)
- Jaime A Castro-Mondragon
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Miriam Ragle Aure
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway,Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Ole Christian Lingjærde
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway,Centre for Bioinformatics, Department of Informatics, University of Oslo, Gaustadalléen 23 B, N-0373 Oslo, Norway,KG Jebsen Centre for B-cell malignancies, Institute for Clinical Medicine, University of Oslo, Ullernchausseen 70, N-0372 Oslo, Norway
| | - Anita Langerød
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway
| | - John W M Martens
- Erasmus MC Cancer Institute and Cancer Genomics Netherlands, University Medical Center Rotterdam, Department of Medical Oncology, 3015GD Rotterdam, The Netherlands
| | - Anne-Lise Børresen-Dale
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway
| | - Vessela N Kristensen
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway,Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway
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31
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Langille E, Al-Zahrani KN, Ma Z, Liang M, Uuskula-Reimand L, Espin R, Teng K, Malik A, Bergholtz H, El Ghamrasni S, Afiuni-Zadeh S, Tsai R, Alvi S, Elia A, Lü Y, Oh RH, Kozma KJ, Trcka D, Narimatsu M, Liu JC, Nguyen T, Barutcu S, Loganathan SK, Bremner R, Bader GD, Egan SE, Cescon DW, Sørlie T, Wrana JL, Jackson HW, Wilson MD, Witkiewicz AK, Knudsen ES, Pujana MA, Wahl GM, Schramek D. Loss of Epigenetic Regulation Disrupts Lineage Integrity, Induces Aberrant Alveogenesis, and Promotes Breast Cancer. Cancer Discov 2022; 12:2930-2953. [PMID: 36108220 PMCID: PMC9812400 DOI: 10.1158/2159-8290.cd-21-0865] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/15/2022] [Accepted: 09/13/2022] [Indexed: 01/21/2023]
Abstract
Systematically investigating the scores of genes mutated in cancer and discerning disease drivers from inconsequential bystanders is a prerequisite for precision medicine but remains challenging. Here, we developed a somatic CRISPR/Cas9 mutagenesis screen to study 215 recurrent "long-tail" breast cancer genes, which revealed epigenetic regulation as a major tumor-suppressive mechanism. We report that components of the BAP1 and COMPASS-like complexes, including KMT2C/D, KDM6A, BAP1, and ASXL1/2 ("EpiDrivers"), cooperate with PIK3CAH1047R to transform mouse and human breast epithelial cells. Mechanistically, we find that activation of PIK3CAH1047R and concomitant EpiDriver loss triggered an alveolar-like lineage conversion of basal mammary epithelial cells and accelerated formation of luminal-like tumors, suggesting a basal origin for luminal tumors. EpiDriver mutations are found in ∼39% of human breast cancers, and ∼50% of ductal carcinoma in situ express casein, suggesting that lineage infidelity and alveogenic mimicry may significantly contribute to early steps of breast cancer etiology. SIGNIFICANCE Infrequently mutated genes comprise most of the mutational burden in breast tumors but are poorly understood. In vivo CRISPR screening identified functional tumor suppressors that converged on epigenetic regulation. Loss of epigenetic regulators accelerated tumorigenesis and revealed lineage infidelity and aberrant expression of alveogenesis genes as potential early events in tumorigenesis. This article is highlighted in the In This Issue feature, p. 2711.
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Affiliation(s)
- Ellen Langille
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Khalid N. Al-Zahrani
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Zhibo Ma
- Gene Expression Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Minggao Liang
- Hospital for Sick Children, Toronto, Ontario, M5G 0A4, Canada
| | | | - Roderic Espin
- Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L’Hospitalet del Llobregat, Barcelona, Spain
| | - Katie Teng
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Ahmad Malik
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Helga Bergholtz
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, 0450 Oslo, Norway
| | - Samah El Ghamrasni
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Somaieh Afiuni-Zadeh
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Ricky Tsai
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Sana Alvi
- Hospital for Sick Children, Toronto, Ontario, M5G 0A4, Canada
| | - Andrew Elia
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - YiQing Lü
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Robin H. Oh
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Katelyn J. Kozma
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Hospital for Sick Children, Toronto, Ontario, M5G 0A4, Canada
| | - Daniel Trcka
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Masahiro Narimatsu
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Jeff C. Liu
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Thomas Nguyen
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Seda Barutcu
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Sampath K. Loganathan
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Rod Bremner
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Gary D. Bader
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Sean E. Egan
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Hospital for Sick Children, Toronto, Ontario, M5G 0A4, Canada
| | - David W. Cescon
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Therese Sørlie
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, 0450 Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, 0315 Oslo, Norway
| | - Jeffrey L. Wrana
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Hartland W. Jackson
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Michael D. Wilson
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Hospital for Sick Children, Toronto, Ontario, M5G 0A4, Canada
| | | | - Erik S. Knudsen
- Center for Personalized Medicine, Roswell Park Cancer Institute, Buffalo, New York
| | - Miguel Angel Pujana
- Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L’Hospitalet del Llobregat, Barcelona, Spain
| | - Geoffrey M. Wahl
- Gene Expression Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Daniel Schramek
- Centre for Molecular and Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
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Liu S, Wei W, Wang P, Liu C, Jiang X, Li T, Li F, Wu Y, Chen S, Sun K, Xu R. LOF variants identifying candidate genes of laterality defects patients with congenital heart disease. PLoS Genet 2022; 18:e1010530. [PMID: 36459505 DOI: 10.1371/journal.pgen.1010530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 12/14/2022] [Accepted: 11/15/2022] [Indexed: 12/03/2022] Open
Abstract
Defects in laterality pattern can result in abnormal positioning of the internal organs during the early stages of embryogenesis, as manifested in heterotaxy syndrome and situs inversus, while laterality defects account for 3~7% of all congenital heart defects (CHDs). However, the pathogenic mechanism underlying most laterality defects remains unknown. In this study, we recruited 70 laterality defect patients with CHDs to identify candidate disease genes by exome sequencing. We then evaluated rare, loss-of-function (LOF) variants, identifying candidates by referring to previous literature. We chose TRIP11, DNHD1, CFAP74, and EGR4 as candidates from 776 LOF variants that met the initial screening criteria. After the variants-to-gene mapping, we performed function research on these candidate genes. The expression patterns and functions of these four candidate genes were studied by whole-mount in situ hybridization, gene knockdown, and gene rescue methods in zebrafish models. Among the four genes, trip11, dnhd1, and cfap74 morphant zebrafish displayed abnormalities in both cardiac looping and expression patterns of early signaling molecules, suggesting that these genes play important roles in the establishment of laterality patterns. Furthermore, we performed immunostaining and high-speed cilia video microscopy to investigate Kupffer's vesicle organogenesis and ciliogenesis of morphant zebrafish. Impairments of Kupffer's vesicle organogenesis or ciliogenesis were found in trip11, dnhd1, and cfap74 morphant zebrafish, which revealed the possible pathogenic mechanism of their LOF variants in laterality defects. These results highlight the importance of rare, LOF variants in identifying disease-related genes and identifying new roles for TRIP11, DNHD1, and CFAP74 in left-right patterning. Additionally, these findings are consistent with the complex genetics of laterality defects.
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Affiliation(s)
- Sijie Liu
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Wei
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Pengcheng Wang
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chunjie Liu
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Xuechao Jiang
- Scientific Research Center, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Tingting Li
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Fen Li
- Department of Cardiology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yurong Wu
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Sun Chen
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Kun Sun
- Department of Pediatric Cardiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Rang Xu
- Scientific Research Center, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
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PANAGOPOULOS IOANNIS, HEIM SVERRE. Neoplasia-associated Chromosome Translocations Resulting in Gene Truncation. Cancer Genomics Proteomics 2022; 19:647-672. [PMID: 36316036 PMCID: PMC9620447 DOI: 10.21873/cgp.20349] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 08/19/2022] [Accepted: 08/23/2022] [Indexed: 11/27/2022] Open
Abstract
Chromosomal translocations in cancer as well as benign neoplasias typically lead to the formation of fusion genes. Such genes may encode chimeric proteins when two protein-coding regions fuse in-frame, or they may result in deregulation of genes via promoter swapping or translocation of the gene into the vicinity of a highly active regulatory element. A less studied consequence of chromosomal translocations is the fusion of two breakpoint genes resulting in an out-of-frame chimera. The breaks then occur in one or both protein-coding regions forming a stop codon in the chimeric transcript shortly after the fusion point. Though the latter genetic events and mechanisms at first awoke little research interest, careful investigations have established them as neither rare nor inconsequential. In the present work, we review and discuss the truncation of genes in neoplastic cells resulting from chromosomal rearrangements, especially from seemingly balanced translocations.
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Affiliation(s)
- IOANNIS PANAGOPOULOS
- Section for Cancer Cytogenetics, Institute for Cancer Genetics and Informatics, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway
| | - SVERRE HEIM
- Section for Cancer Cytogenetics, Institute for Cancer Genetics and Informatics, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
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Barriga FM, Tsanov KM, Ho YJ, Sohail N, Zhang A, Baslan T, Wuest AN, Del Priore I, Meškauskaitė B, Livshits G, Alonso-Curbelo D, Simon J, Chaves-Perez A, Bar-Sagi D, Iacobuzio-Donahue CA, Notta F, Chaligne R, Sharma R, Pe'er D, Lowe SW. MACHETE identifies interferon-encompassing chromosome 9p21.3 deletions as mediators of immune evasion and metastasis. NATURE CANCER 2022; 3:1367-1385. [PMID: 36344707 PMCID: PMC9701143 DOI: 10.1038/s43018-022-00443-5] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 09/13/2022] [Indexed: 11/09/2022]
Abstract
The most prominent homozygous deletions in cancer affect chromosome 9p21.3 and eliminate CDKN2A/B tumor suppressors, disabling a cell-intrinsic barrier to tumorigenesis. Half of 9p21.3 deletions, however, also encompass a type I interferon (IFN) gene cluster; the consequences of this co-deletion remain unexplored. To functionally dissect 9p21.3 and other large genomic deletions, we developed a flexible deletion engineering strategy, MACHETE (molecular alteration of chromosomes with engineered tandem elements). Applying MACHETE to a syngeneic mouse model of pancreatic cancer, we found that co-deletion of the IFN cluster promoted immune evasion, metastasis and immunotherapy resistance. Mechanistically, IFN co-deletion disrupted type I IFN signaling in the tumor microenvironment, leading to marked changes in infiltrating immune cells and escape from CD8+ T-cell surveillance, effects largely driven by the poorly understood interferon epsilon. These results reveal a chromosomal deletion that disables both cell-intrinsic and cell-extrinsic tumor suppression and provide a framework for interrogating large deletions in cancer and beyond.
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Affiliation(s)
- Francisco M Barriga
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Kaloyan M Tsanov
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yu-Jui Ho
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Noor Sohail
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Amy Zhang
- PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Timour Baslan
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Alexandra N Wuest
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Isabella Del Priore
- Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, New York, NY, USA
| | - Brigita Meškauskaitė
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Geulah Livshits
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Direna Alonso-Curbelo
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Janelle Simon
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Almudena Chaves-Perez
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Dafna Bar-Sagi
- Department of Biochemistry, New York University School of Medicine, New York, NY, USA
| | - Christine A Iacobuzio-Donahue
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Faiyaz Notta
- PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Division of Research, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Ronan Chaligne
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Roshan Sharma
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Dana Pe'er
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Scott W Lowe
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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35
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Shah AA, Alturise F, Alkhalifah T, Khan YD. Deep Learning Approaches for Detection of Breast Adenocarcinoma Causing Carcinogenic Mutations. Int J Mol Sci 2022; 23:ijms231911539. [PMID: 36232840 PMCID: PMC9570286 DOI: 10.3390/ijms231911539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/19/2022] [Accepted: 09/23/2022] [Indexed: 11/16/2022] Open
Abstract
Genes are composed of DNA and each gene has a specific sequence. Recombination or replication within the gene base ends in a permanent change in the nucleotide collection in a DNA called mutation and some mutations can lead to cancer. Breast adenocarcinoma starts in secretary cells. Breast adenocarcinoma is the most common of all cancers that occur in women. According to a survey within the United States of America, there are more than 282,000 breast adenocarcinoma patients registered each 12 months, and most of them are women. Recognition of cancer in its early stages saves many lives. A proposed framework is developed for the early detection of breast adenocarcinoma using an ensemble learning technique with multiple deep learning algorithms, specifically: Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), and Bi-directional LSTM. There are 99 types of driver genes involved in breast adenocarcinoma. This study uses a dataset of 4127 samples including men and women taken from more than 12 cohorts of cancer detection institutes. The dataset encompasses a total of 6170 mutations that occur in 99 genes. On these gene sequences, different algorithms are applied for feature extraction. Three types of testing techniques including independent set testing, self-consistency testing, and a 10-fold cross-validation test is applied to validate and test the learning approaches. Subsequently, multiple deep learning approaches such as LSTM, GRU, and bi-directional LSTM algorithms are applied. Several evaluation metrics are enumerated for the validation of results including accuracy, sensitivity, specificity, Mathew’s correlation coefficient, area under the curve, training loss, precision, recall, F1 score, and Cohen’s kappa while the values obtained are 99.57, 99.50, 99.63, 0.99, 1.0, 0.2027, 99.57, 99.57, 99.57, and 99.14 respectively.
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Affiliation(s)
- Asghar Ali Shah
- Department of Computer Science, University of Management and Technology, Lahore 54770, Pakistan
| | - Fahad Alturise
- Department of Computer, College of Science and Arts in Ar Rass, Qassim University, Ar Rass 58892, Qassim, Saudi Arabia
| | - Tamim Alkhalifah
- Department of Computer, College of Science and Arts in Ar Rass, Qassim University, Ar Rass 58892, Qassim, Saudi Arabia
- Correspondence:
| | - Yaser Daanial Khan
- Department of Computer Science, University of Management and Technology, Lahore 54770, Pakistan
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Ocsenas O, Reimand J. Chromatin accessibility of primary human cancers ties regional mutational processes and signatures with tissues of origin. PLoS Comput Biol 2022; 18:e1010393. [PMID: 35947558 PMCID: PMC9365152 DOI: 10.1371/journal.pcbi.1010393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 07/15/2022] [Indexed: 11/19/2022] Open
Abstract
Somatic mutations in cancer genomes are associated with DNA replication timing (RT) and chromatin accessibility (CA), however these observations are based on normal tissues and cell lines while primary cancer epigenomes remain uncharacterised. Here we use machine learning to model megabase-scale mutation burden in 2,500 whole cancer genomes and 17 cancer types via a compendium of 900 CA and RT profiles covering primary cancers, normal tissues, and cell lines. CA profiles of primary cancers, rather than those of normal tissues, are most predictive of regional mutagenesis in most cancer types. Feature prioritisation shows that the epigenomes of matching cancer types and organ systems are often the strongest predictors of regional mutation burden, highlighting disease-specific associations of mutational processes. The genomic distributions of mutational signatures are also shaped by the epigenomes of matched cancer and tissue types, with SBS5/40, carcinogenic and unknown signatures most accurately predicted by our models. In contrast, fewer associations of RT and regional mutagenesis are found. Lastly, the models highlight genomic regions with overrepresented mutations that dramatically exceed epigenome-derived expectations and show a pan-cancer convergence to genes and pathways involved in development and oncogenesis, indicating the potential of this approach for coding and non-coding driver discovery. The association of regional mutational processes with the epigenomes of primary cancers suggests that the landscape of passenger mutations is predominantly shaped by the epigenomes of cancer cells after oncogenic transformation.
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Affiliation(s)
- Oliver Ocsenas
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Jüri Reimand
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Canada
- * E-mail:
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Valcz G, Újvári B, Buzás EI, Krenács T, Spisák S, Kittel Á, Tulassay Z, Igaz P, Takács I, Molnár B. Small extracellular vesicle DNA-mediated horizontal gene transfer as a driving force for tumor evolution: Facts and riddles. Front Oncol 2022; 12:945376. [PMID: 36003770 PMCID: PMC9393732 DOI: 10.3389/fonc.2022.945376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 07/06/2022] [Indexed: 11/13/2022] Open
Abstract
The basis of the conventional gene-centric view on tumor evolution is that vertically inherited mutations largely define the properties of tumor cells. In recent years, however, accumulating evidence shows that both the tumor cells and their microenvironment may acquire external, non-vertically inherited genetic properties via horizontal gene transfer (HGT), particularly through small extracellular vesicles (sEVs). Many phases of sEV-mediated HGT have been described, such as DNA packaging into small vesicles, their release, uptake by recipient cells, and incorporation of sEV-DNA into the recipient genome to modify the phenotype and properties of cells. Recent techniques in sEV separation, genome sequencing and editing, as well as the identification of new secretion mechanisms, shed light on a number of additional details of this phenomenon. Here, we discuss the key features of this form of gene transfer and make an attempt to draw relevant conclusions on the contribution of HGT to tumor evolution.
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Affiliation(s)
- Gábor Valcz
- MTA-SE Molecular Medicine Research Group, Eötvös Loránd Research Network, Budapest, Hungary
- *Correspondence: Gábor Valcz,
| | - Beáta Újvári
- School of Life and Environmental Sciences, Centre for Integrative Ecology, Deakin University, Waurn Ponds, VIC, Australia
| | - Edit I. Buzás
- Department of Genetics, Cell- and Immunobiology, Semmelweis University, Budapest, Hungary
- ELKH-SE Immune-Proteogenomics Extracellular Vesicle Research Group, Semmelweis University, Budapest, Hungary
- HCEMM-SU Extracellular Vesicle Research Group, Semmelweis University, Budapest, Hungary
| | - Tibor Krenács
- 1st Department of Pathology and Experimental Cancer Research, Semmelweis University, Budapest, Hungary
| | - Sándor Spisák
- Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Ágnes Kittel
- Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, Hungary
| | - Zsolt Tulassay
- MTA-SE Molecular Medicine Research Group, Eötvös Loránd Research Network, Budapest, Hungary
| | - Péter Igaz
- MTA-SE Molecular Medicine Research Group, Eötvös Loránd Research Network, Budapest, Hungary
- Department of Internal Medicine and Oncology, Semmelweis University, Budapest, Hungary
- Department of Endocrinology, Semmelweis University, Budapest, Hungary
| | - István Takács
- Department of Internal Medicine and Oncology, Semmelweis University, Budapest, Hungary
| | - Béla Molnár
- MTA-SE Molecular Medicine Research Group, Eötvös Loránd Research Network, Budapest, Hungary
- Department of Internal Medicine and Oncology, Semmelweis University, Budapest, Hungary
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Ran X, Xiao J, Cheng F, Wang T, Teng H, Sun Z. Pan-cancer analyses of synonymous mutations based on tissue-specific codon optimality. Comput Struct Biotechnol J 2022; 20:3567-3580. [PMID: 35860410 PMCID: PMC9287186 DOI: 10.1016/j.csbj.2022.07.005] [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: 03/10/2022] [Revised: 06/22/2022] [Accepted: 07/03/2022] [Indexed: 11/24/2022] Open
Abstract
Developed tissue-specific codon optimality in 29 human tissues. Applied these to analyze synonymous mutations in ∼10,000 tumor and normal samples. Synonymous mutations frequently increase optimal codons in most cancer types. Synonymous mutations frequently increase optimal codons cell cycle-related genes. Frequency of optimal codon gain relates to proliferation, DDR deficiency, and survival.
Codon optimality has been demonstrated to be an important determinant of mRNA stability and expression levels in multiple model organisms and human cell lines. However, tissue-specific codon optimality has not been developed to investigate how codon optimality is usually perturbed by somatic synonymous mutations in human cancers. Here, we determined tissue-specific codon optimality in 29 human tissues based on mRNA expression data from the Genotype-Tissue Expression project. We found that optimal codons were associated with differentiation, whereas non-optimal codons were correlated with proliferation. Furthermore, codons biased toward differentiation displayed greater tissue specificity in codon optimality, and the tissue specificity of codon optimality was primarily present in amino acids with high degeneracy of the genetic code. By applying tissue-specific codon optimality to somatic synonymous mutations in 8532 tumor samples across 24 cancer types and to those in 416 normal cells across six human tissues, we found that synonymous mutations frequently increased optimal codons in tumor cells and cancer-related genes (e.g., genes involved in cell cycle). Furthermore, an elevated frequency of optimal codon gain was found to promote tumor cell proliferation in three cancer types characterized by DNA damage repair deficiency and could act as a prognostic biomarker for patients with triple-negative breast cancer. In summary, this study profiled tissue-specific codon optimality in human tissues, revealed alterations in codon optimality caused by synonymous mutations in human cancers, and highlighted the non-negligible role of optimal codon gain in tumorigenesis and therapeutics.
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Affiliation(s)
- Xia Ran
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China.,CAS Center for Excellence in Biotic Interactions, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinyuan Xiao
- Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou 325000, China
| | - Fang Cheng
- Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou 325000, China
| | - Tao Wang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Kaifu District, Changsha, Hunan 410078, China
| | - Huajing Teng
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Zhongsheng Sun
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China.,CAS Center for Excellence in Biotic Interactions, University of Chinese Academy of Sciences, Beijing 100049, China.,Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou 325000, China
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Khalighi S, Joseph P, Babu D, Singh S, LaFramboise T, Guda K, Varadan V. SYSMut: decoding the functional significance of rare somatic mutations in cancer. Brief Bioinform 2022; 23:bbac280. [PMID: 35804437 PMCID: PMC9618165 DOI: 10.1093/bib/bbac280] [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: 12/09/2021] [Revised: 06/14/2022] [Accepted: 06/16/2022] [Indexed: 11/13/2022] Open
Abstract
Current tailored-therapy efforts in cancer are largely focused on a small number of highly recurrently mutated driver genes but therapeutic targeting of these oncogenes remains challenging. However, the vast number of genes mutated infrequently across cancers has received less attention, in part, due to a lack of understanding of their biological significance. We present SYSMut, an extendable systems biology platform that can robustly infer the biologic consequences of somatic mutations by integrating routine multiomics profiles in primary tumors. We establish SYSMut's improved performance vis-à-vis state-of-the-art driver gene identification methodologies by recapitulating the functional impact of known driver genes, while additionally identifying novel functionally impactful mutated genes across 29 cancers. Subsequent application of SYSMut on low-frequency gene mutations in head and neck squamous cell (HNSC) cancers, followed by molecular and pharmacogenetic validation, revealed the lipidogenic network as a novel therapeutic vulnerability in aggressive HNSC cancers. SYSMut is thus a robust scalable framework that enables the discovery of new targetable avenues in cancer.
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Affiliation(s)
- Sirvan Khalighi
- Division of General Medical Sciences-Oncology, Case Comprehensive Cancer Center
- Department of Genetics and genome Sciences
| | - Peronne Joseph
- Division of General Medical Sciences-Oncology, Case Comprehensive Cancer Center
| | - Deepak Babu
- Division of General Medical Sciences-Oncology, Case Comprehensive Cancer Center
| | - Salendra Singh
- Division of General Medical Sciences-Oncology, Case Comprehensive Cancer Center
| | | | - Kishore Guda
- Division of General Medical Sciences-Oncology, Case Comprehensive Cancer Center
- Digestive Health Research Institute
- Department of Pathology, Case Western Reserve University School of Medicine, Cleveland, OH-44106 U.S.A
| | - Vinay Varadan
- Division of General Medical Sciences-Oncology, Case Comprehensive Cancer Center
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40
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Pan-Cancer Analysis for Immune Cell Infiltration and Mutational Signatures Using Non-Negative Canonical Correlation Analysis. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12136596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Mutational signatures indicate the mutational processes and substitution patterns in cancer cell genomes. However, the functional consequences of mutational signatures remain unclear, and there have been no comprehensive systematic studies to examine the relationships between the mutational signatures and the immune cell infiltration. Here, the relationship between mutational signatures and immune cell infiltration using non-negative canonical correlation analysis based on 8927 patients across 25 tumor types was investigated. By inspecting mutational signatures with the maximal coefficients determined by the non-negative canonical correlation analysis, the study identified mutational signatures related to immune cell infiltration composed of tumor microenvironments. The analysis was validated by showing that the genes associated with the identified mutational signatures were linked to overall survival by a Kaplan–Meier curve and a log-rank test and were mainly related to immunity by gene set enrichment analysis. These results will help expand our knowledge of tumor biology and recognize the functional roles and associations of immune systems with mutational signatures.
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41
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Zeng Z, Bromberg Y. Inferring Potential Cancer Driving Synonymous Variants. Genes (Basel) 2022; 13:778. [PMID: 35627162 PMCID: PMC9140830 DOI: 10.3390/genes13050778] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 04/25/2022] [Accepted: 04/26/2022] [Indexed: 02/01/2023] Open
Abstract
Synonymous single nucleotide variants (sSNVs) are often considered functionally silent, but a few cases of cancer-causing sSNVs have been reported. From available databases, we collected four categories of sSNVs: germline, somatic in normal tissues, somatic in cancerous tissues, and putative cancer drivers. We found that screening sSNVs for recurrence among patients, conservation of the affected genomic position, and synVep prediction (synVep is a machine learning-based sSNV effect predictor) recovers cancer driver variants (termed proposed drivers) and previously unknown putative cancer genes. Of the 2.9 million somatic sSNVs found in the COSMIC database, we identified 2111 proposed cancer driver sSNVs. Of these, 326 sSNVs could be further tagged for possible RNA splicing effects, RNA structural changes, and affected RBP motifs. This list of proposed cancer driver sSNVs provides computational guidance in prioritizing the experimental evaluation of synonymous mutations found in cancers. Furthermore, our list of novel potential cancer genes, galvanized by synonymous mutations, may highlight yet unexplored cancer mechanisms.
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Affiliation(s)
- Zishuo Zeng
- Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ 08873, USA
| | - Yana Bromberg
- Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ 08873, USA
- Department of Genetics, Rutgers University, Piscataway, NJ 08854, USA
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42
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Jia Q, Wang A, Yuan Y, Zhu B, Long H. Heterogeneity of the tumor immune microenvironment and its clinical relevance. Exp Hematol Oncol 2022; 11:24. [PMID: 35461288 PMCID: PMC9034473 DOI: 10.1186/s40164-022-00277-y] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 04/10/2022] [Indexed: 02/08/2023] Open
Abstract
During the course of tumorigenesis and subsequent metastasis, malignant cells gradually diversify and become more heterogeneous. Consequently, the tumor mass might be infiltrated by diverse immune-related components, including the cytokine/chemokine environment, cytotoxic activity, or immunosuppressive elements. This immunological heterogeneity is universally presented spatially or varies temporally along with tumor evolution or therapeutic intervention across almost all solid tumors. The heterogeneity of anti-tumor immunity shows a profound association with the progression of disease and responsiveness to treatment, particularly in the realm of immunotherapy. Therefore, an accurate understanding of tumor immunological heterogeneity is essential for the development of effective therapies. Facilitated by multi-regional and -omics sequencing, single cell sequencing, and longitudinal liquid biopsy approaches, recent studies have demonstrated the potential to investigate the complexity of immunological heterogeneity of the tumors and its clinical relevance in immunotherapy. Here, we aimed to review the mechanism underlying the heterogeneity of the immune microenvironment. We also explored how clinical assessments of tumor heterogeneity might facilitate the development of more effective personalized therapies.
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Affiliation(s)
- Qingzhu Jia
- Institute of Cancer, Xinqiao Hospital, Army Military Medical University, Xinqiao Main Street, Chongqing, 400037, China.,Chongqing Key Laboratory of Immunotherapy, Xinqiao Hospital, Army Medical University, Chongqing, 400037, China
| | - Aoyun Wang
- Institute of Cancer, Xinqiao Hospital, Army Military Medical University, Xinqiao Main Street, Chongqing, 400037, China.,Chongqing Key Laboratory of Immunotherapy, Xinqiao Hospital, Army Medical University, Chongqing, 400037, China
| | - Yixiao Yuan
- Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China
| | - Bo Zhu
- Institute of Cancer, Xinqiao Hospital, Army Military Medical University, Xinqiao Main Street, Chongqing, 400037, China. .,Chongqing Key Laboratory of Immunotherapy, Xinqiao Hospital, Army Medical University, Chongqing, 400037, China.
| | - Haixia Long
- Institute of Cancer, Xinqiao Hospital, Army Military Medical University, Xinqiao Main Street, Chongqing, 400037, China. .,Chongqing Key Laboratory of Immunotherapy, Xinqiao Hospital, Army Medical University, Chongqing, 400037, China.
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43
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Bowers RR, Jones CM, Paz EA, Barrows JK, Armeson K, Long D, Delaney J. SWAN pathway-network identification of common aneuploidy-based oncogenic drivers. Nucleic Acids Res 2022; 50:3673-3692. [PMID: 35380699 PMCID: PMC9023287 DOI: 10.1093/nar/gkac200] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 02/26/2022] [Accepted: 03/14/2022] [Indexed: 02/07/2023] Open
Abstract
Haploinsufficiency drives Darwinian evolution. Siblings, while alike in many aspects, differ due to monoallelic differences inherited from each parent. In cancer, solid tumors exhibit aneuploid genetics resulting in hundreds to thousands of monoallelic gene-level copy-number alterations (CNAs) in each tumor. Aneuploidy patterns are heterogeneous, posing a challenge to identify drivers in this high-noise genetic environment. Here, we developed Shifted Weighted Annotation Network (SWAN) analysis to assess biology impacted by cumulative monoallelic changes. SWAN enables an integrated pathway-network analysis of CNAs, RNA expression, and mutations via a simple web platform. SWAN is optimized to best prioritize known and novel tumor suppressors and oncogenes, thereby identifying drivers and potential druggable vulnerabilities within cancer CNAs. Protein homeostasis, phospholipid dephosphorylation, and ion transport pathways are commonly suppressed. An atlas of CNA pathways altered in each cancer type is released. These CNA network shifts highlight new, attractive targets to exploit in solid tumors.
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Affiliation(s)
- Robert R Bowers
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA
| | - Christian M Jones
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA
| | - Edwin A Paz
- Departments of Neurology, Neurobiology, and Cell Biology, and the Duke Center for Neurodegeneration & Neurotherapeutics, Duke University School of Medicine, Durham, NC, USA
| | - John K Barrows
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA
| | - Kent E Armeson
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - David T Long
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA
| | - Joe R Delaney
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA
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44
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Liu J, Li Y, Shi R. The 2010-2020 National Natural Science Foundation of China: Radiation Therapy. Curr Med Sci 2022; 42:453-461. [PMID: 35089494 DOI: 10.1007/s11596-022-2531-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 11/07/2021] [Indexed: 12/14/2022]
Abstract
OBJECTIVE This study explains the application number and funding rate of oncology projects undertaken by the National Natural Science Foundation of China (NSFC), with focus on tumor radiotherapy-related research over the past 11 years. METHODS A stratified analysis was carried out on the application and funding status of tumor radiotherapy studies in different NSFC project categories, different research areas, and different tumor types. Research areas that required specific focus, such as immunology-related radiotherapy, multimodality imaging and radiomics, and post-radiotherapy organ injury, were separately analyzed. RESULTS The status and development trends of various related research fields were studied, and the research results were presented with the support of the NSFC, in order to provide reference for future applications and funding allocations. CONCLUSION The number of applications for funding increases every year. Although the total number of funded projects has also increased every year, the funding rate has decreased year by year. Projects on radiotherapy and immunization have been at the forefront in recent years, and the funding rate for these projects increases yearly.
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Affiliation(s)
- Jun Liu
- Division VII, Department of Health Sciences, National Natural Science Foundation of China, Beijing, 100085, China.,Department of Thoracic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430062, China
| | - Yang Li
- Division VII, Department of Health Sciences, National Natural Science Foundation of China, Beijing, 100085, China.,Department of Genetics, School of Life Science, Anhui Medical University, Hefei, 230031, China
| | - Rong Shi
- Division VII, Department of Health Sciences, National Natural Science Foundation of China, Beijing, 100085, China.
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45
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Zhao LF, Qi FY, Zhang JG, Pang JR, Ren HM, Shen DD, Zhao LJ, Qi L, Liu HM, Zheng YC. Identification of the upstream regulators of KDM5B in gastric cancer. Life Sci 2022; 298:120458. [DOI: 10.1016/j.lfs.2022.120458] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 02/19/2022] [Accepted: 03/01/2022] [Indexed: 02/03/2023]
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46
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Jiang C, Schaafsma E, Hong W, Zhao Y, Zhu K, Chao CC, Cheng C. Influence of T Cell-Mediated Immune Surveillance on Somatic Mutation Occurrences in Melanoma. Front Immunol 2022; 12:703821. [PMID: 35111147 PMCID: PMC8801458 DOI: 10.3389/fimmu.2021.703821] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 12/16/2021] [Indexed: 01/09/2023] Open
Abstract
Background Neoantigens are presented on the cancer cell surface by peptide-restricted human leukocyte antigen (HLA) proteins and can subsequently activate cognate T cells. It has been hypothesized that the observed somatic mutations in tumors are shaped by immunosurveillance. Methods We investigated all somatic mutations identified in The Cancer Genome Atlas (TCGA) Skin Cutaneous Melanoma (SKCM) samples. By applying a computational algorithm, we calculated the binding affinity of the resulting neo-peptides and their corresponding wild-type peptides with the major histocompatibility complex (MHC) Class I complex. We then examined the relationship between binding affinity alterations and mutation frequency. Results Our results show that neoantigens derived from recurrent mutations tend to have lower binding affinities with the MHC Class I complex compared to peptides from non-recurrent mutations. Tumor samples harboring recurrent SKCM mutations exhibited lower immune infiltration levels, indicating a relatively colder immune microenvironment. Conclusions These results suggested that the occurrences of somatic mutations in melanoma have been shaped by immunosurveillance. Mutations that lead to neoantigens with high MHC class I binding affinity are more likely to be eliminated and thus are less likely to be present in tumors.
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Affiliation(s)
- Chongming Jiang
- Department of Medicine, Baylor College of Medicine, Houston, TX, United States
| | - Evelien Schaafsma
- Department of Molecular and Systems Biology, Dartmouth College, Hanover, NH, United States
| | - Wei Hong
- Department of Medicine, Baylor College of Medicine, Houston, TX, United States
| | - Yanding Zhao
- Department of Medicine, Baylor College of Medicine, Houston, TX, United States
| | - Ken Zhu
- Medical School, UT Southwestern Medical Center, Dallas, TX, United States
| | - Cheng-Chi Chao
- Antibody Discovery, Chempartner Corporation, South San Francisco, CA, United States
| | - Chao Cheng
- Department of Medicine, Baylor College of Medicine, Houston, TX, United States
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, United States
- Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
- The Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, United States
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47
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Lebedeva A, Shaykhutdinova Y, Seriak D, Ignatova E, Rozhavskaya E, Vardhan D, Manicka S, Sharova M, Grigoreva T, Baranova A, Mileyko V, Ivanov M. Incidental germline findings during molecular profiling of tumor tissues for precision oncology: molecular survey and methodological obstacles. J Transl Med 2022; 20:29. [PMID: 35033101 PMCID: PMC8760669 DOI: 10.1186/s12967-022-03230-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 01/05/2022] [Indexed: 12/13/2022] Open
Abstract
Background A fraction of patients referred for complex molecular profiling of biopsied tumors may harbor germline variants in genes associated with the development of hereditary cancer syndromes (HCS). Neither the bioinformatic analysis nor the reporting of such incidental germline findings are standardized. Methods Data from Next-Generation Sequencing (NGS) of biopsied tumor samples referred for complex molecular profiling were analyzed for germline variants in HCS-associated genes. Analysis of variant origin was performed employing bioinformatic algorithms followed by manual curation. When possible, the origin of the variant was validated by Sanger sequencing of the sample of normal tissue. The variants’ pathogenicity was assessed according to ACMG/AMP. Results Tumors were sampled from 183 patients (Males: 75 [41.0%]; Females: 108 [59.0%]; mean [SD] age, 57.7 [13.3] years) and analysed by targeted NGS. The most common tumor types were colorectal (19%), pancreatic (13%), and lung cancer (10%). A total of 56 sequence variants in genes associated with HCS were detected in 40 patients. Of them, 17 variants found in 14 patients were predicted to be of germline origin, with 6 variants interpreted as pathogenic (PV) or likely pathogenic (LPV), and 9 as variants of uncertain significance (VUS). For the 41 out of 42 (97%) missense variants in HCS-associated genes, the results of computational prediction of variant origin were concordant with that of experimental examination. We estimate that Sanger sequencing of a sample of normal tissue would be required for ~ 1–7% of the total assessed cases with PV or LPV, when necessity to follow with genetic counselling referral in ~ 2–15% of total assessed cases (PV, LPV or VUS found in HCS genes). Conclusion Incidental findings of pathogenic germline variants are common in data from cancer patients referred for complex molecular profiling. We propose an algorithm for the management of patients with newly detected variants in genes associated with HCS.
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Affiliation(s)
- Alexandra Lebedeva
- Atlas Oncodiagnostics, LLC, Moscow, Russia. .,Sechenov University, Moscow, Russia.
| | | | | | - Ekaterina Ignatova
- Atlas Oncodiagnostics, LLC, Moscow, Russia.,Department of chemotherapy №2, Federal State Budgetary Institution «N.N. Blokhin National Medical Research Center of Oncology» of the Ministry of Health of the Russian Federation, Moscow, Russia.,Department of Oncogenetics, Institute of Higher and Additional Professional Education, Research Centre for Medical Genetics, Moscow, Russia
| | | | | | - Sofia Manicka
- School of Systems Biology, George Mason University, Mannas, VA, USA
| | | | | | - Ancha Baranova
- School of Systems Biology, George Mason University, Mannas, VA, USA
| | | | - Maxim Ivanov
- Atlas Oncodiagnostics, LLC, Moscow, Russia.,Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia
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48
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Jacquemin V, Antoine M, Dom G, Detours V, Maenhaut C, Dumont JE. Dynamic Cancer Cell Heterogeneity: Diagnostic and Therapeutic Implications. Cancers (Basel) 2022; 14:280. [PMID: 35053446 PMCID: PMC8773841 DOI: 10.3390/cancers14020280] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 01/04/2022] [Accepted: 01/05/2022] [Indexed: 12/12/2022] Open
Abstract
Though heterogeneity of cancers is recognized and has been much discussed in recent years, the concept often remains overlooked in different routine examinations. Indeed, in clinical or biological articles, reviews, and textbooks, cancers and cancer cells are generally presented as evolving distinct entities rather than as an independent heterogeneous cooperative cell population with its self-oriented biology. There are, therefore, conceptual gaps which can mislead the interpretations/diagnostic and therapeutic approaches. In this short review, we wish to summarize and discuss various aspects of this dynamic evolving heterogeneity and its biological, pathological, clinical, diagnostic, and therapeutic implications, using thyroid carcinoma as an illustrative example.
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Affiliation(s)
- Valerie Jacquemin
- Correspondence: (V.J.); (J.E.D.); Tel.: +32-2-555-32-26 (V.J.); +32-2-555-41-34 (J.E.D.)
| | | | | | | | | | - Jacques E. Dumont
- Institut de Recherche Interdisciplinaire en Biologie Humaine et Moléculaire (IRIBHM), Université Libre de Bruxelles, 1070 Brussels, Belgium; (M.A.); (G.D.); (V.D.); (C.M.)
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49
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Liu S, Medina-Perez P, Ha-Thi MC, Wieland A, Stecklum M, Hoffmann J, Tchernitsa O, Sers C, Schäfer R. Rapid testing of candidate oncogenes and tumour suppressor genes in signal transduction and neoplastic transformation. Adv Biol Regul 2021; 83:100841. [PMID: 34866037 DOI: 10.1016/j.jbior.2021.100841] [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: 11/05/2021] [Revised: 11/17/2021] [Accepted: 11/20/2021] [Indexed: 11/18/2022]
Abstract
The COSMIC database (version 94) lists 576 genes in the Cancer Gene Census which have a defined function as drivers of malignancy (oncogenes) or as tumour suppressors (Tier 1). In addition, there are 147 genes with similar functions, but which are less well characterised (Tier 2). Furthermore, next-generation sequencing projects in the context of precision oncology activities are constantly discovering new ones. Since cancer genes differ from their wild-type precursors in numerous molecular and biochemical properties and exert significant differential effects on downstream processes, simple assays that can uncover oncogenic or anti-oncogenic functionality are desirable and may precede more sophisticated analyses. We describe simple functional assays for PTPN11 (protein-tyrosine phosphatase, non-receptor-type 11)/SHP2 mutants, which are typically found in RASopathies and exhibit potential oncogenic activity. We have also designed a functional test for lysyl oxidase (LOX), a prototypical class II tumour suppressor gene whose loss of function may contribute to neoplastic transformation by RAS oncogenes. Moreover, we applied this test to analyse three co-regulated, RAS-responsive genes for transformation-suppressive activity. The integration of these tests into systems biology studies will contribute to a better understanding of cellular networks in cancer.
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Affiliation(s)
- Sha Liu
- Laboratory of Molecular Tumour Pathology and Cancer Systems Biology, Institute of Pathology, Charité Universitätsmedizin Berlin, Charitéplatz 1, D-10117, Berlin, Germany
| | - Paula Medina-Perez
- Laboratory of Molecular Tumour Pathology and Cancer Systems Biology, Institute of Pathology, Charité Universitätsmedizin Berlin, Charitéplatz 1, D-10117, Berlin, Germany
| | - Minh-Cam Ha-Thi
- Laboratory of Molecular Tumour Pathology and Cancer Systems Biology, Institute of Pathology, Charité Universitätsmedizin Berlin, Charitéplatz 1, D-10117, Berlin, Germany
| | - Anja Wieland
- Laboratory of Molecular Tumour Pathology and Cancer Systems Biology, Institute of Pathology, Charité Universitätsmedizin Berlin, Charitéplatz 1, D-10117, Berlin, Germany
| | - Maria Stecklum
- Experimental Pharmacology and Oncology GmbH, Robert-Rössle-Str. 10, D-13125, Berlin-Buch, Germany
| | - Jens Hoffmann
- Experimental Pharmacology and Oncology GmbH, Robert-Rössle-Str. 10, D-13125, Berlin-Buch, Germany
| | - Oleg Tchernitsa
- Laboratory of Molecular Tumour Pathology and Cancer Systems Biology, Institute of Pathology, Charité Universitätsmedizin Berlin, Charitéplatz 1, D-10117, Berlin, Germany
| | - Christine Sers
- Laboratory of Molecular Tumour Pathology and Cancer Systems Biology, Institute of Pathology, Charité Universitätsmedizin Berlin, Charitéplatz 1, D-10117, Berlin, Germany; German Cancer Consortium (DKTK), German Cancer Research Center, Im Neuenheimer Feld 280, D-69120, Heidelberg, Germany
| | - Reinhold Schäfer
- Laboratory of Molecular Tumour Pathology and Cancer Systems Biology, Institute of Pathology, Charité Universitätsmedizin Berlin, Charitéplatz 1, D-10117, Berlin, Germany; German Cancer Consortium (DKTK), German Cancer Research Center, Im Neuenheimer Feld 280, D-69120, Heidelberg, Germany; Charité Comprehensive Cancer Center Berlin, Germany.
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50
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Zhang Y, Chen F, Pleasance E, Williamson L, Grisdale CJ, Titmuss E, Laskin J, Jones SJM, Cortes-Ciriano I, Marra MA, Creighton CJ. Rearrangement-mediated cis-regulatory alterations in advanced patient tumors reveal interactions with therapy. Cell Rep 2021; 37:110023. [PMID: 34788622 PMCID: PMC8630779 DOI: 10.1016/j.celrep.2021.110023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 09/10/2021] [Accepted: 10/27/2021] [Indexed: 11/03/2022] Open
Abstract
The global impact of somatic structural variants (SVs) on gene regulation in advanced tumors with complex treatment histories has been mostly uncharacterized. Here, using whole-genome and RNA sequencing from 570 recurrent or metastatic tumors, we report the altered expression of hundreds of genes in association with nearby SV breakpoints, including oncogenes and G-protein-coupled receptor-related genes such as PLEKHG2. A significant fraction of genes with SV-expression associations correlate with worse patient survival in primary and advanced cancers, including SRD5A1. In many instances, SV-expression associations involve retrotransposons being translocated near genes. High overall SV burden is associated with treatment with DNA alkylating agents or taxanes and altered expression of metabolism-associated genes. SV-expression associations within tumors from topoisomerase I inhibitor-treated patients include chromatin-related genes. Within anthracycline-treated tumors, SV breakpoints near chromosome 1p genes include PDE4B. Patient treatment and history can help understand the widespread SV-mediated cis-regulatory alterations found in cancer.
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Affiliation(s)
- Yiqun Zhang
- Division of Biostatistics, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Fengju Chen
- Division of Biostatistics, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Erin Pleasance
- Canada's Michael Smith Genome Sciences Centre at BC Cancer, Vancouver, British Columbia, Canada
| | - Laura Williamson
- Canada's Michael Smith Genome Sciences Centre at BC Cancer, Vancouver, British Columbia, Canada
| | - Cameron J Grisdale
- Canada's Michael Smith Genome Sciences Centre at BC Cancer, Vancouver, British Columbia, Canada
| | - Emma Titmuss
- Canada's Michael Smith Genome Sciences Centre at BC Cancer, Vancouver, British Columbia, Canada
| | - Janessa Laskin
- Department of Medical Oncology, BC Cancer, Vancouver, British Columbia, Canada
| | - Steven J M Jones
- Canada's Michael Smith Genome Sciences Centre at BC Cancer, Vancouver, British Columbia, Canada; Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada; Department of Molecular Biology and Biochemistry, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Isidro Cortes-Ciriano
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK
| | - Marco A Marra
- Canada's Michael Smith Genome Sciences Centre at BC Cancer, Vancouver, British Columbia, Canada; Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Chad J Creighton
- Division of Biostatistics, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA; Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
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