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1
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Zhang Y, Li D. An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy. Sci Rep 2024; 14:8135. [PMID: 38584220 PMCID: PMC10999435 DOI: 10.1038/s41598-024-58020-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 03/25/2024] [Indexed: 04/09/2024] Open
Abstract
Aneuploidy is a hallmark of cancers, but the role of aneuploidy-related genes in lung adenocarcinoma (LUAD) and their prognostic value remain elusive. Gene expression and copy number variation (CNV) data were enrolled from TCGA and GEO database. Consistency clustering analysis was performed for molecular cluster. Tumor microenvironment was assessed by the xCell and ESTIMATE algorithm. Limma package was used for selecting differentially expressed genes (DEGs). LASSO and stepwise multivariate Cox regression analysis were used to establish an aneuploidy-related riskscore (ARS) signature. GDSC database was conducted to predict drug sensitivity. A nomogram was designed by rms R package. TCGA-LUAD patients were stratified into 3 clusters based on CNV data. The C1 cluster displayed the optimal survival advantage and highest inflammatory infiltration. Based on integrated intersecting DEGs, we constructed a 6-gene ARS model, which showed effective prediction for patient's survival. Drug sensitivity test predicted possible sensitive drugs in two risk groups. Additionally, the nomogram exhibited great predictive clinical treatment benefits. We established a 6-gene aneuploidy-related signature that could effectively predict the survival and therapy for LUAD patients. Additionally, the ARS model and nomogram could offer guidance for the preoperative estimation and postoperative therapy of LUAD.
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Affiliation(s)
- Yalei Zhang
- Department of Thoracic Oncology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510032, China.
| | - Dongmei Li
- Department of Thoracic Oncology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510032, China
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2
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Piergentili R, Marinelli E, Cucinella G, Lopez A, Napoletano G, Gullo G, Zaami S. miR-125 in Breast Cancer Etiopathogenesis: An Emerging Role as a Biomarker in Differential Diagnosis, Regenerative Medicine, and the Challenges of Personalized Medicine. Noncoding RNA 2024; 10:16. [PMID: 38525735 PMCID: PMC10961778 DOI: 10.3390/ncrna10020016] [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: 12/15/2023] [Revised: 02/10/2024] [Accepted: 02/19/2024] [Indexed: 03/26/2024] Open
Abstract
Breast Cancer (BC) is one of the most common cancer types worldwide, and it is characterized by a complex etiopathogenesis, resulting in an equally complex classification of subtypes. MicroRNA (miRNA or miR) are small non-coding RNA molecules that have an essential role in gene expression and are significantly linked to tumor development and angiogenesis in different types of cancer. Recently, complex interactions among coding and non-coding RNA have been elucidated, further shedding light on the complexity of the roles these molecules fulfill in cancer formation. In this context, knowledge about the role of miR in BC has significantly improved, highlighting the deregulation of these molecules as additional factors influencing BC occurrence, development and classification. A considerable number of papers has been published over the past few years regarding the role of miR-125 in human pathology in general and in several types of cancer formation in particular. Interestingly, miR-125 family members have been recently linked to BC formation as well, and complex interactions (competing endogenous RNA networks, or ceRNET) between this molecule and target mRNA have been described. In this review, we summarize the state-of-the-art about research on this topic.
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Affiliation(s)
- Roberto Piergentili
- Institute of Molecular Biology and Pathology, Italian National Research Council (CNR-IBPM), 00185 Rome, Italy;
| | - Enrico Marinelli
- Department of Medico-Surgical Sciences and Biotechnologies, “Sapienza” University of Rome, 04100 Latina, Italy;
| | - Gaspare Cucinella
- Department of Obstetrics and Gynecology, Villa Sofia Cervello Hospital, University of Palermo, 90146 Palermo, Italy; (G.C.); (A.L.); (G.G.)
| | - Alessandra Lopez
- Department of Obstetrics and Gynecology, Villa Sofia Cervello Hospital, University of Palermo, 90146 Palermo, Italy; (G.C.); (A.L.); (G.G.)
| | - Gabriele Napoletano
- Department of Anatomical, Histological, Forensic and Orthopedic Sciences, Section of Forensic Medicine, “Sapienza” University of Rome, 00161 Rome, Italy;
| | - Giuseppe Gullo
- Department of Obstetrics and Gynecology, Villa Sofia Cervello Hospital, University of Palermo, 90146 Palermo, Italy; (G.C.); (A.L.); (G.G.)
| | - Simona Zaami
- Department of Anatomical, Histological, Forensic and Orthopedic Sciences, Section of Forensic Medicine, “Sapienza” University of Rome, 00161 Rome, Italy;
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3
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Risinskaya N, Gladysheva M, Abdulpatakhov A, Chabaeva Y, Surimova V, Aleshina O, Yushkova A, Dubova O, Kapranov N, Galtseva I, Kulikov S, Obukhova T, Sudarikov A, Parovichnikova E. DNA Copy Number Alterations and Copy Neutral Loss of Heterozygosity in Adult Ph-Negative Acute B-Lymphoblastic Leukemia: Focus on the Genes Involved. Int J Mol Sci 2023; 24:17602. [PMID: 38139431 PMCID: PMC10744257 DOI: 10.3390/ijms242417602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 12/08/2023] [Accepted: 12/14/2023] [Indexed: 12/24/2023] Open
Abstract
The landscape of chromosomal aberrations in the tumor cells of the patients with B-ALL is diverse and can influence the outcome of the disease. Molecular karyotyping at the onset of the disease using chromosomal microarray (CMA) is advisable to identify additional molecular factors associated with the prognosis of the disease. Molecular karyotyping data for 36 patients with Ph-negative B-ALL who received therapy according to the ALL-2016 protocol are presented. We analyzed copy number alterations and their prognostic significance for CDKN2A/B, DMRTA, DOCK8, TP53, SMARCA2, PAX5, XPA, FOXE1, HEMGN, USP45, RUNX1, NF1, IGF2BP1, ERG, TMPRSS2, CRLF2, FGFR3, FLNB, IKZF1, RUNX2, ARID1B, CIP2A, PIK3CA, ATM, RB1, BIRC3, MYC, IKZF3, ETV6, ZNF384, PTPRJ, CCL20, PAX3, MTCH2, TCF3, IKZF2, BTG1, BTG2, RAG1, RAG2, ELK3, SH2B3, EP300, MAP2K2, EBI3, MEF2D, MEF2C, CEBPA, and TBLXR1 genes, choosing t(4;11) and t(7;14) as reference events. Of the 36 patients, only 5 (13.8%) had a normal molecular karyotype, and 31 (86.2%) were found to have various molecular karyotype abnormalities-104 deletions, 90 duplications or amplifications, 29 cases of cnLOH and 7 biallelic/homozygous deletions. We found that 11q22-23 duplication involving the BIRC3, ATM and MLL genes was the most adverse prognostic event in the study cohort.
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Affiliation(s)
- Natalya Risinskaya
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Maria Gladysheva
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Abdulpatakh Abdulpatakhov
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Yulia Chabaeva
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Valeriya Surimova
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Olga Aleshina
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Anna Yushkova
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Olga Dubova
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
- Institute of Biodesign and Modeling of Complex Systems, I.M. Sechenov First Moscow State Medical University, 119991 Moscow, Russia
| | - Nikolay Kapranov
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Irina Galtseva
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Sergey Kulikov
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Tatiana Obukhova
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Andrey Sudarikov
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
| | - Elena Parovichnikova
- National Medical Research Center for Hematology, 125167 Moscow, Russia; (M.G.); (A.A.); (Y.C.); (V.S.); (O.A.); (A.Y.); (O.D.); (N.K.); (I.G.); (S.K.); (A.S.); (E.P.)
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4
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Poonia S, Goel A, Chawla S, Bhattacharya N, Rai P, Lee YF, Yap YS, West J, Bhagat AA, Tayal J, Mehta A, Ahuja G, Majumdar A, Ramalingam N, Sengupta D. Marker-free characterization of full-length transcriptomes of single live circulating tumor cells. Genome Res 2023; 33:80-95. [PMID: 36414416 PMCID: PMC9977151 DOI: 10.1101/gr.276600.122] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 11/10/2022] [Indexed: 11/23/2022]
Abstract
The identification and characterization of circulating tumor cells (CTCs) are important for gaining insights into the biology of metastatic cancers, monitoring disease progression, and medical management of the disease. The limiting factor in the enrichment of purified CTC populations is their sparse availability, heterogeneity, and altered phenotypes relative to the primary tumor. Intensive research both at the technical and molecular fronts led to the development of assays that ease CTC detection and identification from peripheral blood. Most CTC detection methods based on single-cell RNA sequencing (scRNA-seq) use a mix of size selection, marker-based white blood cell (WBC) depletion, and antibodies targeting tumor-associated antigens. However, the majority of these methods either miss out on atypical CTCs or suffer from WBC contamination. We present unCTC, an R package for unbiased identification and characterization of CTCs from single-cell transcriptomic data. unCTC features many standard and novel computational and statistical modules for various analyses. These include a novel method of scRNA-seq clustering, named deep dictionary learning using k-means clustering cost (DDLK), expression-based copy number variation (CNV) inference, and combinatorial, marker-based verification of the malignant phenotypes. DDLK enables robust segregation of CTCs and WBCs in the pathway space, as opposed to the gene expression space. We validated the utility of unCTC on scRNA-seq profiles of breast CTCs from six patients, captured and profiled using an integrated ClearCell FX and Polaris workflow that works by the principles of size-based separation of CTCs and marker-based WBC depletion.
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Affiliation(s)
- Sarita Poonia
- Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India
| | - Anurag Goel
- Department of Computer Science and Engineering, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India;,Department of Computer Science and Engineering, Delhi Technological University, New Delhi 110042, India
| | - Smriti Chawla
- Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India
| | - Namrata Bhattacharya
- Department of Computer Science and Engineering, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India
| | - Priyadarshini Rai
- Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India
| | - Yi Fang Lee
- Biolidics Limited, Singapore 118257, Singapore
| | - Yoon Sim Yap
- National Cancer Centre Singapore, Singapore 169610, Singapore
| | - Jay West
- Fluidigm Corporation, South San Francisco, California 94080, USA
| | | | - Juhi Tayal
- Department of Research, Rajiv Gandhi Cancer Institute and Research Centre-Delhi (RGCIRC-Delhi), New Delhi 110085, India
| | - Anurag Mehta
- Department of Laboratory Services and Molecular Diagnostics, Rajiv Gandhi Cancer Institute and Research Centre-Delhi (RGCIRC-Delhi), New Delhi 110085, India
| | - Gaurav Ahuja
- Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India
| | - Angshul Majumdar
- Department of Computer Science and Engineering, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India;,Centre for Artificial Intelligence, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India;,Department of Electronics & Communications Engineering, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India
| | | | - Debarka Sengupta
- Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India;,Department of Computer Science and Engineering, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India;,Centre for Artificial Intelligence, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi 110020, India
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5
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Matsubara D, Yoshimoto T, Akolekar N, Totsuka T, Amano Y, Kihara A, Miura T, Isagawa Y, Sakuma Y, Ishikawa S, Ushiku T, Fukayama M, Niki T. Genetic and phenotypic determinants of morphologies in 3D cultures and xenografts of lung tumor cell lines. Cancer Sci 2022; 114:1757-1770. [PMID: 36533957 PMCID: PMC10067422 DOI: 10.1111/cas.15702] [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: 07/28/2022] [Revised: 12/01/2022] [Accepted: 12/11/2022] [Indexed: 12/23/2022] Open
Abstract
We previously proposed the classification of lung adenocarcinoma into two groups: the bronchial epithelial phenotype (BE phenotype) with high-level expressions of bronchial epithelial markers and actionable genetic abnormalities of tyrosine kinase receptors and the non-BE phenotype with low-level expressions of bronchial Bronchial epithelial (BE) epithelial markers and no actionable genetic abnormalities of tyrosine kinase receptors. Here, we performed a comprehensive analysis of tumor morphologies in 3D cultures and xenografts across a panel of lung cancer cell lines. First, we demonstrated that 40 lung cancer cell lines (23 BE and 17 non-BE) can be classified into three groups based on morphologies in 3D cultures on Matrigel: round (n = 31), stellate (n = 5), and grape-like (n = 4). The latter two morphologies were significantly frequent in the non-BE phenotype (1/23 BE, 8/17 non-BE, p = 0.0014), and the stellate morphology was only found in the non-BE phenotype. SMARCA4 mutations were significantly frequent in stellate-shaped cells (4/4 stellate, 4/34 non-stellate, p = 0.0001). Next, from the 40 cell lines, we successfully established 28 xenograft tumors (18 BE and 10 non-BE) in NOD/SCID mice and classified histological patterns of the xenograft tumors into three groups: solid (n = 20), small nests in desmoplasia (n = 4), and acinar/papillary (n = 4). The latter two patterns were characteristically found in the BE phenotype. The non-BE phenotype exhibited a solid pattern with significantly less content of alpha-SMA-positive fibroblasts (p = 0.0004) and collagen (p = 0.0006) than the BE phenotype. Thus, the morphology of the tumors in 3D cultures and xenografts, including stroma genesis, reflects the intrinsic properties of the cancer cell lines. Furthermore, this study serves as an excellent resource for lung adenocarcinoma cell lines, with clinically relevant information on molecular and morphological characteristics and drug sensitivity.
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Affiliation(s)
- Daisuke Matsubara
- Department of Integrative Pathology, Jichi Medical University, Tochigi, Japan.,Department of Pathology, University of Tsukuba, Ibaraki, Japan
| | - Taichiro Yoshimoto
- Department of Integrative Pathology, Jichi Medical University, Tochigi, Japan
| | | | | | - Yusuke Amano
- Department of Integrative Pathology, Jichi Medical University, Tochigi, Japan
| | - Atsushi Kihara
- Department of Integrative Pathology, Jichi Medical University, Tochigi, Japan
| | - Tamaki Miura
- Department of Integrative Pathology, Jichi Medical University, Tochigi, Japan
| | - Yuriko Isagawa
- Department of Integrative Pathology, Jichi Medical University, Tochigi, Japan
| | - Yuji Sakuma
- Department of Integrative Pathology, Jichi Medical University, Tochigi, Japan
| | - Shumpei Ishikawa
- Department of Preventive Medicine, University of Tokyo, Tokyo, Japan
| | - Tetsuo Ushiku
- Human Pathology Department, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Masashi Fukayama
- Human Pathology Department, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Toshiro Niki
- Department of Integrative Pathology, Jichi Medical University, Tochigi, Japan
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6
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Zhao H, Zhang S, Yin X, Zhang C, Wang L, Liu K, Xu H, Liu W, Bo L, Lin S, Feng K, Lin L, Fei M, Ning S, Wang L. Identifying enhancer-driven subtype-specific prognostic markers in breast cancer based on multi-omics data. Front Immunol 2022; 13:990143. [PMID: 36304471 PMCID: PMC9592759 DOI: 10.3389/fimmu.2022.990143] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 09/27/2022] [Indexed: 11/22/2022] Open
Abstract
Breast cancer is a cancer of high complexity and heterogeneity, with differences in prognosis and survival among patients of different subtypes. Copy number variations (CNVs) within enhancers are crucial drivers of tumorigenesis by influencing expression of their targets. In this study, we performed an integrative approach to identify CNA-driven enhancers and their effect on expression of target genes in four breast cancer subtypes by integrating expression data, copy number data and H3K27ac data. We identified 672, 555, 531, 361 CNA-driven enhancer-gene pairs and 280, 189, 113 and 98 CNA-driven enhancer-lncRNA pairs in the Basal-like, Her2, LumA and LumB subtypes, respectively. We then reconstructed a CNV-driven enhancer-lncRNA-mRNA regulatory network in each subtype. Functional analysis showed CNA-driven enhancers play an important role in the progression of breast cancer subtypes by influencing P53 signaling pathway, PPAR signaling pathway, systemic lupus erythematosus and MAPK signaling pathway in the Basal-like, Her2, LumA and LumB subtypes, respectively. We characterized the potentially prognostic value of target genes of CNV-driven enhancer and lncRNA-mRNA pairs in the subtype-specific network. We identified MUM1 and AC016876.1 as prognostic biomarkers in LumA and Basal-like subtypes, respectively. Higher expression of MUM1 with an amplified enhancer exhibited poorer prognosis in LumA patients. Lower expression of AC016876.1 with a deleted enhancer exhibited poorer survival outcomes of Basal-like patients. We also identified enhancer-related lncRNA-mRNA pairs as prognostic biomarkers, including AC012313.2-MUM1 in the LumA, AC026471.4-PLK5 in the LumB, AC027307.2-OAZ1 in the Basal-like and AC022431.1-HCN2 in the Her2 subtypes. Finally, our results highlighted target genes of CNA-driven enhancers and enhancer-related lncRNA-mRNA pairs could act as prognostic markers and potential therapeutic targets in breast cancer subtypes.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Li Wang
- *Correspondence: Li Wang, ; Shangwei Ning,
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