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Shen F, Li F, Ma Y, Song X, Guo W. Identification of Novel Stemness-based Subtypes and Construction of a Prognostic Risk Model for Patients with Lung Squamous Cell Carcinoma. Curr Stem Cell Res Ther 2024; 19:400-416. [PMID: 37455452 DOI: 10.2174/1574888x18666230714142835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 06/26/2023] [Accepted: 07/05/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND Although cancer stem cells (CSCs) contribute to tumorigenesis, progression, and drug resistance, stemness-based classification and prognostic signatures of lung squamous cell carcinoma (LUSC) remain unclarified. This study attempted to identify stemness-based subtypes and develop a prognostic risk model for LUSC. METHODS Based on RNA-seq data from The Cancer Genome Atlas (TCGA), Gene-Expression Omnibus (GEO) and Progenitor Cell Biology Consortium (PCBC), mRNA expression-based stemness index (mRNAsi) was calculated by one-class logistic regression (OCLR) algorithm. A weighted gene coexpression network (WGCNA) was employed to identify stemness subtypes. Differences in mutation, clinical characteristics, immune cell infiltration, and antitumor therapy responses were determined. We constructed a prognostic risk model, followed by validations in GEO cohort, pan-cancer and immunotherapy datasets. RESULTS LUSC patients with subtype C2 had a better prognosis, manifested by higher mRNAsi, higher tumor protein 53 (TP53) and Titin (TTN) mutation frequencies, lower immune scores and decreased immune checkpoints. Patients with subtype C2 were more sensitive to Imatinib, Pyrimethamine, and Paclitaxel therapy, whereas those with subtype C1 were more sensitive to Sunitinib, Saracatinib, and Dasatinib. Moreover, we constructed stemness-based signatures using seven genes (BMI1, CCDC51, CTNS, EIF1AX, FAM43A, THBD, and TRIM68) and found high-risk patients had a poorer prognosis in the TCGA cohort. Similar results were found in the GEO cohort. We verified the good performance of risk scores in prognosis prediction and therapy responses. CONCLUSION The stemness-based subtypes shed novel insights into the potential roles of LUSC-stemness in tumor heterogeneity, and our prognostic signatures offer a promising tool for prognosis prediction and guide therapeutic decisions in LUSC.
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Affiliation(s)
- Fangfang Shen
- Department of Respiratory Medicine, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030082, China
| | - Feng Li
- Department of thoracic surgery, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030082, China
| | - Yong Ma
- Department of thoracic surgery, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030082, China
| | - Xia Song
- Department of Respiratory Medicine, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030082, China
| | - Wei Guo
- Department of Respiratory Medicine, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030082, China
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Ravindran F, Jain A, Desai S, Menon N, Srivastava K, Bawa PS, Sateesh K, Srivatsa N, Raghunath SK, Srinivasan S, Choudhary B. Whole-exome sequencing of Indian prostate cancer reveals a novel therapeutic target: POLQ. J Cancer Res Clin Oncol 2023; 149:2451-2462. [PMID: 35737091 DOI: 10.1007/s00432-022-04111-0] [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: 04/21/2022] [Accepted: 06/03/2022] [Indexed: 11/25/2022]
Abstract
PURPOSE Prostate cancer is the second most common cancer diagnosed worldwide and the third most common cancer among men in India. This study's objective was to characterise the mutational landscape of Indian prostate cancer using whole-exome sequencing to identify population-specific polymorphisms. METHODS Whole-exome sequencing was performed of 58 treatment-naive primary prostate tumors of Indian origin. Multiple computational and statistical analyses were used to profile the known common mutations, other deleterious mutations, driver genes, prognostic biomarkers, and gene signatures unique to each clinical parameter. Cox analysis was performed to validate survival-associated genes. McNemar test identified genes significant to recurrence and receiver-operating characteristic (ROC) analysis was conducted to determine its accuracy. OncodriveCLUSTL algorithm was used to deduce driver genes. The druggable target identified was modeled with its known inhibitor using Autodock. RESULTS TP53 was the most commonly mutated gene in our cohort. Three novel deleterious variants unique to the Indian prostate cancer subtype were identified: POLQ, FTHL17, and OR8G1. COX regression analysis identified ACSM5, a mitochondrial gene responsible for survival. CYLC1 gene, which encodes for sperm head cytoskeletal protein, was identified as an unfavorable prognostic biomarker indicative of recurrence. The novel POLQ mutant, also identified as a driver gene, was evaluated as the druggable target in this study. POLQ, a DNA repair enzyme implicated in various cancer types, is overexpressed and is associated with a poor prognosis. The mutant POLQ was subjected to structural analysis and modeled with its known inhibitor novobiocin resulting in decreased binding efficiency necessitating the development of a better drug. CONCLUSION In this pilot study, the molecular profiling using multiple computational and statistical analyses revealed distinct polymorphisms in the Indian prostate cancer cohort. The mutational signatures identified provide a valuable resource for prognostic stratification and targeted treatment strategies for Indian prostate cancer patients. The DNA repair enzyme, POLQ, was identified as the druggable target in this study.
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Affiliation(s)
- Febina Ravindran
- Institute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India
| | - Anika Jain
- Institute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India
| | - Sagar Desai
- Institute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India
- Manipal Academy of Higher Education, Manipal, India
| | - Navjoth Menon
- Institute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India
| | - Kriti Srivastava
- Institute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India
| | - Pushpinder Singh Bawa
- Institute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India
| | - K Sateesh
- Healthcare Global Enterprises Ltd, Cancer Centre, Bangalore, India
| | - N Srivatsa
- Healthcare Global Enterprises Ltd, Cancer Centre, Bangalore, India
| | - S K Raghunath
- Healthcare Global Enterprises Ltd, Cancer Centre, Bangalore, India
| | - Subhashini Srinivasan
- Institute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India
| | - Bibha Choudhary
- Institute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India.
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Shukla N, Kour B, Sharma D, Vijayvargiya M, Sadasukhi TC, Medicherla KM, Malik B, Bissa B, Vuree S, Lohiya NK, Suravajhala P. Towards Understanding the Key Signature Pathways Associated from Differentially Expressed Gene Analysis in an Indian Prostate Cancer Cohort. Diseases 2023; 11:diseases11020072. [PMID: 37218885 DOI: 10.3390/diseases11020072] [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: 02/20/2023] [Revised: 04/13/2023] [Accepted: 04/18/2023] [Indexed: 05/24/2023] Open
Abstract
Prostate cancer (PCa) is one of the most prevalent cancers among men in India. Although studies on PCa have dealt with genetics, genomics, and the environmental influence in the causality of PCa, not many studies employing the Next Generation Sequencing (NGS) approaches of PCa have been carried out. In our previous study, we identified some causal genes and mutations specific to Indian PCa using Whole Exome Sequencing (WES). In the recent past, with the help of different cancer consortiums such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC), along with differentially expressed genes (DEGs), many cancer-associated novel non-coding RNAs have been identified as biomarkers. In this work, we attempt to identify differentially expressed genes (DEGs) including long non-coding RNAs (lncRNAs) associated with signature pathways from an Indian PCa cohort using the RNA-sequencing (RNA-seq) approach. From a cohort of 60, we screened six patients who underwent prostatectomy; we performed whole transcriptome shotgun sequencing (WTSS)/RNA-sequencing to decipher the DEGs. We further normalized the read counts using fragments per kilobase of transcript per million mapped reads (FPKM) and analyzed the DEGs using a cohort of downstream regulatory tools, viz., GeneMANIA, Stringdb, Cytoscape-Cytohubba, and cbioportal, to map the inherent signatures associated with PCa. By comparing the RNA-seq data obtained from the pairs of normal and PCa tissue samples using our benchmarked in-house cuffdiff pipeline, we observed some important genes specific to PCa, such as STEAP2, APP, PMEPA1, PABPC1, NFE2L2, and HN1L, and some other important genes known to be involved in different cancer pathways, such as COL6A1, DOK5, STX6, BCAS1, BACE1, BACE2, LMOD1, SNX9, CTNND1, etc. We also identified a few novel lncRNAs such as LINC01440, SOX2OT, ENSG00000232855, ENSG00000287903, and ENST00000647843.1 that need to be characterized further. In comparison with publicly available datasets, we have identified characteristic DEGs and novel lncRNAs implicated in signature PCa pathways in an Indian PCa cohort which perhaps have not been reported. This has set a precedent for us to validate candidates further experimentally, and we firmly believe this will pave a way toward the discovery of biomarkers and the development of novel therapies.
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Affiliation(s)
- Nidhi Shukla
- Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research (BISR), Statue Circle, Jaipur 302001, India
- Department of Chemistry, School of Basic Sciences, Manipal University Jaipur, Jaipur 303007, India
| | - Bhumandeep Kour
- Department of Biotechnology, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara 144001, India
| | - Devendra Sharma
- Department of Urology, Rukmani Birla Hospital, Jaipur 302018, India
| | - Maneesh Vijayvargiya
- Department of Pathology, Mahatma Gandhi University of Medical Sciences and Technology, Jaipur 302022, India
| | - T C Sadasukhi
- Department of Urology, Mahatma Gandhi University of Medical Sciences and Technology, Jaipur 302022, India
| | - Krishna Mohan Medicherla
- Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research (BISR), Statue Circle, Jaipur 302001, India
- Department of Bioengineering, Birla Institute of Technology, Mesra Jaipur Campus, 27-Malaviya Industrial Area, Jaipur 302017, India
| | - Babita Malik
- Department of Chemistry, School of Basic Sciences, Manipal University Jaipur, Jaipur 303007, India
| | - Bhawana Bissa
- Department of Biochemistry, Central University of Rajasthan, Ajmer 305817, India
| | - Sugunakar Vuree
- Bioclues.org, Hyderabad 500072, India
- MNR Foundation for Research & Innovation, MNR University, Sangareddy 502294, India
| | - Nirmal Kumar Lohiya
- Department of Zoology, Center for Advanced Studies, University of Rajasthan, Jaipur 302004, India
| | - Prashanth Suravajhala
- Bioclues.org, Hyderabad 500072, India
- Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam 690525, India
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Lian Y, Gòdia M, Castello A, Rodriguez-Gil JE, Balasch S, Sanchez A, Clop A. Characterization of the Impact of Density Gradient Centrifugation on the Profile of the Pig Sperm Transcriptome by RNA-Seq. Front Vet Sci 2021; 8:668158. [PMID: 34350225 PMCID: PMC8326511 DOI: 10.3389/fvets.2021.668158] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 06/22/2021] [Indexed: 12/18/2022] Open
Abstract
RNA-Seq data from human semen suggests that the study of the sperm transcriptome requires the previous elimination from the ejaculates of somatic cells carrying a larger load of RNA. Semen purification is also carried to study the sperm transcriptome in other species including swine and it is often done by density gradient centrifugation to obtain viable spermatozoa from fresh ejaculates or artificial insemination doses, thereby limiting the throughput and remoteness of the samples that can be processed in one study. The aim of this work was to evaluate the impact of purification with density gradient centrifugation by BoviPureTM on porcine sperm. Four boar ejaculates were purified with BoviPureTM and their transcriptome sequenced by RNA-Seq was compared with the RNA-Seq profiles of their paired non-purified sample. Seven thousand five hundred and nineteen protein coding genes were identified. Correlation, cluster, and principal component analysis indicated high—although not complete—similarity between the purified and the paired non-purified ejaculates. 372 genes displayed differentially abundant RNA levels between treatments. Most of these genes had lower abundances after purification and were mostly related to translation, transcription and metabolic processes. We detected a significant change in the proportion of genes of epididymal origin within the differentially abundant genes (1.3%) when compared with the catalog of unaltered genes (0.2%). In contrast, the proportion of testis-specific genes was higher in the group of unaltered genes (4%) when compared to the list of differentially abundant genes (0%). No proportion differences were identified for prostate, white blood, lymph node, tonsil, duodenum, skeletal muscle, liver, and mammary gland. Altogether, these results suggest that the purification impacts on the RNA levels of a small number of genes which are most likely caused by the removal of epididymal epithelial cells but also premature germinal cells, immature or abnormal spermatozoa or seminal exosomes with a distinct load of RNAs.
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Affiliation(s)
- Yu Lian
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus UAB, Barcelona, Spain
| | - Marta Gòdia
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus UAB, Barcelona, Spain
| | - Anna Castello
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus UAB, Barcelona, Spain.,Unit of Animal Science, Department of Animal and Food Science, Autonomous University of Barcelona, Barcelona, Spain
| | - Joan Enric Rodriguez-Gil
- Unit of Animal Reproduction, Department of Animal Medicine and Surgery, Autonomous University of Barcelona, Barcelona, Spain
| | | | - Armand Sanchez
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus UAB, Barcelona, Spain.,Unit of Animal Science, Department of Animal and Food Science, Autonomous University of Barcelona, Barcelona, Spain
| | - Alex Clop
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus UAB, Barcelona, Spain.,Consejo Superior de Investigaciones Científicas, Barcelona, Spain
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Shukla NI, Siva N, Sivakumar M, Parveen R, Mishra A, Shah A, Medicherla K, Suravajhala P. Extraction of DNA and RNA from Formalin-fixed Paraffin-embedded Tissue Specimens. Bio Protoc 2021. [DOI: 10.21769/bioprotoc.4095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
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Prasad A, Bhargava H, Gupta A, Shukla N, Rajagopal S, Gupta S, Sharma A, Valadi J, Nigam V, Suravajhala P. Next Generation Sequencing. Adv Bioinformatics 2021. [DOI: 10.1007/978-981-33-6191-1_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Padmavathi P, Setlur AS, Chandrashekar K, Niranjan V. A comprehensive in-silico computational analysis of twenty cancer exome datasets and identification of associated somatic variants reveals potential molecular markers for detection of varied cancer types. INFORMATICS IN MEDICINE UNLOCKED 2021. [DOI: 10.1016/j.imu.2021.100762] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
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