Systematic identification of long non-coding RNAs with cancer-testis expression patterns in 14 cancer types

Background The “dark matter” of the genome harbors several non-coding RNA species including Long non-coding RNAs (lncRNAs), which have been implicated in neoplasia but remain understudied. RNA-seq has provided deep insights into the nature of lncRNAs in cancer but current RNA-seq data are rarely accompanied by longitudinal patient survival information. In contrast, a plethora of microarray studies have collected these clinical metadata that can be leveraged to identify novel associations between gene expression and clinical phenotypes. Methods In this study, we developed an analysis framework that computationally integrates RNA-seq and microarray data to systematically screen 9,463 lncRNAs for association with mortality risk across 20 cancer types. Results In total, we identified a comprehensive list of associations between lncRNAs and patient survival and demonstrate that these prognostic lncRNAs are under selective pressure and may be functional. Our results provide valuable insights that facilitate further exploration of lncRNAs and their potential as cancer biomarkers and drug targets.

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Accentuating CircRNA-miRNA-Transcription Factors Axis: A Conundrum in Cancer Research

Frontiers in Pharmacology ◽

10.3389/fphar.2021.784801 ◽

2022 ◽

Vol 12 ◽

Author(s):

Deepti Singh ◽

Prashant Kesharwani ◽

Nabil A. Alhakamy ◽

Hifzur R. Siddique

Keyword(s):

Transcription Factors ◽

Expression Patterns ◽

Regulatory Function ◽

Circular Rnas ◽

Cancer Management ◽

Disease Biology ◽

Scientific World ◽

Cancer Types ◽

Non Coding Rnas ◽

Mirna Sponges

Circular RNAs (circRNAs) are the newly uncovered class of non-coding RNAs being cognized as profound regulators of gene expression in developmental and disease biology. These are the covalently closed RNAs synthesized when the pre-mRNA transcripts undergo a back-splicing event. In recent years, circRNAs are gaining special attention in the scientific world and are no longer considered as “splicing noise” but rather structurally stable molecules having multiple biological functions including acting as miRNA sponges, protein decoys/scaffolds, and regulators of transcription and translation. Further, emerging evidence suggests that circRNAs are also differentially expressed in multiple cancers where they play oncogenic roles. In addition, circRNAs in association with miRNAs change the expression patterns of multiple transcription factors (TFs), which play important roles in cancer. Thus, the circRNA-miRNA-TFs axis is implicated in the progression or suppression of various cancer types and plays a role in cell proliferation, invasion, and metastasis. In this review article, we provide an outline of the biogenesis, localization, and functions of circRNAs specifically in cancer. Also, we highlight the regulatory function of the circRNA-miRNA-TFs axis in the progression or suppression of cancer and the targeting of this axis as a potential therapeutic approach for cancer management. We anticipate that our review will contribute to expanding the knowledge of the research community about this recent and rapidly growing field of circRNAs for further thorough investigation which will surely help in the management of deadly disease cancer.

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Systematic identification of genes with a cancer-testis expression pattern in 19 cancer types

Nature Communications ◽

10.1038/ncomms10499 ◽

2016 ◽

Vol 7 (1) ◽

Cited By ~ 59

Author(s):

Cheng Wang ◽

Yayun Gu ◽

Kai Zhang ◽

Kaipeng Xie ◽

Meng Zhu ◽

...

Keyword(s):

Expression Pattern ◽

Cancer Types ◽

Systematic Identification ◽

Cancer Testis

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Identification and Roles of miR-29b-1-3p and miR29a-3p-Regulated and Non-Regulated lncRNAs in Endocrine-Sensitive and Resistant Breast Cancer Cells

Cancers ◽

10.3390/cancers13143530 ◽

2021 ◽

Vol 13 (14) ◽

pp. 3530

Author(s):

Penn Muluhngwi ◽

Carolyn M. Klinge

Keyword(s):

Breast Cancer ◽

Cancer Survival ◽

Expression Patterns ◽

Endocrine Resistance ◽

Estrogen Receptor Α ◽

Resistant Cell ◽

Differentially Expressed ◽

Primary Tumors ◽

Non Coding Rnas ◽

Mcf 7

Despite improvements in the treatment of endocrine-resistant metastatic disease using combination therapies in patients with estrogen receptor α (ERα) primary tumors, the mechanisms underlying endocrine resistance remain to be elucidated. Non-coding RNAs (ncRNAs), including microRNAs (miRNA) and long non-coding RNAs (lncRNA), are targets and regulators of cell signaling pathways and their exosomal transport may contribute to metastasis. Previous studies have shown that a low expression of miR-29a-3p and miR-29b-3p is associated with lower overall breast cancer survival before 150 mos. Transient, modest overexpression of miR-29b1-3p or miR-29a-3p inhibited MCF-7 tamoxifen-sensitive and LCC9 tamoxifen-resistant cell proliferation. Here, we identify miR-29b-1/a-regulated and non-regulated differentially expressed lncRNAs in MCF-7 and LCC9 cells using next-generation RNA seq. More lncRNAs were miR-29b-1/a-regulated in LCC9 cells than in MCF-7 cells, including DANCR, GAS5, DSCAM-AS1, SNHG5, and CRND. We examined the roles of miR-29-regulated and differentially expressed lncRNAs in endocrine-resistant breast cancer, including putative and proven targets and expression patterns in survival analysis using the KM Plotter and TCGA databases. This study provides new insights into lncRNAs in endocrine-resistant breast cancer.

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Upregulation of 15 Antisense Long Non-Coding RNAs in Osteosarcoma

Genes ◽

10.3390/genes12081132 ◽

2021 ◽

Vol 12 (8) ◽

pp. 1132

Author(s):

Emel Rothzerg ◽

Xuan Dung Ho ◽

Jiake Xu ◽

David Wood ◽

Aare Märtson ◽

...

Keyword(s):

Tumour Progression ◽

Expression Profiles ◽

Expression Patterns ◽

Regulation Of Gene Expression ◽

Osteosarcoma Cell ◽

Osteoblast Cell Line ◽

Antisense Lncrnas ◽

Non Coding Rnas ◽

Polymerase Chain ◽

Multiple Levels

The human genome encodes thousands of natural antisense long noncoding RNAs (lncRNAs); they play the essential role in regulation of gene expression at multiple levels, including replication, transcription and translation. Dysregulation of antisense lncRNAs plays indispensable roles in numerous biological progress, such as tumour progression, metastasis and resistance to therapeutic agents. To date, there have been several studies analysing antisense lncRNAs expression profiles in cancer, but not enough to highlight the complexity of the disease. In this study, we investigated the expression patterns of antisense lncRNAs from osteosarcoma and healthy bone samples (24 tumour-16 bone samples) using RNA sequencing. We identified 15 antisense lncRNAs (RUSC1-AS1, TBX2-AS1, PTOV1-AS1, UBE2D3-AS1, ERCC8-AS1, ZMIZ1-AS1, RNF144A-AS1, RDH10-AS1, TRG-AS1, GSN-AS1, HMGA2-AS1, ZNF528-AS1, OTUD6B-AS1, COX10-AS1 and SLC16A1-AS1) that were upregulated in tumour samples compared to bone sample controls. Further, we performed real-time polymerase chain reaction (RT-qPCR) to validate the expressions of the antisense lncRNAs in 8 different osteosarcoma cell lines (SaOS-2, G-292, HOS, U2-OS, 143B, SJSA-1, MG-63, and MNNG/HOS) compared to hFOB (human osteoblast cell line). These differentially expressed IncRNAs can be considered biomarkers and potential therapeutic targets for osteosarcoma.

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Abnormal Long Non-Coding RNAs Expression Patterns Have the Potential Ability for Predicting Survival and Treatment Response in Breast Cancer

Genes ◽

10.3390/genes12070996 ◽

2021 ◽

Vol 12 (7) ◽

pp. 996

Author(s):

Ana Carolina Pavanelli ◽

Flavia Rotea Mangone ◽

Luciana R. C. Barros ◽

Juliana Machado-Rugolo ◽

Vera L. Capelozzi ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Patients ◽

Predictive Value ◽

Expression Patterns ◽

Survival Rates ◽

In Silico Analysis ◽

Cancer Prognosis ◽

Response To Treatment ◽

Breast Cancer Patients ◽

Non Coding Rnas

Abnormal long non-coding RNAs (lncRNAs) expression has been documented to have oncogene or tumor suppressor functions in the development and progression of cancer, emerging as promising independent biomarkers for molecular cancer stratification and patients’ prognosis. Examining the relationship between lncRNAs and the survival rates in malignancies creates new scenarios for precision medicine and targeted therapy. Breast cancer (BRCA) is a heterogeneous malignancy. Despite advances in its molecular classification, there are still gaps to explain in its multifaceted presentations and a substantial lack of biomarkers that can better predict patients’ prognosis in response to different therapeutic strategies. Here, we performed a re-analysis of gene expression data generated using cDNA microarrays in a previous study of our group, aiming to identify differentially expressed lncRNAs (DELncRNAs) with a potential predictive value for response to treatment with taxanes in breast cancer patients. Results revealed 157 DELncRNAs (90 up- and 67 down-regulated). We validated these new biomarkers as having prognostic and predictive value for breast cancer using in silico analysis in public databases. Data from TCGA showed that compared to normal tissue, MIAT was up-regulated, while KCNQ1OT1, LOC100270804, and FLJ10038 were down-regulated in breast tumor tissues. KCNQ1OT1, LOC100270804, and FLJ10038 median levels were found to be significantly higher in the luminal subtype. The ROC plotter platform results showed that reduced expression of these three DElncRNAs was associated with breast cancer patients who did not respond to taxane treatment. Kaplan–Meier survival analysis revealed that a lower expression of the selected lncRNAs was significantly associated with worse relapse-free survival (RFS) in breast cancer patients. Further validation of the expression of these DELncRNAs might be helpful to better tailor breast cancer prognosis and treatment.

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Non-Coding RNAs as Prognostic Markers for Endometrial Cancer

International Journal of Molecular Sciences ◽

10.3390/ijms22063151 ◽

2021 ◽

Vol 22 (6) ◽

pp. 3151 ◽

Cited By ~ 2

Author(s):

Roberto Piergentili ◽

Simona Zaami ◽

Anna Franca Cavaliere ◽

Fabrizio Signore ◽

Giovanni Scambia ◽

...

Keyword(s):

Endometrial Cancer ◽

Prognostic Markers ◽

Classification Systems ◽

Prognostic Role ◽

Protein Coding ◽

Pathological Characteristics ◽

Epigenetic Events ◽

Cancer Types ◽

Non Coding Rnas

Endometrial cancer (EC) has been classified over the years, for prognostic and therapeutic purposes. In recent years, classification systems have been emerging not only based on EC clinical and pathological characteristics but also on its genetic and epigenetic features. Noncoding RNAs (ncRNAs) are emerging as promising markers in several cancer types, including EC, for which their prognostic value is currently under investigation and will likely integrate the present prognostic tools based on protein coding genes. This review aims to underline the importance of the genetic and epigenetic events in the EC tumorigenesis, by expounding upon the prognostic role of ncRNAs.

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Genome-wide identification and characterization of long non-coding RNAs involved in flag leaf senescence of rice

Plant Molecular Biology ◽

10.1007/s11103-021-01121-3 ◽

2021 ◽

Author(s):

Xiaoping Huang ◽

Hongyu Zhang ◽

Qiang Wang ◽

Rong Guo ◽

Lingxia Wei ◽

...

Keyword(s):

Transcription Factors ◽

Leaf Senescence ◽

Flag Leaf ◽

Reduction Process ◽

Sequencing Analysis ◽

Biological Processes ◽

Genome Wide ◽

A Genome ◽

Non Coding Rnas ◽

Systematic Identification

Abstract Key message This study showed the systematic identification of long non-coding RNAs (lncRNAs) involving in flag leaf senescence of rice, providing the possible lncRNA-mRNA regulatory relationships and lncRNA-miRNA-mRNA ceRNA networks during leaf senescence. Abstract LncRNAs have been reported to play crucial roles in diverse biological processes. However, no systematic identification of lncRNAs associated with leaf senescence in plants has been studied. In this study, a genome-wide high throughput sequencing analysis was performed using rice flag leaves developing from normal to senescence. A total of 3953 lncRNAs and 38757 mRNAs were identified, of which 343 lncRNAs and 9412 mRNAs were differentially expressed. Through weighted gene co-expression network analysis (WGCNA), 22 continuously down-expressed lncRNAs targeting 812 co-expressed mRNAs and 48 continuously up-expressed lncRNAs targeting 1209 co-expressed mRNAs were considered to be significantly associated with flag leaf senescence. Gene Ontology results suggested that the senescence-associated lncRNAs targeted mRNAs involving in many biological processes, including transcription, hormone response, oxidation–reduction process and substance metabolism. Additionally, 43 senescence-associated lncRNAs were predicted to target 111 co-expressed transcription factors. Interestingly, 8 down-expressed lncRNAs and 29 up-expressed lncRNAs were found to separately target 12 and 20 well-studied senescence-associated genes (SAGs). Furthermore, analysis on the competing endogenous RNA (CeRNA) network revealed that 6 down-expressed lncRNAs possibly regulated 51 co-expressed mRNAs through 15 miRNAs, and 14 up-expressed lncRNAs possibly regulated 117 co-expressed mRNAs through 21 miRNAs. Importantly, by expression validation, a conserved miR164-NAC regulatory pathway was found to be possibly involved in leaf senescence, where lncRNA MSTRG.62092.1 may serve as a ceRNA binding with miR164a and miR164e to regulate three transcription factors. And two key lncRNAs MSTRG.31014.21 and MSTRG.31014.36 also could regulate the abscisic-acid biosynthetic gene BGIOSGA025169 (OsNCED4) and BGIOSGA016313 (NAC family) through osa-miR5809. The possible regulation networks of lncRNAs involving in leaf senescence were discussed, and several candidate lncRNAs were recommended for prior transgenic analysis. These findings will extend the understanding on the regulatory roles of lncRNAs in leaf senescence, and lay a foundation for functional research on candidate lncRNAs.

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A Pan-Cancer Census of Dominant Tumor Immune Archetypes

10.1101/2021.04.26.441344 ◽

2021 ◽

Author(s):

Alexis J. Combes ◽

Bushra Samad ◽

Jessica Tsui ◽

Nayvin W. Chew ◽

Peter Yan ◽

...

Keyword(s):

Immune System ◽

Expression Patterns ◽

Tumor Biology ◽

Surrounding Tissue ◽

Driver Mutations ◽

Significant Heterogeneity ◽

Tumor Immune Microenvironment ◽

Cancer Types ◽

System Archetypes ◽

Tumor Gene Expression

SUMMARYCancers display significant heterogeneity with respect to tissue of origin, driver mutations and other features of the surrounding tissue. It is likely that persistent tumors differentially engage inherent patterns–here ‘Archetypes’–of the immune system, to both benefit from a tumor immune microenvironment (TIME) and to disengage tumor-targeting. To discover dominant immune system archetypes, the Immunoprofiler Initiative (IPI) processed 364 individual tumors across 12 cancer types using standardized protocols. Computational clustering of flow cytometry and transcriptomic data obtained from cell sub compartments uncovered archetypes that exist across indications. These Immune composition-based archetypes differentiate tumors based upon unique immune and tumor gene-expression patterns. Archetypes discovered this way also tie closely to well-established classifications of tumor biology. The IPI resource provides a template for understanding cancer immunity as a collection of dominant patterns of immune infiltration and provides a rational path forward to learn how to modulate these patterns to improve therapy.

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Pan-cancer systematic identification of lncRNAs associated with cancer prognosis

10.1101/353334 ◽

2018 ◽

Author(s):

Matthew H. Ung ◽

Evelien Schaafsma ◽

Daniel E. Mattox ◽

George L. Wang ◽

Chao Cheng

Keyword(s):

Drug Targets ◽

Patient Survival ◽

Cancer Prognosis ◽

Rna Seq ◽

Non Coding Rna ◽

Cancer Types ◽

Microarray Studies ◽

Systematic Identification ◽

Pan Cancer ◽

Novel Associations

AbstractThe “dark matter” of the genome harbors several non-coding RNA species including IncRNAs, which have been implicated in neoplasias but remain understudied. RNA-seq has provided deep insights into the nature of lncRNAs in cancer but current RNA-seq data are rarely accompanied by longitudinal patient survival information. In contrast, a plethora of microarray studies have collected these clinical metadata that can be leveraged to identify novel associations between gene expression and clinical phenotypes. In this study, we developed an analysis framework that computationally integrates RNA-seq and microarray data to systematically screen 9,463 lncRNAs for association with mortality risk across 20 cancer types. In total, we identified a comprehensive list of associations between lncRNAs and patient survival and demonstrate that these prognostic lncRNAs are under selective pressure and may be functional. Our results provide valuable insights that facilitate further exploration of lncRNAs and their potential as cancer biomarkers and drug targets.

Download Full-text