Ferroptosis-Related Prognostic Gene LAMP2 Is a Potential Biomarker Differential Expressed in Castration Resistant Prostate Cancer

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Abstract

Background

It remains unclear about the mechanisms of prostate cancer progressing to castration resistant prostate cancer (CRPC) and the correlation with ferroptosis.

Methods

We compared the gene profiles between localized prostate cancer and metastatic CRPC using the GEO dataset and intersected with a cluster of known ferroptosis-related genes. We received differentially expressed genes (DEGs) in CRPC related to ferroptosis and performed survival analysis to analyze the prognostic values. Furthermore, we conducted single sample gene set enrichment analysis (ssGSEA) to analyze immune infiltration and investigate microRNA crosstalk and methylation for prognostic genes using online databases.

Results

We identified 84 DEGs in CRPC related to ferroptosis and 19 hub genes densely connected into networks by enrichment analysis. We performed survival analysis and Cox regression for these genes and identified LAMP2 with significantly prognostic values in overall survival (OS) and disease-specific survival (DSS) of prostate cancer. Furthermore, we found immune infiltration of various immune cells significantly correlated with LAMP2 expression in prostate cancer and identified multiple microRNAs associated with LAMP2 expression in prostate cancer. In addition, we found that the methylation level of LAMP2 in prostate cancer was significantly associated with cancer and identified 8 methylation sites for LAMP2.

Conclusion

Ferroptosis-related gene LAMP2 is a potential biomarker with prognostic value for prostate cancer.

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Most cited references 26

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New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

E A Eisenhauer, P Therasse, J. Bogaerts … (2009)

Assessment of the change in tumour burden is an important feature of the clinical evaluation of cancer therapeutics: both tumour shrinkage (objective response) and disease progression are useful endpoints in clinical trials. Since RECIST was published in 2000, many investigators, cooperative groups, industry and government authorities have adopted these criteria in the assessment of treatment outcomes. However, a number of questions and issues have arisen which have led to the development of a revised RECIST guideline (version 1.1). Evidence for changes, summarised in separate papers in this special issue, has come from assessment of a large data warehouse (>6500 patients), simulation studies and literature reviews. HIGHLIGHTS OF REVISED RECIST 1.1: Major changes include: Number of lesions to be assessed: based on evidence from numerous trial databases merged into a data warehouse for analysis purposes, the number of lesions required to assess tumour burden for response determination has been reduced from a maximum of 10 to a maximum of five total (and from five to two per organ, maximum). Assessment of pathological lymph nodes is now incorporated: nodes with a short axis of 15 mm are considered measurable and assessable as target lesions. The short axis measurement should be included in the sum of lesions in calculation of tumour response. Nodes that shrink to <10mm short axis are considered normal. Confirmation of response is required for trials with response primary endpoint but is no longer required in randomised studies since the control arm serves as appropriate means of interpretation of data. Disease progression is clarified in several aspects: in addition to the previous definition of progression in target disease of 20% increase in sum, a 5mm absolute increase is now required as well to guard against over calling PD when the total sum is very small. Furthermore, there is guidance offered on what constitutes 'unequivocal progression' of non-measurable/non-target disease, a source of confusion in the original RECIST guideline. Finally, a section on detection of new lesions, including the interpretation of FDG-PET scan assessment is included. Imaging guidance: the revised RECIST includes a new imaging appendix with updated recommendations on the optimal anatomical assessment of lesions. A key question considered by the RECIST Working Group in developing RECIST 1.1 was whether it was appropriate to move from anatomic unidimensional assessment of tumour burden to either volumetric anatomical assessment or to functional assessment with PET or MRI. It was concluded that, at present, there is not sufficient standardisation or evidence to abandon anatomical assessment of tumour burden. The only exception to this is in the use of FDG-PET imaging as an adjunct to determination of progression. As is detailed in the final paper in this special issue, the use of these promising newer approaches requires appropriate clinical validation studies.

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GSVA: gene set variation analysis for microarray and RNA-Seq data

Sonja Hänzelmann, Robert Castelo, Justin Guinney (2013)

Background Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. Results To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. Conclusions GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.

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Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

Yingyao Zhou, Bin Zhou, Lars Pache … (2019)

A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.

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Author and article information

Contributors

Qingfeng Hu:

ORCID: https://orcid.org/0000-0003-0075-100X

Journal

Journal ID (nlm-ta): Dis Markers

Journal ID (iso-abbrev): Dis Markers

Journal ID (publisher-id): DM

Title: Disease Markers

Publisher: Hindawi

ISSN (Print): 0278-0240

ISSN (Electronic): 1875-8630

Publication date Collection: 2023

Publication date (Electronic): 20 January 2023

Volume: 2023

Electronic Location Identifier: 8295113

Affiliations

¹Department of Urology, Huashan Hospital, Fudan University, Shanghai, China

²Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai, China

Author notes

Academic Editor: Zhijie Xu

Author information

Chuanyu Sun https://orcid.org/0000-0003-4291-8920

Ningning Zhang https://orcid.org/0000-0002-7525-4203

Qingfeng Hu https://orcid.org/0000-0003-0075-100X

Guowei Xia https://orcid.org/0000-0002-1257-3100

Article

DOI: 10.1155/2023/8295113

PMC ID: 9893524

SO-VID: 5d18d4b8-9d22-4c52-8ad6-a70ddff24e66

License:

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date received : 4 July 2022

Date revision received : 20 September 2022

Date accepted : 3 November 2022

Ferroptosis-Related Prognostic Gene LAMP2 Is a Potential Biomarker Differential Expressed in Castration Resistant Prostate Cancer

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Abstract

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Most cited references 26

New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

GSVA: gene set variation analysis for microarray and RNA-Seq data

Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

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