2. MATERIALS AND METHODS

3. RESULTS

3.1. Retrieval of RIAR-associated Pathway Genes

The existence of the RIAR response among various experiment models has been confirmed using the endpoints such as cell viability, clonogenic ability, DNA damages, chromosomal abnormalities, cell cycle arrest, and apoptosis. Expression of those changes is known to be regulated by different signaling molecules/pathways. The NCBI database was adopted to retrieve genes that are reported to be involved in mediating the response. The output data comprising 69 genes associated with several pathways have been found to be associated with pathways like DNA repair, DNA damage response, oxidative stress, hypoxia, ferroptosis, cellular and metabolic stress, heat shock process, apoptosis, autophagy, cell cycle regulation, cell proliferation, metastasis, inflammation, immune regulation, tumor oncogene or suppressor functions, cell survival, cell proliferation, glutathione metabolism, cell migration, and genomic stability [Supplementary Table 1]. From the earlier studies [7], RIAR-associated pathways related genes with P < 0.05 and logFC|>1| were considered. Few genes also have radioprotective effect. The genes associated with various mechanisms/pathways that are found to alter the RIAR phenomenon are represented in Figure 1.

Table 1: Enriched miRNAs as targets for Radiation-Induced Adaptive Response evaluation during breast cancer radiotherapy.

miRNAs	5’- 3’ Sequence	Overlap	Corresponding genes
hsa-miR-124-3p	UAAGGCACGCGGUGAAUGCCAA	8	ANGPTL7, CD274, HMOX1, IKBKE, MGMT, NCF2, SIRT1, VIM
hsa-miR-17-5p	CAAAGUGCUUACAGUGCAGGUAG	8	APEX1, EPAS1, HIF1A, MDM2, MYC, RUNX1, SOD2, TGFB1
hsa-miR-335-5p	UCAAGAGCAAUAACGAAAAAUGU	8	BRCA1, EGFR, G6PD, HMOX1, MDM2, MYC, NEIL1, PARP1
hsa-miR-128-3p	UCACAGUGAACCGGUCUCUUU	7	APEX1, BMI1, EGFR, HMOX1, PARP1, RUNX1, SIRT1
hsa-miR-155-5p	UUAAUGCUAAUCGUGAUAGGGGUU	7	CAT, EGFR, HIF1A, IKBKE, MYC, NFKB1, SIRT1
hsa-miR-185-5p	UGGAGAGAAAGGCAGUUCCUGA	7	APEX1, ATR, EPAS1, MDM2, MYC, SOD2, TGFB1
hsa-miR-106a-5p	AAAAGUGCUUACAGUGCAGGUAG	7	ATG7, ATM, HIF1A, MDM2, RUNX1, SOD2, TGFB1
hsa-miR-15a-5p	UAGCAGCACAUAAUGGUUUGUG	6	BMI1, BRCA1, CD274, NFKB1, PDCD1, PRKCD
hsa-miR-20a-5p	UAAAGUGCUUAUAGUGCAGGUAG	6	EPAS1, HIF1A, MDM2, MYC, RUNX1, SOD2
hsa-miR-218-5p	UUGUGCUUGAUCUAACCAUGU	6	ATM, ATR, BMI1, EGFR, HMOX1, MDM2
hsa-miR-27a-3p	UUCACAGUGGCUAAGUUCCGC	6	APEX1, BMI1, EGFR, HIF1A, NFE2L2, RUNX1
hsa-miR-34a-5p	UGGCAGUGUCUUAGCUGGUUGU	7	ATG7, BRCA1, FEN1, MYC, NFKB1, SIRT1, XRCC1
hsa-miR-93-5p	CAAAGUGCUGUUCGUGCAGGUAG	6	CDC16, HIF1A, MDM2, MYC, SOD2, TGFB1
hsa-let-7a-5p	UGAGGUAGUAGGUUGUAUAGUU	5	EGFR, MYC, NFKB1, PARP1, SOD2
hsa-miR-145-5p	GUCCAGUUUUCCCAGGAAUCCCU	5	EGFR, EPAS1, HIF1A, MDM2, MYC
hsa-miR-181a-5p	AACAUUCAACGCUGUCGGUGAGU	5	ATM, BRCA1, PRKCD, RUNX1, SIRT1
hsa-miR-24-3p	UGGCUCAGUUCAGCAGGAACAG	5	BRCA1, FEN1, HMOX1, MYC, TGFB1
hsa-miR-9-5p	UCUUUGGUUAUCUAGCUGUAUGA	5	NFKB1, RUNX1, SIRT1, SOD2, VIM
hsa-miR-92a-3p	UAUUGCACUUGUCCCGGCCUGU	5	ATM, MDM2, MYC, NFKB1, SIRT1

Figure 1: Analysis of genes playing a role in radiation-induced adaptive response-associated pathways. [Click here to view]

3.2. GSEA

GSEA was performed to derive the functional relationship among the genes involved in RIAR. There are 35 gene-set libraries in Enrichr with six categories, namely, transcription, pathways, ontologies, diseases/drugs, cell types, and miscellaneous; some of these libraries were built exclusively for Enrichr, while others have been obtained from other tools. The gene enrichment results with respect to genes and pathways are represented in Figure 2a-c. Figure 2a represents the common genes intersecting among the RIAR-related pathways. The order of highly enriched genes involved in the major pathways associated with RIAR is represented in Figure 2b. The enriched genes pertaining to their pathways based on “WikiPathways 2024 Human” with their combined scores are presented as Figure 2c. These genes that are found to be involved with increased combined scores. A maximum number of enriched genes are involved in oxidative stress followed by DNA repair pathways, immune regulation, miRNA-transcription factor regulation, TP53 network, ATM signaling, and genes involved in cellular response by ATM, ATR, and DNA damage response pathway.

Figure 2: Gene Enrichment Analysis of genes involved in inducing radiation-induced adaptive response (RIAR) phenomenon. (a) Common genes intersecting among the RIAR-related pathways. (b) Order of highly enriched genes involved in the major pathways associated with RIAR. (c) Pathways of enriched genes based on “WikiPathways 2024 Human” presented with their combined scores. [Click here to view]

3.3. Gene Interactions Involved in RIAR

Cytoscape remains an efficient tool for retrieving data from different networks via web-service application programming interfaces, hence a more suitable approach for studying gene interactions as they aid in better visualization and analysis of interacting networks, also help us in grouping genes based on their functionality. The gene interactions were grouped into networks based on their functions using Cytoscape (v 3.10.2) and are represented [Figure 3a]. Genes such as PARP1, APEX1, LIG1, hOGG1, and MGMT have been found to be involved in DNA repair mechanisms that repair double-strand breaks caused by IR exposure. This repair is one of the prime mechanisms leading to radioresistance, contributing to RIAR. The adaptation involves cells to survive for the long term; hence, genes such as TGFβ-1, HSPB1, CSF1, PRKCD, and DUSP1 are involved in RIAR. HSPA9 and HIF1A are involved in oxidative stress-induced RIAR. MYC, EPAS1, and EGFR expression are altered and regulate the cell cycle upon pre-exposure to the priming dose. The inflammatory genes such as TLR2, TLR3, TLR4, IL22, NFATC2, IKBKE, PDCD1, CD274, NFkB1 are responsible for mediating RIAR. VIM mediates cell migration hence known to induce RIAR. The gene interactions performed by the STRING database are represented [Figure 3b]. p53 plays the primary role in interacting with the first set of interactors such as ATM, HIF1A, MYC, MDM2, BCL2, SIRT1, MAPK, and BRCA1. These are some evolutionary well-conserved defense mechanisms found to play a role in RIAR induction. The second highest interactors are DNA repair genes followed by inflammation-associated genes, DNA damage response genes, and finally genes involved in oxidative stress with an interaction score of 0.999. The other genes involved in similar pathways either directly or indirectly had an interaction score of 0.98. Since most of the genes of the vital pathways were highly interacting, the genes with at least a score of 0.98 were considered.

Figure 3: Gene interactions among Radiation-Induced Adaptive Response (RIAR)-associated pathway genes. (a) Cytoscape network of function-based RIAR gene interactions. (b) STRING-based functional gene interactions of RIAR genes. [Click here to view]

4. DISCUSSION

Breast cancer is the most common type of cancer in women diagnosed as of 2020, and it is the leading cause of cancer morbidity, disability, and mortality in women globally [14]. The RT remains a standard palliative therapy for curing breast cancer. The types of gene interactions may be categorized into gene regulatory networks, protein-protein interactions, regulation of gene expression, and crosstalk among pathways [15-17]. The coordinated cellular response to radiation depends on these gene-gene interactions, which affect the cancer patient’s response to RT. The genes represented in Figure 1 are known to be reported in previous literature, among which DNA repair and oxidative stress pathways are highly involved in RIAR. Also, the GSEA results comprising the genes and highly enriched pathways such as DNA repair and oxidative stress [Figure 2a-c] were in correlation with the gene-gene interaction results from Cytoscape (v 3.10.2) [Figure 3a] and STRING databases [Figure 3b]. p53 plays a main role in regulating other genes and is a major contributor for the occurrence of RIAR via seven major pathways [Figure 3b].

miRNAs serve as prognostic biomarkers for radio-resistance as reported in the literature [18]. miRNAs in this study can more effectively serve as potential targets for targeting genes involved in RIAR-associated mechanisms to enhance the effectiveness of RT. They are vital in controlling gene expression to enable the cells to respond to stress and cellular damage induced by radiation. Thus, miRNAs make cells adapt to radiation exposure, thereby promoting cell survival and maintaining genomic integrity; these correspond to the radio-adaptive response phenomenon. These can target genes in the homologous recombination and non-homologous end-joining pathway, thereby repairing the radiation-induced damages efficiently. miRNAs regulate genes involved in the oxidative stress response pathways, such as superoxide dismutase (SOD) and nuclear factor erythroid 2-related factor 2 such that cells have increased production of reactive oxygen species during radiation exposure [19].

Enrichr is a web-based enrichment analysis tool, which is simple to use and intuitive, providing an assortment of visualization summaries of the collective purposes of gene lists. Another noteworthy feature of the online analysis tool Enrichr is its comprehensiveness, ease of use, and interactive visualization of results. Enrichr tool predicts disease-specific signatures or transcriptional signatures. The tools used in this study identify disease-specific signatures via a comparison of gene expression patterns between the normal and diseased tissues [20]. Studies have reported the alterations in genes in various other cancers, i.e., about 381 genes have been associated with RT response in rectal cancers [21]. Genes such as SELP, PIM2, CCL19, SDS, NRP1, and SF3A2 were associated with RT sensitivity in cervical cancers [22].

miRNAs are long non-coding RNAs that target genes and have regulatory functions. miRNA microarray analysis in AG01522 normal human fibroblasts upon exposure to 5 cGy followed by 2 Gy has revealed the trigger of miRNAs upon low-dose-induced RIAR. Earlier in silico and in vitro studies have analyzed miRNAs as potential targets in atherosclerosis [23]. Two separate miRNA signatures comprising 4 up-regulated and 5 down-regulated miRNAs in breast tumors were identified from 1165 breast cancer patients retrieved from the Cancer Genome Atlas (TCGA-BRCA) [24]. miRNAs have oncogenic or tumour-suppressive functions and hence remain dysregulated in several cancers [25]. Alterations in the circulating miRNAs in blood plasma or serum can reflect the patient’s response to RT.

The miTarBase and miRNet enhance data usability and accessibility; thus, these are regarded as authentic databases for miRNA information. The enrichMiR tool seems to be highly advanced for interpretation and visualization of enrichment results due to its routine updates, also it uses the input data via integration with high-confidence and authentic databases like ScanMiR, TargetScan, miRTarBase & oRNAment. The enrichMiR tool provides results based on various choices such as overlap features of miRNA, and it also performs a comprehensive prediction based on miRNAs functionally relevant to target genes apart from statistically significant miRNAs [26]. The role of miRNAs associated with those 69 genes and breast cancer are discussed in Table 1. A network of miRNAs, namely miR-21, miR-155, and miR-205, has been identified as potential biomarkers for monitoring the radiation response in cancer patients [27-29]. miR-124 contributes to RIAR by either enhancing or suppressing inflammation and immune responses [27]. miR-17 downregulates p21 expression, leading to radio-resistance of cancer cells, thereby facilitating cell survival and proliferation [30]. miR-335 is involved in the DNA damage response pathway [31]. Overexpression of miR-106a leads to increased cell proliferation, conferring radio-resistance, and miR-128 can either enhance or suppress DNA damage response genes, leading to RIAR [32]. miR-185 enhances radiation-induced apoptosis and inhibits cell proliferation via targeting ATM and ATR [33]. miR-15a regulates the SMPD1, which is involved in apoptosis and inflammation upon radiation response [34]. miR-20a-5p targets Rab27b involved in apoptosis, altering radio-resistance [35]. miR-218 targets stress response pathways involved in radiation-induced stress [36]. miR-27a targets genes involved in DNA repair and cell survival [37]. miR-34a downregulates factors involved in cancer stem cell maintenance and thereby reduces cell survival, proliferation, and alters RIAR [38]. miR-93 serves to be a promising therapeutic target for enhancing RT outcomes in cancer treatment by increasing tumor radiosensitivity [39]. hsa-let-7a-5p regulates the balance between DNA repair-mediated radio-resistance and apoptosis-mediated radiosensitivity following radiation exposure [40]. miR-145 contributes to enhanced tumor radio-resistance; hence, targeting this can be more beneficial towards RT outcomes. miR-181a targets ATM and RAD52; hence, altering miR-181a can enhance DNA damage thereby reducing radio-resistance [41]. miR-24 enhances radiosensitivity by enhancing apoptosis and inhibiting cell proliferation [19]. miR-9-5p targets Suppressor of Cytokine Signaling 5, thereby exploring miR-9-5p can alter angiogenesis and cell survival, thereby altering RIAR [42]. miR-92a has been found to be involved in oxidative stress influencing RIAR by producing reactive oxygen species [43]. Hence, we found that about 19 miRNAs were found to be enriched in our study; these were majorly involved in the regulation of pathways such as oxidative stress, inflammation, DNA damage response, DNA repair, apoptosis, cell proliferation, and cell survival. Therefore, these 19 miRNAs can serve as predictive therapeutic targets to be explored more via further molecular approaches for the occurrence of RIAR in breast cancer. Exploring and monitoring the miRNAs in this study, i.e., the miRNAs associated with the RIAR phenomenon and those important in breast cancer may help in the dynamic assessment of RT efficacy in breast cancer patients. This can maximize the therapeutic efficacy in spite of the non-targeted effects of radiation.

miRNAs that regulate genes upon radiation exposure (also known as radio-miRs) act as gatekeepers in regulating the cellular mechanisms and pathways that lead to radio-resistance or RIAR [44]. This study has witnessed the involvement of about 19 miRNAs that modify several radio-adaptive response pathways notably, DNA repair, DNA damage response, cell survival, proliferation, and apoptosis via targeting RIAR genes and carcinoma of the breast. The tools used in this study remain advantageous due to the advancement in software/databases. A deeper understanding of these mechanisms and targeting miRNAs via molecules involved in these mechanisms can lead to more precise combination treatments. This is an in silico study based on the genes and miRNA targets available from databases. However, the targets mentioned in this study have to be evaluated using in vitro studies, either in blood samples of cancer patients or in cancer cell lines for analyzing and confirmation of targets being involved in RIAR during RT. The targets can be validated in breast cancer cell lines in in vitro by methods such as qRT-PCR, northern blotting, microarray analysis, next-generation sequencing, luciferase reporter assay, in situ hybridization, and specifically, western blot and flow cytometry for analysing the expression of proteins targeted by miRNAs. Combining these methods will give an understanding of miRNA roles in RIAR during RT, or therapy resistance. Evaluating in vitro will further confirm the effectiveness of the identified targets. Hence, this study serves as a preliminary basis for more futuristic lab studies for improving therapeutic efficacy.

5. CONCLUSION

The molecules and their expression patterns can be altered by the radiation treatment approaches (conventional or fractionated clinical dose regimes). Therefore, targeting these molecules may decrease tumor resistance and improve patient outcomes in RT. A better knowledge of these mechanisms via these in silico approaches will improve our understanding and alter the tumor prognosis due to RIAR alterations in breast cancer therapy. Although this study has found the possible miRNA targets of genes involved in RIAR during breast cancer RT via in silico approaches, more extensive validation via in vitro approaches on the found miRNA targets is required for them to be proven for their roles in RIAR. Hence, this was the limitation of this study. The dysregulation of miRNAs targeting these RIAR genes in breast cancer can be regulated by altering the radiation doses during RT, which will further help in regulating or normalizing the gene expression patterns of RIAR genes that may clinically correlate for the betterment of cancer cure. Analysing these enriched miRNAs resulting from this study may enhance the possibilities of exploring novel RT strategies in breast cancers for the advancement of therapeutic efficacy in the future.

6. AUTHORS’ CONTRIBUTIONS

All authors made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; took part in drafting the article or revising it critically for important intellectual content; agreed to submit to the current journal; gave final approval of the version to be published; and agreed to be accountable for all aspects of the work. All the authors are eligible to be an author as per the International Committee of Medical Journal Editors (ICMJE) requirements/guidelines.

7. FUNDING

The authors acknowledge the fellowship (Reg. No: U02B210734) support to Aishwarya Thathamangalam Ananthanarayanan, from Founder Chancellor Shri N.P.V Ramaswamy Udayar Research Fellowship, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Porur, Chennai, Tamil Nadu, India.

8. CONFLICTS OF INTEREST

The authors report no financial or any other conflicts of interest in this work.

9. ETHICAL APPROVALS

This study does not involve experiments on animals or human subjects.

10. DATA AVAILABILITY

The datasets of retrieved genes and miRNAs of Homo sapiens presented in this study can be found in online repositories.

11. PUBLISHER’S NOTE

All claims expressed in this article are solely those of the authors and do not necessarily represent those of the publisher, the editors and the reviewers. This journal remains neutral with regard to jurisdictional claims in published institutional affiliation.

12. USE OF ARTIFICIAL INTELLIGENCE (AI)-ASSISTED TECHNOLOGY

The authors declare that we have not used artificial intelligence (AI)-tools for writing and editing of the manuscript, and no images were manipulated using AI.

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