Cisplatin resistance-related multi-omics differences and the establishment of machine learning models

Integrated analysis reveals critical cisplatin-resistance regulators E2F7 contributed to tumor progression and metastasis in lung adenocarcinoma

BACKGROUND

Drug resistance poses a significant challenge in cancer treatment, particularly as a leading cause of therapy failure. Cisplatin, the primary drug for lung adenocarcinoma (LUAD) chemotherapy, shows effective treatment outcomes. However, the development of resistance against cisplatin is a major obstacle. Therefore, identifying genes resistant to cisplatin and adopting personalized treatment could significantly improve patient outcomes.

METHODS

By examining transcriptome data of cisplatin-resistant LUAD cells from the GEO database, 181 genes associated with cisplatin resistance were identified. Using univariate regression analysis, random forest and multivariate regression analyses, two prognostic genes, E2F7 and FAM83A, were identified. This study developed a prognostic model utilizing E2F7 and FAM83A as key indicators. The Cell Counting Kit 8 assay, Transwell assay, and flow cytometry were used to detect the effects of E2F7 on the proliferation, migration, invasiveness and apoptosis of A549/PC9 cells. Western blotting was used to determine the effect of E2F7 on AKT/mTOR signaling pathway.

RESULTS

This study has pinpointed two crucial genes associated with cisplatin resistance, E2F7 and FAM83A, and developed a comprehensive model to assist in the diagnosis, prognosis, and evaluation of relapse risk in LUAD. Analysis revealed that patients at higher risk, according to these genetic markers, had elevated levels of immune checkpoints (PD-L1 and PD-L2). The prognostic and diagnosis values of E2F7 and FAM83A were further confirmed in clinical data. Furthermore, inhibiting E2F7 in lung cancer cells markedly reduced their proliferation, migration, invasion, and increased apoptosis. In vivo experiments corroborated these findings, showing reduced tumor growth and lung metastasis upon E2F7 suppression in lung cancer models.

CONCLUSION

Our study affirms the prognostic value of a model based on two DEGs, offering a reliable method for predicting the success of tumor immunotherapy in patients with LUAD. The diagnostic and predictive model based on these genes demonstrates excellent performance. In vitro, reducing E2F7 levels shows antitumor effects by blocking LUAD growth and progression. Further investigation into the molecular mechanisms has highlighted E2F7's effect on the AKT/mTOR signaling pathway, underscoring its therapeutic potential. In the era of personalized medicine, this DEG-based model promises to guide clinical practice.

Pollutants to pathogens: The role of heavy metals in modulating TGF-β signaling and lung cancer risk

Lung cancer is a malignant tumor that develops in the lungs due to the uncontrolled growth of aberrant cells. Heavy metals, such as arsenic, cadmium, mercury, and lead, are metallic elements characterized by their high atomic weights and densities. Anthropogenic activities, such as industrial operations and pollution, have the potential to discharge heavy metals into the environment, hence presenting hazards to ecosystems and human well-being. The TGF-β signalling pathways have a crucial function in controlling several cellular processes, with the ability to both prevent and promote tumor growth. TGF-β regulates cellular responses by interacting in both canonical and non-canonical signalling pathways. Research employing both in vitro and in vivo models has shown that heavy metals may trigger TGF-β signalling via complex molecular pathways. Experiments conducted in a controlled laboratory environment show that heavy metals like cadmium and arsenic may directly bind to TGF-β receptors, leading to alterations in their structure that enable the receptor to be phosphorylated. Activation of this route sets in motion subsequent signalling cascades, most notably the canonical Smad pathway. The development of lung cancer has been linked to heavy metals, which are ubiquitous environmental pollutants. To grasp the underlying processes, it is necessary to comprehend their molecular effect on TGF-β pathways. With a particular emphasis on its consequences for lung cancer, this abstract delves into the complex connection between exposure to heavy metals and the stimulation of TGF-β signalling.

A risk prediction nomogram for resistant hypertension in patients with obstructive sleep apnea

Patients with obstructive sleep apnea (OSA) are liable to have resistant hypertension (RH) associated with unfavorable cardiovascular events. It is of necessity to predict OSA patients who are susceptible to resistant hypertension. Hence, we conducted a retrospective study based on the clinical records of OSA patients admitted to Yixing Hospital Affiliated to Jiangsu University from January 2018 to December 2022. According to different time periods, patients diagnosed between January 2018 and December 2021 were included in the training set (n = 539) for modeling, and those diagnosed between January 2022 and December 2022 were enrolled into the validation set (n = 259) for further assessment. The incidence of RH in the training set and external validation set was comparable (P = 0.396). The related clinical data of patients enrolled were collected and analyzed through univariate analysis and least absolute shrinkage and selection operator (LASSO) logistic regression analysis to identify independent risk factors and construct a nomogram. Finally, five variables were confirmed as independent risk factors for OSA patients with RH, including smoking, heart disease, neck circumference, AHI and T90. The nomogram established on the basis of variables above was shown to have good discrimination and calibration in both the training set and validation set. Decision curve analysis indicated that the nomogram was useful for a majority of OSA patients. Therefore, our nomogram might be useful to identify OSA patients at high risk of developing RH and facilitate the individualized management of OSA patients in clinical practice.

Cancer Mutations Converge on a Collection of Protein Assemblies to Predict Resistance to Replication Stress

Rapid proliferation is a hallmark of cancer associated with sensitivity to therapeutics that cause DNA replication stress (RS). Many tumors exhibit drug resistance, however, via molecular pathways that are incompletely understood. Here, we develop an ensemble of predictive models that elucidate how cancer mutations impact the response to common RS-inducing (RSi) agents. The models implement recent advances in deep learning to facilitate multidrug prediction and mechanistic interpretation. Initial studies in tumor cells identify 41 molecular assemblies that integrate alterations in hundreds of genes for accurate drug response prediction. These cover roles in transcription, repair, cell-cycle checkpoints, and growth signaling, of which 30 are shown by loss-of-function genetic screens to regulate drug sensitivity or replication restart. The model translates to cisplatin-treated cervical cancer patients, highlighting an RTK-JAK-STAT assembly governing resistance. This study defines a compendium of mechanisms by which mutations affect therapeutic responses, with implications for precision medicine.

SIGNIFICANCE

Zhao and colleagues use recent advances in machine learning to study the effects of tumor mutations on the response to common therapeutics that cause RS. The resulting predictive models integrate numerous genetic alterations distributed across a constellation of molecular assemblies, facilitating a quantitative and interpretable assessment of drug response. This article is featured in Selected Articles from This Issue, p. 384.

Role of HOXA1-4 in the development of genetic and malignant diseases

The HOXA genes, belonging to the HOX family, encompass 11 members (HOXA1-11) and exert critical functions in early embryonic development, as well as various adult processes. Furthermore, dysregulation of HOXA genes is implicated in genetic diseases, heart disease, and various cancers. In this comprehensive overview, we primarily focused on the HOXA1-4 genes and their associated functions and diseases. Emphasis was placed on elucidating the impact of abnormal expression of these genes and highlighting their significance in maintaining optimal health and their involvement in the development of genetic and malignant diseases. Furthermore, we delved into their regulatory mechanisms, functional roles, and underlying biology and explored the therapeutic potential of targeting HOXA1-4 genes for the treatment of malignancies. Additionally, we explored the utility of HOXA1-4 genes as biomarkers for monitoring cancer recurrence and metastasis.

Targeting TAM-secreted S100A9 effectively enhances the tumor-suppressive effect of metformin in treating lung adenocarcinoma

Metformin's effect on tumor treatment was complex, because it significantly reduced cancer cell proliferation in vitro, but made no difference in prognosis in several clinical cohorts. Our transcriptome sequencing results revealed that tumor-associated macrophage (TAM) infiltration significantly increased in active lung adenocarcinoma (LUAD) patients with long-term metformin use. We further identified that the tumor suppressive effect of metformin was more significant in mice after the depletion of macrophages, suggesting that TAMs might play an important role in metformin's effects in LUAD. Combining 10X Genomics single-cell sequencing of tumor samples, transcriptome sequencing of metformin-treated TAMs, and the ChIP-Seq data of the Encode database, we identified and validated that metformin significantly increased the expression and secretion of S100A9 of TAMs through AMPK-CEBP/β pathway. For the downstream, S100A9 binds to RAGE receptors on the surface of LUAD cells, and then activates the NF-κB pathway to promote EMT and progression of LUAD, counteracting the inhibitory effect of metformin on LUAD cells. In cell-derived xenograft models (CDX) and patient-derived xenograft models (PDX) models, our results showed that neutralizing antibodies targeting TAM-secreted S100A9 effectively enhanced the tumor suppressive effect of metformin in treating LUAD. Our results will enable us to better comprehend the complex role of metformin in LUAD, and advance its clinical application in cancer treatment.

New perspectives on the potential of tetrandrine in the treatment of non-small cell lung cancer: bioinformatics, Mendelian randomization study and experimental investigation

BACKGROUND

Although there are numerous treatment methods for NSCLC, long-term survival remains a challenge for patients. The objective of this study is to investigate the role and causal relationship between the target of tetrandrine and non-small cell lung cancer (NSCLC) through transcriptome and single-cell sequencing data, summary-data-based Mendelian Randomization (SMR) and basic experiments. The aim is to provide a new perspective for the treatment of NSCLC.

METHODS

We obtained the drug target gene of tetrandrine through the drug database, and then used the GSE19188 data set to obtain the NSCLC pathogenic gene, established a drug-disease gene interaction network, screened out the hub drug-disease gene, and performed bioinformatics and tumor cell immune infiltration analysis. Single-cell sequencing data (GSE148071) to determine gene location, SMR to clarify causality and drug experiment verification.

RESULTS

10 drug-disease genes were obtained from 213 drug targets and 529 disease genes. DO/GO/KEGG analysis showed that the above genes were all related to the progression and invasion of NSCLC. Four drug-disease genes were identified from a drug-disease PPI network. These four genes were highly expressed in tumors and positively correlated with plasma cells, T cells, and macrophages. Subsequent single-cell sequencing data confirmed that these four genes were distributed in epithelial cells, and SMR analysis revealed the causal relationship between CCNA2 and CCNB1 and the development of NSCLC. The final molecular docking and drug experiments showed that CCNA2 and CCNB1 are key targets for tetrandrine in the treatment of NSCLC.

Role of interferon regulatory factor 5 (IRF5) in tumor progression: Prognostic and therapeutic potential

Canonically, the transcription factor interferon regulatory factor 5 (IRF5) is a key mediator of innate and adaptive immunity downstream of pathogen recognition receptors such as Toll-like receptors (TLRs). Hence, dysregulation of IRF5 function has been widely implicated in inflammatory and autoimmune diseases. Over the last few decades, dysregulation of IRF5 expression has been also reported in hematologic malignancies and solid cancers that support a role for IRF5 in malignant transformation, tumor immune regulation, clinical prognosis, and treatment response. This review will provide an in-depth overview of the current literature regarding the mechanisms by which IRF5 functions as either a tumor suppressor or oncogene, its role in metastasis, regulation of the tumor-immune microenvironment, utility as a prognostic indicator of disease, and new developments in IRF5 therapeutics that may be used to remodel tumor immunity.

Molecular Networks of Platinum Drugs and Their Interaction with microRNAs in Cancer

The precise mechanism of resistance to anti-cancer drugs such as platinum drugs is not fully revealed. To reveal the mechanism of drug resistance, the molecular networks of anti-cancer drugs such as cisplatin, carboplatin, oxaliplatin, and arsenic trioxide were analyzed in several types of cancers. Since diffuse-type stomach adenocarcinoma, which has epithelial-mesenchymal transition (EMT)-like characteristics, is more malignant than intestinal-type stomach adenocarcinoma, the gene expression and molecular networks in diffuse- and intestinal-type stomach adenocarcinomas were analyzed. Analysis of carboplatin revealed the causal network in diffuse large B-cell lymphoma. The upstream regulators of the molecular networks of cisplatin-treated lung adenocarcinoma included the anti-cancer drug trichostatin A (TSA), a histone deacetylase inhibitor. The upstream regulator analysis of cisplatin revealed an increase in FAS, BTG2, SESN1, and CDKN1A, and the involvement of the tumor microenvironment pathway. The molecular networks were predicted to interact with several microRNAs, which may contribute to the identification of new drug targets for drug-resistant cancer. Analysis of oxaliplatin, a platinum drug, revealed that the SPINK1 pancreatic cancer pathway is inactivated in ischemic cardiomyopathy. The study showed the importance of the molecular networks of anti-cancer drugs and tumor microenvironment in the treatment of cancer resistant to anti-cancer drugs.

Cell cycle-specific phosphorylation of p53 protein in A549 cells exposed to cisplatin and standardized air pollutants

Exposure to particulate matter is associated with DNA damage and the risk of lung cancer. Protein p53 is activated by multi-site phosphorylation in the early stages of DNA damage and affects cell outcome. Our study aimed to assess the effect of (100 µg/mL-1/24 h) standardized air pollutants: carbon black (CB), urban dust (UD), and nanoparticle carbon black (NPCB) on cell cycle, DNA damage and 53 phosphorylation at Ser 9, Ser 20, Ser 46, and Ser 392 in proliferating and quiescent A549 cells and in cells that survived cisplatin (CisPT) exposure. Phosphorylated p53 was quantified in cell subpopulations by flow cytometry using specific fluorochrome-tagged monoclonal antibodies and analysis of bivariate fluorescence distribution scatterplots. CisPT, UD and NPCB increased site-specific p53 phosphorylation producing unique patterns. NPCB activated all sites irrespectively on the cell cycle, while the UD was more selective. p53 Ser 9-P and p53 Ser 20-P positively correlated with the numbers of CisPT-treated cells at G0/G1, and NPCB and NPCB + CisPT produced a similar effect. A positive correlation and integrated response were also found between Ser 20-P and Ser 392-P in resting A549 cells treated with NPCB and CisPT but not UD. Interdependence between the expression of p53 phosphorylated at Ser 20, and Ser 392 and cell cycle arrest show that posttranslational alterations are related to functional activation. Our data suggest that p53 protein phosphorylation in response to specific DNA damage is driven by multiple independent and integrated pathways to produce functional activation critical in cancer prevention and treatment.

The genomic signature of resistance to platinum-containing neoadjuvant therapy based on single-cell data

BACKGROUND

Neoadjuvant chemotherapy (NACT) becomes the first-line option for advanced tumors, while patients who are not sensitive to it may not benefit. Therefore, it is important to screen patients suitable for NACT.

METHODS

Single-cell data of lung adenocarcinoma (LUAD) and esophageal squamous carcinoma (ESCC) before and after cisplatin-containing (CDDP) NACT and cisplatin IC50 data of tumor cell lines were analyzed to establish a CDDP neoadjuvant chemotherapy score (NCS). Differential analysis, GO, KEGG, GSVA and logistic regression models were performed by R. Survival analysis were applied to public databases. siRNA knockdown in A549, PC9, TE1 cell lines, qRT-PCR, western-blot, cck8 and EdU experiments were used for further verification in vitro.

RESULTS

485 genes were expressed differentially in tumor cells before and after neoadjuvant treatment for LUAD and ESCC. After combining the CDDP-associated genes, 12 genes, CAV2, PHLDA1, DUSP23, VDAC3, DSG2, SPINT2, SPATS2L, IGFBP3, CD9, ALCAM, PRSS23, PERP, were obtained and formed the NCS score. The higher the score, the more sensitive the patients were to CDDP-NACT. The NCS divided LUAD and ESCC into two groups. Based on differentially expressed genes, a model was constructed to predict the high and low NCS. CAV2, PHLDA1, ALCAM, CD9, IGBP3 and VDAC3 were significantly associated with prognosis. Finally, we demonstrated that the knockdown of CAV2, PHLDA1 and VDAC3 in A549, PC9 and TE1 significantly increased the sensitivity to cisplatin.

CONCLUSIONS

NCS scores and related predictive models for CDDP-NACT were developed and validated to assist in selecting patients who might benefit from it.

RNA methylation and cellular response to oxidative stress-promoting anticancer agents

Disruption of the complex network that regulates redox homeostasis often underlies resistant phenotypes, which hinder effective and long-lasting cancer eradication. In addition, the RNA methylome-dependent control of gene expression also critically affects traits of cellular resistance to anti-cancer agents. However, few investigations aimed at establishing whether the epitranscriptome-directed adaptations underlying acquired and/or innate resistance traits in cancer could be implemented through the involvement of redox-dependent or -responsive signaling pathways. This is unexpected mainly because: i) the effectiveness of many anti-cancer approaches relies on their capacity to promote oxidative stress (OS); ii) altered redox milieu and reprogramming of mitochondrial function have been acknowledged as critical mediators of the RNA methylome-mediated response to OS. Here we summarize the current state of understanding on this topic, as well as we offer new perspectives that might lead to original approaches and strategies to delay or prevent the problem of refractory cancer and tumor recurrence.

A glycolysis-related gene signatures in diffuse large B-Cell lymphoma predicts prognosis and tumor immune microenvironment

Background: Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma which that highly aggressive and heterogeneous. Glycolysis has been implicated in the regulation of tumor microenvironment (TME) and development. In this study, we aimed to establish a glycolysis-related prognostic model for the risk stratification, prognosis prediction, and immune landscape evaluation in patients with DLBCL. Methods: Three independent datasets GSE181063, GSE10846, and GSE53786 containing gene expression profiles and clinical data were downloaded from the Gene Expression Omnibus (GEO) database. The glycolysis-related prognostic model was developed with Cox and Least Absolute Shrinkage and Selector Operation (LASSO) regression and validated. A nomogram integrating clinical factors and glycolytic risk scores was constructed. The composition of the TME was analyzed with the ESTIMATE algorithm and single-sample gene set enrichment analysis (ssGSEA). Results: A glycolytic risk model containing eight genes was developed. The area under the receiver operating characteristic (ROC) curve (AUC) for the 1-, 3-, and 5-year was 0.718, 0.695, and 0.688, respectively. Patients in the high-risk group had significantly lower immune scores, elevated tumor purity, and poorer survival compared with those in the low-risk group. The nomogram constructed based on glycolytic risk score, age, Eastern Cooperative Oncology Group performance status (ECOG-PS), use of rituximab, and cell of origin (COO) displayed better prediction performance compared with the International Prognostic Index (IPI) in DLBCL. The glycolytic risk score was negatively correlated with the infiltration level of activated CD8 T cells, activated dendritic cells, natural killer cells, and macrophages and immune checkpoint molecules including PD-L2, CTLA4, TIM-3, TIGIT, and B7-H3. Conclusion: These results suggested that the glycolytic risk model could accurately and stably predict the prognosis of patients with DLBCL and might unearth the possible explanation for the glycolysis-related poor prognosis.

A deep tabular data learning model predicting cisplatin sensitivity identifies BCL2L1 dependency in cancer

Cisplatin, a platinum-based chemotherapeutic agent, is widely used as a front-line treatment for several malignancies. However, treatment outcomes vary widely due to intrinsic and acquired resistance. In this study, cisplatin-perturbed gene expression and pathway enrichment were used to define a gene signature, which was further utilized to develop a cisplatin sensitivity prediction model using the TabNet algorithm. The TabNet model performed better (>80 % accuracy) than all other machine learning models when compared to a wide range of machine learning algorithms. Moreover, by using feature importance and comparing predicted ovarian cancer patient samples, BCL2L1 was identified as an important gene contributing to cisplatin resistance. Furthermore, the pharmacological inhibition of BCL2L1 was found to synergistically increase cisplatin efficacy. Collectively, this study developed a tool to predict cisplatin sensitivity using cisplatin-perturbed gene expression and pathway enrichment knowledge and identified BCL2L1 as an important gene in this setting.

HNF4G increases cisplatin resistance in lung adenocarcinoma via the MAPK6/Akt pathway

Background

Lung adenocarcinoma is one of the most common tumors, and cisplatin is frequently used in treating lung adenocarcinoma patients. This study aimed to look into the roles and mechanisms of HNF4G in cisplatin resistance of lung adenocarcinoma.

Materials & Methods

Cisplatin resistance and gene expression data of 542 cell lines from the CTRP and CCLE databases were analyzed. HNF4G expression was detected in the lung adenocarcinoma cell lines after treatment with various concentrations of cisplatin. Cisplatin sensitivity curves were detected in cells that overexpressed or knocked down HNF4G. The ChIP-Seq data were then analyzed to identify the targets of HNF4G involved in cisplatin resistance. Expression and phosphorylation of the MAPK6/Akt pathway were detected after HNF4G was overexpressed or knocked down. Finally, ChIP-qPCR and dual-luciferase assays were used to investigate the regulation of HNF4G on MAPK6.

Results

In cell lines, high expression of HNF4G was significantly positively correlated with cisplatin resistance, and lung adenocarcinoma patients who had high HNF4G expression had a poor prognosis. Cisplatin treatment increased HNF4G expression, and overexpression of HNF4G significantly increased the resistance to cisplatin in A549 and HCC827 cells, whereas knockdown of HNF4G had the opposite effect. HNF4G overexpression increased MAPK6 expression and activated the MAPK6/Akt pathway, while an Akt inhibitor reduced the effects of HNF4G on cisplatin resistance. HNF4G bound to the MAPK6 promoter region, promoting MAPK6 expression, according to ChIP-qPCR and luciferase assays.

Conclusion

By binding to the MAPK6 promoter region, HNF4G promotes MAPK6 expression and subsequent Akt phosphorylation, resulting in resistance to cisplatin in lung adenocarcinoma.

Genomic characteristics of two breast malignant phyllodes tumors during pregnancy and lactation identified through whole-exome sequencing

Background

The genomic landscape of breast malignant phyllodes tumors (PTs) is not well defined, especially pregnancy-related malignant PTs. To clarify this topic, whole-exome next-generation sequencing (NGS) was performed on tumor samples and paired normal breast tissues from two pregnancy-related malignant PTs, followed by a functional analysis of the genetic alterations.

Methods

DNA from malignant PT samples and matched normal breast tissues of both patients were subjected to molecular profiling. NGS of the whole-exome was performed in a commercial molecular pathology laboratory. Predictive tools were used to estimate genetic variation in somatic and germline genes.

Results

In total, 29 somatic genomic alterations and 18 germline alterations were found in both patients. In Patient 1, 12 aberrations were identified in the tumor tissue, and 9 alterations were identified in matched normal breast tissue. One pathogenic variant in tumor suppressor genes (TP53) was detected in patient 1. In Patient 2, 18 and 10 variants were found in the tumor and matched normal breast tissue, respectively. In Patient 2, pathogenic alterations were identified in two tumor suppressor genes (PTEN and TP53). PTEN and TP53 may be potential drug targets. The functional predictive tools showed that genes of unknown significance for PTs, including FCHO1 in Patient 1, and LRP12 and PKM in Patient 2, were pathogenic. Several genes, including FCHO1, LRP12 and PKM, were shown for the first time to be altered in malignant PTs. A potentially pathogenic germline variant in PRF1, was detected in Patient 1.

Conclusion

Our study first demonstrated somatic and germline gene alterations in two malignant PTs during pregnancy and lactation. These two PTs shared major genetic events, including TP53 mutation, which commonly occurs in malignant PTs; additionally, we identified two potential genes for targeted therapy, TP53 and PTEN. One germline mutation in PRF1 was also detected. These results provide clues regarding tumor pathogenesis and precision therapy development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-022-02537-w.

HOXA1 is a radioresistance marker in multiple cancer types

Radiotherapy is an important therapeutic method for patients with cancer. However, radioresistance can cause treatment failure. Thus, there is an urgent need to investigate mechanisms of radioresistance and identity markers that could be used to predict radioresistance and prognosis of post-radiotherapy cancer patients. In the present study, we propose HOXA1 as a candidate biomarker of intrinsic radioresistance in multiple cancer types. By analyzing data from The Cancer Genome Atlas (TCGA), we found that HOXA1 was aberrantly upregulated in multiple cancers, and that elevated HOXA1 was significantly associated with poor prognosis of post-radiotherapy head and neck squamous cell carcinoma (HNSCC) and low-grade glioma (LGG) patients. Correlation analysis showed that HOXA1 expression was positively correlated with expression of EGFR, CDK6, and CAV1, which have been reported to enhance radioresistance. In addition, gene set enrichment analysis (GSEA) showed that the oxidative phosphorylation gene set was negatively enriched in HOXA1 high-expression samples in both HNSCC and LGG. Moreover, immunohistochemical assays indicated that high HOXA1 expression was significantly correlated with a high recurrence rate of nasopharyngeal carcinoma (NPC) after radiotherapy. Further in vitro experiments demonstrated that HOXA1 knockdown markedly attenuated the DNA repair capacity of NPC cells and sensibilized NPC cells to irradiation. Taken together, the results of this study demonstrate that HOXA1 has potential to be a predictive marker for radioresistance and post-radiotherapy prognosis that could help to guide individualized treatment in multiple cancer types.