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. 2026 Apr 4;17:752. doi: 10.1007/s12672-026-04693-y

Multi-omics analysis reveals the role of the XRCC gene family in diagnosis, prognosis, and immunity in pan-cancer

Jianhui Chen 1,#, Hantian Guan 2,#, Yitian Bai 2,#, Yangyang Guo 2,3, Xuejian Wang 4,✉, Dandan Wang 5,✉
PMCID: PMC13199539  PMID: 41934520

Abstract

Members of the XRCC family have been reported to be closely associated with the initiation and progression of certain human cancers. The purpose of this study is to comprehensively analyze the role of the XRCC family in pan-cancer. In this study, we primarily utilized data downloaded from The Cancer Genome Atlas (TCGA). We investigated the prognostic significance of the XRCC family and its association with tumor mutation burden (TMB), microsatellite instability (MSI), drug sensitivity, and immunotherapy in several human cancers. The findings indicated that the expression of the XRCC family was primarily upregulated in most tumors. The XRCC family was associated with the prognosis of cancer patients. Then, XRCC family genes showed a significant association with tumor immune microenvironment and tumor cell stemness. Finally, we also analyzed the potential role of the XRCC family in cancer therapy. This study conducts a comprehensive analysis of the role of the XRCC family in pan-cancer, which contributes to providing a potential direction for cancer diagnosis and treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12672-026-04693-y.

Keywords: XRCC family, Pan-cancer, Diagnosis, Prognosis, Immunity

Introduction

Nowadays, cancer has become a major cause of death in the world, as well as an obstacle to preventing life extension [1]. The hallmarks of cancer consist of continuous proliferation, avoidance of growth suppressors, resistance to cell death, unlimited replication, angiogenesis, migration and invasion, reprogramming of energy metabolism, and immune escape [2]. These hallmarks are based on genomic instability. The progression of tumors is closely related to the tumor microenvironment, which is believed to influence the growth and metastasis of tumors. The tumor microenvironment also contributes to the immune escape of tumor tissue [3]. Therefore, tumor markers that can change the biological function or immune microenvironment of the tumor will help improve the prognosis of tumor patients. Meanwhile, with the development of bioinformatics, an increasing number of tumor markers have been identified and excavated [4–7].

DNA damage repair (DDR) is a response of cells to DNA damage. If DNA damage is not effectively repaired, genomic instability and mutation will be formed, which is the basis for the emergence of cancer [2]. The X-ray repair cross-complementing (XRCC) gene family mainly includes XRCC1, XRCC2, XRCC3, XRCC4, XRCC5, and XRCC6, which are important components of the DNA repair pathway [8]. The abnormal expression of XRCC family genes could affect the process of DNA repair, leading to the progress of cancer [9–12]. On the other hand, the DNA damage repair mechanism also provides a novel direction for cancer treatment.

Previous studies have demonstrated that genetic polymorphisms and abnormal expression of XRCC family genes are closely associated with the prognosis of various cancers [13, 14]. However, existing research still has notable gaps. Most studies focus on the biological function of a single XRCC member in specific tumor types, lacking a systematic pan-cancer analysis of the expression patterns and clinical significance of the entire XRCC family. The potential driving mechanisms of XRCC family dysregulation in tumors remain unclear, and the regulatory links between XRCC family and tumor microenvironment (TME), cancer stem cell (CSC) stemness, and drug resistance have not been fully elucidated. In addition, the specific biomarker value of different XRCC members for tumor prognosis and immunotherapy response needs further refinement. To address these gaps, we conducted a comprehensive pan-cancer analysis of the XRCC family to clarify its expression characteristics, clinical prognostic value, and correlation with TME, TMB/MSI, CSC stemness, and drug sensitivity, and further explore its potential as a tumor diagnostic/prognostic biomarker and therapeutic target. This study may offer novel molecular insights for the diagnosis and treatment of cancers.

Methods

Data download

We downloaded TCGA (The Cancer Genome Atlas) data on 33 types of cancer from the Xena Browser website (https://xenabrowser.net/datapages/) for analysis in this study. These data included RNA-Seq (HTSeq-FPKM), clinical data (phenotype and survival data), immune subtypes, mutation data, DNA methylation-induced tumor stem cell properties (DNAss), and mRNA induced tumor stem cell properties (RNAss) data. We downloaded the transcriptome data and drug sensitivity data from the CellMiner website (https://discover.nci.nih.gov/cellminer/home.do).

Pan-cancer analysis

We retained cancers with ≥ 5 matching normal tissues for pan-cancer expression analysis. The “ggpubr” R package was performed to reveal the expression characteristic of the XRCC gene family. Finally, the gene expression heatmap made by the “pheatmap” R package presented our results. Correlation among members of the XRCC family was analyzed using the “corrplot” R package.

Prognostic analysis

We successively utilized Cox analysis and Kaplan–Meier curves to show the pan-cancer prognosis of the XRCC gene family. The results obtained from Cox analysis were ultimately visualized using forest plots.

Tumor microenvironment and tumor stemness analysis

We run the “estimate” R package to obtain StromalScore, ImmuneScore, ESTIMATEScore, and TumorPurity of each tumor sample. We utilized data related to immune subtypes to analyze the association between XRCC family genes and six distinct immune subtypes (C1, C2, C3, C4, C5, and C6). We utilized the Spearman correlation coefficient to analyze the association between the XRCC family and tumor stem cell properties. We explored the effect of XRCC gene family members on the immune microenvironment of lung adenocarcinoma via online analysis of Timer 3.0 (https://compbio.cn/timer3/) [15]. The IMvigor210 dataset was selected as the anti-PD-L1 immunotherapy cohort for this research to assess the correlation between the XRCC family and the effectiveness of anti-PD-L1 therapy.

Drug sensitivity analysis

Drug sensitivity-related datasets were downloaded from the Cellminer database. Finally, the visualization of the results was achieved via R studio.

Tumor mutation burden (TMB) and microsatellite instability (MSI) analysis

TMB refers to the total number of mutations per megabase in tumor tissue. MSI refers to the phenomenon where the mismatch repair mechanism (MMR) fails during DNA replication, causing changes in the length of microsatellites. Based on the TCGA mRNA transcriptome, the correlation between the XRCC family members and MSI/TMB was executed by the “ggstatsplot” R package.

Sample acquisition and quantitative reverse transcription‑polymerase chain reaction (qRT‑PCR)

In this study, 4 pairs of breast cancer tissues and their adjacent normal tissues, as well as 4 pairs of liver cancer tissues and their adjacent normal tissues were collected from The First Affiliated Hospital of Ningbo University for subsequent validation analyses. We extracted total RNA from tissues using TRIZOL reagent (Takara, Japan) and measured the RNA quantity using a spectrophotometer. SYBR Green was used to detect the mRNA expression levels in normal and tumor tissues by qRT-PCR. GAPDH was utilized as the internal standard in qRT-PCR experiments. This research was approved by the Ethics Committee of the First Affiliated Hospital of Ningbo University.

Statistical analyses

TIMER was used to examine the immune infiltration of the XRCC family in lung adenocarcinoma. All other results were analyzed using the 4.0 version of R and corresponding R packages. Among all the results, P < 0.05 was recognized as having significant statistical differences.

Results

The expression characteristics of the XRCC family in pan-cancer

At the beginning of this research, we examined the expression levels of six XRCC family members in pan-cancer. The results demonstrated that the expression levels of XRCC5 and XRCC6 were relatively high, with XRCC1 exhibiting an intermediate level, whereas XRCC2, XRCC3, and XRCC4 had lower expression levels (Fig. 1A). Then, we conducted a further analysis of the expression characteristics of the XRCC family across various cancers. The XRCC family members exhibited an abnormally upregulated expression trend in most malignant tumors compared to normal tissues (Fig. 1B-G). However, an opposite trend can also be observed in certain tumors. For example, the expression levels of XRCC1, XRCC4, XRCC5, and XRCC6 in normal kidney tissue were higher than those in KICH. XRCC4 showed downregulation in PRAD, and XRCC5 and XRCC6 also showed similar trends in KIRC. The heatmap visually illustrated the expression patterns of XRCC family members across various types of cancers. (Fig. 1H). There was a broad correlation among the XRCC family members, with XRCC2 and XRCC3 having the most significant positive correlation (Correlation coefficient = 0.6) (Fig. 1I).

Fig. 1.

Fig. 1

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The expression level of XRCC family in pan cancer. (A)The overall expression of the XRCC family in 33 types of cancer. (B) XRCC1, (C) XRCC2, (D) XRCC3, (E) XRCC4, (F) XRCC5, (G) XRCC6 expression levels in different cancers (red) and normal tissue (blue). (H) Expression of XRCC family members in different types of cancers. (I) Expression correlation among members of the XRCC family

Prognostic value of XRCC family

We performed a Cox analysis to assess the predictive value of XRCC family members in pan-cancer (Fig. 2). XRCC1 was a protective factor in BRCA(HR < 1) and a risk factor in LGG(HR > 1). XRCC2 was associated with poor prognosis in patients suffering from various types of cancer, including ACC, KICH, KIRC, KIRP, LGG, LIHC, MESO, PAAD, PCPG, and SARC (HR > 1). However, XRCC2 was defensive in THYM (HR < 1). XRCC3 predicted poor prognosis in ACC, KIRC, LIHC, PCPG, and PRAD patients (HR > 1). XRCC4 played a predictive role in the prognosis of patients with BRCA, KICH, LIHC, and SKCM. XRCC5 predicted a negative prognosis in ACC, LIHC, LUAD, PAAD, and UVM patients (HR > 1), yet a favorable prognosis in KIRC patients (HR < 1). XRCC6 was associated with the prognosis of patients with ACC, KICH, LAML, LIHC, LUAD, DLBC, ESCA, PCPG, and READ.

Fig. 2.

Fig. 2

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Univariate Cox regression analysis the prognosis of XRCC family members across 33 cancer types. HR < 1 represents low risk and HR > 1 represents high risk

Then, we used Kaplan–Meier survival curves to further analyze the prognostic role of XRCC family members in pan-cancer (Fig. 3). Among the six members of the XRCC family, XRCC1 was predictive of a poor prognosis in patients with LGG. By contrast, in patients with CESC and LUSC, it indicated a better prognosis. Up-regulated XRCC2 was strongly associated with poor prognosis in ACC, BRCA, KICH, KIRC, KIRP, LGG, LIHC, LUAD, MESO, PAAD and PCPG patients. In CESC, DLBC, and THYM, up-regulated XRCC3 predicted longer survival time. However, in ACC, KIRC, LIHC, PCPG, and UVM, XRCC3 was found to be a detrimental factor. XRCC4 predicted a better prognosis in KIRC, but the opposite holds in UCEC. Up-regulated XRCC5 was shown to be harmful in ACC, LIHC, LUAD, and PAAD, but it was advantageous in KIRC. In DLBC, PCPG, READ, and THYM, XRCC6 played a protective role. XRCC6 predicted poor prognosis in patients with ACC, LIHC, and LUAD.

Fig. 3.

Fig. 3

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Kaplan–Meier survival curves comparing the prognostic differences of XRCC family members in different cancers between high and low expression groups (p < 0.05).

The roles of the XRCC family in the TME

The tumor microenvironment is inextricably associated with the genesis, progression, and prognosis of tumors. We performed the immune infiltration analysis to explore the roles of XRCC family members in the tumor microenvironment. The results demonstrated that XRCC family members exhibited different expression patterns in different immune subtypes (P < 0.05)(Fig. 4A). Interestingly, members of the XRCC family exhibited high expression levels in subtypes C1 and C2. Apart from XRCC4, we found XRCC family members presented a negative correlation with the ImmuneScore, StromalScore, and ESTIMATEScore in most types of tumors. There was a significant positive correlation between XRCC4 and StromalScore in BLCA, LAML, LUAD, PCPG, SARC, and THCA. Similar results were found in the analysis of XRCC4 with ImmuneScore and ESTIMATEScore. These findings demonstrated that the XRCC family have potential roles in the tumor microenvironment (Fig. 4B). We revealed that elevated expressions of XRCC family members, except for XRCC4, were associated with objective response to anti-PD-L1 treatment via the IMvigor210 cohort (Fig. 5).

Fig. 4.

Fig. 4

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The role of XRCC family in the tumor immune microenvironment. (A) Differential expression of XRCC family members in different immune subtypes. (B) The relationship of XRCC family members expression levels with the ImmuneScore, StromalScore , ESTIMATEScore and TumorPurity

Fig. 5.

Fig. 5

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Expression of XRCC family in the IMvigor210 cohort.

Tumor stemness analysis of the XRCC family

We analyzed RNAss and DNAss using the TCGA tumor stemness database to estimate the association between the XRCC family members and tumor stemness. We found a closely positive correlation between XRCC family members and RNAss in most tumors. In terms of DNAss, THYM had a negatively significant correlation with the XRCC family. TGCT was positively correlated with XRCC family except for XRCC1 (Fig. 6).

Fig. 6.

Fig. 6

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The correlation between XRCC family members and RNAss and DNAss

The correlation between XRCC and TMB/MSI

We analyzed the association of XRCC family members with TMB/MSI. We found that the expressions of XRCC family members were correlated with TMB and MSI in various tumors (Fig. 7).

Fig. 7.

Fig. 7

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The relationship of XRCC family members expression levels with TMB and MSI

Drug sensitivity analysis of the XRCC family

To further explore the value of XRCC family members in tumor therapy, we performed a drug sensitivity analysis. The drug activity of multiple drugs, including Chelerythrine, Nelarabine, Cladribine, Acrichine, PX-316, Cisplatin, Vorinostat, Olaparib, Fostamatinib, Procarbazine, Allopurinal were associated with XRCC family members (Fig. 8).

Fig. 8.

Fig. 8

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The correlation between the XRCC family and drug sensitivity

The roles of the XRCC family in LUAD

At present, lung cancer is still one of the cancers with the highest incidence rate in the world. Therefore, we further examined the immune infiltration levels of the XRCC family in LUAD using Timer. The results exhibited that the copy number of the XRCC family could affect the level of immune infiltration (Figure S1). In LUAD, the expressions of XRCC1 and XRCC3 showed the strongest positive correlation with CD4 + T cell. The expressions of XRCC2, XRCC4, and XRCC5 showed a significant positive correlation with neutrophil. XRCC6 showed a negative correlation with B cell and CD4 + T cell (Figure S2). Then, we identified the expressions of the XRCC family in different immune subgroups. This finding revealed that the XRCC family members were highly expressed in the C1 and C2 subgroups (Figure S3A). Moreover, we analyzed the correlation between the XRCC family and clinical characteristics of LUAD. As tumor staging progresses, the expressions of XRCC5 and XRCC6 gradually increased (Figure S3B). The XRCC family showed a positive correlation with DNAss and RNAss. XRCC4 was positively correlated with ImmuneScore, StromalScore, and ESTIMATEScore, while other family members showed opposite trends (Figure S4).

 Expression characteristics of XRCC family members in BRCA and LIHC

We identified the mRNA expressions of the collected tissue samples. Whether in BRCA or LIHC, the mRNA expression levels of XRCC family members in tumor tissues were higher than those in adjacent tissues (Fig. 9).

Fig. 9.

Fig. 9

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The expression of XRCC family members in LIHC and BRCA

Discussion

The XRCC family plays a significant role in DNA damage repair and genetic stability [16]. Previous studies have demonstrated that the polymorphism of XRCC family genes was intimately related to the prognosis of various cancers [17]. In this research, we conducted a systematic analysis of the expression patterns of XRCC family members across various cancers. The results indicated that compared to adjacent tissues, the XRCC family members generally exhibited an upregulated expression trend in most tumors. However, there were also opposite situations. For example, XRCC1 was downregulated in KICH. The expression of XRCC4 in KICH and PRAD was lower than that in corresponding adjacent cancer tissues. The expressions of XRCC5 and XRCC6 were downregulated in both KICH and KIRC. Then, we identified the expression characteristics of the XRCC family in the collected clinical samples using qPCR technology. The results demonstrated that the members of the XRCC family were abnormally upregulated in both BRCA and LIHC, which is consistent with our pan-cancer analysis results. These findings suggested that XRCC family members had potential as diagnostic biomarkers in LIHC and BRCA, providing a basis for clinical early screening.

The universal upregulation of the XRCC family in most tumors is not a random phenomenon, but may be driven by multiple molecular mechanisms that synergistically regulate the DDR pathway to adapt to the high genomic instability state of tumor cells. First, cancer-specific genomic instability is a core initiating factor. Tumor cells exhibit massive DNA damage during rapid proliferation, and the body activates the DDR pathway in a compensatory manner, leading to the upregulation of XRCC family members to enhance DNA repair capacity and ensure tumor cell survival [9]. Second, abnormal activation of upstream signaling pathways plays a regulatory role. ATM/ATR pathway is the key sensor of DNA double-strand breaks, and its abnormal activation in tumors can directly bind to the promoter regions of XRCC2/3 and promote their transcription [18, 19]. The expression of XRCC1 is regulated by p53 and STAT3 [20, 21]. In addition, Epigenetic regulation, such as promoter methylation, may also be involved in the expression of XRCC family genes [22]. These mechanisms jointly drive the dysregulation of the XRCC family in tumors, and their specific regulatory networks need to be further verified by molecular experiments.

In addition, we used Cox analysis and KM curve to examine the prognostic value of XRCC family members in pan-cancer by integrating the mRNA transcriptome data of the TCGA database with clinical data. The results indicated that the expression of XRCC family genes may be correlated with the prognosis of patients with certain types of tumors. Combined with the results of KM curve and Cox analysis, we concluded that XRCC1 may serve as a prognostic biomarker for LGG; XRCC2 for ACC, KICH, KIRC, KIRP, LGG, LIHC, MESO, PAAD, and PCPG; XRCC3 for ACC, KIRC, LIHC, and PCPG; XRCC5 for ACC, LIHC, LUAD, and PAAD; and XRCC6 for ACC, LIHC, and LUAD. In addition, Wang et al. also found that high expression of XRCC1 was closely related to poor prognosis in patients with gallbladder cancer [23]. This finding contributed to improving and perfecting our pan-cancer analysis of XRCC1. Previous studies have reported some different perspectives. For example, high XRCC1 protein expression was associated with poorer survival in HNSC patients [24], and glioblastoma patients with high XRCC5 expression had poorer prognosis outcomes [25]. Shouyu Wang et al. found that the expression of XRCC1 was down-regulated in gastric cancer, and low expression of XRCC1 indicated a shorter survival time [26]. These reports were inconsistent with our results, which may be due to differences in data collection methods or different effects of genetic biological characteristics. Therefore, further exploration through molecular experiments and clinical research is necessary.

Our pan-cancer results demonstrated a close correlation between the expression of the XRCC family and RNAss/DNAss. Meanwhile, recent studies have revealed that the XRCC family may maintain the stemness characteristics of cancer stem cells through multiple mechanisms, including enhancing the efficiency of DNA damage repair, mediating the synergistic crosstalk between the tumor microenvironment and cancer stem cells, and regulating downstream inflammatory/metabolic pathways [27–30]. Therefore, we hypothesize that high XRCC expression may promote CSC survival and self-renewal by maintaining genomic stability, thereby enhancing tumor chemoresistance and recurrence risk.

Vesteinn Thorsson et al. identified six immune subtypes in cancer types [31]. Therefore, we examined the correlation between the expressions of XRCC family members and immune subtypes in pan-cancer patients. Previous studies suggested that the C1 and C2 had poor prognoses, despite their abundant immune components. C4 and C6 had the worst prognosis [31]. Our pan-cancer analysis exhibited that XRCC family genes were highly expressed in C1 and C2. In this pan-cancer analysis, it was also revealed that members of the XRCC family were related to TME. The TME is a complex environment that includes tumor cells and their surrounding immune cells, tumor-associated fibroblasts, vascular endothelial cells, etc. It plays a pivotal role in the initiation, progression, invasion, and metastasis of cancers [32, 33]. ESTIMATE is an algorithm that uses gene expression signatures to infer tumor purity and the fraction of stromal and immune cell in tumor samples [34]. Tumors can influence DNA damage and repair pathways through the TME [35]. Dysfunctional expression of the XRCC family in tumor cells, on the one hand, induces genomic instability, which impinges on the generation and presentation of tumor neoantigens; on the other hand, it modulates the expression of immune-related molecules and the function of immune cells through the aberrant activation of the DDR signaling pathway, thereby shaping the phenotype of the tumor immune microenvironment [36, 37]. Our study revealed that in most tumors, the expression of most XRCC family members was negatively correlated with immune scores and stromal scores of the TME, suggesting that their expression was predominantly enriched in tumor cells rather than immune cells or stromal components. This indicated that high XRCC expression may corresponds to an immunosuppressive “cold tumor” phenotype characterized by sparse immune cell infiltration and reduced stromal content. High XRCC expression may contribute to tumor immune escape by reducing tumor immunogenicity and inhibiting the recruitment and infiltration of effector immune cells. Notably, the expression profile of XRCC4 in TME was significantly distinct from that of other XRCC family members: its expression level was positively correlated with both the immune score and stromal score of the TME in some tumors, indicating that XRCC4 exhibited unique functional heterogeneity in TME regulation. As a core component of the non-homologous end joining (NHEJ) pathway, XRCC4 may actively engage in the activation of the immune microenvironment by regulating innate immune signaling pathways (such as the cGAS-STING pathway) [38]. This functional feature was also consistent with the high expression of XRCC4 in the C2 subtype (IFN-γ Dominant), a typical “hot tumor” with robust immune activation. Future research will further focus on the tissue specificity and tumor-type specificity of immune differences among family members, deepen the analysis of regulatory networks of key molecules, develop precise combined immunotherapy strategies based on immune differential characteristics, and provide new ideas and support for individualized tumor treatment.

In recent years, immunotherapy has become a hotspot in cancer treatment, which has changed the treatment of several types of cancer. As predictive biomarkers for immunotherapy, the detection of MSI and TMB helps to distinguish patients who benefit from immune checkpoint inhibitors(ICIs) [39]. Germline or somatic mutations of genes in the mismatch repair (MMR) system or high methylation of the MLH15 gene promoter result in MMR deficiency (dMMR), leading to MSI [40]. In a research report on colon cancer, it was pointed out that dMMR colorectal cancers(CRCs) have higher mutations and more predicted numbers of neoantigens, which may render tumors more immunogenic and more likely to respond to immunotherapy [41]. Previous studies have reported that advanced CRC patients with dMMR can benefit from pembrolizumab, nivolumab, and nivolumab ipilimumab combination therapy [42–44]. High TMB may increase the ability of tumors to generate neoantigens. Compared to low TMB, high TMB was considered to enable patients to benefit more from multiple ICIs [45]. To date, there have been relatively few reports investigating the association between the XRCC family and MSI/TMB. Junya Fukuda et al. revealed that decreased expression of XRCC6 was associated with high TMB in pMMR colorectal cancer, suggesting that XRCC6 could serve as a potential biomarker for predicting the benefit of ICI therapy in patients with pMMR colorectal cancer [46].However, the specific underlying mechanism remains unclear. We hypothesize that abnormal XRCC expression may drive MSI and TMB elevation by regulating MMR and HR efficiency. This regulatory mechanism may enhance tumor sensitivity to ICIs by increasing neoantigen load. Our study found that XRCC family members were closely associated with MSI and TMB in various cancers, and XRCC1/2/3/5/6 were closely correlated with the response to anti-PD-L1 therapy, suggesting that the XRCC family may serve as a potential target for ICI treatment.

Drug sensitivity is an important factor affecting the effectiveness of drug therapy. Our study analyzed the correlation between XRCC family members and drug sensitivity using the CellMiner database, and combined with existing reports, we propose mechanistic hypotheses for key drugs. Olaparib, a PARP inhibitor targeting HR deficiency, may have enhanced efficacy in tumors with low XRCC2/3 expression—XRCC2/3 are core components of HR repair, and their downregulation may further aggravate HR deficiency, thereby increasing tumor sensitivity to Olaparib [47]. Cisplatin, which induces DNA interstrand crosslinks (ICL) and relies on nucleotide excision repair (NER) for damage repair, may have reduced efficacy in tumor cells with high XRCC1 expression—XRCC1 participates in NER and base excision repair (BER), and high expression may enhance DNA repair capacity, leading to cisplatin resistance [48]. In addition, Knockdown of XRCC3 significantly reduces the repair rate of DNA double-strand breaks (DSBs) after temozolomide treatment, thereby increasing drug sensitivity [49]. Knockdown of XRCC4 results in accumulated DNA damage and enhanced cisplatin sensitivity in ovarian cancer [50]. Several other studies on the XRCC family and sensitivity to other drugs have been reported. XRCC1 knockdown could improve the sensitivity of gallbladder cancer cells to 5-Fluorouracil [23]. Jiaojiao Shan et al. found that XRCC2 inhibited the sensitivity of non-small cell lung cancer to bevacizumab combined with radiotherapy [10]. Down-regulation of XRCC2 may enhance the sensitivity of CRC cells to 5-FU chemotherapy. XRCC5 have been found to be associated with temozolomide sensitivity in glioma cells [25]. Based on these core findings, the potential therapeutic directions are highlighted: (1) Develop XRCC family subtype-specific inhibitors to reverse Olaparib and Cisplatin resistance; (2) Construct combined therapy regimens: XRCC inhibitor + PARPi/platinum drugs for chemotherapy-resistant tumors; (3) Use the expression level of XRCC family members to screen patients who are sensitive to chemotherapy drugs, and implement personalized drug selection.

The in-depth LUAD analysis was a major strength of this study, and its XRCC regulatory pattern could be used as a paradigm for solid tumor research: the high expression of XRCC members in C1/C2, positive correlation with RNAss, and immune infiltration were common regulatory features of the XRCC family in solid tumors. However, tumor-specific unique features are also observed: for example, XRCC5 was downregulated in KIRC but upregulated in LUAD/BRCA/LIHC; the correlation between XRCC2 expression and TMB in LIHC was significantly weaker than that in LUAD/BRCA. These unique features were related to the specific genetic background, TME characteristics, and DDR pathway activity of different tumors, and required subtype-specific analysis and verification in subsequent research.

However, our research also has certain limitations. Although we have analyzed the prognostic roles of XRCC members in pan-cancer and their potential impact on the tumor microenvironment through bioinformatics, many experiments, including in vivo and in vitro experiments, are essential to verify.

Conclusions

Collectively, we conducted a systematic pan-cancer analysis on members of the XRCC family. Our research demonstrated the expressions and prognostic roles of the XRCC family in various cancers and further revealed the correlation between the XRCC family and the tumor microenvironment. Our results suggested that the XRCC family may have potential applications as tumor markers and provide new targets for tumor therapy.

Supplementary Information

Below is the link to the electronic supplementary material.

12672_2026_4693_MOESM1_ESM.docx (1,008.4KB, docx)

Supplementary Material 1. Figure S1. The correlation between SCNA of the XRCC family members and immune infiltration in LUAD. Figure S2. The correlation between the expression of XRCC family members and immune cell infiltration in LUAD. Figure S3. The role of XRCC family in LUAD progression. (A) Differential expression of XRCC family members in different LUAD immune subtypes. (B) The correlation between XRCC family and clinical characteristics of LUAD. Figure S4. The effect of XRCC family on tumor stemness and immune microenvironment in LUAD.

Acknowledgements

Not applicable.

Author contributions

Conceptualization, D.W. and X.W.; methodology, Y.G. and H.G.; software, Y.G.; validation, Y.T.; formal analysis, J.C. and H.G.; investigation, J.C. and H.G.; resources, D.W. and X.W.; writing—original draft preparation, J.C.; writing—review and editing, H.G. and Y.B.; funding acquisition, J.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by Medical and Healthcare Science and Technology Plan Project of Zhejiang Province (No:2024XY126), Medical and Health Science and Technology Project of Hangzhou(No: B20232071), Science and Technology Plan Project of Linping District(No: Lpwj2022-02-03).

Data availability

The data used in this research were all from publicly available databases that are free of charge. UCSC Xena (https://xenabrowser.net/datapages/?cohort=TCGA%20Pan-Cancer%20(PANCAN)), TIMER3.0 (https://compbio.cn/timer3/). Further results can be reasonably requested from the corresponding author.

Declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee of the First Affiliated Hospital of Ningbo University. Informed consent was obtained from all participants prior to data collection, in accordance with ethical standards for human research. We confirm that all methods were performed in accordance with the relevant guidelines. All procedures were performed in accordance with the ethical standards laid down in the Declaration of Helsinki and its later amendments.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Jianhui Chen, Hantian Guan and Yitian Bai have contributed equally to this work.

Contributor Information

Xuejian Wang, Email: wang1xue2jian@126.com.

Dandan Wang, Email: 15922281540@163.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

12672_2026_4693_MOESM1_ESM.docx (1,008.4KB, docx)

Supplementary Material 1. Figure S1. The correlation between SCNA of the XRCC family members and immune infiltration in LUAD. Figure S2. The correlation between the expression of XRCC family members and immune cell infiltration in LUAD. Figure S3. The role of XRCC family in LUAD progression. (A) Differential expression of XRCC family members in different LUAD immune subtypes. (B) The correlation between XRCC family and clinical characteristics of LUAD. Figure S4. The effect of XRCC family on tumor stemness and immune microenvironment in LUAD.

Data Availability Statement

The data used in this research were all from publicly available databases that are free of charge. UCSC Xena (https://xenabrowser.net/datapages/?cohort=TCGA%20Pan-Cancer%20(PANCAN)), TIMER3.0 (https://compbio.cn/timer3/). Further results can be reasonably requested from the corresponding author.

Articles from Discover Oncology are provided here courtesy of Springer

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