Along with some chronic diseases such as cardiovascular disease, cancer remains one of the biggest killers of human health . The World Health Organization (WHO, https://www.who.int/) has recently announced on 5 March, 2021 that, the breast cancer has now overtaken lung cancer as the world’s mostly commonly-diagnosed cancer and the new global breast cancer initiative highlights renewed commitment to improve survival. At the same day, new WHO publication provides guidance on radiotherapy equipment to fight cancer like colorectal and lung cancer. Radiotherapy is remain one of the most effective tools to mitigate pain and suffering associated with advanced cancers, also, improve the quality of life and survival [33, 34]. Nevertheless, heterogeneity in terms of tumor characteristics, prognosis, and survival among cancer patients has been a persistent problem for many decades. Vast studies have shown that, the investigation of biomarkers related to radiation could provide another means by which radiotherapy could become personalized [2, 35].
Understanding the mechanism of tumors is also a major issue in identifying effective biomarkers and potential drug targets of radiosensitivity [36, 37]. PD-1 and its ligand PD-L1 are important immune checkpoints as a potential therapeutic target in cancer. PD-L1/PD-1 pathway plays a critical role in transmitting co-stimulatory molecules to activate T cells as the second signal and maintain the balance of the immune microenvironment . Well, when the body is invaded by the tumors, the balance of the immune microenvironment is destroyed. PD-L1 on tumor cells may engage the PD-1 receptors resulting in suppression of T-cell mediated immune response. Studies show that therapeutic antibodies blocking the PD-1/PD-L1 pathway by targeting PD-L1 or PD-1 are highly effective in rescuing T cell anti-tumor effector functions [18, 39]. In addition, the expression level of PD-L1 seems to be related to the radiotherapy sensitivity of tumors [20, 22]. As PD-L1 expression is regulated by the upstream signaling pathway, while PD-1/PD-L1 combination is transferred to the downstream T cell regulation as the second signal, the expression level of relevant genes in regulating PD-L1 expression and in PD-1 checkpoint pathway in cancer appears to be of vital importance, which may indicate the potential sensitivity of the tumor to radiotherapy.
In this study, we identified the radiosensitivity of genes in PD-L1 expression and PD-1 checkpoint pathway in cancer using the TCGA datasets of BRCA, HNSC and STAD. Because radiotherapy had non-positive effect (HR > = 1) to OS in lung cancer and LGG, we excluded these type of tumors for further exploration and perhaps they could be the subject of the next study. Then, we developed a more comprehensive definition of radiosensitive genes since most studies have neglected many genes that directly affect the OS of patients without radiotherapy (scenario D). Such as gene IFNG, although its expression level did no effect to OS when people received RT, in non-RT group, patients with low expression of IFNG had a significantly amazing lower OS than the high (scenario D, see Fig. 2/3). And through scenario B we can see, patients with low expression of IFNG with RT had a much improved OS.
In addition, we systematically considered clinical factors in the datasets as many as possible. We performed multiple interpolation to missing clinical variables and stacked them to perform weighted multivariate Cox regression. Therefore, the clinical variables were well controlled to ensure the reliability of the results. In the BRCA dataset, radiotherapy, chemotherapy, age, surgery type, margin status, PR status, menopause status, NM stage and pathological stage were the impact factors of OS, which were reasonable and validated . In the HNSC dataset, the impact factors included radiotherapy, age, gender, TN stage, margin status, anatomic site and smoking. Notably, females OS was not as good as males (HR: 1.149(1.016, 2.066), P = 0.041). And as for STAD, radiotherapy, age, gender, TN stage and residual tumor were the main influencing factors.
Totally, among genes in regulating PD-1/PD-L1 pathway in cancer, we identified 10 RS genes in BRCA dataset, 11 RS genes in STAD dataset and 13 RS genes in HNSC dataset, with overlapping genes between each other to varying degrees. CD274 was the common gene in the three tumor datasets. As known to all, CD274 is the gene that encodes PD-L1, predicting the expression level of PD-L1. The expression level of CD274 has been speculated to be related to radiosensitivity of a variety of cancers [22, 23, 25]. Theoretically, there are two types of radiosensitive genes. The expression level of the first type of genes (A genes) do not affect patients' OS, but their different expression level can influence patients' OS after radiotherapy, like RASGRP1 and TRAF6. Only those with high expression of these genes could obtain benefit from RT. More often, however, are the second type of genes (B genes). Their expression could influence patients' OS, for instance, patients with low expression of CD274 had much lower OS than the high. But these patients would benefit much receiving RT. And these genes can be thought as independent factors to identify the sensitivity of cancer patients to radiotherapy (Fig. 3/5). In addition, in B genes, there were moderate co-expression relationships and interactions (Fig. 6). Functional enrichment analysis showed that most of these genes were related to T cells. Nevertheless, more experimental studies are needed to confirm the findings of this study. In the external validation, ZAP70 was verified as a RS gene. Many studies have shown that it is related to the immunity of cancers [41, 42]. Importantly, there was also a strong co-expression relationship between PDCD1 and ZAP70 in METABRIC (r = 0.8) (See FigureS1).
This study has its merits. Firstly, we expanded the definition of radiosensitive genes and identified radiosensity of those genes in important pathway of cancer using TCGA public datasets recognized as authoritative. Secondly, we took into account as much useful clinical information as possible to control influence factors by stacking multiple interpolation data, making the results more persuasively. Thirdly, we also validated the results with a big external dataset, METABRIC, although only one gene ZAP70 was turned out to be consistent. However, this might be due to different sample sizes and large gaps in follow-up time. The limitation of this study is that we don’t have performed experimental study, also no cohort to verify the findings. In addition, because we only explored a few major cancers, more tumor types should be brought into the discussion.
In conclusion, our study identified potential radiosensitive biomarkers of several main cancer types in an important tumor immune checkpoint pathway. New types of RS genes may be identified based on expanded definition to RS genes. Different types of tumors may share common carcinogenic mechanisms and may have same RS genes. We hope that further studies will be performed to confirm our findings.