BACKGROUND: XRCC4 is a NHEJ factor identified recently that plays a vital role in repairing DNA double-stranded breaks. Studies have reported the associations between abnormal expression of XRCC4 and tumor susceptibility and radiosensitivity, but the potential biological mechanisms by which XRCC4 exerts effects on tumorigenesis are not fully understood. This study aimed to systematically investigate the role of XRCC4 across cancer types. METHODS: The TIMER, GTEX and Xiantao Academic database were used to interpret the expression of XRCC4. Genomic alterations and protein expression in human organic and tumor tissues were applied in cBioPortal and the Human Protein Atlas databases. Correlations between XRCC4 expression and immune and molecular subtypes were analyzed by using the TISIDB database. Protein-protein interactions, GO and KEGG enrichment were also applied for XRCC4-related genes. The TIMER and the Tumor Immune Single Cell Hub (TISCH) online databases were used to explore the relationship between XRCC4 and tumor immune microenvironment. Drug sensitivity information was acquired from the CellMiner database to analyze the effect of XRCC4 on sensitivity analysis. RESULTS: The XRCC4 expression was significantly upregulated in 15 tumor types and downregulated in two tumor types compared with the normal tissues, most of which were validated by the results of Xiantao academic platform. XRCC4 was expressed at intermediate level in malignant cells. The XRCC4 expression was related to the molecular and immune subtypes of human cancers, and the survival outcome of 11 types of cancers, including KIRC, STAD and LIHC. The main type of frequent genetic alteration is amplification. Strong correlations were also found between XRCC4 and immune checkpoint genes in 33 human cancers. Furthermore, the abnormal expression of XRCC4 was related to immune cell infiltration and drug sensitivity. Enrichment analysis showed that XRCC4 was significantly correlated with DNA damage response. CONCLUSIONS: This comprehensive pan-cancer analysis suggested that XRCC4 may play a vital role in the prognosis and immunotherapy response in cancer patients, and it is a promising therapy target in the future.

This article presents a fast algorithm for finding the Adams consensus tree of a set of conflicting phylogenetic trees with identical leaf labels. Its worst-case running time is O(knlog⁡n), where k is the number of input trees and n is the size of the leaf label set; in comparison, the original algorithm of Adams has a worst-case running time of O(kn2). To achieve subquadratic running time, the centroid path decomposition technique is applied in a novel way that traverses the input trees by following a centroid path in each of them in unison. For k=2, an even faster algorithm running in O(n⋅log⁡nlog⁡log⁡n) time is provided, which relies on an extension of the wavelet tree-based technique of Bose et al. for orthogonal range counting on a grid. Our extended wavelet tree data structure also supports truncated range maximum/minimum queries efficiently.

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This paper presents a fast algorithm for finding the Adams consensus tree of a set of conflicting phylogenetic trees with identical leaf labels, for the first time improving the time complexity of a widely used algorithm invented by Adams in 1972 [1]. Our algorithm applies the centroid path decomposition technique [9] in a new way to traverse the input trees' centroid paths in unison, and runs in O(k n \log n) time, where k is the number of input trees and n is the size of the leaf label set. (In comparison, the old algorithm from 1972 has a worst-case running time of O(k n^2).) For the special case of k = 2, an even faster algorithm running in O(n \cdot \frac{\log n}{\log\log n}) time is provided, which relies on an extension of the wavelet tree-based technique by Bose et al. [6] for orthogonal range counting on a grid. Our extended wavelet tree data structure also supports truncated range maximum queries efficiently and may be of independent interest to algorithm designers.