Long noncoding RNAs (lncRNAs) can act as microRNA (miRNA) sponges to regulate protein-coding gene expression; therefore, lncRNAs are considered a major part of the competitive endogenous RNA (ceRNA) network and have attracted growing attention. The present study explored the regulatory mechanisms and functional roles of lncRNAs as ceRNAs in hepatocellular carcinoma (HCC) and their potential impact on HCC patient prognosis. In this study, we systematically studied the expression profiles and prognostic value of lncRNA, miRNA, and mRNA from a total of 838 HCC patients from five HCC cohorts (TCGA, GSE54236, GSE76427, GSE64041 and GSE14520). The TCGA, GSE54236 and GSE76427 HCC cohorts were utilized to establish a prognosis-related network of dysregulated ceRNAs by bioinformatics methods. The GSE64041 and GSE14520 HCC cohorts were utilized to verify the expression of candidate genes. In total, 721 lncRNAs, 73 miRNAs, and 1563 mRNAs were aberrantly expressed in HCC samples. A ceRNA network including 26 lncRNAs, four miRNAs, and six mRNAs specific to HCC was established. The survival analysis showed that four lncRNAs (MYCNOS, DLX6-AS1, LINC00221, and CRNDE) and two mRNAs (CCNB1 and SHCBP1) were prognostic biomarkers for patients with HCC in both the TCGA and GEO databases. The proposed ceRNA network may help elucidate the regulatory mechanism by which lncRNAs function as ceRNAs and contribute to the pathogenesis of HCC. Importantly, the candidate lncRNAs, miRNAs, and mRNAs involved in the ceRNA network can be further evaluated as potential therapeutic targets and prognostic biomarkers for HCC.

Purpose:: In the absence of a collimation system the lateral penumbra of spot scanning (SS) dose distributions delivered by low energy proton beams is highly dependent on the spot size. For current commercial equipment, spot size increases with decreasing proton energy thereby reducing the benefit of the SS technique. This paper presents a dynamic collimation system (DCS) for sharpening the lateral penumbra of proton therapy dose distributions delivered by SS.Methods:: The collimation system presented here exploits the property that a proton pencil beam used for SS requires collimation only when it is near the target edge, enabling the use of trimmers that are in motion at times when the pencil beam is away from the target edge. The device consists of two pairs of parallel nickel trimmer blades of 2 cm thickness and dimensions of 2 cm × 18 cm in the beamˈs eye view. The two pairs of trimmer blades are rotated 90° relative to each other to form a rectangular shape. Each trimmer blade is capable of rapid motion in the direction perpendicular to the central beam axis by means of a linear motor, with maximum velocity and acceleration of 2.5 m/s and 19.6 m/s², respectively. The blades travel on curved tracks to match the divergence of the proton source. An algorithm for selecting blade positions is developed to minimize the dose delivered outside of the target, and treatment plans are created both with and without the DCS.Results:: The snout of the DCS has outer dimensions of 22.6 × 22.6 cm² and is capable of delivering a minimum treatment field size of 15 × 15 cm². Using currently available components, the constructed system would weigh less than 20 kg. For irregularly shaped fields, the use of the DCS reduces the mean dose outside of a 2D target of 46.6 cm² by approximately 40% as compared to an identical plan without collimation. The use of the DCS increased treatment time by 1–3 s per energy layer.Conclusions:: The spread of the lateral penumbra of low‐energy SS proton treatments may be greatly reduced with the use of this system at the cost of only a small penalty in delivery time.

Gastrointestinal (GI) malignant neoplasms have a high global incidence and treatment prospects for patients with advanced GI tumors are dismal. PD-1/PD-L1 inhibitors emerged as a frontline treatment for several types of cancer. However, the shortcomings of PD-1/PD-L1 inhibitors have been observed, including low objective response rates and acquired tumor resistance, especially in patients receiving PD-1/PD-L1 inhibitors as a single treatment. Accumulating evidence from clinical trials increasingly suggests that combined immunotherapies enhance therapeutic responses in patients with malignances, especially for GI tumors which have a complex matrix, and significant molecular and immunological differences. Preclinical and clinical studies suggest there are advantages to combined immunological regimens, which represents the next logical step in this field, although further research is necessary. This literature review explores the current limitations of monotherapies, before critically discussing the rationale behind combination regimens. Then, we provide a summary of the clinical applications for gastrointestinal cancers.

Background: Immune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of many cancers. However, the limited population that benefits from ICI therapy makes it necessary to screen predictive biomarkers for stratifying patients. Currently, many biomarkers, such as tumor mutational burden (TMB), have been used in the clinic as indicative biomarkers. However, some high-TMB patients with mutations in genes that are closely related to immunotherapeutic resistance are not sensitive to ICI therapy. Thus, there is a need to move beyond TMB and identify specific genetic determinants of the response to ICI therapy. In this study, we established a comprehensive mutation-based gene set across different tumor types to predict the efficacy of ICI therapy. Methods: We constructed and validated a mutational signature to predict the prognosis of patients treated with ICI therapy. Then, the underlying immune response landscapes of different subtypes were investigated with multidimensional data. Results: This study included genomic and clinical data for 12,647 patients. An eleven-gene mutation-based gene set was generated to divide patients into a high-risk group and a low-risk group in a training cohort (1572 patients with 9 types of cancers who were treated with ICI therapy). Validation was performed in a validation cohort (932 patients with 5 types of cancers who were treated with ICI therapy). Mutations in these 11 genes were associated with a better response to ICI therapy. In addition, the mutation-based gene set was demonstrated to be an independent prognostic factor after ICI therapy. We further explored the role of the immune context in determining the benefits of immunotherapy in 10,143 patients with 33 types of cancers and found distinct immune landscapes for the high- and low-risk groups. Conclusions: The mutation-based gene set developed in this study can be used to reliably predict survival benefit across cancers in patients receiving ICI therapy. The close interplay between the extrinsic and intrinsic immune landscapes in the identified patient subgroups and the subgroups’ differing responses to ICI therapy could guide immunotherapy treatment decisions for cancer patients.