PD-1/PD-L1 immune checkpoint inhibitors in the treatment of unresectable locally advanced or metastatic triple negative breast cancer: a meta-analysis on their efficacy and safety.

Background: Triple negative breast cancer (TNBC) represents a particularly aggressive and clinically challenging subtype of breast cancer, characterized by its invasive nature and generally poor prognosis. Treatment options for unresectable TNBC are limited. In recent years, the advent of PD-1/PD-L1 immune checkpoint inhibitors has offered a promising new treatment option for unresectable TNBC.

Overexpression of ESYT3 improves radioimmune responses through activating cGAS-STING pathway in lung adenocarcinoma.

Background: Radiotherapy can modulate systemic antitumor immunity, while immune status in the tumor microenvironment also influences the efficacy of radiotherapy, but relevant molecular mechanisms are poorly understood in lung adenocarcinoma (LUAD).

Methods: In this study, we innovatively proposed a radiotherapy response classification for LUAD, and discovered ESYT3 served as a tumor suppressor and radioimmune response sensitizer. ESYT3 expression was measured both in radioresistant and radiosensitive LUAD tissues and cells.

Pretreatment radiomic biomarker for immunotherapy responder prediction in stage IB-IV NSCLC (LCDigital-IO Study): a multicenter retrospective study.

Background: The predictive efficacy of current biomarker of immune checkpoint inhibitors (ICIs) is not sufficient. This study investigated the causality between radiomic biomarkers and immunotherapy response status in patients with stage IB-IV non-small cell lung cancer (NSCLC), including its biological context for ICIs treatment response prediction.

Methods: CT images from 319 patients with pretreatment NSCLC receiving immunotherapy between January 2015 and November 2021 were retrospectively collected and composed a discovery (n=214), independent validation (n=54), and external test cohort (n=51).

Radiation-sensitive genetic prognostic model identifies individuals at risk for radiation resistance in head and neck squamous cell carcinoma.

Background: The advantages of radiotherapy for head and neck squamous cell carcinoma (HNSCC) depend on the radiation sensitivity of the patient. Here, we established and verified radiological factor-related gene signature and built a prognostic risk model to predict whether radiotherapy would be beneficial.

Methods: Data from The Cancer Genome Atlas, Gene Expression Omnibus, and RadAtlas databases were subjected to LASSO regression, univariate COX regression, and multivariate COX regression analyses to integrate genomic and clinical information from patients with HNSCC.

Towards artificial intelligence to multi-omics characterization of tumor heterogeneity in esophageal cancer.

Esophageal cancer is a unique and complex heterogeneous malignancy, with substantial tumor heterogeneity: at the cellular levels, tumors are composed of tumor and stromal cellular components; at the genetic levels, they comprise genetically distinct tumor clones; at the phenotypic levels, cells in distinct microenvironmental niches acquire diverse phenotypic features. This heterogeneity affects almost every process of esophageal cancer progression from onset to metastases and recurrence, etc. Intertumoral and intratumoral heterogeneity are major obstacles in the treatment of esophageal cancer, but also offer the potential to manipulate the heterogeneity themselves as a new therapeutic strategy.

Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma.

Background: Autophagy, a key regulator of programmed cell death, is critical for maintaining the stability of the intracellular environment. Increasing evidence has revealed the clinical importance of interactions between autophagy and immune status in lung adenocarcinoma. The present study evaluated the potential of autophagy-immune-derived biomarkers to predict prognosis and therapeutic response in patients with lung adenocarcinoma.