RESUMO
Background: Hepatocellular carcinoma (HCC), one of the highest causes of cancer-associated death, has effective treatments, especially for patients with advanced HCC. Circadian rhythm participates in several important physiological functions, and its chronic disruption results in many disordered diseases, including cancer. However, the role of circadian rhythm in the overall survival (OS) of patients with HCC remains unclear. Methods: We investigated the expression, copy number variation (CNV), and mutation profiles of core circadian clock genes in normal and tumor tissues. We developed and validated a messenger RNA signature (mRNASig) based on prognostic circadian clock genes. A set of bioinformatic tools were applied for functional annotation and tumor-associated microenvironment (TME) analysis. Results: Core circadian clock genes were disrupted in terms of the transcription and CNV of HCC samples. The mRNASig, including NPAS2, NR1D1, PER1, RORC, and TIMELESS, was constructed. We divided patients with HCC into high-risk group and low-risk group based on the median value of the risk score. The high-risk group had a poorer prognosis than the low-risk group. The high-risk group was associated with malignant processes (e.g., proliferation, oncogenic pathway, DNA repair), metabolism, and tumor mutational burden (TMB). Surprisingly, the low-risk group was associated with enriched angiogenesis and was linked to enhanced response to sorafenib. Moreover, the high-risk group showed poor infiltration of CD8 T cells and natural killer cells accompanied by higher expression of CTLA4, PDCD1, TIGIT, and TIM3. Additionally, the mRNASig was associated with TMB. Conclusions: The mRNASig based on core circadian clock genes is a potential prognostic signature and therapeutic strategy and is significantly associated with the malignant biology of HCC.
RESUMO
Background: Small cell lung cancer (SCLC) is an aggressive lung malignancy with high relapse rates and poor survival outcomes. Ferroptosis is a recently identified type of cell death caused by excessive intracellular iron accumulation and lipid peroxidation, which may mediate tumor-infiltrating immune cells to influence anti-cancer immunity. But prognostic value of ferroptosis-related genes and its relationship with the treatment response of immunotherapies in SCLC have not been elucidated. Methods: The RNA-sequencing and clinical data of SCLC patients were downloaded from the cBioPortal database. A ferroptosis-related prognostic risk-scoring model was constructed based on univariable and multivariable Cox-regression analysis. Kaplan-Meier (K-M) survival curves and receiver operating characteristics (ROC) curves were constructed to assess the sensitivity and specificity of the risk-scoring model. And the correlations between ferroptosis-related prognostic genes and immune microenvironment were explored. The IC50 values of anti-cancer drugs were downloaded from the Genomics of Drug Sensitivity in Cancer (GDSC) database and the correlation analysis with the key gene thioredoxin-interacting protein (TXNIP) was performed. In addition, immunohistochemistry (IHC) staining was employed to detect the expression of TXNIP in 20 SCLC patients who received first-line chemo-immunotherapy. Immunotherapeutic response according to iRECIST (Response Evaluation Criteria in Solid Tumours for immunotherapy trials) were recorded. Results: We constructed a risk-score successfully dividing patients in the low- and high-risk groups (with better and worse prognosis, respectively). The area under the curve (AUC) of this risk-scoring model was 0.812, showing it had good utility in predicting the prognosis of SCLC. Moreover, ferroptosis-related genes were associated with the degree of immune infiltration of SCLC. Most importantly, we found that the TXNIP expression was highly correlated with the degree of immune invasion and the efficacy of chemotherapy in combination with immunotherapy in SCLC patients. Conclusions: The ferroptosis-related prognostic risk-scoring model proposed in this study can potentially predict the prognosis of SCLC patients. TXNIP may serve as a potential biomarker to predict the prognosis and efficacy of chemotherapy combined with immunotherapy in SCLC patients.