The role of CD28 in the prognosis of young lung adenocarcinoma patients

An immune checkpoint-based signature predicts prognosis and chemotherapy response for patients with small cell lung cancer

BACKGROUND

Therapeutic options for small cell lung cancer (SCLC), a particularly lethal malignancy, remain limited. Members of the B7-CD28 family are compelling targets for immune checkpoint blockade strategies, which involve activating, inhibiting, and fine-tuning the T cell immune response. However, their clinical features and significance have not been explored comprehensively.

METHOD

We enrolled 228 patients with an initial diagnosis of SCLC, including 77 cases from Cbioportal and a validation cohort of 151 cases with qPCR data. Kaplan-Meier analysis and LASSO Cox model were used to identify a signature based on the B7-CD28 family, which was applied for accurate prediction of chemotherapy benefit and prognosis for SCLC patients. In addition, we applied bioinformatics analysis to explore potential signature-related molecular mechanisms and the immune landscape.

RESULTS

The mutation profiles of healthy tissues and SCLC tissues were distinct. A signature consisting of seven genes (CD86, ICOSLG, CD276, CD28, CTLA-4, PDCD1, and TMIGD2) was identified and applied to group patients based on risk level (high-risk and low-risk), producing two groups for which survival outcomes differed significantly (HR = 3.81, 95% CI: 2.16-6.74, P < 0.001). The immune checkpoint-based signature accurately predicted patient outcomes for the selected training and validation sets. Notably, low-risk patients were more likely to benefit from chemotherapy and showed greater immune activation. Additionally, time-dependent ROC curves and C-index analysis confirmed that the immune checkpoint-based signature has excellent predictive power for prognosis and chemotherapy benefit compared to clinically recognized parameters. Finally, multivariate analysis confirmed the identified signature as an independent risk factor for prognosis and chemotherapeutic response.

CONCLUSION

We systematically obtained a comprehensive molecular profile for B7-CD28 family members in SCLC patients, from which we produced a reliable and robust prognostic immune checkpoint-based signature with the potential to improve prognostic stratification and therapy strategies for SCLC patients.

A 13-gene signature to predict the prognosis and immunotherapy responses of lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) comprises 20–30% of all lung cancers. Immunotherapy has significantly improved the prognosis of LUSC patients; however, only a small subset of patients responds to the treatment. Therefore, we aimed to develop a novel multi-gene signature associated with the immune phenotype of the tumor microenvironment for LUSC prognosis prediction. We stratified the LUSC patients from The Cancer Genome Atlas dataset into hot and cold tumor according to a combination of infiltration status of immune cells and PD-L1 expression level. Kaplan–Meier analysis showed that hot tumors were associated with shorter overall survival (OS). Enrichment analyses of differentially expressed genes (DEGs) between the hot and cold tumors suggested that hot tumors potentially have a higher immune response ratio to immunotherapy than cold tumors. Subsequently, hub genes based on the DEGs were identified and protein–protein interactions were constructed. Finally, we established an immune-related 13-gene signature based on the hub genes using the least absolute shrinkage and selection operator feature selection and multivariate cox regression analysis. This gene signature divided LUSC patients into high-risk and low-risk groups and the former inclined worse OS than the latter. Multivariate cox proportional hazard regression analysis showed that the risk model constructed by the 13 prognostic genes was an independent risk factor for prognosis. Receiver operating characteristic curve analysis showed a moderate predictive accuracy for 1-, 3- and 5-year OS. The 13-gene signature also performed well in four external cohorts (three LUSC and one melanoma cohorts) from Gene Expression Omnibus. Overall, in this study, we established a reliable immune-related 13-gene signature that can stratify and predict the prognosis of LUSC patients, which might serve clinical use of immunotherapy.

The Potential Predictive Biomarkers for Advanced Hepatocellular Carcinoma Treated With Anti-Angiogenic Drugs in Combination With PD-1 Antibody

Background

Based on molecular biomarkers, anti-angiogenic drugs in combination with programmed cell death protein 1 (PD-1) antibodies can screen the potentially beneficial populations with hepatocellular carcinoma (HCC) and predict the efficacy after treatment. Therefore, we aimed to study predictive molecular biomarkers to improve the effectiveness of immuno-targeted combination therapy for HCC.

Patients and Methods

Baseline clinical data, blood samples, and imaging data of the first evaluation after two cycles of treatment were collected for 40 patients with advanced HCC who underwent combination therapy, and then these data were compared according to the efficacy. Since 15 patients had complete hematology samples, we additionally tested the T lymphocyte subpopulations of these 15 patients and also compared them according to the efficacy. In addition, we also selected five patients who benefited the most from the combination therapy and five patients with the worst curative effect for gene detection based on survival time and efficacy evaluation. Finally, the relationship between certain clinical characteristics, laboratory indicators, specific T lymphocyte subpopulations, gene mutations and the response of immuno-targeted combination therapy for HCC was evaluated.

Results

The high levels of CD3⁺CD4⁺CD279⁺, CD3⁺CD8⁺CD45RO⁺CD62L⁺T lymphocytes and tumor mutational burden (TMB) were associated with good efficacy of the combination therapy (P=0.03, P<0.01 and P=0.03). The high levels of CD3⁺CD4⁺CD28⁺ T lymphocytes were associated with poor efficacy of the combination therapy (P=0.02). The high mutation frequency of TP53 and ARID1A appeared in the non-response cohort. In addition, amplification mutation of 11q13-CCND1, FGF3, FGF4, and FGF19 was found in a patient with hyperprogression (HP).

Conclusions

The certain clinical characteristics, laboratory indicators, specific T lymphocyte subpopulations, and gene mutations established in this paper were potential predictive biomarkers for HCC patients treated with combination therapy.

Expression of CD28 in Hepatocellular Carcinoma and Its Prognostic Value

Background: CD28 expression is correlated with malignancy development in long-term survivors after liver transplantation. Immune cell activation is mediated by the interaction of CD28 with CD4 and CD8. Objectives: In this study, we attempted to investigate the expression level and prognostic value of CD28 in hepatocellular carcinoma (HCC). Methods: A total of 54 HCC patients with complete clinical information were examined. The expression level of CD28 in HCC tissues was detected by immunohistochemistry. The correlations of CD28 expression with clinical characteristics, CD4+/CD8+ T-cells, and prognosis in HCC were analyzed. The expression profile of CD28 and survival time of HCC patients were retrieved from the TCGA database, followed by survival analysis. Results: The positive expression rate of CD28 in HCC tissues was 70.73%. The CD28 expression was significantly higher in the positive expression group (area: 659174.9 ± 670060, IOD: 123348.3 ± 106348.6) than in the negative expression group (area: 8405.7 ± 9983.3, IOD: 1959.6 ± 2117.7) (P < 0.01). The CD4+ and CD8+ cell counts were 526.13 ± 258.17 cells/µL and 383.93 ± 223.39 cells/µL, respectively. The expression level of CD28 was significantly related to the degree of differentiation and the number of CD4+ and CD8+ T-cells (P < 0.05). The survival time of patients was longer in the positive CD28 expression group than in the negative expression group. Based on the CD28 expression profiles of 406 HCC patients retrieved from the TCGA database, patients with high CD28 expression showed a better prognosis than those with low expression (P < 0.05). Conclusions: CD28 may play a vital role in the occurrence, development, and prognosis of HCC by interacting with CD4+ and CD8+ T-cells. Thus, CD28 could be suggested as the immune checkpoint target for HCC treatment.

Telomere Shortening and Its Association with Cell Dysfunction in Lung Diseases

Telomeres are localized at the end of chromosomes to provide genome stability; however, the telomere length tends to be shortened with each cell division inducing a progressive telomere shortening (TS). In addition to age, other factors, such as exposure to pollutants, diet, stress, and disruptions in the shelterin protein complex or genes associated with telomerase induce TS. This phenomenon favors cellular senescence and genotoxic stress, which increases the risk of the development and progression of lung diseases such as idiopathic pulmonary fibrosis, chronic obstructive pulmonary disease, SARS-CoV-2 infection, and lung cancer. In an infectious environment, immune cells that exhibit TS are associated with severe lymphopenia and death, whereas in a noninfectious context, naïve T cells that exhibit TS are related to cancer progression and enhanced inflammatory processes. In this review, we discuss how TS modifies the function of the immune system cells, making them inefficient in maintaining homeostasis in the lung. Finally, we discuss the advances in drug and gene therapy for lung diseases where TS could be used as a target for future treatments.

Nomogram to Predict Cancer Specific Survival in Patients with Pathological Stage IA Non-small Cell Lung Cancer

We identified the prognostic factors of resected stage IA non-small cell lung cancer (NSCLC) and developed a nomogram, with purpose of defining the high-risk population who may need closer follow-up or more intensive care. Eligible stage IA NSCLC cases from the Surveillance, Epidemiology, and End Results (SEER) database and the Sun Yat-sen University Cancer Center (SYSUCC) were included. Stage IB NSCLCs were also included for evaluating the risk stratification efficacy. Cancer specific survival (CSS) was compared between groups. Statistically significant factors from multivariate analysis were entered into the nomogram. The performance of the nomogram was evaluated by concordance index (C-index) and calibration plots. A total of 23,112 NSCLC cases (SEER stage IA training cohort, N=7,777; SEER stage IA validation cohort, N=7,776; SEER stage IB cohort, N=7,559) from the SEER database were included. 1,304 NSCLC cases (SYSUCC stage IA validation cohort, N=684; SYSUCC stage IB cohort, N=620) from the SYSUCC were also included. Younger age, female, lobectomy, well differentiated, smaller size and more examined lymph nodes were identified as favorable prognostic factors. A nomogram was established. The C-index was 0.68 (95%CI, 0.67-0.69), 0.66 (95% CI, 0.64-0.68) and 0.66 (95% CI, 0.61-0.71) for the SEER training cohort, SEER validation cohort and SYSUCC validation cohort. A risk classification system was constructed to stratify stage IA NSCLC into low-risk subgroup and high-risk subgroup. The CSS curves of these two subgroups showed statistically significant distinctions. This nomogram delivered a prognostic prediction for stage IA NSCLC and may aid individual clinical practice.