Clinical efficacy and safety of maintenance therapy for advanced non-small cell lung cancer: a retrospective real-world study

Identification of an immune-related genes signature in lung adenocarcinoma to predict survival and response to immune checkpoint inhibitors

BACKGROUND

Although advances in immune checkpoint inhibitor (ICI) research have provided a new treatment approach for lung adenocarcinoma (LUAD) patients, their survival is still unsatisfactory, and there are issues in the era of response prediction to immunotherapy.

METHODS

Using bioinformatics methods, a prognostic signature was constructed, and its predictive ability was validated both in the internal and external datasets (GSE68465). We also explored the tumor-infiltrating immune cells, mutation profiles, and immunophenoscore (IPS) in the low-and high-risk groups.

RESULTS

As far as we are aware, this is the first study which introduces a novel prognostic signature model using BIRC5, CBLC, S100P, SHC3, ANOS1, VIPR1, LGR4, PGC, and IGKV4.1. According to multivariate analysis, the 9-immune-related genes (IRGs) signature provided an independent prognostic factor for the overall survival (OS). The low-risk group had better OS, and the tumor mutation burden (TMB) was significantly lower in this group. Moreover, the risk scores were negatively associated with the tumor-infiltrating immune cells, like CD8+ T cells, macrophages, dendritic cells, and NK cells. In addition, the IPS were significantly higher in the low-risk group as they had higher gene expression of immune checkpoints, suggesting that ICIs could be a promising treatment option for low-risk LUAD patients.

CONCLUSION

The combination of these 9-IRGs not only could efficiently predict overall survival of LUAD patients but also show a powerful association with the expression of immune checkpoints and response to ICIs based on IPS; hoping this model paves the way for better stratification and management of patients in clinical practice.

Systematic evaluation of clinical efficacy of CYP1B1 gene polymorphism in EGFR mutant non-small cell lung cancer observed by medical image

Lung cancer is the cancer with the highest mortality rate and the highest incidence in the world at this stage. Among them, non-small lung cancer is the most common type of lung cancer, and most small cancers have disappeared, which is the optimal time for surgery at the time of diagnosis. To explore and systematically evaluate the clinical efficacy of CYP1B1 gene polymorphism in the treatment of epidermal growth factor receptor (EGFR) Mutant non-small cell lung cancer, this article proposes the principles of lung cancer screening based on CYP1B1 gene polymorphism and polarization imaging and explores the diagnosis and treatment of non-EGFR mutant lung cancer. Based on a large number of medical image data, imageomics can directly reflect the correlation between tumor molecular phenotype and image characteristics by deeply mining some imaging features of the image, which has important value in the early diagnosis of disease, the formulation of personalized treatment plan, and efficacy evaluation and prognosis prediction. A total of 141 NSCLC patients with sensitive EGFR mutation were included in this study, including 101 patients with EGFR single-gene mutation and 40 patients with EGFR multigene mutation coexisting mutation. Both groups of patients were female, aged ≥60 years, no smoking history, no family history of leukemia, adenocarcinoma, lung cancer, stage IV, lymph node metastasis, living, far from metastasis, and ECOG score of 0-2. This study examined the relative number of gene expression and PFS in EGFR multigene co-existing mutations. When the number of mixed genes is 1, 2, and higher, the PFS is 9 months, 8 months, and 6 months, respectively. The PFS time of this group of patients gradually shortened. Therefore, this study examined the benefit of polygenic mutation in estimation by comparing the clinical characteristics of patients with EGFR single-gene mutation and polygenic mutation, to provide measurement of EGFR-TKI and to provide suggestions for future drug selection.

Nanoformulations-Based Metronomic Chemotherapy: Mechanism, Challenges, Recent Advances, and Future Perspectives

Cancer-related death is a significant health and economic burden worldwide, and some conventional chemotherapy is associated with limited effectiveness in completely curing various cancers, severe adverse effects, and destruction of healthy cells. To overcome the complications associated with conventional treatment, metronomic chemotherapy (MCT) is extensively suggested. In this review, we aim to highlight the importance of MCT over conventional chemotherapeutic approach with emphasis on nanoformulations-based MCT, their mechanism, challenges, recent advances, and future perspectives. Nanoformulations-based MCT revealed remarkable antitumor activity in both preclinical and clinical settings. For example, the metronomic scheduling of oxaliplatin-loaded nanoemulsion and polyethylene glycol-coated stealth nanoparticles incorporating paclitaxel were proven very effective in tumor-bearing mice and rats, respectively. Additionally, several clinical studies have demonstrated the benefit of MCT with acceptable tolerance. Moreover, metronomic might be a promising treatment strategy for improving cancer care in low- and middle-income nations. However, an appropriate alternative to a metronomic regimen for an individual ailment, suitable combinational delivery and scheduling, and predictive biomarkers are certain parts that remain unanswered. Further clinical-based comparative research studies are mandatory to be performed before entailing this treatment modality in clinical practice as alternative maintenance therapy or in place of transferring to therapeutic management.

Real-world maintenance therapy and survival outcomes for pembrolizumab plus pemetrexed and platinum for non-small-cell lung cancer in USA

Aim: To evaluate treatment patterns and overall survival (OS) in real world metastatic non-squamous non-small-cell lung cancer (NSQ-NSCLC) patients that received pembrolizumab plus pemetrexed-platinum (pembro+pem+plat) aligned with KEYNOTE-189. Materials & methods: OS was evaluated for the overall cohort and maintenance therapy (MT) subgroups and analyzed using Kaplan-Meier estimates and Cox proportional hazards model. Results: Of 2488 patients that received first-line treatment, 45.1% received less than four cycles of pembro+pem+plat, 43.9% received four cycles plus MT with pembro and/or pem, and 11.1% received four cycles without continuing on MT. The median OS was 21.0 months and 9.1 months in patients that continued and did not continue MT. Conclusion: Real world patients that received KEYNOTE-189-aligned treatment had similar OS benefits.

Identification of a TGF-β signaling-related gene signature for prediction of immunotherapy and targeted therapy for lung adenocarcinoma

BACKGROUND

Transforming growth factor (TGF)-β signaling functions importantly in regulating tumor microenvironment (TME). This study developed a prognostic gene signature based on TGF-β signaling-related genes for predicting clinical outcome of patients with lung adenocarcinoma (LUAD).

METHODS

TGF-β signaling-related genes came from The Molecular Signature Database (MSigDB). LUAD prognosis-related genes were screened from all the genes involved in TGF-β signaling using least absolute shrinkage and selection operator (LASSO) Cox regression analysis and then used to establish a risk score model for LUAD. ESTIMATE and CIBERSORT analyzed infiltration of immune cells in TME. Immunotherapy response was analyzed by the TIDE algorithm.

RESULTS

A LUAD prognostic 5-gene signature was developed based on 54 TGF-β signaling-related genes. Prognosis of high-risk patients was significantly worse than low-risk patients. Both internal validation and external dataset validation confirmed a high precision of the risk model in predicting the clinical outcomes of LUAD patients. Multivariate Cox analysis demonstrated the model independence in OS prediction of LUAD. The risk model was significantly related to the infiltration of 9 kinds of immune cells, matrix, and immune components in TME. Low-risk patients tended to respond more actively to anti-PD-1 treatment, while high-risk patients were more sensitive to chemotherapy and targeted therapy.

CONCLUSIONS

The 5-gene signature based on TGF-β signaling-related genes showed potential for LUAD management.

B7-H3 is eligible for predicting clinical outcomes in lung adenocarcinoma patients treated with EGFR tyrosine kinase inhibitors

BACKGROUND

Not all lung adenocarcinoma (LUAD) patients with activating epidermal growth factor receptor (EGFR) mutations respond to tyrosine kinase inhibitors (TKIs) as intended. Thus, biomarkers are needed to identify patients who benefit most from EGFR-targeted therapy. Our previous in vitro data has shown that the co-signal molecule B7-H3 determines EGFR-TKI gefitinib susceptibility of EGFR-mutated LUAD cell lines, based on the potential crosslinking between B7-H3-induced signaling and EGFR signaling.

METHODS

We detected tumoral B7-H3 expression in the original biopsy from 56 treatment-naïve LUAD patients and analyzed the association between high/low B7-H3 expression with the clinical outcomes of first-line anti-EGFR therapy. The main criteria for the analysis of response were overall response rate (ORR), disease control rate (DCR), and progression-free survival (PFS), and the secondary criterion was overall survival (OS).

RESULTS

In the subgroups of B7-H3 high and low expression, the ORR were 16.0% (4/25) and 74.2% (23/31) (p<0.001), and the DCR were 36.0% (9/25) and 87.1% (27/31) (p<0.001), respectively. The PFS of B7-H3 high [median 8.7, 95% confidence interval (CI) 4.0-13.4] was significantly worse than that of B7-H3 low (median not reached) [HR 6.54 (95% CI 2.18-19.60), p=0.001]. The median OS was 15.9 (95% CI 10.0-21.8) months in the B7-H3 high cohort and 25.7 (95% CI 9.0-42.4) months in the B7-H3 low subjects [HR 2.08 (95% CI 1.07-4.02), p=0.03], respectively. Both the univariate and multivariate analyses identified B7-H3 as an independent factor associated with poor PFS (p=0.001, p=0.000) and OS (p=0.03, p=0.015).

CONCLUSION

B7-H3 may serve as a potential biomarker to predict clinical outcomes in EGFR-mutated LUAD patients treated with first-line EGFR-TKIs.