Molecular classification reveals the sensitivity of lung adenocarcinoma to radiotherapy and immunotherapy: multi-omics clustering based on similarity network fusion

BACKGROUND

Due to individual differences in tumors and immune systems, the response rate to immunotherapy is low in lung adenocarcinoma (LUAD) patients. Combinations with other therapeutic strategies improve the efficacy of immunotherapy in LUAD patients. Although radioimmunotherapy has been demonstrated to effectively suppress tumors, the underlying mechanisms still need to be investigated.

METHODS

Total RNA from LUAD cells was sequenced before and after radiotherapy to identify differentially expressed radiation-associated genes. The similarity network fusion (SNF) algorithm was applied for molecular classification based on radiation-related genes, immune-related genes, methylation data, and somatic mutation data. The changes in gene expression, prognosis, immune cell infiltration, radiosensitivity, chemosensitivity, and sensitivity to immunotherapy were assessed for each subtype.

RESULTS

We used the SNF algorithm and multi-omics data to divide TCGA-LUAD patients into three subtypes. Patients with the CS3 subtype had the best prognosis, while those with the CS1 and CS2 subtypes had poorer prognoses. Among the strains tested, CS2 exhibited the most elevated immune cell infiltration and expression of immune checkpoint genes, while CS1 exhibited the least. Patients in the CS2 subgroup were more likely to respond to PD-1 immunotherapy. The CS2 patients were most sensitive to docetaxel and cisplatin, while the CS1 patients were most sensitive to paclitaxel. Experimental validation of signature genes in the CS2 subtype showed that inhibiting the expression of RHCG and TRPA1 could enhance the sensitivity of lung cancer cells to radiation.

CONCLUSIONS

In summary, this study identified a risk classifier based on multi-omics data that can guide treatment selection for LUAD patients.

Clinical Outcomes of Afatinib Versus Osimertinib in Patients With Non-Small Cell Lung Cancer With Uncommon EGFR Mutations: A Pooled Analysis

BACKGROUND

The purpose of this analysis was to investigate the effectiveness of afatinib compared to that of osimertinib in patients with non-small cell lung cancer (NSCLC) who harbored uncommon epidermal growth factor receptor (EGFR) mutations.

METHODS

A PubMed database-based literature review was conducted to retrieve related studies. Patients harboring EGFR mutations besides the deletion in exon 19 (19del) and point mutation of L858R were included in this analysis. The primary outcome events were the objective response rate (ORR) and progression-free survival (PFS). Propensity score matching (PSM) at a ratio of 1:1 was used between afatinib and osimertinib groups to control the confounding factors. Uncommon EGFR mutations were categorized into 4 groups: insertion in exon 20 (ex20ins), non-ex20ins single uncommon EGFR mutations, compound EGFR mutations that with 19del or L858R, and compound EGFR mutations without 19del or L858R.

RESULTS

After PSM, 71 patients in either the afatinib or osimertinib group were matched. The afatinib group had an ORR of 60.6%, slightly higher than the osimertinib group's (50.3%), the difference was not statistically significant (P = .610). However, the afatinib group showed a significantly superior PFS benefit than the osimertinib group (11.0 vs. 7.0 months, P = .044). In addition, patients harboring non-ex20ins single uncommon EGFR mutations yield the best ORR and PFS, following treatment of either afatinib (ORR: 76.7%, mPFS: 14.1 months) or osimertinib (ORR: 68.8%, mPFS: 15.1 months). Moreover, there was no significant difference in terms of ORR or PFS between the cohort of patients treated with afatinib or osimertinib, regardless of whether or not the patients had brain metastases.

CONCLUSIONS

Both afatinib and osimertinib displayed favorable clinical activities toward uncommon EGFR mutations. Afatinib showed a more profound and durable PFS benefit than osimertinib, although no efficacy advantage was observed.