Immunotherapy in Advanced NSCLC Without Driver Mutations: Available Therapeutic Alternatives After Progression and Future Treatment Options

Effects of Acetaminophen Exposure on Outcomes of Patients Receiving Immune Checkpoint Inhibitors for Advanced Non-Small-Cell Lung Cancer: A Propensity Score-Matched Analysis

(1) Background: Several studies have investigated potential interactions between immune checkpoint inhibitors (ICIs) and commonly prescribed medications. Although acetaminophen (APAP) has not been considered susceptible to interaction with ICIs, recent research has shown that detectable plasma levels of this drug can hinder the efficacy of PD-1/PD-L1 blockade therapies. A reliable assessment of the potential interaction between APAP and ICIs in advanced non-small cell lung cancer (NSCLC) patients would be worthwhile since it is often prescribed in this condition. We sought to evaluate the impact of the concomitant use of APAP in patients with advanced NSCLC on PD-1/PD-L1 blockade using real-world evidence. (2) Methods: This study included consecutive patients with histologically proven stage IV NSCLC who underwent first-line therapy with pembrolizumab as a single agent or in combination with platinum-based chemotherapy, or second-line therapy with pembrolizumab, nivolumab, or atezolizumab. The intensity of APAP exposure was classified as low (therapeutic intake lasting less than 24 h or a cumulative intake lower than 60 doses of 1000 mg) or high (therapeutic intake lasting more than 24 h or a total intake exceeding 60 doses of 1000 mg). The favorable outcome of anti-PD-1/PD-L1 therapies was defined by durable clinical benefit (DCB). Progression-free survival (PFS) and overall survival (OS) were relevant to our efficacy analysis. Propensity score matching (PSM) methods were applied to adjust for differences between the APAP exposure subgroups. (3) Results: Over the course of April 2018 to October 2022, 80 patients were treated with first-line pembrolizumab either as single-agent therapy or in combination with platinum-based chemotherapy. During the period from June 2015 to November 2022, 145 patients were given anti-PD-1/PD-L1 blockade therapy as second-line treatment. Subsequent efficacy analyses relied on adjusted PSM populations in both treatment settings. Multivariate testing revealed that only the level of APAP and corticosteroid intake had an independent effect on DCB in both treatment lines. Multivariate Cox regression analysis confirmed high exposure to APAP and immunosuppressive corticosteroid therapy as independent predictors of shorter PFS and OS in both treatment settings. (4) Conclusions: Our findings would strengthen the available evidence that concomitant intake of APAP blunts the efficacy of ICIs in patients with advanced NSCLC. The detrimental effects appear to depend on the cumulative dose and duration of exposure to APAP. The inherent shortcomings of the current research warrant confirmation in larger independent series.

Identification of age- and immune-related gene signatures for clinical outcome prediction in lung adenocarcinoma

BACKGROUND

The understanding of the factors causing decreased overall survival (OS) in older patients compared to younger patients in lung adenocarcinoma (LUAD) remains.

METHODS

Gene expression profiles of LUAD were obtained from publicly available databases by Kaplan-Meier analysis was performed to determine whether age was associated with patient OS. The immune cell composition in the tumor microenvironment (TME) was evaluated using CIBERSORT. The fraction of stromal and immune cells in tumor samples were also using assessed using multiple tools including ESTIMATE, EPIC, and TIMER. Differentially expressed genes (DEGs) from the RNA-Seq data that were associated with age and immune cell composition were identified using the R package DEGseq. A 22-gene signature composed of DEGs associated with age and immune cell composition that predicted OS were constructed using Least Absolute Shrinkage and Selection Operator (LASSO).

RESULTS

In The Cancer Genome Atlas (TCGA)-LUAD dataset, we found that younger patients (≤70) had a significant better OS compared to older patients (>70). In addition, older patients had significantly higher expression of immune checkpoint proteins including inhibitory T cell receptors and their ligands. Moreover, analyses using multiple bioinformatics tools showed increased immune infiltration, including CD4+ T cells, in older patients compared to younger patients. We identified a panel of genes differentially expressed between patients >70 years compared to those ≤70 years, as well as between patients with high or low immune scores and selected 84 common genes to construct a prognostic gene signature. A risk score calculated based on 22 genes selected by LASSO predicted 1, 3, and 5-year OS, with an area under the curve (AUC) of 0.72, 0.72, 0.69, receptively, in TCGA-LUAD dataset and an independent validation dataset available from the European Genome-phenome Archive (EGA).

CONCLUSION

Our results demonstrate that age contributes to OS of LUAD patients atleast in part through its association with immune infiltration in the TME.

Next-generation sequencing methodologies to detect low-frequency mutations: "Catch me if you can"

Mutations, the irreversible changes in an organism's DNA sequence, are present in tissues at a variant allele frequency (VAF) ranging from ∼10-8 per bp for a founder mutation to ∼10-3 for a histologically normal tissue sample containing several independent clones - compared to 1%- 50% for a heterozygous tumor mutation or a polymorphism. The rarity of these events poses a challenge for accurate clinical diagnosis and prognosis, toxicology, and discovering new disease etiologies. Standard Next-Generation Sequencing (NGS) technologies report VAFs as low as 0.5% per nt, but reliably observing rarer precursor events requires additional sophistication to measure ultralow-frequency mutations. We detail the challenge; define terms used to characterize the results, which vary between laboratories and sometimes conflict between biologists and bioinformaticists; and describe recent innovations to improve standard NGS methodologies including: single-strand consensus sequence methods such as Safe-SeqS and SiMSen-Seq; tandem-strand consensus sequence methods such as o2n-Seq and SMM-Seq; and ultrasensitive parent-strand consensus sequence methods such as DuplexSeq, PacBio HiFi, SinoDuplex, OPUSeq, EcoSeq, BotSeqS, Hawk-Seq, NanoSeq, SaferSeq, and CODEC. Practical applications are also noted. Several methods quantify VAF down to 10-5 at a nt and mutation frequency (MF) in a target region down to 10-7 per nt. By expanding to > 1 Mb of sites never observed twice, thus forgoing VAF, other methods quantify MF < 10-9 per nt or < 15 errors per haploid genome. Clonal expansion cannot be directly distinguished from independent mutations by sequencing, so it is essential for a paper to report whether its MF counted only different mutations - the minimum independent-mutation frequency MFminI - or all mutations observed including recurrences - the larger maximum independent-mutation frequency MFmaxI which may reflect clonal expansion. Ultrasensitive methods reveal that, without their use, even mutations with VAF 0.5-1% are usually spurious.

The development of a tumor-associated autoantibodies panel to predict clinical outcomes for immune checkpoint inhibitor-based treatment in patients with advanced non-small-cell lung cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) have become one important therapeutic strategy for advanced non-small-cell lung cancer (NSCLC). It remains imperative to identify reliable and convenient biomarkers to predict both the efficacy and toxicity of immunotherapy, and tumor-associated autoantibodies (TAAbs) are recognized as one of the promising candidates for this.

PATIENTS AND METHODS

This study enrolled 97 advanced NSCLC patients with ICI-based immunotherapy treatment, who were divided into a training cohort (n = 48) and a validation cohort (n = 49), and measured for the serum level of 35 TAAbs. According to the statistical association between the serum positivity and clinical outcome of each TAAb in the training cohort, a TAAb panel was developed to predict the progression-free survival (PFS), and further examined in the validation cohort and in different subgroups. Similarly, another TAAb panel was derived to predict the occurrence of immune-related adverse events (irAEs).

RESULTS

In the training cohort, a 7-TAAb panel composed of p53, CAGE, MAGEA4, GAGE7, UTP14A, IMP2, and PSMC1 TAAbs was derived to predict PFS (median PFS [mPFS] 9.9 vs. 4.3 months, p = 0.043). The statistical association between the panel positivity and longer PFS was confirmed in the validation cohort (mPFS 11.1 vs. 4.8 months, p = 0.015) and in different subgroups of patients. Moreover, another 4-TAAb panel of BRCA2, MAGEA4, ZNF768, and PARP TAAbs was developed to predict the occurrence of irAEs, showing higher risk in panel-positive patients (71.43% vs. 28.91%, p = 0.0046).

CONCLUSIONS

Collectively, our study developed and validated two TAAb panels as valuable prognostic biomarkers for immunotherapy.