RPL13A and GNL3 May Help Assess Immunotherapy Resistance for NSCLC

Precision therapies for lung cancer may be improved by targeting RPL13A and GNL3, potentially indicative biomarkers of PD-1 inhibitor resistance.

Ribosomal RNA genes, ribosomal protein L13a (RPL13A) and G protein nucleolar (GNL3), may be used to help assess immunotherapy resistance for patients with non-small cell lung cancer (NSCLC), according to a study published in the Journal for Immunotherapy of Cancer.¹

Of 54,000 gene variables generated per case, 25,740 that expressed a prespecified frequency or higher were analyzed. Twelve genes were identified after a Cox proportional hazards model analysis was performed for overall survival (OS) and progressive-free survival (PFS) and gene intersection was used across 4 tissue microarray (TMA) pots per patient. Of the 12 identified, RPL13A and GNL3 in tumor-cell compartment within a validation cohort were significantly associated with OS and PFS, respectively (CK: HR, 2.48; P = .02 and HR, 5.33; P = .04).

“[Immune checkpoint inhibition] is not a drug that you want to give lightly. In early cancer, we want to make sure that the patient is going to benefit before they get the drug,” principal investigator David Rimm, MD, PhD, Anthony N. Brady Professor of Pathology, professor of medical oncology, member of Yale Cancer Center, stated in a press release on the findings.² “You can imagine someday a patient might be tested for these biomarkers, and then if they’re negative, they could have immune checkpoint inhibitors in the adjuvant setting. If they’re positive, we might want to opt for other adjuvant options and not expose them to the risk of an immune checkpoint inhibitor.”

Retrospectively collected baseline/pretreatment formalin-fixed paraffin-embedded tumor specimens were analyzed in 4 TMA format from 56 patients with NSCLC treated with a checkpoint inhibitor between 2017 and 2019 at the Yale School of Medicine. Tissue samples, collected from retrospective immunotherapy-treated cohorts from a single institution, were used to create a discovery cohort and a validation set within individual molecular compartments to discover immunotherapy-resistant biomarkers.

Tumors were reviewed by using hematoxylin and eosin (H&E)-stained preparations to select representative tumor areas for TMA construction. Afterward, four cores 0.28 mm2 in area and 600 µm in diameter were arrayed in four recipient TMA master blocks following extraction from pathologist-selected regions from each tumor block. Tumor core selection was based on viable tumor (CK+) cell presence with morphology and associated disease-representing stromal features by pathologist’s discretion. An initial cohort included 56 NSCLC cases, individually made up of four TMA cores in four master blocks; with two sets created for each compartment. The discovery set included samples across all 4 cores and the validation set included the remaining patient samples.

In 34 YTMA-tested patients with adequate tumor, increased expression of two RNA transcripts TFCP2L1 and CYBA was significantly associated with worse outcomes in the discovery set, but not in the validation cohort. Although numerous RNAs were associated with shorter OS in the discovery set, only RPL13A and GNL3 were also associated with shorter OS in the validation cohort (HR, 2.48; P = .02; HR, 5.33, P = .04). CYBA and AP1M1 were both associated with shorter PFS in all 4 TMAs, but not in the validation cohort.

In 22 YTMA-tested patients with adequate lymphocytes increased expression of NELFE in TYMA2 and YTMA3 and increased expression of LIMS3 was common. High secreted frizzled-related protein 2 (SFRP2) was significantly associated with OS in the discovery set yet not in the validation cohort. Mitochondrial carrier 1 (MTCH1) was only associated with shorter PFS in YTMA2 and YTMA3.

Additionally, in 12 patients with adequate macrophages, no common YTMA associations were found. Rho GTPase-activating protein (ARHGAP) was associated with shorter OS in YTMA 1-3 as well as the validation cohort (HR, 10.35; P = 0.04).

“Diverse mechanisms of immunotherapy resistance have been characterized, and more continue to be uncovered. rRNAs have multiple functions as systemic regulators in biological processes and may also play a crucial role in immunotherapy resistance. Future explorations are warranted to discover more immune-related rRNAs and elucidate their common mechanisms of immune regulation NSCLC, thus giving more direct indications to deal with immune resistance,” Rimm and study coauthors concluded.

References

1. Moutafi MK, Bates KM, Aung TW, et al. High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC). Journal for ImmunoTherapy Cancer. 2024;12(6):e009039. doi:10.1136/jitc-2024-009039
2. Immunotherapy for NSCLC: potential biomarkers for resistance are identified. News release. Published July 9, 2024. Accessed July 17, 2024. https://tinyurl.com/yrce7vub