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Plasma extracellular vesicle transcriptomics identifies CD160 for predicting immunochemotherapy efficacy in lung cancer.

ABSTRACT: Better biomarkers are needed to improve the efficacy of immune checkpoint inhibitors in lung adenocarcinoma (LUAD) treatment. We investigated the plasma extracellular vesicle (EV)-derived long RNAs (exLRs) in unresectable/advanced LUAD to explore biomarkers for immunochemotherapy. Seventy-four LUAD patients without targetable mutations receiving first-line anti-programmed cell death 1 (PD-1) immunochemotherapy were enrolled. Their exLRs were profiled through plasma EV transcriptome sequencing. Biomarkers were analyzed against response rate and survival using pre- and post-treatment samples in the retrospective cohort (n = 36) and prospective cohort (n = 38). The results showed that LUAD patients demonstrated a distinct exLR profile from the healthy individuals (n = 56), and T-cell activation-related pathways were enriched in responders. Among T-cell activation exLRs, CD160 exhibited a strong correlation with survival. In the retrospective cohort, the high baseline EV-derived CD160 level correlated with prolonged progression-free survival (PFS) (P < 0.001) and overall survival (OS) (P = 0.005), with an area under the curve (AUC) of 0.784 for differentiating responders from non-responders. In the prospective cohort, the CD160-high patients also showed prolonged PFS (P = 0.003) and OS (P = 0.014) and a promising AUC of 0.648. The predictive value of CD160 expression was validated by real-time quantitative PCR. We also identified the dynamics of EV-derived CD160 for monitoring therapeutic response. The elevated baseline CD160 reflected a higher abundance of circulating NK cells and CD8⁺ -naïve T cells, suggesting more active host immunity. In addition, increased CD160 levels of tumors also correlated with a favorable prognosis in LUAD patients. Together, plasma EV transcriptome analysis revealed the role of the baseline CD160 level and early post-treatment CD160 dynamics for predicting the response to anti-PD-1 immunochemotherapy in LUAD patients.

SUBMITTER: Liao J

PROVIDER: S-EPMC10323081 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Plasma extracellular vesicle transcriptomics identifies CD160 for predicting immunochemotherapy efficacy in lung cancer.

Liao Jiatao J Lai Hongyan H Liu Chang C Zhang Xin X Ou Qiuxiang Q Li Qiaojuan Q Li Yan Y Wang Zhen Z Liu Cuicui C Wu Xianghua X Wang Huijie H Yu Hui H Sun Si S Zhao Xinmin X Hu Zhihuang Z Zhang Yao Y Lin Ying Y Yu Bo B Huang Shenglin S Wang Jialei J

Cancer science 20230420 7

Better biomarkers are needed to improve the efficacy of immune checkpoint inhibitors in lung adenocarcinoma (LUAD) treatment. We investigated the plasma extracellular vesicle (EV)-derived long RNAs (exLRs) in unresectable/advanced LUAD to explore biomarkers for immunochemotherapy. Seventy-four LUAD patients without targetable mutations receiving first-line anti-programmed cell death 1 (PD-1) immunochemotherapy were enrolled. Their exLRs were profiled through plasma EV transcriptome sequencing. B ...[more]

PMID: 37014183

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Project description:IntroductionThe introduction of Immune Checkpoint Inhibitors (ICIs) has marked a paradigm shift in treating Lung Squamous Cell Carcinoma (LUSC), emphasizing the urgent need for precise molecular biomarkers to reliably forecast therapeutic efficacy. This study aims to identify potential biomarkers for immunochemotherapy efficacy by focusing on plasma extracellular vesicle (EV)-derived long RNAs (exLRs).MethodsWe enrolled 78 advanced LUSC patients undergoing first-line immunochemotherapy. Plasma samples were collected, and exLR sequencing was conducted to establish baseline profiles. A retrospective analysis was performed on 42 patients to identify differentially expressed exLRs. Further validation of the top differentially expressed exLRs was conducted using quantitative reverse transcription PCR (qRT-PCR). Univariate Cox analysis was applied to determine the prognostic significance of these exLRs. Based on these findings, we developed a predictive signature (p-Signature).ResultsIn the retrospective analysis of 42 patients, we identified 460 differentially expressed exLRs, with pathways related to leukocyte migration notably enriched among non-responders. Univariate Cox analysis revealed 45 exLRs with prognostic significance. The top 6 protein-coding exLRs were validated using qRT-PCR, identifying CXCL8, SSH3, and SDHAF1 as differentially expressed between responders and non-responders. The p-Signature, comprising these three exLRs, demonstrated high accuracy in distinguishing responders from non-responders, with an Area Under the Curve (AUC) of 0.904 in the retrospective cohort and 0.812 in the prospective cohort.DiscussionThis study highlighted the potential of plasma exLR profiles in predicting LUSC treatment efficacy. Intriguingly, lower p-Signature scores were associated with increased abundance of activated CD4+ and CD8+ T cells, indicating a more robust immune environment. These findings suggest that the p-Signature could serve as a valuable tool in guiding personalized and effective therapeutic strategies for LUSC.

Project description:BackgroundResistance to chemotherapy continues to be a challenge when treating epithelial ovarian cancer (EOC), contributing to low patient survival rates. While CA125, the conventional EOC biomarker, has been useful in monitoring patients' response to therapy, there are no biomarkers used to predict treatment response prior to chemotherapy. Previous work in vitro showed that plasma gelsolin (pGSN) is highly expressed in chemoresistant EOC cell lines, where it is secreted in small extracellular vesicles (sEVs). Whether sEVs from tumour cells are secreted into the circulation of EOC patients and could be used to predict patient chemoresponsiveness is yet to be determined. This study aims to identify if sEV-pGSN in the circulation could be a predictive biomarker for chemoresistance in EOC.MethodsSandwich ELISA was used to measure pGSN concentrations from plasma samples of 96 EOC patients (primarily high grade serous EOC). sEVs were isolated using ExoQuick ULTRA and characterized using western blot, nanoparticle tracking analysis, and electron microscopy after which pGSN was measured from the sEVs. Patients were stratified as platinum sensitive or resistant groups based on first progression free interval (PFI) of 6 or 12 months.ResultsTotal circulating pGSN was significantly decreased and sEV-pGSN increased in patients with a PFI ≤ 12 months (chemoresistant) compared to those with a PFI > 12 months (chemosensitive). The ratio of total pGSN to sEV-pGSN further differentiated these groups and was a strong predictive marker for chemoresistance (sensitivity: 73.91%, specificity: 72.46%). Predetermined CA125 was not different between chemosensitive and chemoresistant groups and was not predictive of chemoresponsiveness prior to treatment. When CA125 was combined with the ratio of total pGSN/sEV-pGSN, it was a significant predictor of chemoresponsiveness, but the test performance was not as robust as the total pGSN/sEV-pGSN alone.ConclusionsTotal pGSN/sEV-pGSN was the best predictor of chemoresponsiveness prior to treatment, outperforming the individual biomarkers (CA125, total pGSN, and sEV-pGSN). This multianalyte predictor of chemoresponsiveness could help to inform physicians' treatment and follow up plan at the time of EOC diagnosis, thus improving patients' outcomes.

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Plasma extracellular vesicle transcriptomics identifies CD160 for predicting immunochemotherapy efficacy in lung cancer.

Publications

Plasma extracellular vesicle transcriptomics identifies CD160 for predicting immunochemotherapy efficacy in lung cancer.

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