Biological insights from plasma proteomics of non-small cell lung cancer patients treated with immunotherapy.

Introduction: Immune checkpoint inhibitors have made a paradigm shift in the treatment of non-small cell lung cancer (NSCLC). However, clinical response varies widely and robust predictive biomarkers for patient stratification are lacking. Here, we characterize early on-treatment proteomic changes in blood plasma to gain a better understanding of treatment response and resistance. Methods: Pre-treatment (T0) and on-treatment (T1) plasma samples were collected from 225 NSCLC patients receiving PD-1/PD-L1 inhibitor-based regimens. Plasma was profiled using aptamer-based technology to quantify approximately 7000 plasma proteins per sample. Proteins displaying significant fold changes (T1:T0) were analyzed further to identify associations with clinical outcomes using clinical benefit and overall survival as endpoints. Bioinformatic analyses of upregulated proteins were performed to determine potential cell origins and enriched biological processes. Results: The levels of 142 proteins were significantly increased in the plasma of NSCLC patients following ICI-based treatments. Soluble PD-1 exhibited the highest increase, with a positive correlation to tumor PD-L1 status, and, in the ICI monotherapy dataset, an association with improved overall survival. Bioinformatic analysis of the ICI monotherapy dataset revealed a set of 30 upregulated proteins that formed a single, highly interconnected network, including CD8A connected to ten other proteins, suggestive of T cell activation during ICI treatment. Notably, the T cell-related network was detected regardless of clinical benefit. Lastly, circulating proteins of alveolar origin were identified as potential biomarkers of limited clinical benefit, possibly due to a link with cellular stress and lung damage. Conclusions: Our study provides insights into the biological processes activated during ICI-based therapy, highlighting the potential of plasma proteomics to identify mechanisms of therapy resistance and biomarkers for outcome.

Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have revolutionized the cancer therapy landscape due to long-term benefits in patients with advanced metastatic disease. However, robust predictive biomarkers for response are still lacking and treatment resistance is not fully understood. METHODS: We profiled approximately 800 pre-treatment and on-treatment plasma proteins from 143 ICI-treated patients with non-small cell lung cancer (NSCLC) using ELISA-based arrays. Different clinical parameters were collected from the patients including specific mutations, smoking habits, and body mass index, among others. Machine learning algorithms were used to identify a predictive signature for response. Bioinformatics tools were used for the identification of patient subtypes and analysis of differentially expressed proteins and pathways in each response group. RESULTS: We identified a predictive signature for response to treatment comprizing two proteins (CXCL8 and CXCL10) and two clinical parameters (age and sex). Bioinformatic analysis of the proteomic profiles identified three distinct patient clusters that correlated with multiple parameters such as response, sex and TNM (tumors, nodes, and metastasis) staging. Patients who did not benefit from ICI therapy exhibited significantly higher plasma levels of several proteins on-treatment, and enrichment in neutrophil-related proteins. CONCLUSIONS: Our study reveals potential biomarkers in blood plasma for predicting response to ICI therapy in patients with NSCLC and sheds light on mechanisms underlying therapy resistance.

Host response to immune checkpoint inhibitors contributes to tumor aggressiveness.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have made a paradigm shift in clinical oncology due to unprecedented long-term remissions. However, only a small proportion of patients respond to ICI therapy. It is, therefore, essential to understand the mechanisms driving therapy resistance and to develop strategies for increasing response rates. We previously demonstrated that in response to various cancer treatment modalities, the host activates a range of biological processes that promote tumor regrowth and metastasis. Here, we characterize the host-mediated response to ICI therapy, and investigate its contribution to therapy resistance. METHODS: Tumor cell migration, invasion and motility were assessed in the presence of plasma from ICI-treated mice and patients. Immune cell composition in peripheral blood and tumors of ICI-treated mice was assessed by flow and mass cytometry. Plasma host factors driving tumor aggressiveness were identified by proteomic profiling, followed by bioinformatic analysis. The therapeutic effect of inhibiting host-mediated processes in ICI-treated mice was assessed in a tumor model. RESULTS: Tumor cells exhibit enhanced migratory and invasive properties in vitro on exposure to plasma from anti-PD1-treated mice. Moreover, mice intravenously injected with plasma-exposed tumor cells display increased metastatic burden and mortality rate in comparison to control arms. Furthermore, tumors from anti-PD1-treated mice as well as Matrigel plugs containing plasma from anti-PD1-treated mice are highly infiltrated with immune cell types associated with both antitumor and protumor activity. These collective findings suggest that anti-PD1 treatment induces a systemic host response that potentially counteracts the drug's therapeutic activity. Proteomic profiling of plasma from anti-PD1-treated mice reveals an activation of multiple biological pathways associated with tumor aggressiveness. Consequently, blocking IL-6, one of the key drivers of the identified biological pathways, counteracts ICI-induced metastatic properties in vitro and improves ICI treatment efficacy in vivo. Lastly, plasma samples from ICI-treated non-small cell lung cancer patients differentially affect tumor cell aggressiveness in vitro, with enhanced tumor cell motility correlating with a worse clinical outcome. CONCLUSIONS: ICI therapy induces host-mediated processes that contribute to therapy resistance. Identification and analysis of such processes may lead to the discovery of biomarkers for clinical response and strategies for overcoming therapy resistance.

PAX8 activates a p53-p21-dependent pro-proliferative effect in high grade serous ovarian carcinoma.

High grade serous carcinoma (HGSC) is the most common subtype of ovarian cancer and it is now widely accepted that this disease often originates from the fallopian tube epithelium. PAX8 is a fallopian tube lineage marker with an essential role in embryonal female genital tract development. In the adult fallopian tube, PAX8 is expressed in the fallopian tube secretory epithelial cell (FTSEC) and its expression is maintained through the process of FTSEC transformation to HGSC. We now report that PAX8 has a pro-proliferative and anti-apoptotic role in HGSC. The tumor suppressor gene TP53 is mutated in close to 100% of HGSC; in the majority of cases, these are missense mutations that endow the mutant p53 protein with potential gain of function (GOF) oncogenic activities. We show that PAX8 positively regulates the expression of TP53 in HGSC and the pro-proliferative role of PAX8 is mediated by the GOF activity of mutant p53. Surprisingly, mutant p53 transcriptionally activates the expression of p21, which localizes to the cytoplasm of HGSC cells where it plays a non-canonical, pro-proliferative role. Together, our findings illustrate how TP53 mutations in HGSC subvert a normal regulatory pathway into a driver of tumor progression.

The MAPK/ERK and PI3K pathways additively coordinate the transcription of recombination-activating genes in B lineage cells.

Rag-1 and Rag-2 are essential for the construction of the BCR repertoire. Regulation of Rag gene expression is tightly linked with BCR expression and signaling during B cell development. Earlier studies have shown a major role of the PI(3)K/Akt pathway in regulating the transcription of Rag genes. In this study, by using the 38c13 murine B cell lymphoma we show that transcription of Rag genes is also regulated by the MEK/ERK pathways, and that both pathways additively coordinate in this regulation. The additive effect is observed for both ligand-dependent (upon BCR ligation) and ligand independent (tonic) signals. However, whereas the PI(3)K/Akt regulation of Rag transcription is mediated by Foxo1, we show in this study that the MEK/ERK pathway coordinates with the regulation of Rag by controlling the phosphorylation and turnover of E47 and its consequential binding to the Rag enhancer regions. Our results suggest that the PI(3)K and MEK/ERK pathways additively coordinate in the regulation of Rag transcription in an independent manner.