Plasma exosome microRNA-155 expression in patients with metastatic renal cell carcinoma treated with immune checkpoint inhibitors: A potential biomarker of response to systemic therapy.
Bibliographic record
Abstract
4570 Background: The search for a reliable predictive biomarker of response to immune checkpoint-based therapy (ICBT) remains a critically unmet need in the management of metastatic renal cell carcinoma (mRCC). We sought to evaluate the biomarker potential of plasma exosome microRNAs (miRNAs) implicated in RCC and in augmentation of the tumour microenvironment (TME) for such a role. Methods: Eleven miRNAs that are over-expressed in RCC and/or immune-associated were evaluated in 40 patients with mRCC (prior to initiating ICBT) and in 30 healthy volunteers. Exosomes were extracted from 500 uL of plasma and were used for miRNAs extraction. MiRNAs expression was evaluated by RT-PCR. Cycle threshold values were normalized to miR-30-3b, and the relative quantity of the expression (RQ) was compared to those of healthy volunteers and calculated using the 2ΔΔCt method. Mann-Whitney U test was used to evaluate the expression of miRNAs between mRCC pts and healthy volunteers according to best response to first line ICBT between responders (n = 27) v non-responders (n = 13). The cut-off value of significant expression was established by Youden’s index. Responders were defined as those patients experiencing complete response, partial response or stable disease and non-responders were those who experienced progressive disease. Results: The most common first line ICBT was nivolumab + ipilimumab (n = 32), followed by pembrolizumab + axitinib (n = 5), and avelumab + axitinib (n = 3). A significantly higher expression of miRNA-1233 (median 1.85 v 0.81 p = 0.008) and miRNA-155 [miR-155] (3.69 v 0.21 p = 0.006) were found in patients compared to healthy volunteers. Higher miR-155 expression was associated with higher Fuhrman grade (p = 0.002). There was no association with other clinical prognostic factors. MiR-155 was expressed at a significantly lower level in responders than in non-responders (median 0.61 v 35.29, p = 0.042). Response rate amongst patients with low and high expression of miR-155 (RQ ≤ 2.5) was statistically different (p = 0.042) and 84.2% of the pts with low miR-155 expression responded to the treatment. Conclusions: Lower expression of miR-155 was associated with response to ICBT in patients with mRCC. Functionally, miR-155 is involved in regulation and modulation of the TME. These results underscore the need for further work in this area to elucidate the role of this and other miRNAs as biomarkers of response in mRCC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".