Nemvaleukin alfa, a novel engineered IL-2 fusion protein, drives antitumor immunity and inhibits tumor growth in small cell lung cancer
Bibliographic record
Abstract
Background Small cell lung cancer (SCLC) is a deadly disease with a 5-year survival of less than 7%. The addition of immunotherapy to chemotherapy was recently approved as first-line treatment; however, the improved clinical benefit is modest, highlighting an urgent need for new treatment strategies. Nemvaleukin alfa, a novel engineered interleukin-2 fusion protein currently in phase I–III studies, is designed to selectively expand cytotoxic natural killer (NK) cells and CD8+ T cells. Here, using a novel SCLC murine model, we investigated the effects of a mouse version of nemvaleukin (mNemvaleukin) on tumor growth and antitumor immunity. Methods A novel Rb1 −/− p53 −/− p130 −/− SCLC model that mimics human disease was generated. After confirming tumor burden by MRI, mice were randomized into four treatment groups: vehicle, mNemvaleukin alone, chemotherapy (cisplatin+etoposide) alone, or the combination of mNemvaleukin and chemotherapy. Tumor growth was measured by MRI and survival was recorded. Tumor-infiltrating lymphocytes and peripheral blood immune cells were analyzed by flow cytometry. Cytokine and chemokine secretion were quantified and transcriptomic analysis was performed to characterize the immune gene signatures. Results mNemvaleukin significantly inhibited SCLC tumor growth, which was further enhanced by the addition of chemotherapy. Combining mNemvaleukin with chemotherapy provided the most significant survival benefit. Profiling of tumor-infiltrating lymphocytes revealed mNemvaleukin expanded the total number of tumor-infiltrating NK and CD8+ T cells. Furthermore, mNemvaleukin increased the frequencies of activated and proliferating NK and CD8+ T cells in tumors. Similar immune alterations were observed in the peripheral blood of mNemvaleukin-treated mice. Of note, combining mNemvaleukin with chemotherapy had the strongest effects in activating effector and cytotoxic CD8+ T cells. mNemvaleukin alone, and in combination with chemotherapy, promoted proinflammatory cytokine and chemokine production, which was further confirmed by transcriptomic analysis. Conclusions mNemvaleukin, a novel cytokine-based immunotherapy, significantly inhibited murine SCLC tumor growth and prolonged survival, which was further enhanced by the addition of chemotherapy. mNemvaleukin alone, and in combination with chemotherapy, drove a strong antitumor immune program elicited by cytotoxic immune cells. Our findings support the evaluation of nemvaleukin alone or in combination with chemotherapy in clinical trials for the treatment of SCLC.
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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 | 0.000 |
| 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".