Cancer cell genotype associated tumor immune microenvironment exhibits differential response to therapeutic STING pathway activation in high-grade serous ovarian cancer
Bibliographic record
Abstract
Background High-grade serous ovarian carcinoma (HGSC) is the most lethal gynecologic malignancy characterized by resistance to chemotherapy and high rates of recurrence. HGSC tumors display a high prevalence of tumor suppressor gene loss. Given the type 1 interferon regulatory function of BRCA1 and PTEN genes and their associated contrasting T-cell infiltrated and non-infiltrated tumor immune microenvironment (TIME) states, respectively, in this study we investigated the potential of stimulator of interferon genes (STING) pathway activation in improving overall survival via enhancing chemotherapy response, specifically in tumors with PTEN deficiency. Methods Expression of PTEN protein was evaluated in tissue microarrays generated using pretreatment tumors collected from a cohort of 110 patients with HGSC. Multiplex immunofluorescence staining was performed to determine spatial profiles and density of selected lymphoid and myeloid cells. In vivo studies using the syngeneic murine HGSC cell lines, ID8- Trp53 –/– ; Pten –/– and ID8- Trp53 –/– ; Brca1 –/– , were conducted to characterize the TIME and response to carboplatin chemotherapy in combination with exogenous STING activation therapy. Results Patient tumors with absence of PTEN protein exhibited a significantly decreased disease specific survival and intraepithelial CD68+ macrophage infiltration as compared with intact PTEN expression. In vivo studies demonstrated that Pten -deficient ovarian cancer cells establish an immunosuppressed TIME characterized by increased proportions of M2-like macrophages, GR1+MDSCs in the ascites, and reduced effector CD8+ cytotoxic T-cell function compared with Brca1 -deficient cells; further, tumors from mice injected with Pten -deficient ID8 cells exhibited an aggressive behavior due to suppressive macrophage dominance in the malignant ascites. In combination with chemotherapy, exogenous STING activation resulted in longer overall survival in mice injected with Pten -deficient ID8 cells, reprogrammed intraperitoneal M2-like macrophages derived from Pten -deficient ascites to M1-like phenotype and rescued CD8+ cytotoxic T-cell activation. Conclusions This study reveals the importance of considering the influence of cancer cell intrinsic genetic alterations on the TIME for therapeutic selection. We establish the rationale for the optimal incorporation of interferon activating therapies as a novel combination strategy in PTEN-deficient HGSC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".