Abstract 4136: Properties of the immune microenvironment associated with clonal diversity in high-grade serous ovarian cancer
Bibliographic record
Abstract
Abstract High-grade serous ovarian cancer (HGSC) is a challenging disease characterized by poor survival and relapse. Our group has revealed extensive clonal diversity of malignant cells in HGSC, which is thought to facilitate the emergence of resistance and recurrence in response to chemotherapy. Moreover, we have shown that the presence of tumor infiltrating lymphocytes (TILs) is associated with longer patient survival in HGSC, suggesting that the immune system can contend with the clonal diversity of tumors in some patients. We sought to determine how TIL abundance and repertoire diversity relates to the degree of tumor clone diversity in HGSC. We performed whole-genome sequencing, targeted amplicon deep sequencing, gene expression profiling, and T-cell receptor sequencing on 34 spatially separated HGSC tumor samples (8 patients) including ovarian masses and peritoneal foci. In addition, tissue sections were immunohistochemically stained for CD3, CD8, CD20, CD79a, and CD138 to detect major TIL subsets. Using PyClone, we decomposed each tumor sample into its constituent malignant clones and inferred clonal genotypes. We discovered profound intra- and inter-patient variation in the degree of tumor clone diversity from phylogenetic analysis. Widespread inter-patient variation was also observed in TIL counts and T-cell receptor repertoires. Intraepithelial CD3+ cell counts ranged from 2.2-173.2 per HPF and the number of unique T-cell receptor clonotypes varied from 422 to 3164 per sample. Remarkably, quantitative metrics of tumor clone diversity—as defined by phylogenetic divergence and entropy in the malignant composition of each tumor—was associated with the ‘proliferative’ molecular subtype and, accordingly, low TIL density. Tumor clone diversity showed no correlation with the number of unique T-cell receptor species. Moreover, preliminary analyses reveal no association between tumor clone diversity and the expression of several ligands and receptors involved in inhibitory immune signaling (CTLA-4, PD-1, PD-L1, PD-L2). Our results reveal an association between low TIL abundance and high diversity of malignant clones. This suggests that immune infiltration may inhibit tumor proliferation and clonal diversification, or vice versa. Collectively, our findings expose a relationship of the immune microenvironment with the clonal dynamics of malignant cells that could be exploited to overcome therapeutic resistance associated with clonal evolution in HGSC. Citation Format: Allen W. Zhang, Andrew McPherson, Andrew Roth, David R. Kroeger, Katy Milne, Wyeth W. Wasserman, Jessica N. McAlpine, Robert A. Holt, Brad H. Nelson, Sohrab P. Shah. Properties of the immune microenvironment associated with clonal diversity in high-grade serous ovarian cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4136.
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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 | 0.001 | 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".