Abstract 273: Prostate cancer metastasis induces irregular bone formation associated to specific androgen dependent phenotypes
Bibliographic record
Abstract
Abstract Bone metastases (BM) occur in ~80% of advanced prostate cancer (PC) patients, and are a major cause of morbidity. PCBMs are predominantly osteoblastic with mixed, and lytic regions; all of which compromise bone strength. How PCs alter bone structure is unresolved. Prolonged use of modern androgen receptor (AR) targeting agents has increased development of AR pathway-independent PC phenotypes. We hypothesize that defining the structural changes, cellular composition, and PC classification of PCBM-affected bone will help reveal mechanisms of PCBM pathology, and identify potential therapeutic opportunities. We analyze the 3D structure of 14 cadaveric PCBM lumbar vertebrae using micro-computed tomography (microCT). We performed scanning electron microscopy quantitative backscattering electron (qBSE), and energy-dispersive X-ray spectroscopy (EDX) to determine mineral morphology and composition. We analyzed sequential decalcified sections for collagen structure, fibril orientation, and extracellular matrix composition using bright field and polarized light microscopy. We determined lesion structure and cell distribution from two PCBM vertebral specimens resected during decompression surgery using histology and immunohistochemistry, and characterized PCBM cell populations using single cell RNA sequencing (sc RNA Seq) on one vertebral specimen. MicroCT imaging revealed three distinct dysmorphic bone patterns: 1) osteolytic, defined by thinned broken trabecula of well-organized mineral and collagen structures; 2) osteoblastic, with disorganized matrix deposited on pre-existing trabecula; and 3) osteoblastic, with little, if any, residual trabecula, and dominated by accumulation of disorganized mineralized matrix. qBSE and EDX revealed heterogeneous mineral composition, with higher variability in mineral content. Disorganized matrix had a higher voids or “lacunae” density, poorly organized collagen fiber alignment, and higher decorin and pan-proteoglycan content. Sc RNA Seq revealed a PCBM tumor microenvironment composed of a variety of immune cells, hematopoietic progenitors, and bone resident cells. Importantly, we identified AR-high, AR-low, and double-negative PC cells in the same lesion, with minimum neuroendocrine component. Simultaneous presence of these PC phenotypes was confirmed by immunohistochemistry. Morphologically, AR-positive cells adopt two configurations in PCBM, i) clusters within bone cavities in which cells maintain secretory polarization and resemble prostate acini, and ii) diffuse cells in intimate contact with bone-resident cells that lack polarization. PCBM lesions have abnormal bone structures lacking collagen organization, and with mineral heterogeneity consistent with bone weakness. PC cells interact with bone cells, but how distinct PC phenotypes affect bone turnover and structure need further analysis. Citation Format: Felipe Eltit, Qiong Wang, Raphaële Charest-Morin, Colm Morrissey, Eva Corey, Rizhi Wang, Michael E. Cox. Prostate cancer metastasis induces irregular bone formation associated to specific androgen dependent phenotypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 273.
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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) | 0.005 | 0.001 |
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".