The Tumor Immune Contexture of Prostate Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
One in seven men in North America is expected to be diagnosed with prostate cancer (PCa) during their lifetime (1, 2). While a wide range of treatment options including surgery, radiation, androgen deprivation and chemotherapy have been in practice for the last few decades, there are limited treatment options for metastatic and treatment resistant disease. Immunotherapy targeting T-cell associated immune checkpoints such as CTLA-4, PD-L1, and PD-1 have not yet proven to be efficacious in PCa. Tumor mutational burden, mutations in DNA damage repair genes, immune cell composition and density in combination with their spatial organization, and expression of immune checkpoint proteins are some of the factors influencing the success of immune checkpoint inhibitor therapies. The paucity of these features in PCa potentially makes them unresponsive to contemporary immune checkpoint inhibition. In this review, we highlight the hallmark events in the PCa tumor immune microenvironment and provide insights into the current state of knowledge in this field with a focus on the role of tumor cell intrinsic events that potentially regulate immune related events and determine therapeutic outcomes. We surmise that the cumulative impact of factors such as the pre-treatment immune status, PTEN expression, DNA damage repair gene mutations, and the effects of conventionally used treatments on the anti-tumor immune response should be considered in immunotherapy trial design in PCa.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it