Enhancement of immune surveillance in breast cancer by targeting hypoxic tumor endothelium: Can it be an immunological switch point?
Bibliographic record
Abstract
Breast cancer ranks second among the causes of cancer-related deaths in women. In spite of the recent advances achieved in the diagnosis and treatment of breast cancer, further study is required to overcome the risk of cancer resistance to treatment and thereby improve the prognosis of individuals with advanced-stage breast cancer. The existence of a hypoxic microenvironment is a well-known event in the development of mutagenesis and rapid proliferation of cancer cells. Tumor cells, purposefully cause local hypoxia in order to induce angiogenesis and growth factors that promote tumor growth and metastatic characteristics, while healthy tissue surrounding the tumor suffers damage or mutate. It has been found that these settings with low oxygen levels cause immunosuppression and a lack of immune surveillance by reducing the activation and recruitment of tumor infiltrating leukocytes (TILs). The immune system is further suppressed by hypoxic tumor endothelium through a variety of ways, which creates an immunosuppressive milieu in the tumor microenvironment. Non responsiveness of tumor endothelium to inflammatory signals or endothelial anergy exclude effector T cells from the tumor milieu. Expression of endothelial specific antigens and immunoinhibitory molecules like Programmed death ligand 1,2 (PDL–1, 2) and T cell immunoglobulin and mucin-domain containing-3 (TIM-3) by tumor endothelium adds fuel to the fire by inhibiting T lymphocytes while promoting regulatory T cells. The hypoxic microenvironment in turn recruits Myeloid Derived Suppressor Cells (MDSCs), Tumor Associated Macrophages (TAMs) and T regulatory cells (Treg). The structure and function of newly generated blood vessels within tumors, on the other hand, are aberrant, lacking the specific organization of normal tissue vasculature. Vascular normalisation may work for a variety of tumour types and show to be an advantageous complement to immunotherapy for improving tumour access. By enhancing immune response in the hypoxic tumor microenvironment, via immune-herbal therapeutic and immune-nutraceuticals based approaches that leverage immunological evasion of tumor, will be briefly reviewed in this article. Whether these tactics may be the game changer for emerging immunological switch point to attenuate the breast cancer growth and prevent metastatic cell division, is the key concern of the current study.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".