ReviewCurrent oncology reports2017
Cancer Clonal Theory, Immune Escape, and Their Evolving Roles in Cancer Multi-Agent Therapeutics.
Review in Current oncology reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Therapeutic vaccines for NSCLC: From mechanisms to clinical translation.Chinese medical journal pulmonary and critical care medicine · 2026Review
- Deciphering and targeting oncogenic pathways through integrated approaches and amino acid metabolism in hematologic malignancies.Discover oncology · 2025Review
- Unveiling diagnostic and therapeutic strategies for cervical cancer: biomarker discovery through proteomics approaches and exploring the role of cervical cancer stem cells.Frontiers in oncology · 2023Review
- Cancer Stem Cells and Their Possible Implications in Cervical Cancer: A Short Review.International journal of molecular sciences · 2022Review
- Intranasal Delivery of Recombinant S100A8 Protein Delays Lung Cancer Growth by Remodeling the Lung Immune Microenvironment.Frontiers in immunology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewThe knowledge base of malignant cell growth and resulting targets is rapidly increasing every day. Clonal theory is essential to understand the changes required for a cell to become malignant. These changes are then clues to therapeutic intervention strategies. Immune system optimization is a critical piece to find, recognize, and eliminate all cancer cells from the host. Only by administering (1) multiple therapies that counteract the cancer cell's mutational and externally induced survival traits and (2) by augmenting the immune system to combat immune suppression processes and by enhancing specific tumor trait recognition can cancer begin to be treated with a truly targeted focus. RECENT
findingsSince the sequencing of the human genome during the 1990s, steady progress in understanding genetic alterations and gene product functions are being unraveled. In cancer, this is proceeding very fast and demonstrates that genetic mutations occur very rapidly to allow for selection of survival traits within various cancer clones. Hundreds of mutations have been identified in single individual cancers, but spread across many clones in the patient's body. Precision oncology will require accurate measurement of these cancer survival-benefiting mutations to develop strategies for effective therapy. Inhibiting these cellular mechanisms is a first step, but these malignant cells need to be eliminated by the host's mechanisms, which we are learning to direct more specifically. Cancer is one of the most complicated cellular aberrations humans have encountered. Rapidly developing significant survival traits require prompt, repeated, and total body measurements of these attributes to effectively develop multi-agent treatment of the individual's malignancy. Focused drug development to inhibit these beneficial mutations is critical to slowing cancer cell growth and, perhaps, triggering apoptosis. In many cases, activation and targeting of the immune system to kill the remaining malignant cells is essential to a cure.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.