2019 John A. Catanzaro

“Hot” tumors often have a high mutational load. They express changes in DNA coding that cause the cancer cells to produce distinctive new molecules called “neoantigens” on their cell surface. These neoantigens make the tumor more prone to recognition by the immune system, and thus more likely to provoke a strong immune response.

“Cold” tumors, are cancers that haven’t been recognized or haven’t provoked a strong response by the immune system. Immune T cells have been unable to penetrate such tumors. The T cells have been excluded by components of the tumor microenvironment. The tumor microenvironment in and around tumor cells comprises blood vessels, structural elements, and specialized immune cells; the latter include myeloid-derived suppressor cells and regulatory T cells, or Tregs. These Tregs turn down the volume on the normal immune response by secreting immunosuppressive chemical messengers like cytokines that impede the movement of T cells into the tumor. The result is tumor resistance, tolerance and evasion.

Tumor Moiety

The architecture and histology of the the tumor moiety is a nano-paradox. Each of the players in the arena of defense and resistance reveal vital codes and clues to curative breakthroughs.

Cellular infiltrates within the tumor microenvironment. Established cancers consist of a wide array of immune cells that contribute to the tumor stroma of a growing malignancy. Tumors possess infiltrating cells of both innate and acquired immunity, such as MDSCs, macrophages, DCs, mast cells, eosinophils, neutrophils, NK cells, and lymphocytes. These cells coordinately form a complex regulatory network that fosters tumor growth by creating an environment that enables cancers to evade immune surveillance and destruction. G-CSF, granulocyte colony-stimulating factor; GM-CSF, granulocyte-macrophage colony-stimulating factor; NO, nitric oxide; ROS, reactive oxygen species. http://cancerres.aacrjournals.org/content/72/13/3125

Hallmark Architecture

Cancer Hallmark Analytics and Immunocentrics is a precision-based profiling and personalized product development model providing analytics in patient immune compatibility and capability. This model is an expandable concept that profiles each of the known and potential future cancer hallmark expressions. Cancer Hallmark constituents in sequential order are essential demonstrating the hierarchal order of cancer initiation, progression, survival, resistance, defense and regulation.

Cancer Hallmark Constituents

  1. Genome Instability and Mutation (DNA Repair, DNA Damage, Mutation, Strand Breaks, Adducts) https://www.linkedin.com/pulse/genomic-instability-mutations-john-catanzaro/?published=t
  2. Metabolic and Oxidative Environmental Stress (Metabolism and Oxidative Maladaptation)
  3. Deregulating Cellular Energetics (Glycolysis / Warburg Effect)
  4. Evading Growth Suppressors (Cell Cycle, Deregulating Checkpoint, Evading Contact Inhibition)
  5. Sustaining Proliferative Signaling (Cell Cycle, Growth Factors, Receptors, Downstream Signaling)
  6. Inducing Angiogenesis (Angiogenic Factors, Deregulating angiogenesis)
  7. Activating Invasion and Metastasis (Invasion and Metastasis Distribution Patterns)
  8. Tumor Promoting Inflammation (Inflammation Immune Cell Stress Factors and Oxidative Triggers)
  9. Immune Surveillance, Evasion / Escape (Avoiding Immune Destruction, Immune Response / Suppression)
  10. Resisting Cell Death (Apoptosis, Autophagy and Necrosis)
  11. Enabling Replicative Immortality (Immortalization and senescence)

Hot and Cold Tumors Immunology

This video is a good explanation of hot verses cold tumor.

This video explains “hot” and “cold” tumors and very easy presentation

Tumor Microenvironment

There are four types of tumor microenvironments based on the presence of CD8+ cells and PD-L1 expression. “Hot tumors” are Type I (adaptive immune resistance), the most auspicious for anti-PD(L)1 treatments; by blocking the PD-(L)1 axis via checkpoint therapy, immune-mediated killing by CD8+ T-cells is restored. The goal then is to either prevent hot tumors from cooling off, that is, transitioning to Types II-IV, and turning “cold tumors hot.”

Target Landscape

The Cancer Research Institute maintains a current list of the 1,105 checkpoint combination trials geared to induce change in the tumor microenvironment to favor the Type I phenotype — https://cancerresearch.org/scientists/clinical-accelerator/landscape-of-immuno-oncology-drug-development.

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The landscape analysis of targets of anti-PD-1/L1 combination trials. The size of the bubble correlates to the number of trials. Number of trials using common combo strategies: Anti-CTLA-4 agents (251); Chemotherapies (170); Radiotherapies (64); Anti-VEGFA agents (43); Chemoradiotherapy combos (42). https://cancerresearch.org/scientists/clinical-accelerator/landscape-of-immuno-oncology-drug-development

Patient-Precision Based Profiling for Enhancing Immune Response

The complexity of the cancer environment requires a much more comprehensive immunocentric analytic that is patient centered to assess both compatibility and capability of immune status and immunoediting features.

For example the commonly studied checkpoint molecule PD-1 acts like a brake on the immune response by keeping T cells in an inactive or “exhausted” state. While the CDK4/6 inhibitors didn’t eradicate tumors on their own, they worked synergistically with PD-1 checkpoint inhibitors in the laboratory models, suggesting that the combination is worth trying in patients. The main complication of these working laboratory models is that the patient is, in fact, the missing piece in determining what will work or not work. Expansion of immunocentric innovations require analytics in determining the best selection of patient immunogenic and patient compatible neoantigens.

AI / API Patient-Precision Immunocentric Analysis

Currently, we recommend eighteen patient profiling points that provide characteristic behavior any time in the cancer cell and tumor microenvironment life cycle. This analysis can be evaluated as a primary baseline to reveal patient compatibility and immune capability to assist with immunocentric precision immune-based treatment innovation and as a periodic scheduled progress screening in response to innovated clinical treatment. It is also a useful tool at any time to assist with evaluating immune resistance and further revisions of immunoediting features.

  1. Patient Extrinsic / Intrinsic Risk Index (EIRI)
  2. WGS Patient / Cancer / Tumor (WGSCT)- Attention to the Non-Coding Regions
  3. Patient HLA Matched Immunogenic Mapping (HLA-MIM)
  4. Telomere Analysis Index (TAI)
  5. Diagnostic Imaging (PET / MRI) Proliferation Index (DIPI)
  6. Metabolic / Oxidative Stress Index (MOSI)
  7. Warburg Effect Analysis (WEA)
  8. Cancer Cell Mutation Rate (CCMR)
  9. Cancer Cell Migration Load (CCML)
  10. Cancer Proliferation Index (CPI)
  11. Hot-Cold Tumor Proliferative Index (HCTPX)
  12. Tumor Mutation Rate (TMR)
  13. Tumor Migration Load (TML)
  14. Tumor Proliferation Index (TPI)
  15. Inflammation / Immune Cell Stress Index (IICSI)
  16. Cancer Cell / Tumor Antigen Mapping (CCTAM)
  17. Precision Immunogenic Vaccine Mapping (PIVM)
  18. Patient -Product Development Schema (PPDS)

Summary

This proposal for patient-based precision analytics and immunocentric modeling requires collaboration and networking in order to develop cooperative AI platform and interface providing a personalized patient approach. My attempt in this article, points to the amazing developments, challenges and difficulties in final development of a patient precision product.

Some researchers favor mRNA approaches, some APC / APM approaches and some direct induction. Nanoengineering and integration is allowing us to move into the unseen tumor microenvironments for direct presentation of immunogens and defense regulators. However, we must be better at identifying rejection, resistance and prevention of severe autoimmune crisis that can be a complication of incompatibility in neoantigen selection and any immunogenic delivery innovation. Again, coding verses noncoding transcription is another consideration, as well as, metabolic profiling of the individual mutated cells and tumor microenvironment. The tumor microenvironment cellular matrix can vary from cell to cell in antigen expression. The use of WGS verses WES in profiling patient and cancer cell / tumor environment is another key element in this process. The use of diagnostic imaging API of PET scans and MRI to determine distribution patterns and metabolic characteristics is another crucial feature.

This article is more than just a thought experiment, it is a reality we face in real time. An immunogenic immunoediting model requires such sophistication for efficient profiling, typing, sequencing, synthesis and delivery of a personalized patient regimen that can be upgradable at any time in the cancer process to initiate defense, regulation and overcome resistance. The standard cliche of failed chemotherapy or biological therapy because of eventual tolerance and resistance of the agent will be in the history books and practiced no more. Immunocentric and immunoediting will overcome these barriers and move the patient towards progressive cure with enhancements, not destroying the crucial matirix of their immune system and adaptive mechanisms.

John A. Catanzaro is CEO of Neo7logix, a bioscience company that designs precision and personalized treatment designs. www.neo7logix.com

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