Preprint / Version 2

Influential Force: from Higgs to the novel immune checkpoint KYNU

##article.authors##

  • Tsutomu Mori Department of Human Lifesciences, Fukushima Medical University School of Nursing
  • Takashi Kawamura Department of Human Lifesciences, Fukushima Medical University School of Nursing
  • Daisuke Donald Ikeda Kitajima-cho, Itano-gun
  • Susumu Goyama Division of Molecular Oncology, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo
  • Hiroshi Haeno Medical Mathematical Modelling Laboratory, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo
  • Kazuhiko Ikeda Division of Blood Transfusion and Transplantation Immunology, Fukushima Medical University
  • Yoshiki Yamaguchi Division of Structural Glycobiology, Institute of Molecular Biomembrane and Glycobiology, Tohoku Medical and Pharmaceutical University https://researchmap.jp/yoshikiyamaguchi
  • Tsuyoshi Shirai Department of Frontier Bioscience, Faculty of Bioscience, Nagahama Institute of Bio-Science and Technology https://researchmap.jp/read0184084
  • Katsue Adachi Chi Co., Ltd.
  • Yoshihiko Saito Chi Co., Ltd.
  • Tomoyoshi Horisawa Chi Co., Ltd.
  • Junzo Suzuki Fukushima Preservative Service Association of Health
  • Seiichi Takenoshita Fukushima Medical University

DOI:

https://doi.org/10.51094/jxiv.156

Keywords:

influential force, unified theory, Higgs mechanism, exchange interaction, dark energy, inflation, equivalence principle, hierarchy problem, systems biology, ab initio genetic orbital method, bioinformatics, population genetics, immune checkpoint KYNU

Abstract

Nature has a tendency to evolve to a more probable state, and we regard this tendency as a force of probability. All fundamental interactions are transmitted by mediator particles, and their unification has long been attempted. However, no theory has fully unified the interactions into a single simple formula. Here, we show that fundamental interactions are unified by a novel “influential force” driven by probability under the canonical distribution of the transmitted information. This force affects the information distance denoting transmission difficulty, based on a universal gauge symmetry within information coordinate spacetime. We develop statistical mechanics of mutual information and reveal that the influential force exists in both physical and biological systems, offering clues to solve many intractable problems. In the field of physics, the influential force provides a coherent explanation of the spontaneous symmetry breaking of the Higgs field and its relationship with gravity, inflation, quantum entanglement entropy, and the hierarchy problem.   In the field of biology, the force endows genes with huge network information, which leads to the development of the ab initio genetic orbital method and identification of a novel, potentially targetable immune checkpoint, KYNU / kynureninase. Our findings demonstrate that the influential force acts between highly divergent beings, thereby shaping the essential properties of nature.

Conflicts of Interest Disclosure

The authors declare no potential conflict of interests.

Downloads *Displays the aggregated results up to the previous day.

Download data is not yet available.

References

Van Wylen, G. J., Sonntag, R. E. & Borgnakke, C. Fundamentals of classical thermodynamics. 4th edn, (Wiley, 1994).

Maxwell, J. C. VIII. A dynamical theory of the electromagnetic field. Philosophical transactions of the Royal Society of London, 459-512 (1865).

Salam, A. & Ward, J. C. Weak and electromagnetic interactions. Il Nuovo Cimento 11, 568-577, doi:10.1007/bf02726525 (1959).

Weinberg, S. A Model of Leptons. Physical Review Letters 19, 1264-1266, doi:10.1103/ PhysRevLett.19.1264 (1967).

Georgi, H. & Glashow, S. Unity of All Elementary Particle Forces. Physical Review Letters 32, 438-441 (1974).

Buras, A. J., Ellis, J., Gaillard, M. K. & Nanopoulos, D. V. Aspects of the grand unification of strong, weak and electromagnetic interactions. Nuclear Physics B 135, 66-92, doi:10.1016/0550-3213(78)90214-6 (1978).

Schwarz, J. H. Superstring theory. Physics Reports 89, 223-322, doi:10.1016/0370-1573(82)90087-4 (1982).

Kaku, M. Introduction to superstrings and M-theory. (Springer Science & Business Media, 2012).

Witten, E. String theory dynamics in various dimensions. Nuclear Physics B 443, 85-126 (1995).

AccessScience, E. Unification theories and a theory of everything. doi:10.1036/1097-8542.BR0814141 (2014).

Collaboration, T. A. Search for squarks and gluinos in final states with jets and missing transverse momentum using 139 fb−1 of √s =13 TeV p p collision data with the ATLAS detector. arXiv (2021).

Shannon, C. E. A Mathematical Theory of Communication. Bell System Technical Journal 27, 379-423, doi:10.1002/j.1538-7305.1948.tb01338.x (1948).

Müller, I. A history of thermodynamics: the doctrine of energy and entropy. (Springer Science & Business Media, 2007).

Satz, H. Quarkonium binding and entropic force. The European Physical Journal C 75, doi:10.1140/epjc/s10052-015-3424-7 (2015).

Neumann, R. M. Entropic approach to Brownian movement. American Journal of Physics 48, 354-357 (1980).

Verlinde, E. On the Origin of Gravity and the Laws of Newton. Journal of High Energy Physics 2011, 1-27 (2011).

Bekenstein, J. D. Information in the holographic universe. Sci Am 289, 58-65, doi:10.1038/ scientificamerican0803-58 (2003).

Gaudenzi, R. Entropy? Exercices de Style. Entropy (Basel) 21, 742, doi:10.3390/e21080742 (2019).

Parrondo, J. M., Horowitz, J. M. & Sagawa, T. Thermodynamics of information. Nature physics 11, 131-139 (2015).

Toyabe, S., Sagawa, T., Ueda, M., Muneyuki, E. & Sano, M. Experimental demonstration of information-to-energy conversion and validation of the generalized Jarzynski equality. Nature physics 6, 988-992 (2010).

Cover, T. M. Elements of information theory. (John Wiley & Sons, 1999).

Gibbs, J. W. Elementary principles in statistical mechanics: developed with especial reference to the rational foundation of thermodynamics. (Yale University Press, 1914).

Blanco, D. D., Casini, H., Hung, L.-Y. & Myers, R. C. Relative entropy and holography. Journal of High Energy Physics 2013, 1-65 (2013).

Lin, J., Marcolli, M., Ooguri, H. & Stoica, B. Locality of Gravitational Systems from Entanglement of Conformal Field Theories. Phys Rev Lett 114, 221601, doi:10.1103/PhysRevLett.114.221601 (2015).

Lashkari, N., Lin, J., Ooguri, H., Stoica, B. & Van Raamsdonk, M. Gravitational positive energy theorems from information inequalities. Progress of Theoretical and Experimental Physics 2016 (2016).

Witten, E. A mini-introduction to information theory. La Rivista del Nuovo Cimento 43, 187-227 (2020).

Gaveau, B., Jacobson, T., Kac, M. & Schulman, L. Relativistic extension of the analogy between quantum mechanics and Brownian motion. Physical Review Letters 53, 419 (1984).

Inoue, T. & Collaboration, H. Q. in AIP Conference Proceedings. 020002 (AIP Publishing LLC).

Ade, P. A. et al. Planck 2013 results. I. Overview of products and scientific results. Astronomy & Astrophysics 571, A1 (2014).

Weinberg, S. The quantum theory of fields. Vol. 2 (Cambridge university press, 1995).

Morse, P. M. Diatomic molecules according to the wave mechanics. II. Vibrational levels. Physical review 34, 57 (1929).

Hellmann, R., Bich, E. & Vogel, E. Ab initio potential energy curve for the helium atom pair and thermophysical properties of dilute helium gas. I. Helium–helium interatomic potential. Molecular Physics 105, 3013-3023 (2007).

Hurly, J. J. & Mehl, J. B. 4He thermophysical properties: new ab initio calculations. Journal of research of the National Institute of Standards and Technology 112, 75 (2007).

Granados, V. & Aquino, N. The correspondence between the states of the two-dimensional isotropic harmonic oscillator and the Morse potential. Journal of Molecular Structure: THEOCHEM 493, 37-41 (1999).

Nalewajski, R. F. in Frontiers of quantum chemistry 315-351 (Springer, 2018).

Church, K. & Hanks, P. Word association norms, mutual information, and lexicography. Computational linguistics 16, 22-29 (1990).

Hamada, K.-j. BRST Conformal Symmetry as A Background-Free Nature of Quantum Gravity. arXiv preprint arXiv:1707.06351 (2017).

Bezrukov, F. & Shaposhnikov, M. The Standard Model Higgs boson as the inflaton. Physics Letters B 659, 703-706 (2008).

Starobinsky, A. A. A new type of isotropic cosmological models without singularity. Physics Letters B 91, 99-102 (1980).

Hinshaw, G. et al. Nine-year Wilkinson Microwave Anisotropy Probe (WMAP) observations: cosmological parameter results. The Astrophysical Journal Supplement Series 208, 19 (2013).

Aghanim, N. et al. Planck 2018 results-VI. Cosmological parameters. Astronomy & Astrophysics 641, A6 (2020).

Hazumi, M. et al. Litebird: A satellite for the studies of b-mode polarization and inflation from cosmic background radiation detection. Journal of Low Temperature Physics 194, 443-452 (2019).

Puspus, X. M., Villegas, K. H. & Paraan, F. N. Entanglement spectrum and number fluctuations in the spin-partitioned BCS ground state. Physical Review B 90, 155123 (2014).

Di Tullio, M., Gigena, N. & Rossignoli, R. Fermionic entanglement in superconducting systems. Physical Review A 97, 062109 (2018).

Kimura, M. The neutral theory of molecular evolution. (Cambridge University Press, 1983).

Strachan, T. & Read, A. Human molecular genetics. Garland science. Edition, Kapitel 13, 418 (2011).

Kimura, M. On the probability of fixation of mutant genes in a population. Genetics 47, 713-719, doi:10.1093/genetics/47.6.713 (1962).

Maloof, A. C. et al. The earliest Cambrian record of animals and ocean geochemical change. Geological Society of America Bulletin 122, 1731-1774 (2010).

Nikoh, N. et al. An estimate of divergence time of Parazoa and Eumetazoa and that of Cephalochordata and Vertebrata by aldolase and triose phosphate isomerase clocks. Journal of molecular evolution 45, 97-106 (1997).

Diamond, J. The third chimpanzee for young people: On the evolution and future of the human animal. (Seven Stories Press, 2014).

Jukes, T. H. Neutral changes during divergent evolution of hemoglobins. J Mol Evol 11, 267-269, doi:10.1007/BF01734488 (1978).

Ohta, T. Effect of initial linkage disequilibrium and epistasis on fixation probability in a small population, with two segregating loci. Theor Appl Genet 38, 243-248, doi:10.1007/BF01245624 (1968).

Kolmogoroff, A. ber die analytischen Methoden in der Wahrscheinlichkeitsrechnung. Mathematische Annalen 104, 415-458 (1931).

Moran, P. A. P. The statistical processes of evolutionary theory. The statistical processes of evolutionary theory. (1962).

Haeno, H., Maruvka, Y. E., Iwasa, Y. & Michor, F. Stochastic Tunneling of Two Mutations in a Population of Cancer Cells. PLoS One 8, e65724, doi:10.1371/journal.pone.0065724 (2013).

Komarova, N. L., Sengupta, A. & Nowak, M. A. Mutation-selection networks of cancer initiation: tumor suppressor genes and chromosomal instability. J Theor Biol 223, 433-450, doi:10.1016/s0022-5193(03)00120-6 (2003).

Akashi, H., Osada, N. & Ohta, T. Weak selection and protein evolution. Genetics 192, 15-31, doi:10.1534/genetics.112.140178 (2012).

Schopf, J. W. Life's origin: the beginnings of biological evolution. (Univ of California Press, 2002).

Huheey, J. E., Keiter, E. A., Keiter, R. L. & Medhi, O. K. Inorganic chemistry: principles of structure and reactivity. (Pearson Education India, 2006).

Bianconi, G. Entropy of network ensembles. Phys Rev E Stat Nonlin Soft Matter Phys 79, 036114, doi:10.1103/PhysRevE.79.036114 (2009).

Taft, R. J., Pheasant, M. & Mattick, J. S. The relationship between non‐protein‐coding DNA and eukaryotic complexity. Bioessays 29, 288-299 (2007).

Califano, A. & Alvarez, M. J. The recurrent architecture of tumour initiation, progression and drug sensitivity. Nat Rev Cancer 17, 116-130, doi:10.1038/nrc.2016.124 (2017).

Rosenthal, R. Meta-Analytic Procedures for Social Science Research Sage Publications: Beverly Hills, 1984, 148 pp. Educational Researcher 15, 18-20 (1986).

Altrock, P. M., Liu, L. L. & Michor, F. The mathematics of cancer: integrating quantitative models. Nat Rev Cancer 15, 730-745, doi:10.1038/nrc4029 (2015).

Foo, J. et al. An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer. PLoS Comput Biol 11, e1004350, doi:10.1371/journal.pcbi.1004350 (2015).

Bozic, I. et al. Accumulation of driver and passenger mutations during tumor progression. Proc Natl Acad Sci U S A 107, 18545-18550, doi:10.1073/pnas.1010978107 (2010).

Gao, J. et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Science signaling 6, pl1-pl1 (2013).

Fukui, K., Yonezawa, T. & Shingu, H. A molecular orbital theory of reactivity in aromatic hydrocarbons. The Journal of Chemical Physics 20, 722-725 (1952).

Jaynes, E. T. Information theory and statistical mechanics. Physical review 106, 620 (1957).

Jaynes, E. T. Information theory and statistical mechanics. II. Physical review 108, 171 (1957).

Barabasi, A. L. & Oltvai, Z. N. Network biology: understanding the cell's functional organization. Nat Rev Genet 5, 101-113, doi:10.1038/nrg1272 (2004).

Goyama, S. & Kitamura, T. Epigenetics in normal and malignant hematopoiesis: An overview and update 2017. Cancer Sci 108, 553-562, doi:10.1111/cas.13168 (2017).

Balasubramani, A. et al. Cancer-associated ASXL1 mutations may act as gain-of-function mutations of the ASXL1-BAP1 complex. Nat Commun 6, 7307, doi:10.1038/ncomms8307 (2015).

Asada, S. et al. Mutant ASXL1 cooperates with BAP1 to promote myeloid leukaemogenesis. Nature Communications 9, doi:10.1038/s41467-018-05085-9 (2018).

Fujino, T. et al. Mutant ASXL1 induces age-related expansion of phenotypic hematopoietic stem cells through activation of Akt/mTOR pathway. Nature Communications 12, doi:10.1038/s41467-021-22053-y (2021).

de Ramon Francas, G., Alther, T. & Stoeckli, E. T. Calsyntenins Are Expressed in a Dynamic and Partially Overlapping Manner during Neural Development. Front Neuroanat 11, 76, doi:10.3389/ fnana.2017.00076 (2017).

Kim, H. et al. Calsyntenin-3 interacts with both α-and β-neurexins in the regulation of excitatory synaptic innervation in specific Schaffer collateral pathways. Journal of Biological Chemistry 295, 9244-9262 (2020).

Lu, Z. et al. Calsyntenin-3 molecular architecture and interaction with neurexin 1alpha. J Biol Chem 289, 34530-34542, doi:10.1074/jbc.M114.606806 (2014).

Rindler, M. J. et al. Calsyntenins are secretory granule proteins in anterior pituitary gland and pancreatic islet alpha cells. J Histochem Cytochem 56, 381-388, doi:10.1369/jhc.7A7351.2007 (2008).

Witzke, K. E. et al. Quantitative Secretome analysis of activated Jurkat cells using click chemistry-based enrichment of secreted glycoproteins. Journal of Proteome Research 16, 137-146 (2017).

Gumy, L. F. et al. The kinesin-2 family member KIF3C regulates microtubule dynamics and is required for axon growth and regeneration. Journal of Neuroscience 33, 11329-11345 (2013).

Ikeda, D. D. et al. CASY-1, an ortholog of calsyntenins/alcadeins, is essential for learning in Caenorhabditis elegans. Proceedings of the National Academy of Sciences 105, 5260-5265 (2008).

Ohno, H. et al. Role of synaptic phosphatidylinositol 3-kinase in a behavioral learning response in C. elegans. Science 345, 313-317, doi:10.1126/science.1250709 (2014).

MacDonald, J. W. & Ghosh, D. COPA—cancer outlier profile analysis. Bioinformatics 22, 2950-2951 (2006).

Marin-Acevedo, J. A. et al. Next generation of immune checkpoint therapy in cancer: new developments and challenges. J Hematol Oncol 11, 39, doi:10.1186/s13045-018-0582-8 (2018).

Hiam-Galvez, K. J., Allen, B. M. & Spitzer, M. H. Systemic immunity in cancer. Nat Rev Cancer 21, 345-359, doi:10.1038/s41568-021-00347-z (2021).

He, J., Hu, Y., Hu, M. & Li, B. Development of PD-1/PD-L1 Pathway in Tumor Immune Microenvironment and Treatment for Non-Small Cell Lung Cancer. Sci Rep 5, 13110, doi:10.1038/ srep13110 (2015).

Breimer, L. H., Nousios, P., Olsson, L. & Brunnstrom, H. Immune checkpoint inhibitors of the PD-1/PD-L1-axis in non-small cell lung cancer: promise, controversies and ambiguities in the novel treatment paradigm. Scand J Clin Lab Invest 80, 360-369, doi:10.1080/00365513.2020.1742369 (2020).

Zhang, B. et al. Predictive effect of PD-L1 expression for immune checkpoint inhibitor (PD-1/PD-L1 inhibitors) treatment for non-small cell lung cancer: A meta-analysis. Int Immunopharmacol 80, 106214, doi:10.1016/j.intimp.2020.106214 (2020).

Lu, S. et al. Comparison of Biomarker Modalities for Predicting Response to PD-1/PD-L1 Checkpoint Blockade: A Systematic Review and Meta-analysis. JAMA Oncol 5, 1195-1204, doi:10.1001/ jamaoncol.2019.1549 (2019).

Al‐Mansoob, M., Gupta, I., Stefan Rusyniak, R. & Ouhtit, A. KYNU, a novel potential target that underpins CD44‐promoted breast tumour cell invasion. Journal of Cellular and Molecular Medicine 25, 2309-2314 (2021).

Bos, P. D. et al. Genes that mediate breast cancer metastasis to the brain. Nature 459, 1005-1009 (2009).

D'Amato, N. C. et al. A TDO2-AhR signaling axis facilitates anoikis resistance and metastasis in triple-negative breast cancer. Cancer research 75, 4651-4664 (2015).

Liu, Q. et al. Comprehensive Analysis of the Expressionand Prognosis for TDO2 in Breast Cancer. Molecular Therapy-Oncolytics 17, 153-168 (2020).

Minn, A. J. et al. Genes that mediate breast cancer metastasis to lung. Nature 436, 518-524 (2005).

Rose, D. P. The influence of sex, age and breast cancer on tryptophan metabolism. Clin Chim Acta 18, 221-225, doi:10.1016/0009-8981(67)90161-1 (1967).

Liu, Y. et al. A novel role of kynureninase in the growth control of breast cancer cells and its relationships with breast cancer. J Cell Mol Med 23, 6700-6707, doi:10.1111/jcmm.14547 (2019).

Schwarcz, R. The kynurenine pathway of tryptophan degradation as a drug target. Current opinion in pharmacology 4, 12-17 (2004).

Monney, L. et al. Th1-specific cell surface protein Tim-3 regulates macrophage activation and severity of an autoimmune disease. Nature 415, 536-541, doi:10.1038/415536a (2002).

Jin, H. T. et al. Cooperation of Tim-3 and PD-1 in CD8 T-cell exhaustion during chronic viral infection. Proc Natl Acad Sci U S A 107, 14733-14738, doi:10.1073/pnas.1009731107 (2010).

Darlington, L. G. et al. On the Biological Importance of the 3-hydroxyanthranilic Acid: Anthranilic Acid Ratio. Int J Tryptophan Res 3, 51-59, doi:10.4137/ijtr.s4282 (2010).

Zhai, L. et al. Molecular Pathways: Targeting IDO1 and Other Tryptophan Dioxygenases for Cancer Immunotherapy. Clin Cancer Res 21, 5427-5433, doi:10.1158/1078-0432.CCR-15-0420 (2015).

Liu, M. et al. Targeting the IDO1 pathway in cancer: from bench to bedside. J Hematol Oncol 11, 100, doi:10.1186/s13045-018-0644-y (2018).

Jacobs, K. R., Castellano-Gonzalez, G., Guillemin, G. J. & Lovejoy, D. B. Major Developments in the Design of Inhibitors along the Kynurenine Pathway. Curr Med Chem 24, 2471-2495, doi:10.2174/ 0929867324666170502123114 (2017).

Cerami, E. et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov 2, 401-404, doi:10.1158/2159-8290.CD-12-0095 (2012).

Sim, N. L. et al. SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res 40, W452-457, doi:10.1093/nar/gks539 (2012).

Adzhubei, I., Jordan, D. M. & Sunyaev, S. R. Predicting functional effect of human missense mutations using PolyPhen-2. Curr Protoc Hum Genet Chapter 7, Unit7 20, doi:10.1002/ 0471142905.hg0720s76 (2013).

Fahrmann, J. F. et al. Mutational Activation of the NRF2 Pathway Upregulates Kynureninase Resulting in Tumor Immunosuppression and Poor Outcome in Lung Adenocarcinoma. Cancers (Basel) 14, 2543, doi:10.3390/cancers14102543 (2022).

Downloads

Posted


Submitted: 2022-09-05 15:16:26 UTC

Published: 2022-09-07 23:26:28 UTC — Updated on 2023-04-24 07:15:47 UTC

Versions

Reason(s) for revision

In this revision, the title was changed. We added an in silico method to evaluate the therapeutic targetability of an immune checkpoint of interest, demonstrating that KYNU has a promising therapeutic targetability.
Section
Physics

License

Copyright (c) 2022 Tsutomu Mori
Takashi Kawamura
Daisuke Donald Ikeda
Susumu Goyama
Hiroshi Haeno
Kazuhiko Ikeda
Yoshiki Yamaguchi
Tsuyoshi Shirai
Katsue Adachi
Yoshihiko Saito
Tomoyoshi Horisawa
Junzo Suzuki
Seiichi Takenoshita

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.