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Молекулярная биология, 2023, T. 57, № 6, стр. 1130-1149

Метаболическая гетерогенность опухолей

М. В. Ширманова a, *, С. Д. Синюшкина a, А. Д. Комарова a, b

a Приволжский исследовательский медицинский университет
603005 Нижний Новгород, Россия

b Нижегородский государственный университет им. Н.И. Лобачевского
603950 Нижний Новгород, Россия

* E-mail: Shirmanovam@mail.ru

Поступила в редакцию 15.02.2023
После доработки 11.04.2023
Принята к публикации 26.04.2023

Аннотация

Опухолевая гетерогенность создает серьезные проблемы как для диагностики и терапии злокачественных новообразований, так и для проведения фундаментальных исследований. Межопухолевые и внутриопухолевые отличия касаются различных характеристик и аспектов жизнедеятельности опухолевых клеток, включая их метаболизм. В представленном обзоре рассмотрена метаболическая гетерогенность опухолей с фокусом на энергетический обмен, ее причины, механизмы и методы исследования. Более подробно описан флуоресцентный времяразрешенный имиджинг как новый перспективный метод наблюдения метаболической гетерогенности на клеточном уровне. Показана важность изучения энергетического обмена опухолей и выявления внутри- и межопухолевых метаболических отличий.

Ключевые слова: опухоль, опухолевая гетерогенность, энергетический метаболизм, окислительное фосфорилирование, гликолиз, метаболические кофакторы, флуоресцентный времяразрешенный имиджинг

Список литературы

  1. Viale A., Corti D., Draetta G.F. (2015) Tumors and mitochondrial respiration: a neglected connection. Cancer Res. 75, 3687.

  2. Bensinger S.J., Christofk H.R. (2012) New aspects of the Warburg effect in cancer cell biology. Semin. Cell Dev. Biol. 23, 352–361.

  3. Solaini G., Sgarbi G., Baracca A. (2011) Oxidative phosphorylation in cancer cells. Biochim. Biophys. Acta (BBA) – Bioenerg. 1807, 534–542.

  4. Cluntun A.A., Lukey M.J., Cerione R.A., Locasale J.W. (2017) Glutamine metabolism in cancer: understanding the heterogeneity. Trends Cancer. 3, 169–180.

  5. Cao Y. (2019) Adipocyte and lipid metabolism in cancer drug resistance. J. Clin. Invest. 129, 3006–3017.

  6. Геращенко Т.С., Денисов Е.В., Литвяков Н.В., Завьялова М.В., Вторушин С.В., Цыганов М.М., Перельмутер В.М., Чердынцева Н.В. (2013) Внутриопухолевая гетерогенность: природа и биологическое значение. Биохимия. 78, 1531–1549.

  7. Nassar A., Radhakrishnan A., Cabrero I.A., Cotsonis G.A., Cohen C. (2010) Intratumoral heterogeneity of immunohistochemical marker expression in breast carcinoma: a tissue microarray-based study. Appl. Immunohistochem. Mol. Morphol. 18, 433–441.

  8. Somasundaram R., Villanueva J., Herlyn M. (2012) Intratumoral heterogeneity as a therapy resistance mechanism. Adv. Pharmacol. 65, 335–359.

  9. Fisher R., Pusztai L., Swanton C. (2013) Cancer heterogeneity: implications for targeted therapeutics. Br. J. Cancer. 108, 479–585.

  10. Prasetyanti P.R., Medema J.P. (2017) Intra-tumor heterogeneity from a cancer stem cell perspective. Mol. Cancer. 16, 41.

  11. Marusyk A., Polyak K. (2010) Tumor heterogeneity: causes and consequences. Biochim. Biophys. Acta (BBA) – Rev. Cancer. 1805, 105–117.

  12. McGranahan N., Swanton C. (2017) Clonal heterogeneity and tumor evolution: past, present, and the future. Cell. 168, 613–628.

  13. Allis C.D., Jenuwein T. (2016) The molecular hallmarks of epigenetic control. Nat. Rev. Genet. 17, 487–500.

  14. Kim J., DeBerardinis R.J. (2019) Mechanisms and implications of metabolic heterogeneity in cancer. Cell Metabolism. 30, 434–446.

  15. Чехун В.Ф., Шербан С.Д., Савцова З.Д. (2012) Гетерогенность опухоли – динамичное состояние. Онкология. 14, 4–12.

  16. Hanahan D., Weinberg R.A. (2011) Hallmarks of cancer: the next generation. Cell. 144, 646–674.

  17. Clevers H. (2011) The cancer stem cell: premises, promises and challenges. Nat. Med. 17, 313–319.

  18. Murata M. (2018) Inflammation and cancer. Environ. Health Preventive Med. 23, 50.

  19. Xiao Z., Dai Z., Locasale J.W. (2019) Metabolic landscape of the tumor microenvironment at single cell resolution. Nat. Commun. 10, 3763.

  20. Balkwill F., Mantovani A. (2001) Inflammation and cancer: back to Virchow? Lancet. 357, 539–545.

  21. Korkaya H., Kim G.I., Davis A., Malik F., Henry N.L., Ithimakin S., Quraishi A.A., Tawakkol N., D’Angelo R., Paulson A.K., Chung S., Luther T., Paholak H.J., Liu S., Hassan K.A., Zen Q., Clouthier S.G., Wicha M.S. (2012) Activation of an IL6 inflammatory loop mediates trastuzumab resistance in HER2+ breast cancer by expanding the cancer stem cell population. Mol. Cell. 47, 570–584.

  22. Бросалов В.М., Судапина А.Р., Микуляк Н.И. (2020) Клональная эволюция рака молочной железы: современные перспективы давней теории (обзор литературы). Известия высших учебных заведений. Поволжский регион. Медицинские науки. 2, 109–119.

  23. Michor F., Polyak K. (2010) The origins and implications of intratumor heterogeneity. Cancer Prevention Res. 3, 1361–1364.

  24. Warmoes M.O., Locasale J.W. (2014) Heterogeneity of glycolysis in cancers and therapeutic opportunities. Biochem. Pharmacol. 92, 12–21.

  25. Diaz-Ruiz R., Rigoulet M., Devin A. (2011) The Warburg and Crabtree effects: on the origin of cancer cell energy metabolism and of yeast glucose repression. Biochim. Biophys. Acta (BBA) – Bioenergetics. 1807, 568–576.

  26. Vander Heiden M.G., Cantley L.C., Thompson C.B. (2009) Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science. 324, 1029–1033.

  27. Stern R., Shuster S., Neudecker B.A., Formby B. (2002) Lactate stimulates fibroblast expression of hyaluronan and CD44: the Warburg effect revisited. Exp. Cell Res. 276, 24–31.

  28. Sonveaux P., Copetti T., De Saedeleer C.J., Végran F., Verrax J., Kennedy K.M., Moon E.J., Dhup S., Danhier P., Frérart F., Gallez B., Ribeiro A., Michiels C., Dewhirst M.W., Feron O. (2012) Targeting the lactate transporter MCT1 in endothelial cells inhibits lactate-induced HIF-1 activation and tumor angiogenesis. PLoS One. 7, e33418.

  29. Cairns R.A., Harris I.S., Mak T.W. (2011) Regulation of cancer cell metabolism. Nat. Rev. Cancer. 11, 85–95.

  30. Lunt S.Y., Vander Heiden M.G. (2011) Aerobic glycolysis: meeting the metabolic requirements of cell proliferation. Annu. Rev. Cell Dev. Biol. 27, 441–464.

  31. Cantor J.R., Sabatini D.M. (2012) Cancer cell metabolism: one hallmark, many faces. Cancer Discov. 2, 881–898.

  32. Smolková K., Bellance N., Scandurra F., Génot E., Gnaiger E., Plecitá-Hlavatá L., Ježek P., Rossignol R. (2010) Mitochondrial bioenergetic adaptations of breast cancer cells to aglycemia and hypoxia. J. Bioenerg. Biomembr. 42, 55–67.

  33. Pavlova N.N., Thompson C.B. (2016) The emerging hallmarks of cancer metabolism. Cell Metabolism. 23, 27–47.

  34. Sengupta D., Pratx G. (2016) Imaging metabolic heterogeneity in cancer. Mol. Cancer. 15, 4.

  35. Sancho P., Barneda D., Heeschen C. (2016) Hallmarks of cancer stem cell metabolism. Br. J. Cancer. 114, 1305–1312.

  36. Ganapathy-Kanniappan S. (2018) Molecular intricacies of aerobic glycolysis in cancer: current insights into the classic metabolic phenotype. Crit. Rev. Biochem. Mol. Biol. 53, 667–682.

  37. Seth Nanda C., Venkateswaran S.V., Patani, N., Yuneva M. (2020) Defining a metabolic landscape of tumours: genome meets metabolism. Br. J. Cancer. 122, 136–149.

  38. Harami-Papp H., Pongor L.S., Munkacsy G., Horvath G., Nagy A.M., Ambrus A., Hauser P., Szabo A., Tretter L., Gyorffy, B. (2016) TP53 mutation hits energy metabolism and increases glycolysis in breast cancer. Oncotarget. 7, 67183–67195.

  39. Zhang X., Wang J., Zhuang J., Liu C., Gao C., Li H., Ma X., Li J., Sun C. (2021) A novel glycolysis-related four-mRNA signature for predicting the survival of patients with breast cancer. Front. Genet. 12, 606937.

  40. Farhadi P., Yarani R., Valipour E., Kiani S., Hoseinkhani Z., Mansouri K. (2022) Cell line-directed breast cancer research based on glucose metabolism status. Biomed. Pharmacotherapy. 146, 112526.

  41. The Cancer Genome Atlas Research Network (2014) Comprehensive molecular profiling of lung adenocarcinoma. Nature. 511, 543–550.

  42. Romero R., Sayin V.I., Davidson S.M., Bauer M.R., Singh S.X., LeBoeuf S.E., Karakousi T.R., Ellis D.C., Bhutkar A., Sánchez-Rivera F.J., Subbaraj L., Martinez B., Bronson R.T., Prigge J.R., Schmidt E.E., Thomas C.J., Goparaju C., Davies A., Dolgalev I., Heguy A., Allaj V., Poirier J.T., Moreira A.L., Rudin C.M., Pass H.I., Vander Heiden M.G., Jacks T., Papagiannakopoulos T. (2017) Keap1 loss promotes Kras-driven lung cancer and results in dependence on glutaminolysis. Nat. Med. 23, 1362–1368.

  43. Yuneva M.O., Fan T.W., Allen T.D., Higashi R.M., Ferraris D.V., Tsukamoto T., Matés J.M., Alonso F.J., Wang C., Seo Y., Chen X., Bishop J.M. (2012) The metabolic profile of tumors depends on both the responsible genetic lesion and tissue type. Cell Metabolism. 15, 157–170.

  44. Patra S., Elahi N., Armorer A., Arunachalam S., Omala J., Hamid I., Ashton A.W., Joyce D., Jiao X., Pestell R.G. (2021) Mechanisms governing metabolic heterogeneity in breast cancer and other tumors. Front. Oncol. 11, 700629.

  45. Goel A., Mathupala S.P., Pedersen P.L. (2003) Glucose metabolism in cancer. J. Biol. Chem. 278, 15333–15340.

  46. Chen M., Zhang J., Li N., Qian Z., Zhu M., Li Q., Zheng J., Wang X., Shi G. (2011) Promoter hypermethylation mediated downregulation of FBP1 in human hepatocellular carcinoma and colon cancer. PLoS One. 6, e25564.

  47. Jose C., Bellance N., Rossignol R. (2011) Choosing between glycolysis and oxidative phosphorylation: a tumor’s dilemma? Biochim. Biophys. Acta (BBA) – Bioenergetics. 1807, 552–561.

  48. Hill R.P., De Jaeger K., Jang A., Cairns R. (2008) pH, hypoxia and metastasis. Novartis Found. Symp. 240, 154–168.

  49. Masson N., Ratcliffe P.J. (2014) Hypoxia signaling pathways in cancer metabolism: the importance of co-selecting interconnected physiological pathways. Cancer Metab. 2, 3.

  50. Muz B., de la Puente P., Azab F., Azab A.K. (2015) The role of hypoxia in cancer progression, angiogenesis, metastasis, and resistance to therapy. Hypoxia. 3, 83–92.

  51. Kierans S.J., Taylor C.T. (2021) Regulation of glycolysis by the hypoxia-inducible factor (HIF): implications for cellular physiology. J. Physiol. 599, 23–37.

  52. Korbecki J., Simińska D., Gąssowska-Dobrowolska M., Listos J., Gutowska I., Chlubek D., Baranowska-Bosiacka I. (2021) Chronic and cycling hypoxia: drivers of cancer chronic inflammation through HIF-1 and NF-κB activation: a review of the molecular mechanisms. Int. J. Mol. Sci. 22, 10701.

  53. Vogelstein B., Kinzler K.W. (2004) Cancer genes and the pathways they control. Nat. Med. 10, 789–799.

  54. Wieman H.L., Wofford J.A., Rathmell J.C. (2007) Cytokine stimulation promotes glucose uptake via phosphatidylinositol-3 kinase/Akt regulation of Glut1 activity and trafficking. MBoC. 18, 1437–1446.

  55. Wise D.R., DeBerardinis R.J., Mancuso A., Sayed N., Zhang X.Y., Pfeiffer H.K., Nissim I., Daikhin E., Yudkoff M., McMahon S.B., Thompson C.B. (2008) Myc regulates a transcriptional program that stimulates mitochondrial glutaminolysis and leads to glutamine addiction. Proc. Natl. Acad. Sci. USA. 105, 18782–18787.

  56. Gao P., Tchernyshyov I., Chang T.C., Lee Y.S., Kita K., Ochi T., Zeller K.I., De Marzo A.M., Van Eyk J.E., Mendell J.T., Dang C.V. (2009) c-Myc suppression of miR-23a/b enhances mitochondrial glutaminase expression and glutamine metabolism. Nature. 458, 762–765.

  57. Reynolds M.R., Lane A.N., Robertson B., Kemp S., Liu Y., Hill B.G., Dean D.C., Clem B.F. (2014) Control of glutamine metabolism by the tumor suppressor Rb. Oncogene. 33, 556–566.

  58. Méndez-Lucas A., Lin W., Driscoll P.C., Legrave N., Novellasdemunt L., Xie C., Charles M., Wilson Z., Jones N.P., Rayport S., Rodríguez-Justo M., Li V., MacRae J.I., Hay N., Chen X., Yuneva M. (2020) Identifying strategies to target the metabolic flexibility of tumours. Nat. Metabolism. 2, 335–350.

  59. Yoshida G.J. (2015) Metabolic reprogramming: the emerging concept and associated therapeutic strategies. J. Exp. Clin. Cancer Res. 34, 111.

  60. Sonveaux P., Végran F., Schroeder T., Wergin M.C., Verrax J., Rabbani Z.N., De Saedeleer C.J., Kennedy K.M., Diepart C., Jordan B.F., Kelley M.J., Gallez B., Wahl M.L., Feron O., Dewhirst M.W. (2008) Targeting lactate-fueled respiration selectively kills hypoxic tumor cells in mice. J. Clin. Invest. 118(12), 3930–3942.

  61. Мещерякова О.В., Чурова М.В., Немова Н.Н. (2010) Митохондриальный лактат-окисляющий комплекс и его значение для поддержания энергетического гомеостаза клеток. Современные проблемы физиологии и биохимии водных организмов: сборник научных статей. Петрозаводск: Карельский научный центр РАН. 163–171.

  62. Stine Z.E., Walton Z.E., Altman B.J., Hsieh A.L., Dang C.V. (2015) MYC, metabolism, and cancer. Cancer Discov. 5, 1024–1039.

  63. Gordan J.D., Thompson C.B., Simon M.C. (2007) HIF and c-Myc: sibling rivals for control of cancer cell metabolism and proliferation. Cancer Cell. 12, 108–113.

  64. Pavlides S., Whitaker-Menezes D., Castello-Cros R., Flomenberg N., Witkiewicz A.K., Frank P.G., Casimiro M.C., Wang C., Fortina P., Addya S., Pestell R.G., Martinez-Outschoorn U.E., Sotgia F., Lisanti M.P. (2009) The reverse Warburg effect: aerobic glycolysis in cancer associated fibroblasts and the tumor stroma. Cell Cycle. 8, 3984–4001.

  65. Dong C., Yuan T., Wu Y., Wang Y., Fan T.W., Miriyala S., Lin Y., Yao J., Shi J., Kang T., Lorkiewicz P., St Clair D., Hung M.C., Evers B.M., Zhou B.P. (2013) Loss of FBP1 by snail-mediated repression provides metabolic advantages in basal-like breast cancer. Cancer Cell. 23, 316–331.

  66. Shen Y.-A., Wang C.-Y., Hsieh Y.-T., Chen Y.-J., Wei Y.-H. (2015) Metabolic reprogramming orchestrates cancer stem cell properties in nasopharyngeal carcinoma. Cell Cycle. 14, 86–98.

  67. Chen C.-L., Uthaya Kumar D.B., Punj V., Xu J., Sher L., Tahara S.M., Hess S., Machida K. (2016) Metabolically reprograms tumor-initiating stem-like cells through tumorigenic changes in oxidative phosphorylation and fatty acid metabolism. Cell Metabolism. 23, 206–219.

  68. Ye X.-Q., Li Q., Wang G.-H., Sun F.-F., Huang G.-J., Bian X.-W., Yu S.-C., Qian G.-S. (2011) Mitochondrial and energy metabolism-related properties as novel indicators of lung cancer stem cells. Int. J. Cancer. 129, 820–831.

  69. Janiszewska M., Suvà M.L., Riggi N., Houtkooper R.H., Auwerx J., Clément-Schatlo V., Radovanovic I., Rheinbay E., Provero P., Stamenkovic I. (2012) Imp2 controls oxidative phosphorylation and is crucial for preserving glioblastoma cancer stem cells. Genes Dev. 26, 1926–1944.

  70. Badr C.E., Silver D.J., Siebzehnrubl F.A., Deleyrolle L.P. (2020) Metabolic heterogeneity and adaptability in brain tumors. Cell. Mol. Life Sci. 77, 5101–5119.

  71. Shah A.T., Diggins K.E., Walsh A.J., Irish J.M., Skala M.C. (2015) In vivo autofluorescence imaging of tumor heterogeneity in response to treatment. Neoplasia. 17, 862–870.

  72. Haffner M.C., Zwart W., Roudier M.P., True L.D., Nelson W.G., Epstein J.I., De Marzo A.M., Nelson P.S., Yegnasubramanian S. (2021) Genomic and phenotypic heterogeneity in prostate cancer. Nat. Rev. Urol. 18, 79–92.

  73. Тлостанова М.С. (2014) Эффективность применения позитронной эмиссионной томографии с 18F-фтордезоксиглюкозой, 11С-метионином и 82Rb-хлоридом в дифференциальной диагностике опухолевых и некоторых воспалительных заболеваний легких. Современные технологии в медицине. 6, 45–50.

  74. Иващенко И.М., Шнякин П.Г., Катаева А.А., Павлова И.С., Григорян К.В., Ширванян М.А. (2018) Возможности позитронно-эмиссионной томографии в диагностике злокачественных опухолей головного мозга (обзор литературы). В мире научных открытий. 10, 72–87.

  75. Shen B., Huang T., Sun Y., Jin Z., Li X.F. (2017) Revisit 18F-fluorodeoxyglucose oncology positron emission tomography: “systems molecular imaging” of glucose metabolism. Oncotarget. 8(26), 43536–43542.

  76. Yao Y., Li Y.-M., He Z.-X., Civelek A.C., Li X.-F. (2021) Likely common role of hypoxia in driving 18F‑FDG uptake in cancer, myocardial ischemia, inflammation and infection. Cancer Biother. Radiopharmaceut. 36, 624–631.

  77. Kaira K., Shimizu K., Kitahara S., Yajima T., Atsumi J., Kosaka T., Ohtaki Y., Higuchi T., Oyama T., Asao T., Mogi A. (2018) 2-Deoxy-2-[fluorine-18] fluoro-d-glucose uptake on positron emission tomography is associated with programmed death ligand-1 expression in patients with pulmonary adenocarcinoma. Eur. J. Cancer. 101, 181–190.

  78. Li X.-F., Du Y., Ma Y., Postel G.C., Civelek A.C. (2014) 18F-fluorodeoxyglucose uptake and tumor hypoxia: revisit 18F-fluorodeoxyglucose in oncology application. Transl. Oncol. 7, 240–247.

  79. Skvortsova T.Yu., Savintceva Z.I., Zakhs D.V., T-yurin R.V., Gurchin A.F., Kholyavin A.I., Trofimova T.N. (2021) Comparison of amino acid radiotracers L-[methyl-11C]methionine and O-2-[18F]fluoroethyl-L-tyrosine for PET/CT imaging of cerebral gliomas. Diagnostic Radiol. Radiother. 12, 49–58.

  80. Mittra E.S., Koglin N., Mosci C., Kumar M., Hoehne A., Keu K.V., Iagaru A. H., Mueller A., Berndt M., Bullich S., Friebe M., Schmitt-Willich H., Gekeler V., Fels L.M., Bacher-Stier C., Moon D.H., Chin F.T., Stephens A.W., Dinkelborg L.M., Gambhir S.S. (2016) Pilot preclinical and clinical evaluation of (4S)-4-(3-[18F]fluoropropyl)-L-glutamate (18F-FSPG) for PET/CT imaging of intracranial malignancies. PLoS One. 11, e0148628.

  81. Horiguchi K., Tosaka M., Higuchi T., Arisaka Y., Sugawara K., Hirato J., Yokoo H., Tsushima Y., Yoshimoto Y. (2017) Clinical value of fluorine-18α-methyltyrosine PET in patients with gliomas: comparison with fluorine-18 fluorodeoxyglucose PET. EJNMMI Res. 7, 50.

  82. Tepede A.A., Welch J., Lee M., Mandl A., Agarwal S.K., Nilubol N., Patel D., Cochran C., Simonds W.F., Weinstein L.S., Jha A., Millo C., Pacak K., Blau J.E. (2020) 18F-FDOPA PET/CT accurately identifies MEN1-associated pheochromocytoma. Endocrinol. Diabetes Metab. Case Rep. 2020, 19-0156.

  83. Crippa F., Alessi A., Serafini G.L. (2012) PET with radiolabeled aminoacid. Quarterly J. Nucl. Med. Mol. Imaging. 56, 151–162.

  84. Бакунович А.В., Синицын В.Е., Мершина Е.А. (2014) Клиническое применение протонной магнитно-резонансной спектроскопии при опухолях головного мозга и прилежащих тканей. Вестник рентгенологии и радиологии. 1, 39–50.

  85. Gillies R.J., Morse D.L. (2005) In vivo magnetic resonance spectroscopy in cancer. Annu. Rev. Biomed. Eng. 7, 287–326.

  86. Nguyen M.L., Willows B., Khan R., Chi A., Kim L., Nour S.G., Sroka T., Kerr C., Godinez J., Mills M., Karlsson U., Altdorfer G., Nguyen N.P., Jendrasiak G. (2014) The potential role of magnetic resonance spectroscopy in image-guided radiotherapy. Front. Oncol. 4, 91.

  87. Peter S.B., Nandhan V.R. (2022) 31Phosphorus magnetic resonance spectroscopy in evaluation of glioma and metastases in 3T MRI. Indian J. Radiol. Imaging. 31, 873–881.

  88. Mishkovsky M., Gusyatiner O., Lanz B., Cudalbu C., Vassallo I., Hamou M.F., Bloch J., Comment A., Gruetter R., Hegi M.E. (2021) Hyperpolarized 13C-glucose magnetic resonance highlights reduced aerobic glycolysis in vivo in infiltrative glioblastoma. Sci. Rep. 11, 5771.

  89. Gallagher F.A., Woitek R., McLean M.A., Gill A.B., Manzano Garcia R., Provenzano E., Riemer F., Kaggie J., Chhabra A., Ursprung S., Grist J.T., Daniels C.J., Zaccagna F., Laurent M.C., Locke M., Hilborne S., Frary A., Torheim T., Boursnell C., Schiller A., Patterson I., Slough R., Carmo B., Kane J., Biggs H., Harrison E., Deen S.S., Patterson A., Lanz T., Kingsbury Z., Ross M., Basu B., Baird R., Lomas D.J., Sala E., Wason J., Rueda O.M., Chin S.F., Wilkinson I.B., Graves M.J., Abraham J.E., Gilbert F.J., Caldas C., Brindle K.M. (2020) Imaging breast cancer using hyperpolarized carbon-13 MRI. Proc. Natl. Acad. Sci. USA. 117, 2092–2098.

  90. Tang S., Meng M.V., Slater J.B., Gordon J.W., Vigneron D.B., Stohr B.A., Larson P.E.Z., Wang Z.J. (2021) Metabolic imaging with hyperpolarized 13C pyruvate magnetic resonance imaging in patients with renal tumors – initial experience. Cancer. 127, 2693–2704.

  91. Nam A.S., Chaligne R., Landau D.A. (2021) Integrating genetic and non-genetic determinants of cancer evolution by single-cell multi-omics. Nat. Rev. Genet. 22, 3–18.

  92. Zeng D., Ye Z., Shen R., Yu G., Wu J., Xiong Y., Zhou R., Qiu W., Huang N., Sun L., Li X., Bin J., Liao Y., Shi M., Liao W. (2021) IOBR: multi-omics immuno-oncology biological research to decode tumor microenvironment and signatures. Front. Immunol. 12, 687 975.

  93. Ding S., Chen X., Shen K. (2020) Single-cell RNA sequencing in breast cancer: understanding tumor heterogeneity and paving roads to individualized therapy. Cancer Commun. 40, 329–344.

  94. Lei Y., Tang R., Xu J., Wang W., Zhang B., Liu J., Yu X., Shi S. (2021) Applications of single-cell sequencing in cancer research: progress and perspectives. J. Hematol. Oncol. 14, 91.

  95. Yu T.J., Ma D., Liu Y.Y., Xiao Y., Gong Y., Jiang Y.Z., Shao Z.M., Hu X., Di G.H. (2021) Bulk and single-cell transcriptome profiling reveal the metabolic heterogeneity in human breast cancers. Mol. Therapy: J. Am. Soc. Gene Therapy. 29, 2350–2365.

  96. Xiao Z., Dai Z., Locasale J.W. (2019) Metabolic landscape of the tumor microenvironment at single cell resolution. Nat. Commun., 10, 3763.

  97. Kou W., Zhao N., Zhao L., Yin Z., Zhang M.C., Zhang L., Song J., Wang Y., Qiao C., Li H. (2022) Single-cell characterization revealed hypoxia-induced metabolic reprogramming of gastric cancer. Heliyon. 8(11), e11866.

  98. Yu Q., Jiang M., Wu L. (2022) Spatial transcriptomics technology in cancer research. Front. Oncol. 12, 1019 111.

  99. Wu L., Yan J., Bai Y., Chen F., Xu J., Zou X.,  Huang A., Hou L., Zhong Y., Jing Z., Zhou X., Sun H., Cheng M., Ji Y., Luo R., Li Q., Wu L., Wang P., Guo D., Huang W., Lei J., Liao S., Li Y., Jiang Z., Yao N., Yu Y., Li Y., Liu F., Zhang M., Yang H., Yang S., Xu X., Liu L., Wang X., Wang J., Fan J., Liu S., Yang X., Chen A., Zhou J. (2021) Spatially-resolved transcriptomics analyses of invasive fronts in solid tumors. bioRxiv. 2021, 10.

  100. Lv J., Shi Q., Han Y., Li W., Liu H., Zhang J., Niu C., Gao G., Fu Y., Zhi R., Wu K., Li S., Gu F., Fu L. (2021) Spatial transcriptomics reveals gene expression characteristics in invasive micropapillary carcinoma of the breast. Cell Death Dis. 12(12), 1095.

  101. Wu Y., Yang S., Ma J., Chen Z., Song G., Rao D., Cheng Y., Huang S., Liu Y., Jiang S., Liu J., Huang X., Wang X., Qiu S., Xu J., Xi R., Bai F., Zhou J., Fan J., Zhang X., Gao Q. (2022) Spatiotemporal immune landscape of colorectal cancer liver metastasis at single-cell level. Cancer Discov. 12(1), 134–153.

  102. Glycolysis & Carbohydrates Assay Kits. In: Assay Genie. [Electronic resource]. URL: https://www.assaygenie.com/glycolysis-and-carbohydrates-assay-kits (accessed: 02.09.2022)

  103. Leippe D., Sobol M., Vidugiris G., Cali J.J., Vidugiriene J. (2017) Bioluminescent assays for glucose and glutamine metabolism: high-throughput screening for changes in extracellular and intracellular metabolites. SLAS Discov. 22, 366–377.

  104. Huang S.-L., Huang Z.-C., Zhang C.-J., Xie J., Lei S.-S., Wu Y.-Q., Fan P.-Z. (2022) LncRNA SN HG5 promotes the glycolysis and proliferation of breast cancer cell through regulating BACH1 via targeting miR-299. Breast Cancer. 29, 65–76.

  105. Qin Y., Zheng Y., Huang C., Li Y., Gu M., Wu Q. (2021) Downregulation of miR-181b-5p inhibits the viability, migration, and glycolysis of gallbladder cancer by upregulating PDHX under hypoxia. Front. Oncol. 11, 683725.

  106. Zhang K., Hu H., Xu J., Qiu L., Chen H., Jiang X., Jiang Y. (2020) Circ_0001421 facilitates glycolysis and lung cancer development by regulating miR-4677-3p/CDCA3. Diagn. Pathol. 15, 133.

  107. Zhang Y., Gao M., Zhu M., Li H., Ma T., Wu C. (2022) Isobavachalcone induces cell death through multiple pathways in human breast cancer MCF-7 cells. J. Southern Med. Univ. 42, 878–885.

  108. Cargill K.R., Stewart C.A., Park E.M., Ramkumar K., Gay C.M., Cardnell R.J., Wang Q., Diao L., Shen L., Fan Y.H., Chan W.K., Lorenzi P.L., Oliver T.G., Wang J., Byers L.A. (2021) Targeting MYC-enhanced glycolysis for the treatment of small cell lung cancer. Cancer Metab. 9, 33.

  109. Mazurkiewicz J., Simiczyjew A., Dratkiewicz E., Pietraszek-Gremplewicz K., Majkowski M., Kot M., Ziętek M., Matkowski R., Nowak D. (2022) Melanoma cells with diverse invasive potential differentially induce the activation of normal human fibroblasts. Cell Commun. Signal. 20, 63.

  110. Lang L., Wang F., Ding Z., Zhao X., Loveless R., Xie J., Shay C., Qiu P., Ke Y., Saba N.F., Teng Y. (2021) Blockade of glutamine-dependent cell survival augments antitumor efficacy of CPI-613 in head and neck cancer. J. Exp. Clin. Cancer Res. 40, 393.

  111. Almouhanna F., Blagojevic B., Can S., Ghanem A., Wölfl S. (2021) Pharmacological activation of pyruvate kinase M2 reprograms glycolysis leading to TXNIP depletion and AMPK activation in breast cancer cells. Cancer Metab. 9, 5.

  112. Zhou X., Mehta S., Zhang J. (2020) Genetically encodable fluorescent and bioluminescent biosensors light up signaling networks. Trends Biochem. Sci. 45, 889–905.

  113. Zhang Z., Cheng X., Zhao Y., Yang Y. (2020) Lighting up live-cell and in vivo central carbon metabolism with genetically encoded fluorescent sensors. Annu. Rev. Analyt. Chem. (Palo Alto, Calif.). 13, 293–314.

  114. Shirmanova M.V., Druzhkova I.N., Lukina M.M., Matlashov M.E., Belousov V.V., Snopova L.B., Prodanetz N.N., Dudenkova V.V., Lukyanov S.A., Zagaynova E.V. (2015) Intracellular pH imaging in cancer cells in vitro and tumors in vivo using the new genetically encoded sensor SypHer2. Biochim. Biophys. Acta. 1850, 1905–1911.

  115. Shimolina L., Potekhina E., Druzhkova I., Lukina M., Dudenkova V., Belousov V., Shcheslavskiy V., Zagaynova E., Shirmanova M. (2022) Fluorescence lifetime-based pH mapping of tumors in vivo using genetically encoded sensor SypHerRed. Biophys. J. 121, 1156–1165.

  116. Parshina Y.P., Komarova A.D., Bochkarev L.N., Kovylina T.A., Plekhanov A.A., Klapshina L.G., Konev A.N., Mozherov A.M., Shchechkin I.D., Sirotkina M.A., Shcheslavskiy V.I., Shirmanova M.V. (2022) Simultaneous probing of metabolism and oxygenation of tumors in vivo using FLIM of NAD(P)H and PLIM of a new polymeric Ir(III) oxygen sensor. Internat. J. Mol. Sci. 23, 10263.

  117. Solomatina A.I., Su S., Lukina M.M., Dudenkova V.V., Shcheslavskiy V.I., Wu C., Chelushkin P.S., Chou P., Koshevoy I.O., Tunik S.P. (2018) Water-soluble cyclometalated platinum(ii) and iridium(iii) complexes: synthesis, tuning of the photophysical properties, and in vitro and in vivo phosphorescence lifetime imaging. RSC Adv. 8, 17224–17236.

  118. Díaz-García C.M., Lahmann C., Martínez-François J.R., Li B., Koveal D., Nathwani N., Rahman M., Keller J.P., Marvin J.S., Looger L.L., Yellen G. (2019) Quantitative in vivo imaging of neuronal glucose concentrations with a genetically encoded fluorescence lifetime sensor. J. Neurosci. Res. 97, 946–960.

  119. Бабиченко И.И. (2008) Новые методы иммуногистохимической диагностики опухолевого роста. Вестник РУДН, сер. Медицина. 4, 94–99.

  120. Fack F., Tardito S., Hochart G., Oudin A., Zheng L., Fritah S., Golebiewska A., Nazarov P.V., Bernard A., Hau A.C., Keunen O., Leenders W., Lund-Johansen M., Stauber J., Gottlieb E., Bjerkvig R., Niclou S.P. (2017) Altered metabolic landscape in IDH – mutant gliomas affects phospholipid, energy, and oxidative stress pathways. EMBO Mol. Med. 9, 1681–1695.

  121. Garrett M., Sperry J., Braas D., Yan W., Le T.M., Mottahedeh J., Ludwig K., Eskin A., Qin Y., Levy R., Breunig J.J., Pajonk F., Graeber T.G., Radu C.G., Christofk H., Prins R.M., Lai A., Liau L.M., Coppola G., Kornblum H.I. (2018) Metabolic characterization of isocitrate dehydrogenase (IDH) mutant and IDH wildtype gliomaspheres uncovers cell type-specific vulnerabilities. Cancer Metab. 6, 4.

  122. Meijer T.W.H., Looijen-Salamo, M.G., Lok J., van den Heuvel M., Tops B., Kaanders J.H.A.M., Span P.N., Bussink J. (2019) Glucose and glutamine metabolism in relation to mutational status in NSCLC histological subtypes. Thoracic. Cancer. 10, 2289–2299.

  123. Pinheiro C., Garcia E.A., Morais-Santos F., Scapulatempo-Neto C., Mafra A., Steenbergen R.D., Boccardo E., Villa L.L., Baltazar F., Longatto-Filho A. (2014) Lactate transporters and vascular factors in HPV-induced squamous cell carcinoma of the uterine cervix. BMC Cancer. 14, 751.

  124. Mikkilineni L., Whitaker-Menezes D., Domingo-Vidal M., Sprandio J., Avena P., Cotzia P., Dulau-Florea A., Gong J., Uppal G., Zhan T., Leiby B., Lin Z., Pro B., Sotgia F., Lisanti M.P., Martinez-Outschoorn U. (2017) Hodgkin lymphoma: a complex metabolic ecosystem with glycolytic reprogramming of the tumor microenvironment. Semin. Oncol. 44, 218–225.

  125. Gooptu M., Whitaker-Menezes D., Sprandio J., Domingo-Vidal M., Lin Z., Uppal G., Gong J., Fratamico R., Leiby B., Dulau-Florea A., Caro J., Martinez-Outschoorn U. (2017) Mitochondrial and glycolytic metabolic compartmentalization in diffuse large B-cell lymphoma. Semin. Oncol. 44, 204–217.

  126. Georgakoudi I., Quinn K.P. (2012) Optical imaging using endogenous contrast to assess metabolic state. Annu. Rev. Biomed. Engin. 14, 351–367.

  127. Shirmanova M.V., Shcheslavskiy V.I., Lukina M.M., Becker W., Zagaynova E.V. (2020) Exploring tumor metabolism with time-resolved fluorescence methods: from single cells to a whole tumor. In: Multimodal Optical Diagnostics of Cancer. Eds Tuchin V.V., Popp J., Zakharov V. Cham: Springer, 133–155.

  128. Chance B., Schoener B., Oshino R., Itshak F., Nakase Y. (1979) Oxidation-reduction ratio studies of mitochondria in freeze-trapped samples. NADH and flavoprotein fluorescence signals. J. Biol. Chem. 254, 4764–4771.

  129. Skala M.C., Riching K.M., Gendron-Fitzpatrick A., Eickhoff J., Eliceiri K.W., White J.G., Ramanujam N. (2007) In vivo multiphoton microscopy of NADH and FAD redox states, fluorescence lifetimes, and cellular morphology in precancerous epithelia. Proc. Natl. Acad. Sci. USA. 104, 19494–19499.

  130. Chorvat D., Chorvatova A. (2009) Multi-wavelength fluorescence lifetime spectroscopy: a new approach to the study of endogenous fluorescence in living cells and tissues. Laser Phys. Lett. 6, 175–193.

  131. Lakowicz J.R., Szmacinski H., Nowaczyk K., Johnson M.L. (1992) Fluorescence lifetime imaging of free and protein-bound NADH. Proc. Natl. Acad. Sci. USA. 89, 1271–1275.

  132. Blacker T.S., Mann Z.F., Gale J.E., Ziegler M., Bain A.J., Szabadkai G., Duchen M.R. (2014) Separating NADH and NAD(P)H fluorescence in live cells and tissues using FLIM. Nat. Commun. 5, 3936.

  133. Kalinina S., Freymueller C., Naskar N., von Einem B., Reess K., Sroka R., Rueck A. (2021) Bioenergetic alterations of metabolic redox coenzymes as NADH, FAD and FMN by means of fluorescence lifetime imaging techniques. Internat. J. Mol. Sci. 22, 5952.

  134. Berezin M.Y., Achilefu S. (2010) Fluorescence lifetime measurements and biological imaging. Chem. Rev. 110, 2641–2684.

  135. Druzhkova I.N., Shirmanova M.V., Lukina M.M., Dudenkova V.V., Mishina N.M., Zagaynova E.V. (2016) The metabolic interaction of cancer cells and fibroblasts – coupling between NAD(P)H and FAD, intracellular pH and hydrogen peroxide. Cell Cycle. 15, 1257–1266.

  136. Shirmanova M.V., Gorbachev D.A., Sarkisyan K.S., Parnes A.P., Gavrina A.I., Polozova A.V., Kovaleva T.F., Snopova L.B., Dudenkova V.V., Zagaynova E.V., Lukyanov K.A. (2021) FUCCI-Red: a single-color cell cycle indicator for fluorescence lifetime imaging. Cell. Mol. Life Sci. 78, 3467–3476.

  137. Lukina M.M., Dudenkova V.V., Ignatova N.I., Druzhkova I.N., Shimolina L.E., Zagaynova E.V., Shirmanova M.V. (2018) Metabolic cofactors NAD(P)H and FAD as potential indicators of cancer cell response to chemotherapy with paclitaxel. Biochim. Biophys. Acta (BBA) – Gen. Subjects. 1862, 1693–1700.

  138. Shirshin E.A., Shirmanova M.V., Gayer A.V., Lukina M.M., Nikonova E.E., Yakimov B.P., Budylin G.S., Dudenkova V.V., Ignatova N.I., Komarov D.V., Yakovlev V.V., Becker W., Zagaynova E.V., Shcheslavskiy V.I., Scully M.O. (2022) Label-free sensing of cells with fluorescence lifetime imaging: the quest for metabolic heterogeneity. Proc. Natl. Acad. Sci. USA. 119, e2118241119.

  139. Yuzhakova D., Kiseleva E., Shirmanova M., Shcheslavskiy V., Sachkova D., Snopova L., Bederina E., Lukina M., Dudenkova V., Yusubalieva G., Belovezhets T., Matvienko D., Baklaushev V. (2022) Highly invasive fluorescent/bioluminescent patient-derived orthotopic model of glioblastoma in mice. Front. Oncol. 12, 897839.

  140. Sharick J.T., Jeffery J.J., Karim M.R., Walsh C.M., Esbona K., Cook R.S., Skala M.C. (2019) Cellular metabolic heterogeneity in vivo is recapitulated in tumor organoids. Neoplasia. 21, 615–626.

  141. Walsh A.J., Castellanos J.A., Nagathihalli N.S., Merchant N.B., Skala M.C. (2016) Optical imaging of drug-induced metabolism changes in murine and human pancreatic cancer organoids reveals heterogeneous drug response. Pancreas. 45, 863–869.

  142. Walsh A.J., Cook R.S., Sanders M.E., Aurisicchio L., Ciliberto G., Arteaga C.L., Skala M.C. (2014) Quantitative optical imaging of primary tumor organoid metabolism predicts drug response in breast cancer. Cancer Res. 74, 5184–5194.

  143. Sharick J.T., Walsh C.M., Sprackling C.M., Pasch C.A., Pham D.L., Esbona K., Choudhary A., Garcia-Valera R., Burkard M.E., McGregor S.M., Matkowskyj K.A., Parikh A.F., Meszoely I.M., Kelley M.C., Tsai S., Deming D.A., Skala M.C. (2020) Metabolic heterogeneity in patient tumor-derived organoids by primary site and drug treatment. Front. Oncol. 10, 553.

  144. Gillette A.A., Babiarz C.P., VanDommelen A.R., Pasch C.A., Clipson L., Matkowskyj K.A., Deming D.A., Skala M.C. (2021) Autofluorescence imaging of treatment response in neuroendocrine tumor organoids. Cancers. 13, 1873.

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