Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data.

Anastasia N Kazakova, Ksenia S Anufrieva, Olga M Ivanova, Polina V Shnaider, Irina K Malyants, Olga I Aleshikova, Andrey V Slonov, Lev A Ashrafyan, Nataliya A Babaeva, Artem V Eremeev, Veronika S Boichenko, Maria M Lukina, Maria A Lagarkova, Vadim M Govorun, Victoria O Shender, Georgij P Arapidi
Author Information
  1. Anastasia N Kazakova: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.
  2. Ksenia S Anufrieva: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.
  3. Olga M Ivanova: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.
  4. Polina V Shnaider: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.
  5. Irina K Malyants: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.
  6. Olga I Aleshikova: National Medical Scientific Centre of Obstetrics, Gynecology and Perinatal Medicine named after V.I. Kulakov, Moscow, Russia.
  7. Andrey V Slonov: National Medical Scientific Centre of Obstetrics, Gynecology and Perinatal Medicine named after V.I. Kulakov, Moscow, Russia.
  8. Lev A Ashrafyan: National Medical Scientific Centre of Obstetrics, Gynecology and Perinatal Medicine named after V.I. Kulakov, Moscow, Russia.
  9. Nataliya A Babaeva: National Medical Scientific Centre of Obstetrics, Gynecology and Perinatal Medicine named after V.I. Kulakov, Moscow, Russia.
  10. Artem V Eremeev: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.
  11. Veronika S Boichenko: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.
  12. Maria M Lukina: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.
  13. Maria A Lagarkova: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.
  14. Vadim M Govorun: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.
  15. Victoria O Shender: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.
  16. Georgij P Arapidi: Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.

Abstract

Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the literature, therefore it is imperative to find a better way to identify reliable markers of CAFs. To this end, we summarized a large number of single-cell RNA-sequencing data of multiple tumor types and corresponding normal tissues. As a result, for 9 different types of cancer, we identified CAF-specific gene expression signatures and found 10 protein markers that showed strongly positive staining of tumor stroma according to the analysis of IHC images from the Human Protein Atlas database. Our results give an insight into selecting the most appropriate combination of cancer-associated fibroblast markers. Furthermore, comparison of different approaches for studying differences between cancer-associated and normal fibroblasts (NFs) illustrates the superiority of transcriptome analysis of fibroblasts obtained from fresh tissue samples. Using single-cell RNA sequencing data, we identified common differences in gene expression patterns between normal and cancer-associated fibroblasts, which do not depend on the type of tumor.

Keywords

References

  1. J Cancer. 2017 Feb 25;8(5):761-773 [PMID: 28382138]
  2. Nucleic Acids Res. 2015 Apr 20;43(7):e47 [PMID: 25605792]
  3. F1000Res. 2015 Dec 30;4:1521 [PMID: 26925227]
  4. Genome Res. 2012 Sep;22(9):1760-74 [PMID: 22955987]
  5. Nat Commun. 2020 Aug 7;11(1):3953 [PMID: 32769974]
  6. Cell. 2019 Jun 13;177(7):1888-1902.e21 [PMID: 31178118]
  7. PLoS Genet. 2013;9(9):e1003789 [PMID: 24068959]
  8. Nat Med. 2018 Aug;24(8):1277-1289 [PMID: 29988129]
  9. Int J Med Sci. 2020 Jan 1;17(1):125-136 [PMID: 31929746]
  10. ACS Omega. 2019 Sep 30;4(16):17048-17059 [PMID: 31646252]
  11. Bioinformatics. 2012 Mar 15;28(6):882-3 [PMID: 22257669]
  12. Trends Pharmacol Sci. 2019 Jun;40(6):419-429 [PMID: 31078320]
  13. Nat Cell Biol. 2021 Jan;23(1):87-98 [PMID: 33420488]
  14. In Vivo. 2009 Jan-Feb;23(1):69-76 [PMID: 19368127]
  15. Cold Spring Harb Mol Case Stud. 2020 Apr 1;6(2): [PMID: 32054662]
  16. Int J Cancer. 2020 Feb 15;146(4):895-905 [PMID: 30734283]
  17. FASEB J. 2018 Mar;32(3):1170-1183 [PMID: 29092903]
  18. Int J Oncol. 2017 Jun;50(6):2033-2042 [PMID: 28498390]
  19. Nat Commun. 2018 Dec 4;9(1):5150 [PMID: 30514914]
  20. Cancer Lett. 2016 Nov 28;382(2):203-214 [PMID: 27609069]
  21. Int J Mol Sci. 2018 May 21;19(5): [PMID: 29883428]
  22. Cell. 2005 May 6;121(3):335-48 [PMID: 15882617]
  23. Physiol Rep. 2017 May;5(9): [PMID: 28507166]
  24. Oncogene. 2019 Jul;38(28):5566-5579 [PMID: 31147602]
  25. Nucleic Acids Res. 2002 Jan 1;30(1):207-10 [PMID: 11752295]
  26. Int J Cancer. 2020 Nov 15;147(10):2879-2890 [PMID: 32638385]
  27. Arthritis Res Ther. 2010;12(3):R83 [PMID: 20462438]
  28. Nat Rev Drug Discov. 2019 Feb;18(2):99-115 [PMID: 30470818]
  29. Front Oncol. 2019 Aug 05;9:716 [PMID: 31428583]
  30. Cancer Cell. 2010 Feb 17;17(2):135-47 [PMID: 20138012]
  31. J Hepatol. 2020 Nov;73(5):1118-1130 [PMID: 32505533]
  32. Front Cell Dev Biol. 2021 Dec 13;9:763875 [PMID: 34966741]
  33. Cells. 2019 Jul 13;8(7): [PMID: 31337073]
  34. J Neuroimmune Pharmacol. 2014 Mar;9(2):168-81 [PMID: 23771592]
  35. OMICS. 2012 May;16(5):284-7 [PMID: 22455463]
  36. Bioinformatics. 2004 Feb 12;20(3):307-15 [PMID: 14960456]
  37. Bioinformatics. 2014 Aug 1;30(15):2114-20 [PMID: 24695404]
  38. Genome Biol. 2014;15(12):550 [PMID: 25516281]
  39. Bioinformatics. 2011 Jun 15;27(12):1739-40 [PMID: 21546393]
  40. Theranostics. 2021 Jul 13;11(17):8322-8336 [PMID: 34373744]
  41. Genome Res. 2018 May;28(5):625-638 [PMID: 29650553]
  42. Oncogenesis. 2017 Jul 3;6(7):e352 [PMID: 28671675]
  43. Nat Rev Cancer. 2006 May;6(5):392-401 [PMID: 16572188]
  44. Sci Adv. 2022 Jun 10;8(23):eabm7981 [PMID: 35687691]
  45. Nat Commun. 2021 Dec 17;12(1):7338 [PMID: 34921143]
  46. Int J Mol Med. 2017 Jan;39(1):153-159 [PMID: 27909731]
  47. Nat Genet. 2020 Jun;52(6):594-603 [PMID: 32451460]
  48. Cell Biosci. 2019 Jun 26;9:53 [PMID: 31391919]
  49. Int J Mol Sci. 2020 Oct 30;21(21): [PMID: 33143259]
  50. Nat Commun. 2020 May 8;11(1):2285 [PMID: 32385277]
  51. Cell. 2020 Jul 23;182(2):497-514.e22 [PMID: 32579974]
  52. NPJ Precis Oncol. 2022 Jan 27;6(1):9 [PMID: 35087207]
  53. Clin Epigenetics. 2020 Jun 22;12(1):90 [PMID: 32571390]
  54. EMBO J. 2021 Jun 1;40(11):e107333 [PMID: 33950524]
  55. Bioinformatics. 2010 Oct 1;26(19):2363-7 [PMID: 20688976]
  56. Nat Biotechnol. 2018 Jun;36(5):411-420 [PMID: 29608179]
  57. Science. 2004 Feb 6;303(5659):848-51 [PMID: 14764882]
  58. Cancer Cell. 2021 Sep 13;39(9):1227-1244.e20 [PMID: 34297917]
  59. Mol Oncol. 2014 Oct;8(7):1290-305 [PMID: 24839936]
  60. Gastroenterology. 2017 Jul;153(1):191-204.e16 [PMID: 28390866]
  61. Nat Rev Cancer. 2020 Mar;20(3):174-186 [PMID: 31980749]
  62. Nat Commun. 2022 Jan 10;13(1):141 [PMID: 35013146]
  63. PLoS One. 2015 Feb 06;10(2):e0117405 [PMID: 25658113]
  64. Nat Genet. 2017 May;49(5):708-718 [PMID: 28319088]
  65. Nat Rev Cancer. 2016 Aug 23;16(9):582-98 [PMID: 27550820]
  66. Am J Respir Cell Mol Biol. 2012 Sep;47(3):340-8 [PMID: 22461426]
  67. Mol Cell Proteomics. 2019 Jul;18(7):1410-1427 [PMID: 31061140]
  68. Nat Commun. 2016 Aug 04;7:12237 [PMID: 27488962]
  69. Cell. 2005 Feb 11;120(3):303-13 [PMID: 15707890]
  70. J Proteomics. 2014 Oct 14;110:155-71 [PMID: 25118038]
  71. Neuro Oncol. 2005 Oct;7(4):452-64 [PMID: 16212810]
  72. Acta Obstet Gynecol Scand. 1988;67(6):539-42 [PMID: 3239385]
  73. Cancer Sci. 2021 Mar;112(3):1251-1261 [PMID: 33393151]
  74. Oncotarget. 2015 Jun 10;6(16):14300-17 [PMID: 25973543]
  75. Cancer Sci. 2015 Oct;106(10):1278-87 [PMID: 26183471]
  76. Genome Med. 2020 Sep 29;12(1):80 [PMID: 32988401]
  77. Cancer Discov. 2020 Sep;10(9):1330-1351 [PMID: 32434947]
  78. Nat Methods. 2017 Apr;14(4):417-419 [PMID: 28263959]
  79. Br J Cancer. 2011 Sep 27;105(7):996-1001 [PMID: 21863023]
  80. Mol Biosyst. 2016 Feb;12(2):477-9 [PMID: 26661513]
  81. Nat Commun. 2017 Jan 16;8:14049 [PMID: 28091601]
  82. Semin Cancer Biol. 2020 May;62:166-181 [PMID: 31415910]
  83. Cancer Gene Ther. 2021 Sep;28(9):984-999 [PMID: 33712707]
  84. NAR Genom Bioinform. 2020 Sep;2(3):lqaa078 [PMID: 33015620]

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