Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Tumour-derived Dilp8/INSL3 induces cancer anorexia by regulating feeding neuropeptides via Lgr3/8 in the brain

Abstract

In patients with advanced-stage cancer, cancer-associated anorexia affects treatment success and patient survival. However, the underlying mechanism is poorly understood. Here, we show that Dilp8, a Drosophila homologue of mammalian insulin-like 3 peptide (INSL3), is secreted from tumour tissues and induces anorexia through the Lgr3 receptor in the brain. Activated Dilp8-Lgr3 signalling upregulated anorexigenic nucleobinding 1 (NUCB1) and downregulated orexigenic short neuropeptide F (sNPF) and NPF expression in the brain. In the cancer condition, the protein expression of Lgr3 and NUCB1 was significantly upregulated in neurons expressing sNPF and NPF. INSL3 levels were increased in tumour-implanted mice and INSL3-treated mouse hypothalamic cells showed Nucb2 upregulation and Npy downregulation. Food consumption was significantly reduced in intracerebrospinal INSL3-injected mice. In patients with pancreatic cancer, higher serum INSL3 levels increased anorexia. These results indicate that tumour-derived Dilp8/INSL3 induces cancer anorexia by regulating feeding hormones through the Lgr3/Lgr8 receptor in Drosophila and mammals.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Cancer anorexia precedes organ wasting in the Drosophila eye tumour model.
Fig. 2: Tumour-derived Dilp8 suppresses food intake through its receptor Lgr3.
Fig. 3: Dilp8-Lgr3 signalling regulates anorexigenic NUCB1 and orexigenic sNPF and NPF expression in the Drosophila brain.
Fig. 4: NUCB1- and Lgr3-expressing neurons are markedly increased and overlapped in the cancer condition.
Fig. 5: INSL3-LGR8 signalling regulates anorexigenic Nucb2 and orexigenic Npy expression in mouse hypothalamic cells.
Fig. 6: INSL3 regulates Nucb2 and Npy, and induces anorexia in the mouse tumour model.
Fig. 7: Serum INSL3 levels correlate with anorexia severity in patients with pancreatic cancer.

Similar content being viewed by others

Data availability

The RNA-seq data have been deposited in the GEO database under accession code GSE154404. Data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.

References

  1. Evans, W. J. et al. Cachexia: a new definition. Clin. Nutr. 27, 793–799 (2008).

    Article  CAS  PubMed  Google Scholar 

  2. Argiles, J. M., Busquets, S., Stemmler, B. & Lopez-Soriano, F. J. Cancer cachexia: understanding the molecular basis. Nat. Rev. Cancer 14, 754–762 (2014).

    Article  CAS  PubMed  Google Scholar 

  3. Tisdale, M. J. Mechanisms of cancer cachexia. Physiol. Rev. 89, 381–410 (2009).

    Article  CAS  PubMed  Google Scholar 

  4. Fearon, K. C. H., Glass, D. J. & Guttridge, D. C. Cancer cachexia: mediators, signaling and metabolic pathways. Cell Metab. 16, 153–166 (2012).

    Article  CAS  PubMed  Google Scholar 

  5. Wagner, E. F. & Petruzzelli, M. Cancer metabolism: a waste of insulin interference. Nature 521, 430–431 (2015).

    Article  CAS  PubMed  Google Scholar 

  6. Sadeghi, M. et al. Cancer cachexia: diagnosis, assessment and treatment. Crit. Rev. Oncol. Hematol. 127, 91–104 (2018).

    Article  PubMed  Google Scholar 

  7. Tisdale, M. J. Cancer anorexia and cachexia. Nutrition 17, 438–442 (2001).

    Article  CAS  PubMed  Google Scholar 

  8. von Haehling, S. & Anker, S. D. Treatment of cachexia: an overview of recent developments. Int. J. Cardiol. 184, 736–742 (2015).

    Article  Google Scholar 

  9. Tranmer, J. E. et al. Measuring the symptom experience of seriously ill cancer and noncancer hospitalized patients near the end of life with the memorial symptom assessment scale. J. Pain Symptom Manage. 25, 420–429 (2003).

    Article  PubMed  Google Scholar 

  10. Bennani-Baiti, N. & Davis, M. P. Cytokines and cancer anorexia cachexia syndrome. Am. J. Hosp. Palliat. Care 25, 407–411 (2008).

    Article  PubMed  Google Scholar 

  11. Patra, S. K. & Arora, S. Integrative role of neuropeptides and cytokines in cancer anorexia-cachexia syndrome. Clin. Chim. Acta 413, 1025–1034 (2012).

    Article  CAS  PubMed  Google Scholar 

  12. Ramos, E. J. et al. Cancer anorexia-cachexia syndrome: cytokines and neuropeptides. Curr. Opin. Clin. Nutr. Metab. Care 7, 427–434 (2004).

    Article  CAS  PubMed  Google Scholar 

  13. Mendes, M. C., Pimentel, G. D., Costa, F. O. & Carvalheira, J. B. Molecular and neuroendocrine mechanisms of cancer cachexia. J. Endocrinol. 226, R29–R43 (2015).

    Article  CAS  PubMed  Google Scholar 

  14. Droujinine, I. A. & Perrimon, N. Interorgan communication pathways in physiology: focus on Drosophila. Annu. Rev. Genet. 50, 539–570 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Gonzalez, H., Hagerling, C. & Werb, Z. Roles of the immune system in cancer: from tumor initiation to metastatic progression. Genes Dev. 32, 1267–1284 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  17. Holmes, D. Metabolism: WAT browning—key feature of cancer-associated cachexia. Nat. Rev. Endocrinol. 10, 578 (2014).

    Article  PubMed  Google Scholar 

  18. Fearon, K., Arends, J. & Baracos, V. Understanding the mechanisms and treatment options in cancer cachexia. Nat. Rev. Clin. Oncol. 10, 90–99 (2013).

    Article  CAS  PubMed  Google Scholar 

  19. Ezeoke, C. C. & Morley, J. E. Pathophysiology of anorexia in the cancer cachexia syndrome. J. Cachexia Sarcopenia Muscle 6, 287–302 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Wang, G. et al. Metastatic cancers promote cachexia through ZIP14 upregulation in skeletal muscle. Nat. Med. 24, 770–781 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Petruzzelli, M. & Wagner, E. F. Mechanisms of metabolic dysfunction in cancer-associated cachexia. Genes Dev. 30, 489–501 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Kir, S. et al. PTH/PTHrP receptor mediates cachexia in models of kidney failure and cancer. Cell Metab. 23, 315–323 (2016).

    Article  CAS  PubMed  Google Scholar 

  23. Kir, S. et al. Tumour-derived PTH-related protein triggers adipose tissue browning and cancer cachexia. Nature 513, 100–104 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Tsai, V. W. et al. Anorexia/cachexia of chronic diseases: a role for the TGF-β family cytokine MIC-1/GDF15. J. Cachexia Sarcopenia Muscle 3, 239–243 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Hsu, J. Y. et al. Non-homeostatic body weight regulation through a brainstem-restricted receptor for GDF15. Nature 550, 255–259 (2017).

    Article  PubMed  Google Scholar 

  26. Tsai, V. W. W., Husaini, Y., Sainsbury, A., Brown, D. A. & Breit, S. N. The MIC-1/GDF15-GFRAL pathway in energy homeostasis: implications for obesity, cachexia and other associated diseases. Cell Metab. 28, 353–368 (2018).

    Article  CAS  PubMed  Google Scholar 

  27. Kwon, Y. et al. Systemic organ wasting induced by localized expression of the secreted insulin/IGF antagonist ImpL2. Dev. Cell 33, 36–46 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Figueroa-Clarevega, A. & Bilder, D. Malignant Drosophila tumors interrupt insulin signaling to induce cachexia-like wasting. Dev. Cell 33, 47–55 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Pan, D. The Hippo signaling pathway in development and cancer. Dev. Cell 19, 491–505 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Zeng, Q. & Hong, W. The emerging role of the Hippo pathway in cell contact inhibition, organ size control and cancer development in mammals. Cancer Cell 13, 188–192 (2008).

    Article  CAS  PubMed  Google Scholar 

  31. Meng, Z., Moroishi, T. & Guan, K. L. Mechanisms of Hippo pathway regulation. Genes Dev. 30, 1–17 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Harvey, K. F., Zhang, X. & Thomas, D. M. The Hippo pathway and human cancer. Nat. Rev. Cancer 13, 246–257 (2013).

    Article  CAS  PubMed  Google Scholar 

  33. Halder, G. & Camargo, F. D. The Hippo tumor suppressor network: from organ size control to stem cells and cancer. Cancer Res. 73, 6389–6392 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Misra, J. R. & Irvine, K. D. The Hippo signaling network and its biological functions. Annu. Rev. Genet. 52, 65–87 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Shell, B. C. et al. Measurement of solid food intake in Drosophila via consumption–excretion of a dye tracer. Sci. Rep. 8, 11536 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Diegelmann, S. et al. The CApillary FEeder assay measures food intake in Drosophila melanogaster. J. Vis. Exp. (2017); https://doi.org/10.3791/55024

  37. Ja, W. W. et al. Prandiology of Drosophila and the CAFE assay. Proc. Natl Acad. Sci. USA 104, 8253–8256 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Colombani, J. et al. Drosophila Lgr3 couples organ growth with maturation and ensures developmental stability. Curr. Biol. 25, 2723–2729 (2015).

    Article  CAS  PubMed  Google Scholar 

  39. Garelli, A., Gontijo, A. M., Miguela, V., Caparros, E. & Dominguez, M. Imaginal discs secrete insulin-like peptide 8 to mediate plasticity of growth and maturation. Science 336, 579–582 (2012).

    Article  CAS  PubMed  Google Scholar 

  40. Garelli, A. et al. Dilp8 requires the neuronal relaxin receptor Lgr3 to couple growth to developmental timing. Nat. Commun. 6, 8732 (2015).

    Article  CAS  PubMed  Google Scholar 

  41. Vallejo, D. M., Juarez-Carreño, S., Bolivar, J., Morante, J. & Dominguez, M. A brain circuit that synchronizes growth and maturation revealed through Dilp8 binding to Lgr3. Science 350, aac6767 (2015).

    Article  PubMed  Google Scholar 

  42. Oh-I, S. et al. Identification of nesfatin-1 as a satiety molecule in the hypothalamus. Nature 443, 709–712 (2006).

    Article  CAS  PubMed  Google Scholar 

  43. Halls, M. L., Bathgate, R. A. D., Sutton, S. W., Dschietzig, T. B. & Summers, R. J. International union of basic and clinical pharmacology. XCV. Recent advances in the understanding of the pharmacology and biological roles of relaxin family peptide receptors 1–4, the receptors for relaxin family peptides. Pharmacol. Rev. 67, 389–440 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Kageyama, H., Takenoya, F., Shiba, K. & Shioda, S. Neuronal circuits involving ghrelin in the hypothalamus-mediated regulation of feeding. Neuropeptides 44, 133–138 (2010).

    Article  CAS  PubMed  Google Scholar 

  45. Schwartz, M. W., Woods, S. C., Porte, D., Seeley, R. J. & Baskin, D. G. Central nervous system control of food intake. Nature 404, 661–671 (2000).

    Article  CAS  PubMed  Google Scholar 

  46. Talbert, E. E. et al. Modeling human cancer-induced cachexia. Cell Rep. 28, 1612–1622 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Ronga, I., Gallucci, F., Riccardi, F. & Uomo, G. Anorexia-cachexia syndrome in pancreatic cancer: recent advances and new pharmacological approach. Adv. Med. Sci. 59, 1–6 (2014).

    Article  PubMed  Google Scholar 

  48. Boone, E., Colombani, J., Andersen, D. S. & Léopold, P. The Hippo signalling pathway coordinates organ growth and limits developmental variability by controlling dilp8 expression. Nat. Commun. 7, 13505 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Petruzzelli, M. et al. A switch from white to brown fat increases energy expenditure in cancer-associated cachexia. Cell Metab. 20, 433–447 (2014).

    Article  CAS  PubMed  Google Scholar 

  50. Katheder, N. S. et al. Microenvironmental autophagy promotes tumour growth. Nature 541, 417–420 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Stengel, A., Mori, M. & Tache, Y. The role of nesfatin-1 in the regulation of food intake and body weight: recent developments and future endeavors. Obes. Rev. 14, 859–870 (2013).

    Article  CAS  PubMed  Google Scholar 

  52. Stengel, A. & Tache, Y. Role of brain NUCB2/nesfatin-1 in the regulation of food intake. Curr. Pharm. Des. 19, 6955–6959 (2013).

    Article  CAS  PubMed  Google Scholar 

  53. Yvette, T. Editorial: New developments on NUCB2/nesfatin-1. Curr. Pharm. Des. 19, 6919–6920 (2013).

    Article  Google Scholar 

  54. Goebel, M., Stengel, A., Lambrecht, N. W. G., Wang, L. & Taché, Y. Nesfatin-1 immunoreactivity in rat brain and spinal cord autonomic nuclei. Neurosci. Lett. 452, 241–246 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Campos, C. A. et al. Cancer-induced anorexia and malaise are mediated by CGRP neurons in the parabrachial nucleus. Nat. Neurosci. 20, 934–942 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Ishida, E. et al. Nesfatin-1 induces the phosphorylation levels of cAMP response element-binding protein for intracellular signaling in a neural cell line. PLoS ONE 7, e50918 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Brailoiu, G. C. et al. Nesfatin-1: distribution and interaction with a G protein-coupled receptor in the rat brain. Endocrinology 148, 5088–5094 (2007).

    Article  CAS  PubMed  Google Scholar 

  58. Aydin, S. Multi-functional peptide hormone NUCB2/nesfatin-1. Endocrine 44, 312–325 (2013).

    Article  CAS  PubMed  Google Scholar 

  59. Rubin, G. M. & Spradling, A. C. Genetic transformation of Drosophila with transposable element vectors. Science 218, 348–353 (1982).

    Article  CAS  PubMed  Google Scholar 

  60. Gaj, T., Gersbach, C. A. & Barbas, C. F. 3rd ZFN, TALEN and CRISPR/Cas-based methods for genome engineering. Trends Biotechnol. 31, 397–405 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Lee, J. S. et al. RNA-guided genome editing in Drosophila with the purified Cas9 protein. G3 (Bethesda) 4, 1291–1295 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Colombani, J., Andersen, D. S. & Léopold, P. Secreted peptide Dilp8 coordinates Drosophila tissue growth with developmental timing. Science 336, 582–585 (2012).

    Article  CAS  PubMed  Google Scholar 

  63. Lee, K.-S., You, K.-H., Choo, J.-K., Han, Y.-M. & Yu, K. Drosophila short neuropeptide F regulates food intake and body size. J. Biol. Chem. 279, 50781–50789 (2004).

    Article  CAS  PubMed  Google Scholar 

  64. Han, S. K. et al. OASIS 2: online application for survival analysis 2 with features for the analysis of maximal lifespan and healthspan in aging research. Oncotarget 7, 56147–56152 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  65. Conway, J. M., Ingwersen, L. A., Vinyard, B. T. & Moshfegh, A. J. Effectiveness of the US Department of Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. Am. J. Clin. Nutr. 77, 1171–1178 (2003).

    Article  CAS  PubMed  Google Scholar 

  66. Conway, J. M., Ingwersen, L. A. & Moshfegh, A. J. Accuracy of dietary recall using the USDA five-step multiple-pass method in men: an observational validation study. J. Am. Diet. Assoc. 104, 595–603 (2004).

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank A.M. Gontijo, P. Leopold, M. Dominguez and P. Shen for providing reagents, D.-W. Kim and G. Wee for helping with experiments, O.-Y. Kwon for suggesting nesfatin in flies, and J.-S. Lee, K.-W. Choi, Y.-J. Kim and M. Subramanian for comments on the manuscript. Drosophila stocks were obtained from the Bloomington Stock Center (Bloomington) and Vienna Drosophila RNAi Center (VDRC). This work was supported by grants from the KRIBB Research Initiative Program, the National Research Council of Science & Technology (CRC-15-04-KIST), the National Research Foundation of Korea (2015R1A5A1009024, 2017K1A1A2013124, 2018R1A2A3075389, 2019R1A2C2004149 and 2019R1A2C2089484) and the Korean Health Technology R&D Project, Ministry of Health & Welfare, Korea (HI14C2640).

Author information

Authors and Affiliations

Authors

Contributions

E.Y., K.-S.L. and K.Y. designed the research. S.C.K. provided key reagents. E.Y., H.S., W.Y., E.J., S.H.H., D.-W.K. and T.H.R. performed experiments. E.Y., S.K., J.M.S., S.C.K., K.-S.L. and K.Y. analysed the data. E.Y., K.-S.L. and K.Y. wrote the manuscript.

Corresponding authors

Correspondence to Jae Myoung Suh, Song Cheol Kim, Kyu-Sun Lee or Kweon Yu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Cell Biology thanks Gregory Longmore, Alessandro Laviano and the other, anonymous, reviewer for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Generation of the Drosophila cancer anorexia model.

a, Drosophila cancer model was established by overexpressing a wild-type (ykiWT) and a constitutively active form of yki (ykiS168A) using GMR-Gal4. Expression of the wild-type of yki (GMR > ykiWT) caused the mild rough eye phenotype, whereas the active form (GMR > ykiSA) showed dramatic protrusion of the eye. Scale bars are 200μm. b, The 10 day-old yki overexpression flies showed decreased food intake compared with that of the control in the blue dye feeding assay. n = 3 biologically independent experiments; 1.5 days *P = 0.022, 2 days **P = 0.003. c, UAS-ykiWT and UAS-ykiSA control flies showed normal feeding. n = 3 biologically independent experiments. d, The triglyceride levels of GMR > ykiSA was analyzed with female flies. n = 3 biologically independent experiments; day 10 *P = 0.038, day 15 *P = 0.035, day 20 *P = 0.012. e, Quantification of ovary size in Fig. 1c. n = 3 biologically independent experiments; day 10 ***P = 0.0006, day 15 **P = 0.0014, day 20 ***P < 0.001. f, The thoracic muscle of 15-day-old GMR > ykiSA showed abnormal mitochondrial structure and irregular packing of mitochondria between muscle fibers. n = 3 biologically independent experiments. Scale bar is 10μm. Data are presented as the mean ± s.e.m. Statistical significance was determined with two-tailed Student’s t-test; *P < 0.05, **P < 0.01, ***P < 0.001. Statistical source data.

Source data

Extended Data Fig. 2 RNA-seq analysis, anorexia in sev > Rasv12 flies, Lgr3Δ50 generation, Lgr3 expression in adult tissues, and eye phenotypes in GMR > ykiSA and the mutants of Dilp8 and Lgr3.

a, RNA-seq analysis showed the increased levels of three tumor-secreted factors (Dilp8, ImpL2, and Upd2) in GMR > ykiSA flies. b, sev > Rasv12 flies showed anorexia and this phenotype was effectively rescued by Dilp8-RNAi. n = 3 biologically independent experiments; sev > Rasv12 *P = 0.012, sev > Rasv12 Dilp8-RNAi *P = 0.013, sev > Rasv12 ImpL2-RNAi *P = 0.019. c, Dilp8 antibody test was performed by western blot and showed almost no expression in the Dilp8M100727 mutant. d, Dilp8 protein was increased in GMR > ykiSA fly heads and reduced in GMR > ykiSA, Dilp8-RNAi fly heads by western blot. e, The quantification of d using ImageJ program. n = 3 biologically independent experiments; GMR > ykiSA *P = 0.047, GMR > ykiSA Dilp8-RNAi *P = 0.045. f, The Lgr3Δ50 mutant was obtained using the CRISPR/Cas9-mediated mutagenesis. It consists of 50 base pair deletion in the intron region upstream of target sequences. g, Lgr3 mRNA expression in the Lgr3Δ50 mutant showed that the Lgr3Δ50 mutant is a strong hypomorphic allele. n = 3 biologically independent experiments, **P = 0.007. h, GMR > ykiSA,Dilp8MI00727 and GMR > ykiSA, Lgr3Δ50 flies respectively blunted or reversed the cancer anorexia phenotype observed in GMR > ykiSA flies. n = 4 biologically independent experiments; GMR > ykiSA *P = 0.010, GMR > ykiSADilp8M100727 *P = 0.012, GMR > ykiSALgr3Δ50 *P = 0.027. i, Dilp8 overexpression flies (GMR > Dilp8) showed reduced food intake. n = 6 biologically independent experiments, *P = 0.034. j, In GMR > ykiSA and GMR-Gal4 control flies, the Lgr3 mRNA expression level in the head is very high relative to other tissues. n = 3 biologically independent experiments; head *P = 0.017; thorax **P = 0.006, gut *P = 0.035. k, The eye phenotype in GMR > ykiSA is similar with those of GMR > ykiSA, Dilp8M100727 and GMR > ykiSA, Lgr3Δ50. Scale bar is 200μm. l, Lgr3-Gal4 expression marked by GFP. Lgr3 expression was not detectable in sNPF neurons. Scale bar is 100μm. m-n, sNPF (m) (*P = 0.018) and NPF (n) (*P = 0.048) mRNA levels were reduced by RNAi lines with Lgr3-Gal4. n = 3 biologically independent experiments. Data are presented as the mean ± s.e.m. Statistical significance was determined with two-tailed Student’s t-test; *P < 0.05, **P < 0.01. Statistical source data and unprocessed western blots.

Source data

Extended Data Fig. 3 Sequence homology of NUCB1 and NUCB2 in Drosophila and mammals.

The very similar signal peptide and cleavage site among mammalian NUCB2 and Drosophila NUCB1 suggest that the evolutionary conserved Nesfatin1 might be produced.

Extended Data Fig. 4 Intensity quantification of NUCB1 and Lgr3 antibodies immunostaining.

a, NUCB1 antibody specificity was tested by the NUCB1 inhibition using heat-shock Gal4 (Hs > NUCB1-RNAi). b, Staining intensity of neurons was measured with LSM 5 software program by drawing a dotted line as shown. c-e, The staining intensity of neuronal cells in Fig. 4 was quantified using LSM 5 software program and illustrated as intensity graphs. Control (n = 5), GMR > ykiSA (n = 10), GMR > ykiSA, Lgr3Δ50 (n = 5). f-g, A subset of sNPF (f) and NPF (g) expressing neurons in the cancer condition (GMR > ykiSA) were overlapped with NUCB1 expressing neurons. Scale bars are 100 μm. Statistical source data and unprocessed western blots.

Source data

Extended Data Fig. 5 NUCB1 protein expression in the cancer condition, ex vivo analysis, and Lgr3 expression by the Dilp8 treatment.

a, In western blot of adult heads with the NUCB1 antibody, NUCB1 protein level is increased in GMR > ykiSA, reduced in the Lgr3Δ50 mutant, and restored to the control level in GMR > ykiSA, Lgr3Δ50. b, The western blot bands of (a) were quantified using ImageJ program. n = 3 biologically independent experiments; GMR > ykiSA **P = 0.003, Lgr3Δ50 *P = 0.038, GMR > ykiSALgr3Δ50 ** P = 0.002. c, The schematic presentation of ex vivo culture assay in which the synthetic Dilp8 peptide was treated to the dissected adult brains in the culture media. d, Lgr3 mRNA level was increased after Dilp8 peptide treatment in the ex vivo culture. n = 3 biologically independent experiments; 0.5 hr *P = 0.020, 1 hr *P = 0.021. Data are presented as the mean ± s.e.m. Statistical significance was determined with two-tailed Student’s t-test; *P < 0.05, **P < 0.01. Statistical source data and unprocessed western blots.

Source data

Extended Data Fig. 6 Conservation of INSL3/Lgr8 in mammals, and cachexia-anorexia phenotype of C26 or LLC implanted mice.

a. The phylogenetic comparative analysis of Drosophila Lgr3 and mammalian Lgr family shows that Lgr7/8 is a homologue of Lgr3. b, The phylogenetic comparative analysis of fly Dilp8 and mammalian INSL3 shows that they are classified as close peptides. c, Lgr8 protein is strongly expressed in the hypothalamic region and hippocampus of the mouse brain. d, In the RNA FISH, Lgr8 mRNA is strongly expressed in the hypothalamic region and hippocampus of the mouse brain. e, Lgr8 is expressed in the mouse hypothalamic N3 cells, but not in N39 cells. f-g, Body weight was changed in C26 tumor implanted mice (f) not in LLC tumor implanted mice (g). n = 7 mice for both groups. f, 2w + 2day *P = 0.027, 2w + 4day ***P = 0.0004, 2w + 6day **P = 0.0034. h, Tumor volume and weight changes were measured in C26 and LLC implanted mice. n = 6 mice for both groups. i-j, Muscle and fat weight of C26 tumor implanted mice at day 12 (i) and day 21 (j). Tibialis anterior (TA), gastrocnemius (GCM), inguinal white adipose tissue (iWAT), and epididymal white adipose tissue (eWAT). Control n = 3 mice, C26 day 12 n = 5 mice, C26 day 21 n = 4 mice. i, iWAT *P = 0.024, eWAT *P = 0.094. j, GCM *P = 0.038, iWAT **P = 0.001, eWAT *P = 0.013. k-l, Nucb2 (k) and Npy (l) mRNA levels were not changed in LLC implanted mice. n = 5 mice for both groups. m, INSL3 i.p. injected wild-type mice didn’t show reduction of food intake. n = 7 mice for both groups. n-o, Nucb2 (n) and Npy (o) mRNA levels were not changed in INSL3 i.p. injected wild-type mice hypothalamus. n = 3 mice for both groups. Data are presented as the mean ± s.e.m. Statistical significance was determined with two-tailed Student’s t-test; *P < 0.05, **P < 0.01, ***P < 0.001. Statistical source data and unprocessed western blots.

Source data

Extended Data Fig. 7 Anorexia-associated body mass changes of human pancreatic cancer implanted mice.

a, Tumor volumes were increased in Panc1 and Capan1 implanted mice. n = 4 mice for three groups; 3 week *P = 0.049, 4 week *P = 0.049, 5 week *P = 0.033. b, Body mass were reduced in Panc1 and Capan1 implanted mice compared to the control mice. n = 4 mice for each group; 3 week Panc1 **P = 0.0014 and Capan1 *P = 0.049, 5 week Panc1 ***P < 0.0001 and Capan1 ***P < 0.0001. 6 week Panc1 ***P < 0.0001 and Capan1 ***P < 0.0001. c, Relaxin-INSL family mRNA expression levels in Capan1 cells. n = 3 biologically independent experiments; Rxn vs INSL3 **P = 0.003. Data are presented as the mean ± s.e.m. Statistical significance was determined with two-tailed Student’s t-test; *P < 0.05. Statistical source data.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–6.

Reporting Summary

Peer Review Information

Supplementary Tables 1–3

Supplementary Table 1. Feeding regulatory neuropeptides in Drosophila were identified in the RNA sequencing analysis of GMR>ykiSA. Supplementary Table 2. Clinicopathological characteristics among patients with pancreatic cancer and other diseases. Supplementary Table 3. Clinicopathological characteristics of patients enrolled in food intake analysis.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 2

Unprocessed blots.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 6

Statistical source data.

Source Data Fig. 7

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 2

Unprocessed blots.

Source Data Extended Data Fig. 4

Statistical source data.

Source Data Extended Data Fig. 4

Unprocessed blots.

Source Data Extended Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 5

Unprocessed blots.

Source Data Extended Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 6

Unprocessed blots.

Source Data Extended Data Fig. 7

Statistical source data.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yeom, E., Shin, H., Yoo, W. et al. Tumour-derived Dilp8/INSL3 induces cancer anorexia by regulating feeding neuropeptides via Lgr3/8 in the brain. Nat Cell Biol 23, 172–183 (2021). https://doi.org/10.1038/s41556-020-00628-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41556-020-00628-z

This article is cited by

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer