Microscopy analysis of tumour samples is commonly performed on fixed, thinly sectioned and protein-labelled tissues. However, these examinations do not reveal the intricate three-dimensional structures of tumours, nor enable the detection of aberrant transcripts. Here, we report a method, which we name DIIFCO (for diagnosing in situ immunofluorescence-labelled cleared oncosamples), for the multimodal volumetric imaging of RNAs and proteins in intact tumour volumes and organoids. We used DIIFCO to spatially profile the expression of diverse coding RNAs and non-coding RNAs at the single-cell resolution in a variety of cancer tissues. Quantitative single-cell analysis revealed spatial niches of cancer stem-like cells, and showed that the niches were present at a higher density in triple-negative breast cancer tissue. The improved molecular phenotyping and histopathological diagnosis of cancers may lead to new insights into the biology of tumours of patients.
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The main data supporting the results in this study are available within the paper and its Supplementary Information. The raw and analysed datasets generated during the study are too large to be publicly shared, yet they are available for research purposes from the corresponding authors on reasonable request.
The custom code used in this study is available at GitHub (https://github.com/uhlen-lab).
Andor, N. et al. Pan-cancer analysis of the extent and consequences of intratumor heterogeneity. Nat. Med. 22, 105–113 (2016).
Wang, K. et al. Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer. Nat. Genet. 46, 573–582 (2014).
Gerlinger, M. et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366, 883–892 (2012).
Sachs, N. et al. A living biobank of breast cancer organoids captures disease heterogeneity. Cell 172, 373–386 (2018).
Vogelstein, B. et al. Cancer genome landscapes. Science 339, 1546–1558 (2013).
McGranahan, N. & Swanton, C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell 27, 15–26 (2015).
Uhlen, P. & Tanaka, N. Improved pathological examination of tumors with 3D light-sheet microscopy. Trends Cancer 4, 337–341 (2018).
Tanaka, N. et al. Whole-tissue biopsy phenotyping of three-dimensional tumours reveals patterns of cancer heterogeneity. Nat. Biomed. Eng. 1, 796–806 (2017).
Chen, F. et al. Nanoscale imaging of RNA with expansion microscopy. Nat. Methods 13, 679–684 (2016).
Choi, H. M. T. et al. Programmable in situ amplification for multiplexed imaging of mRNA expression. Nat. Biotechnol. 28, 1208–1212 (2010).
Lovett-Barron, M. et al. Ancestral circuits for the coordinated modulation of brain state. Cell 171, 1411–1423 (2017).
Choi, H. M. T. et al. Mapping a multiplexed zoo of mRNA expression. Development 143, 3632–3637 (2016).
Choi, H. M. T. et al. Third-generation in situ hybridization chain reaction: multiplexed, quantitative, sensitive, versatile, robust. Development 145, dev165753 (2018).
Stefanits, H. et al. KINFix—A formalin-free non-commercial fixative optimized for histological, immunohistochemical and molecular analyses of neurosurgical tissue specimens. Clin. Neuropathol. 35, 3–12 (2016).
Kap, M. et al. Histological assessment of PAXgene tissue fixation and stabilization reagents. Plos ONE 6, e27704 (2011).
Lykidis, D. et al. Novel zinc-based fixative for high quality DNA, RNA and protein analysis. Nucleic Acids Res. 35, e85 (2007).
Wester, K. et al. Zinc-based fixative improves preservation of genomic DNA and proteins in histoprocessing of human tissues. Lab. Invest. 83, 889–899 (2003).
Sylwestrak, E. L., Rajasethupathy, P., Wright, M. A., Jaffe, A. & Deisseroth, K. Multiplexed intact-tissue transcriptional analysis at cellular resolution. Cell 164, 792–804 (2016).
Renier, N. et al. Mapping of brain activity by automated volume analysis of immediate early genes. Cell 165, 1789–1802 (2016).
Hatzis, C. et al. Effects of tissue handling on RNA integrity and microarray measurements from resected breast cancers. J. Natl Cancer Inst. 103, 1871–1883 (2011).
Snippert, H. J. et al. Prominin-1/CD133 marks stem cells and early progenitors in mouse small intestine. Gastroenterology 136, 2187–2194 (2009).
Medema, J. P. Cancer stem cells: the challenges ahead. Nat. Cell Biol. 15, 338–344 (2013).
Brugnoli, F., Grassilli, S., Al-Qassab, Y., Capitani, S. & Bertagnolo, V. CD133 in breast cancer cells: more than a stem cell marker. J. Oncol. 2019, 7512632 (2019).
Joseph, C. et al. Overexpression of the cancer stem cell marker CD133 confers a poor prognosis in invasive breast cancer. Breast Cancer Res. Treat. 174, 387–399 (2019).
Liu, T. J. et al. CD133+ cells with cancer stem cell characteristics associates with vasculogenic mimicry in triple-negative breast cancer. Oncogene 32, 544–553 (2013).
Panaccione, A., Guo, Y., Yarbrough, W. G. & Ivanov, S. V. Expression profiling of clinical specimens supports the existence of neural progenitor-like stem cells in basal breast cancers. Clin. Breast Cancer 17, 298–306 (2017).
Iwai, Y., Hamanishi, J., Chamoto, K. & Honjo, T. Cancer immunotherapies targeting the PD-1 signaling pathway. J. Biomed. Sci. 24, 26 (2017).
Anastasiadou, E., Jacob, L. S. & Slack, F. J. Non-coding RNA networks in cancer. Nat. Rev. Cancer 18, 5–18 (2018).
Schmitt, A. M. & Chang, H. Y. Long noncoding RNAs in cancer pathways. Cancer Cell 29, 452–463 (2016).
Arun, G. et al. Differentiation of mammary tumors and reduction in metastasis upon Malat1 lncRNA loss. Genes Dev. 30, 34–51 (2016).
Xue, M., Chen, W. & Li, X. Urothelial cancer associated 1: a long noncoding RNA with a crucial role in cancer. J. Cancer Res. Clin. Oncol. 142, 1407–1419 (2016).
Weber, J. et al. Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma. N. Engl. J. Med. 377, 1824–1835 (2017).
Uhlen, M. et al. Tissue-based map of the human proteome. Science 347, 1260419 (2015).
Clevers, H. Modeling development and disease with organoids. Cell 165, 1586–1597 (2016).
Choi, H. M., Beck, V. A. & Pierce, N. A. Next-generation in situ hybridization chain reaction: higher gain, lower cost, greater durability. ACS Nano 8, 4284–4294 (2014).
Han, R., Chen, S., Wang, J., Zhao, Y. & Li, G. LncRNA UCA1 affects epithelial–mesenchymal transition, invasion, migration and apoptosis of nasopharyngeal carcinoma cells. Cell Cycle 18, 3044–3053 (2019).
Brabletz, T., Kalluri, R., Nieto, M. A. & Weinberg, R. A. EMT in cancer. Nat. Rev. Cancer 18, 128–134 (2018).
Pastushenko, I. et al. Identification of the tumour transition states occurring during EMT. Nature 556, 463–468 (2018).
Gutschner, T. et al. The noncoding RNA MALAT1 is a critical regulator of the metastasis phenotype of lung cancer cells. Cancer Res. 73, 1180–1189 (2013).
Murrow, L. M. et al. Mapping the complex paracrine response to hormones in the human breast at single-cell resolution. Preprint at bioRxiv https://doi.org/10.1101/430611 (2020).
Diggle, P. J. Statistical Analysis of Spatial Point Patterns (Academic, 1983).
Park, Y. G. et al. Protection of tissue physicochemical properties using polyfunctional crosslinkers. Nat. Biotechnol. 37, 73–83 (2019).
Azaripour, A. et al. A survey of clearing techniques for 3D imaging of tissues with special reference to connective tissue. Prog. Histochem. Cytochem. 51, 9–23 (2016).
Kreso, A. & Dick, J. E. Evolution of the cancer stem cell model. Cell Stem Cell 14, 275–291 (2014).
Nassar, D. & Blanpain, C. Cancer stem cells: basic concepts and therapeutic implications. Annu Rev. Pathol. 11, 47–76 (2016).
O’Brien, C. A., Pollett, A., Gallinger, S. & Dick, J. E. A human colon cancer cell capable of initiating tumour growth in immunodeficient mice. Nature 445, 106–110 (2007).
Al-Hajj, M., Wicha, M. S., Benito-Hernandez, A., Morrison, S. J. & Clarke, M. F. Prospective identification of tumorigenic breast cancer cells. Proc. Natl Acad. Sci. USA 100, 3983–3988 (2003).
Lathia, J. D. & Liu, H. Overview of cancer stem cells and stemness for community oncologists. Target Oncol. 12, 387–399 (2017).
Batlle, E. & Clevers, H. Cancer stem cells revisited. Nat. Med. 23, 1124–1134 (2017).
Schulenburg, A. et al. Cancer stem cells in basic science and in translational oncology: can we translate into clinical application? J. Hematol. Oncol. 8, 16 (2015).
Desai, A., Yan, Y. & Gerson, S. L. Concise reviews: cancer stem cell targeted therapies: toward clinical success. Stem Cells Transl. Med. 8, 75–81 (2019).
Prasad, S., Ramachandran, S., Gupta, N., Kaushik, I. & Srivastava, S. K. Cancer cells stemness: a doorstep to targeted therapy. Biochim. Biophys. Acta Mol. Basis Dis. 1866, 165424 (2020).
Klonisch, T. et al. Cancer stem cell markers in common cancers—therapeutic implications. Trends Mol. Med. 14, 450–460 (2008).
Enderling, H. Cancer stem cells: small subpopulation or evolving fraction? Integr. Biol. 7, 14–23 (2015).
Hoefflin, R. et al. Spatial niche formation but not malignant progression is a driving force for intratumoural heterogeneity. Nat. Commun. 7, ncomms11845 (2016).
Neumeister, V., Agarwal, S., Bordeaux, J., Camp, R. L. & Rimm, D. L. In situ identification of putative cancer stem cells by multiplexing ALDH1, CD44, and cytokeratin identifies breast cancer patients with poor prognosis. Am. J. Pathol. 176, 2131–2138 (2010).
Yang, F. et al. Evaluation of breast cancer stem cells and intratumor stemness heterogeneity in triple-negative breast cancer as prognostic factors. Int. J. Biol. Sci. 12, 1568–1577 (2016).
Ricci-Vitiani, L. et al. Tumour vascularization via endothelial differentiation of glioblastoma stem-like cells. Nature 468, 824–828 (2010).
Lancaster, M. A. & Knoblich, J. A. Generation of cerebral organoids from human pluripotent stem cells. Nat. Protoc. 9, 2329–2340 (2014).
Camp, J. G. et al. Human cerebral organoids recapitulate gene expression programs of fetal neocortex development. Proc. Natl Acad. Sci. USA 112, 15672–15677 (2015).
Uhlin, E. et al. Derivation of human iPS cell lines from monozygotic twins in defined and xeno free conditions. Stem Cell Res. 18, 22–25 (2017).
Sato, T. et al. Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett’s epithelium. Gastroenterology 141, 1762–1772 (2011).
Chung, K. et al. Structural and molecular interrogation of intact biological systems. Nature 497, 332–337 (2013).
Tanaka, N. et al. Mapping of the three-dimensional lymphatic microvasculature in bladder tumours using light-sheet microscopy. Br. J. Cancer 118, 995–999 (2018).
Tomer, R., Ye, L., Hsueh, B. & Deisseroth, K. Advanced CLARITY for rapid and high-resolution imaging of intact tissues. Nat. Protoc. 9, 1682–1697 (2014).
Bria, A. & Iannello, G. TeraStitcher—a tool for fast automatic 3D-stitching of teravoxel-sized microscopy images. BMC Bioinformatics 13, 316 (2012).
Rueden, C. T. et al. ImageJ2: ImageJ for the next generation of scientific image data. BMC Bioinformatics 18, 529 (2017).
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).
We thank A. Östman for discussions. This study was supported by the Swedish Research Council (grant nos. 2009-3364, 2013-3189 and 2017-00815, to P.U.), the Swedish Cancer Society (grant nos. CAN 2016-801, 19 0544 Pj and 19 0545 Us, to P.U.), the Swedish Childhood Cancer Foundation (grant no. PR2018-0123, to P.U.), the Swedish Brain Foundation (grant nos. FO2018-0209, to P.U., and FO2018-0281, to A.F.), the Olle Engkvist foundation (to P.U.), the David and Astrid Hagelén Foundation (to N.T.), the Karolinska Institutet Research Foundation (to N.T., S.K. and P.U.), the Takeda Science Foundation (to N.T.), Grant-in-Aid for Scientific Research (KAKENHI 18H04906, 18K19482 and 19H03792, to N.T.), the Kobayashi Foundation for Cancer Research (to N.T.), the Keio Gijuku Academic Development Funds (to N.T.), the Scandinavia-Japan Sasakawa Foundation (to N.T., K.F. and S.K.), and the Wenner-Gren Foundation (to S.K.). The light-sheet microscopy infrastructure used in this research received grants from the Strategic Research Area in Neuroscience (StratNeuro) and the Strategic Research Area in Stem Cells and Regenerative Medicine (StratRegen), supported by the Swedish government.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Figs. 1–10 and captions for Supplementary Videos 1–6.
Volume rendering of a mouse embryo.
Cell-by-cell analysis of human breast cancer tissue.
Parvalbumin RNA and protein staining of a mouse cortical section.
Volume rendering of a human organoid.
Cell-by-cell analysis of human colon cancer tissue.
Spatial niche analysis of human breast cancer tissue.
Probe sequences and accession numbers of the targeted RNAs.
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Tanaka, N., Kanatani, S., Kaczynska, D. et al. Three-dimensional single-cell imaging for the analysis of RNA and protein expression in intact tumour biopsies. Nat Biomed Eng 4, 875–888 (2020). https://doi.org/10.1038/s41551-020-0576-z