The extracellular matrix supports cancer cell growth under amino acid starvation by promoting tyrosine catabolism

  1. Mona Nazemi
  2. Bian Yanes
  3. Montserrat Llanses Martinez
  4. Heather Walker
  5. Frederic Bard
  6. Elena Rainero

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Abstract

Breast and pancreatic tumours are embedded in a collagen I-rich extracellular matrix (ECM) network, where nutrients are scarce due to limited blood flow and elevated tumour growth. Metabolic adaptation is required for cancer cells to endure these conditions. Here, we demonstrated that the presence of ECM supported the growth of invasive breast cancer cells, but not non-transformed mammary epithelial cells, and pancreatic cancer cells under amino acid starvation, through a mechanism that required macropinocytosis-dependent ECM uptake. Importantly, we showed that this behaviour was acquired during carcinoma progression. ECM internalisation, followed by lysosomal degradation, contributed to the upregulation of the intracellular levels of several amino acids, most notably tyrosine and phenylalanine. This resulted in elevated tyrosine catabolism on ECM under starvation, leading to increased fumarate levels, potentially feeding into the tricarboxylic acid cycle. Interestingly, this pathway was required for ECM-dependent cell growth under amino acid starvation, as the knockdown of p-hydroxyphenylpyruvate hydroxylase-like protein (HPDL), the third enzyme of the pathway, opposed cell growth on ECM in both 2D and 3D systems, without affecting cell proliferation on plastic. Finally, high HPDL expression correlated with poor prognosis in breast and pancreatic cancer patients. Collectively, our results highlight that the ECM in the tumour microenvironment represents an alternative source of nutrients to support cancer cell growth, by regulating phenylalanine and tyrosine metabolism.

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    Reply to the reviewers

    We would like to thank all the reviewers for their positive evaluations of our work and constructive comments, in particular for highlighting that our work “provides new insight into cancer metabolism knowledge”, is “conceptually interesting and experimentally well performed” and “the findings presented here will be very interesting to a broad range of researchers, including the cancer, metabolism and wider cell biology communities”.

    Reviewer #1 (Evidence, reproducibility and clarity (Required)):* Nazemi et al. show that the extracellular matrix (ECM) has a crucial role in sustaining the growth of invasive breast and pancreatic cells during nutrient deprivation. In particular, under amino acid starvation, cancer cells internalize ECM by macropinocytosis and activate phenylalanine and tyrosine catabolism, which in turn support cell growth in nutrient stress conditions. The paper is well written and the results shown are very interesting. The experimental plan is well designed to assess the hypothesis and the description of the methods is sufficiently detailed to reproduce the analyses, which are also characterized by appropriate internal controls. Finally, the data provided sustain the conclusions proposed by the authors.*

    Major comment:*

    Since the authors performed their experiments on invasive breast and pancreatic cancers and it has been noted that stress conditions could promote the escape of cancer cells from the site of origin (e.g., Jimenez and Goding, Cell Metabolism 2018; Manzano et al, EMBO Reports 2020), it would be interesting to evaluate how ECM internalization could have a role in sustaining the invasive abilities of cancer cells under amino acid starvation. Which is the impact of the inhibition of macropinocytosis and tyrosine catabolism on cell invasion? The authors could evaluate this aspect by in vitro 2D and 3D analysis.

    This is a very important point, and we are planning to investigate this by using:

    • 2D single cell migration assays on cell-derived matrices (we have extensively used this system to characterise invasive cell migration; Rainero et al., 2015; Rainero et al., 2012)
    • 3D spheroids assays, to assess collective/3D cell invasion through collagen I and matrigel mixtures. Both experiments will be performed under amino acid starvation, in the presence of pharmacological inhibitors and siRNAs targeting macropinocytosis (FRAX597, PAK1) and tyrosine catabolism (Nitisinone, HPDL). Preliminary data suggest that both FRAX597 and Nitisinone reduce cell invasiveness.

    In addition, to strengthen the paper and give a stronger significance in terms of clinical translatability, it could be useful to implement the analysis of breast and pancreatic patients by publicly dataset evaluating for example free survival, disease free survival, overall survival and metastasis free survival.

    We have now included in the manuscript new data in figure 6 O-R showing that high HPDL expression correlates with reduces overall survival, distant metastasis-free survival, relapse-free survival and palliative performance scale in breast cancer patients. In response to other reviewers’ comments, we have removed the pancreatic cancer data from our manuscript.

    Minor Comment:

    The text and the figures are clear and accurate. The references cited support the hypothesis, rightly introduce the results and are appropriate for the discussion. However, the paragraph relative to figure 4 is a little confusing. Changing the order of the description of the results could be useful.

    We apologise for the lack of clarity in this section. We have now re-organised the data both in the figure and in the result section, to describe the findings in a more logical way.

    Reviewer #1 (Significance (Required)):* Based on my metabolic background in tumour aetiology and progression, I think that this study provides new insights into cancer metabolism knowledge, in particular on how the stroma may drive metabolic reprogramming of cancer cells sustaining cell growth in nutrient stress conditions. Together with other similar studies on the stromal non-cellular components, the data here shown can contribute to expand the knowledge on the factors that promote cancer metabolic plasticity, which is exploited from cancer cells to obtain advantages in terms of growth, survival and progression. In conclusion, I think that the results shown are new and the manuscript is well presented. Following the short revision process suggested, it will be eligible for a final publication in a medium-high impact factor journal.*

    Reviewer #2 (Evidence, reproducibility and clarity (Required)):

    • Please find enclosed my reviewing comments on the manuscript entitled "The extracellular matrix supports cancer cell growth under amino acid starvation by promoting tyrosine catabolism" by Nazemi et al.*

    In this manuscript the group of Elena Romero and colleagues provides evidence that breast cancer cells, and pancreatic cancer cell, use matrix proteins degradation to feed their proliferative metabolic needs under amino acid starvation. Under this drastic condition, cancer cells use micropinocytosis to uptake matrix proteins, a process that requires mTORC1 activation and PAK1. Furthermore, a metabolomic study demonstrates that ECM-dependent cancer cell growth relies on tyrosine catabolism.* Altogether, I found this study conceptually interesting and experimentally well performed. Experiments are well controlled and state-of-the-art technologies used in this manuscript make it a good candidate for publication. However, some aspects of the work need to be strengthen to reinforce the overall good quality of the manuscript, therefore, please find below some experimental propositions.* 1. Despite the reviewer proposition, I believe that the additional experiments using the PDAC cancer cell does not improve the quality of the manuscript. Instead, it brings confusion to me, since the relative addition is minor compare to what is demonstrated using breast cancer cells.

    We have decided to remove the pancreatic cancer cell data from the manuscript.

    To importantly improve the potential impact of this manuscript, I suggest to add in vivo data using either syngenic mice model of breast cancer or xenografted human breast cancer cells in nude mice. What would be the impact of micropinocytosis and tyrosine catabolism inhibition on cancer growth, in vivo, should be demonstrated? If possible, it may be interesting to demonstrate that this micropinocytosis may interfere with cancer evolution toward a metastatic phenotype using, for example, the PyMT-MMTV mice model of breast cancer development?

    We will perform orthotopic mammary fat pad injections in immunocompetent mice, to monitor primary tumour growth and localised invasion in the presence of Nitisinone or vehicle control. PyMT-driven breast cancer cells have been generated in the Blyth lab, from FVB-pure MMTV-PyMT mice and we have preliminary data indicating that these cells are able to internalise ECM and grow under starvation in an ECM-dependent manner. Prior to performing any in vivo work, we will perform further in vitro experiment to confirm the role of tyrosine catabolism in these cells. Nitisinone is an FDA-approved drug that has already been used in mouse models. Blood tyrosine levels can be measured to assess tyrosine catabolism inhibition by Nitisinone. These experiments will be conducted in collaboration with the Blyth lab at the CRUK Beatson Institute in Glasgow.

    Data obtained using cancer cells with different metastatic property suggest that the ability to use ECM to compensate for soluble nutrient starvation is acquired during cancer progression. To further demonstrate that it is the case, would it be possible that non metastatic breast cancer cells are not able to perform micropinocytosis? Is PAK1 overexpressed with increase cancer cells metastatic ability, without affecting invasive capacity in 3D spheroids?

    To address these points, we have started to measure PAK1 expression across the MCF10 series of cell lines, where MCF10A are non-transformed mammary epithelial cells, MCF10A-DCIS are ductal carcinoma in situ cells and MCF10CA1 are metastatic breast cancer cells. Our preliminary data show that there is no upregulation of PAK1 expression in the metastatic cells compared to non-transformed or non-invasive cancer cells. This suggest that the over-expression of PAK1 might not be a valuable strategy to address this point.

    In addition, we found that collagen I uptake was upregulated in MCF10CA1 compared to MCF10A and MCF10A-DCIS. We will corroborate our preliminary data by quantifying collagen I and cell-derived matrices internalisation across the 3 cell lines.

    What would be the efficacy to promote the ECM-dependent growth under starvation following a mTORC1 in non-invasive cancer cells?

    We will measure the growth of MCF10A and MCF10A-DCIS on ECM under starvation in the presence of the mTOR activator MHY1485. Western blot analysis of downstream targets of mTORC1 (p-S6 and p-4EBP1) will confirm the extent of mTOR activation.

    The discrepancy of cancer cells proliferation under starvation condition between plastic and ECM-based supports could be explained by the massive difference of support rigidity. This is also probably the case between CDM made by normal fibroblast and CAF. It brings the question of studying the role of matrix stiffness in regard to micropinocytosis-dependent cancer cells growth. It would also explain why this process is link to aggressive cancer cell behaviour, as ECM goes stiffer with time in cancer development. It may not be the case, but the demonstration that mechanical cues from the ECM could regulate the micropinocytosis-dependent cancer cells growth under amino acid starvation could bring additional value to the manuscript.

    We will use 2 experimental approaches to address the effect of different stiffness in ECM-dependent cell growth:

    1. Polyacrylamide hydrogels coated with different ECM components.
    2. Collagen I gels in which the stiffness is modified by Ribose treatment (this approach has been published by the Parson’s lab). Our preliminary data confirmed that ribose cross-linking increased YAP nuclear localisation and collagen I can still be internalised under these conditions. We will assess ECM endocytosis and cell growth under starvation conditions (using EdU incorporation in conjunction with A and high throughput imaging with B)

    Along with this, it has been demonstrated that matrix rigidity regulates glutaminolysis in breast cancer, resulting in aspartate production and cancer cells proliferation. Is asparate production increase by micropinocytosis? Could you rescue cancer cells growth by aspartate supplementation?

    Our metabolomics experiments were performed under amino acid starvation; therefore glutamine was not present in the media. Nor glutaminolysis intermediates nor aspartate were upregulated on ECM compared to plastic in our datasets, suggesting that aspartate might not be involved in this system. We added this point in the discussion. However, glutamine, glutamate and aspartate were found to be upregulated on collagen I compared to plastic in complete media, where the most enriched pathway was alanine, aspartate and glutamate metabolism. Future work will address the role of the ECM in supporting cancer cell metabolism in the absence of nutrient starvation.

    Data presented in Fig 1 and SF1 show that breast cancer cell lines growth in a comparable manner either they are cultured on plastic or on 3D ECM substrates in complete media. Again, on thick 3D substrates, in which the stiffness is lower compared to plastic, I would have thought that cancer cells would have grown slower. Could you please discuss this finding in regard to the literature?

    Our experiments in full media were performed in the presence of dialysed serum, to represent a better control for the starvation conditions, which were in the presence of dialysed serum. This is consistent with a vast body of literature assessing nutrient starvation conditions in the presence of dialysed serum. This could explain the discrepancy between ours and published results. We have addressed this point in the discussion.

    If you have the capacity to do so in your lab or in collaboration, would it be possible to measure the exact stiffness of the different matrix you use in this manuscript? Or using hydrogel, would it be possible to study the role of matrix stiffness in the ECM-dependent cancer cells growth under AA starvation? I would understand that this may be out of the scope of the present manuscript, but I again believe that such finding would reinforce the manuscript.

    We don’t have the capacity to measure the stiffness in our lab, however NF-CDM and CAF-CDM, generated by the same cells and using the same protocol, have been previously measured at ~0.4kPa and ~0.8 kPa, respectively (Hernandez-Fernaud et al., 2017). We have now included this in the paper. As mentioned in response to point 4, we will use hydrogels to directly test the effect of matrix stiffness on ECM-dependent cell growth under nutrient starvation.

    In SF 3A-C, it is shown that ECM does not affect caspase-dependent cell death under AA starvation. Did you considered a non-caspase dependent cell death that may be triggered by AA starvation?

    We will complement the caspase 3/7 data by performing PI staining, to detect all forms of cell death. Preliminary data indicate that, consistent with our cas3/7 data, amino acid starvation promotes cell death, but the presence of the ECM doesn’t affect the percentage of PI positive cells, corroborating our conclusions that the ECM modulates cell proliferation and not cell death. We will complete these experiments in both MDA-MB-231 and MCF10CA1 cells and will include them in figure S3.In fig 5, it is shown that inhibition of Focal Adhesion Kinase (FAK) does not impair the ECM-dependent rescue of cancer cell growth under starvation. To further decipher the concept of adhesion dependent signalling, maybe the authors could also inhibit the Src kinase or ITG-beta1 activation?

    Integrin b1 is also required for ECM internalisation (our unpublished data), therefore interfering with integrin function would make the interpretation of the data quite complex. As suggested by the reviewer, we will use the Src inhibitor PP2, which has been extensively used in the literature in MDA-MB-231 cells. Preliminary data indicate that, despite significantly reducing cell proliferation in complete media, Src inhibition does not affect cell growth on collagen I under amino acid starvation, consistent with our FAK inhibitor data. We will complete these experiments on both collagen I and cell-derived matrices and will include them in figure 5.

    Minor comment, in F1B, it is written "AA free starvation" while in every others legend, it is written "AA starvation". I believe the "free" should be removed.

    We apologise for this mistake; we have now removed “free” from the legend.

    Reviewer #2 (Significance (Required)):* Altogether, I found this study conceptually interesting and experimentally well performed. Experiments are well controlled and state-of-the-art technologies used in this manuscript make it a good candidate for publication. However, some aspects of the work need to be strengthen to reinforce the overall good quality of the manuscript.*

    Reviewer #3 (Evidence, reproducibility and clarity (Required)):* In this manuscript the authors explore the mechanisms that metastatic cancer cells use to adapt their metabolism. The authors show that the growth of cancer cell lines is supported by uptake of ECM components in nutrient-starved conditions. The authors propose a very interesting mechanism in which the cells adapt their metabolism to ECM uptake as nutrient source via a PAK1-dependent macropinocytosis pathway which in turn increases tyrosine catabolism. Several key aspects of the authors complex hypothesis require further controls to fully support the authors ideas. As a disclaimer we do not feel qualified enough to comment on the metabolite experiments. Please find our detailed comments below.*

    Major -The ECM mediated increase of cell growth under amino acid (AA) starvation is nicely shown In Fig.1 but the authors should include the full medium data from figure S1 in the graphs of Fig. 1 to enable the reader to evaluate the magnitude of rescue effect of the ECM components. The values should also be included in the results text*.

    We have now moved all the complete media data into the main figure and highlighted the extent of the rescue in the result section.

    Also the authors only glutamine starve in Fig1&2 and then don't mention it again can the authors please include a sentence to explain why this experiment was dropped.

    As now highlighted in the result section, we focused on the amino acid starvation as it resulted in the strongest difference between normal and cancer. On the one hand, also non-invasive breast cancer cells can use ECM (namely matrigel) to grow under glutamine starvation, while this is not the case under amino acid starvation. On the other hand, only CAF-CDM, but not normal-CDM, could rescue cell growth under amino acid starvation. We reasoned that this condition was more likely to identify cancer-specific phenotypes.

    - The evaluation of uptake pathways is very interesting. The focus on macropinocytosis is not entirely justified in our opinion looking at FigS4A. Caveolin1/2 and DNM1/3 seem to have strongest effect on uptake of Matrigel and not PAK1? Statements like "Since our data indicate that macropinocytosis is the main pathway controlling ECM endocytosis..." are not justified nor are they really needed in our opinion. Several pathways can be implicated in passive uptake.

    We have now removed the statement, as suggested by the reviewer. In addition, we will assess CDM uptake upon caveolin 1/2 and DNM 2/3 knock-down, to test whether the effects are matrigel specific.

    - The authors use FAK inhibition to evaluate the effect of focal adhesion signalling on their phenotypes and conclude that there is no connection between the observed increase of cell proliferation in presence of ECM and adhesion signalling. To make this assessment the authors need at the very least to show that their FAK inhibitor treatment at the used concentration results in changes in focal adhesions and the associated force transduction.

    In the result section, we are including a western blot analysis showing that the concentration of FAK inhibitor used in sufficient so significantly reduced FAK auto-phosphorylation. Based on published evidence (Horton et al., 2016), FAK inhibition does not affect focal adhesion formation, but only the phosphorylation events. Therefore, we don’t think that we will be able to detected changes in focal adhesions regardless of the concentration of the inhibitor we use. To strengthen the observation that ECM-dependent cell growth in independent from adhesion signalling, as suggested by reviewer #2, we will use the Src inhibitor PP2, which has been extensively used in the literature in MDA-MB-231 cells. Preliminary data indicate that, despite significantly reducing cell proliferation in complete media, Src inhibition does not affect cell growth on collagen I under amino acid starvation, consistent with our FAK inhibitor data. We will complete these experiments on both collagen I and cell-derived matrices and will include them in figure 5.

    -The pancreatic cancer data currently feels a bit like an afterthought. We suggest to remove this data from the manuscript. If this data is included we suggest the authors should expand this section and repeat key experiments of earlier figures.

    We have now removed these data from the manuscript, as this was also the suggestion of reviewer #2.

    -Was the fetal bovine serum (FBS) and Horse Serum (HS) the authors use in their experiments tested for ECM components? The authors mention that the FBS for MDA231 cells was dialysed but not the HS.

    HS was used at a much lower concentration that FBS in our cell proliferation experiments (2.5% compared to 10%). We will characterise both sera components by mass spectrometry analysis, in collaboration with Dr Collins, biOMICS Facility, University of Sheffield.

    Minor comments:

    -Please can the authors provide experimental data directly comparing NF-CAM versus CAF-CDM on the same graph (Figure 1D-E).

    In the experiments included in the manuscript, the two matrices were generated independently, and we don’t feel it is appropriate to combine the results in the same graph. We are now repeating these experiments by generating both matrices in the same plates, so that we can present the data in the same graph. -Please can the authors give more insight to the use of 25% Plasmax to mimic starved tumor microenvironment. Is there previous research that suggests the nutrient values are representative of TME?

    Apologies for not clarifying this in the initial submission, the rationale behind this choice is based on the observation that, in pancreatic cancers, nutrients were shown to be depleted between 50-75% (Kamphorst et al., 2015). We have now stated this in the result section.

    -Fig3E Can the authors please include example images of the pS6 staining in the supplementary figures and explain "mTOR endosomal index" in figure legend.

    We have now included the representative images (new figure 3E) and we have described how the mTOR endosomal index was calculated both in the figure legend and in the method section. -Can the authors include a negative control for the mTORC1 localisation in Fig.3 (such as use of rapamycin/Torin)?

    Amino acid starvation is the gold-standard control for mTORC1 lysosomal targeting, as described in a variety of publications, including Manifava et al., 2016; Meng et al., 2021; Averous et al., 2014. In addition, Torin 1 treatment has been shown to result in a significant accumulation of mTOR on lysosomes compared with untreated cells (Settembre et al., 2012). Consistent with this, we looked at mTOR localisation in the presence of Rapamycin and we did not detect any reduction in lysosomal targeting.

    - The PAK1 expression level blots in the knockdown experiments should be quantified from N=3.

    We have not included the quantification of the western blots in the new supplementary figure 5.

    -What is the FA index in Fig.5, explain how it is calculated. Why not use FA size alone?

    We have now defined this is the method section. We haven’t used FA size alone, as this measure can be affected by cell size. If a cell is bigger, the overall FA size will be bigger, but this doesn’t necessarily reflect a change in adhesions.

    -Can the authors please use paragraphs on page 9 to improve readability. We apologise for overlooking this, we have now used paragraph in this section.

    Reviewer #3 (Significance (Required)):* The findings presented here will be very interesting to a broad range of researchers including the cancer, metabolism and wider cell biology communities. The Rainero lab has progressed the idea that ECM uptake supports cancer progression and the data presented here has the potential to significantly advance our understanding of the underlying cellular mechanisms*.

  2. Review Commons

    Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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    Referee #3

    Evidence, reproducibility and clarity

    In this manuscript the authors explore the mechanisms that metastatic cancer cells use to adapt their metabolism. The authors show that the growth of cancer cell lines is supported by uptake of ECM components in nutrient-starved conditions. The authors propose a very interesting mechanism in which the cells adapt their metabolism to ECM uptake as nutrient source via a PAK1-dependent macropinocytosis pathway which in turn increases tyrosine catabolism. Several key aspects of the authors complex hypothesis require further controls to fully support the authors ideas. As a disclaimer we do not feel qualified enough to comment on the metabolite experiments. Please find our detailed comments below.

    Major

    • The ECM mediated increase of cell growth under amino acid (AA) starvation is nicely shown In Fig.1 but the authors should include the full medium data from figure S1 in the graphs of Fig. 1 to enable the reader to evaluate the magnitude of rescue effect of the ECM components. The values should also be included in the results text. Also the authors only glutamine starve in Fig1&2 and then don't mention it again can the authors please include a sentence to explain why this experiment was dropped.
    • The evaluation of uptake pathways is very interesting. The focus on macropinocytosis is not entirely justified in our opinion looking at FigS4A. Caveolin1/2 and DNM1/3 seem to have strongest effect on uptake of Matrigel and not PAK1? Statements like "Since our data indicate that macropinocytosis is the main pathway controlling ECM endocytosis..." are not justified nor are they really needed in our opinion. Several pathways can be implicated in passive uptake.
    • The authors use FAK inhibition to evaluate the effect of focal adhesion signalling on their phenotypes and conclude that there is no connection between the observed increase of cell proliferation in presence of ECM and adhesion signalling. To make this assessment the authors need at the very least to show that their FAK inhibitor treatment at the used concentration results in changes in focal adhesions and the associated force transduction.
    • The pancreatic cancer data currently feels a bit like an afterthought. We suggest to remove this data from the manuscript. If this data is included we suggest the authors should expand this section and repeat key experiments of earlier figures.
    • Was the fetal bovine serum (FBS) and Horse Serum (HS) the authors use in their experiments tested for ECM components? The authors mention that the FBS for MDA231 cells was dialysed but not the HS.

    Minor comments:

    • Please can the authors provide experimental data directly comparing NF-CAM versus CAF-CDM on the same graph (Figure 1D-E)
    • Please can the authors give more insight to the use of 25% Plasmax to mimic starved tumor microenvironment. Is there previous research that suggests the nutrient values are representative of TME?
    • Fig3E Can the authors please include example images of the pS6 staining in the supplementary figures and explain "mTOR endosomal index" in figure legend.
    • Can the authors include a negative control for the mTORC1 localisation in Fig.3 (such as use of rapamycin/Torin)?
    • The PAK1 expression level blots in the knockdown experiments should be quantified from N=3
    • What is the FA index in Fig.5, explain how it is calculated. Why not use FA size alone?
    • Can the authors please use paragraphs on page 9 to improve readability.

    Significance

    The findings presented here will be very interesting to a broad range of researchers including the cancer, metabolism and wider cell biology communities. The Rainero lab has progressed the idea that ECM uptake supports cancer progression and the data presented here has the potential to significantly advance our understanding of the underlying cellular mechanisms.

  3. Review Commons

    Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

    Learn more at Review Commons

    Referee #2

    Evidence, reproducibility and clarity

    Please find enclosed my reviewing comments on the manuscript entitled "The extracellular matrix supports cancer cell growth under amino acid starvation by promoting tyrosine catabolism" by Nazemi et al.

    In this manuscript the group of Elena Romero and colleagues provides evidence that breast cancer cells, and pancreatic cancer cell, use matrix proteins degradation to feed their proliferative metabolic needs under amino acid starvation. Under this drastic condition, cancer cells use micropinocytosis to uptake matrix proteins, a process that requires mTORC1 activation and PAK1. Furthermore, a metabolomic study demonstrates that ECM-dependent cancer cell growth relies on tyrosine catabolism.

    Altogether, I found this study conceptually interesting and experimentally well performed. Experiments are well controlled and state-of-the-art technologies used in this manuscript make it a good candidate for publication. However, some aspects of the work need to be strengthen to reinforce the overall good quality of the manuscript, therefore, please find below some experimental propositions.

    1. Despite the reviewer proposition, I believe that the additional experiments using the PDAC cancer cell does not improve the quality of the manuscript. Instead, it brings confusion to me, since the relative addition is minor compare to what is demonstrated using breast cancer cells.
    2. To importantly improve the potential impact of this manuscript, I suggest to add in vivo data using either syngenic mice model of breast cancer or xenografted human breast cancer cells in nude mice. What would be the impact of micropinocytosis and tyrosine catabolism inhibition on cancer growth, in vivo, should be demonstrated? If possible, it may be interesting to demonstrate that this micropinocytosis may interfere with cancer evolution toward a metastatic phenotype using, for example, the PyMT-MMTV mice model of breast cancer development?
    3. Data obtained using cancer cells with different metastatic property suggest that the ability to use ECM to compensate for soluble nutrient starvation is acquired during cancer progression. To further demonstrate that it is the case, would it be possible that non metastatic breast cancer cells are not able to perform micropinocytosis? Is PAK1 overexpressed with increase cancer cells metastatic ability, without affecting invasive capacity in 3D spheroids? What would be the efficacy to promote the ECM-dependent growth under starvation following a mTORC1 activation or PAK1 activation in non-invasive cancer cells?
    4. The discrepancy of cancer cells proliferation under starvation condition between plastic and ECM-based supports could be explained by the massive difference of support rigidity. This is also probably the case between CDM made by normal fibroblast and CAF. It brings the question of studying the role of matrix stiffness in regard to micropinocytosis-dependent cancer cells growth. It would also explain why this process is link to aggressive cancer cell behaviour, as ECM goes stiffer with time in cancer development. It may not be the case, but the demonstration that mechanical cues from the ECM could regulate the micropinocytosis-dependent cancer cells growth under amino acid starvation could bring additional value to the manuscript.
    5. Along with this, it has been demonstrated that matrix rigidity regulates glutaminolysis in breast cancer, resulting in aspartate production and cancer cells proliferation. Is asparate production increase by micropinocytosis? Could you rescue cancer cells growth by aspartate supplementation?
    6. Data presented in Fig 1 and SF1 show that breast cancer cell lines growth in a comparable manner either they are cultured on plastic or on 3D ECM substrates in complete media. Again, on thick 3D substrates, in which the stiffness is lower compared to plastic, I would have thought that cancer cells would have grown slower. Could you please discuss this finding in regard to the literature? If you have the capacity to do so in your lab or in collaboration, would it be possible to measure the exact stiffness of the different matrix you use in this manuscript? Or using hydrogel, would it be possible to study the role of matrix stiffness in the ECM-dependent cancer cells growth under AA starvation? I would understand that this may be out of the scope of the present manuscript, but I again believe that such finding would reinforce the manuscript.
    7. In SF 3A-C, it is shown that ECM does not affect caspase-dependent cell death under AA starvation. Did you considered a non-caspase dependent cell death that may be triggered by AA starvation?
    8. In fig 5, it is shown that inhibition of Focal Adhesion Kinase (FAK) does not impair the ECM-dependent rescue of cancer cell growth under starvation. To further decipher the concept of adhesion dependent signalling, maybe the authors could also inhibit the Src kinase or ITG-beta1 activation?
    9. Minor comment, in F1B, it is written "AA free starvation" while in every others legend, it is written "AA starvation". I believe the "free" should be removed.

    Significance

    Altogether, I found this study conceptually interesting and experimentally well performed. Experiments are well controlled and state-of-the-art technologies used in this manuscript make it a good candidate for publication. However, some aspects of the work need to be strengthen to reinforce the overall good quality of the manuscript.

  4. Review Commons

    Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

    Learn more at Review Commons

    Referee #1

    Evidence, reproducibility and clarity

    Nazemi et al. show that the extracellular matrix (ECM) has a crucial role in sustaining the growth of invasive breast and pancreatic cells during nutrient deprivation. In particular, under amino acid starvation, cancer cells internalize ECM by macropinocytosis and activate phenylalanine and tyrosine catabolism, which in turn support cell growth in nutrient stress conditions.

    The paper is well written and the results shown are very interesting. The experimental plan is well designed to assess the hypothesis and the description of the methods is sufficiently detailed to reproduce the analyses, which are also characterized by appropriate internal controls. Finally, the data provided sustain the conclusions proposed by the authors.

    Major comment:

    Since the authors performed their experiments on invasive breast and pancreatic cancers and it has been noted that stress conditions could promote the escape of cancer cells from the site of origin (e.g., Jimenez and Goding, Cell Metabolism 2018; Manzano et al, EMBO Reports 2020), it would be interesting to evaluate how ECM internalization could have a role in sustaining the invasive abilities of cancer cells under amino acid starvation. Which is the impact of the inhibition of macropinocytosis and tyrosine catabolism on cell invasion? The authors could evaluate this aspect by in vitro 2D and 3D analysis. In addition, to strengthen the paper and give a stronger significance in terms of clinical translatability, it could be useful to implement the analysis of breast and pancreatic patients by publicly dataset evaluating for example free survival, disease free survival, overall survival and metastasis free survival.

    Minor Comment:

    The text and the figures are clear and accurate. The references cited support the hypothesis, rightly introduce the results and are appropriate for the discussion. However, the paragraph relative to figure 4 is a little confusing. Changing the order of the description of the results could be useful.

    Significance

    Based on my metabolic background in tumour aetiology and progression, I think that this study provides new insights into cancer metabolism knowledge, in particular on how the stroma may drive metabolic reprogramming of cancer cells sustaining cell growth in nutrient stress conditions. Together with other similar studies on the stromal non-cellular components, the data here shown can contribute to expand the knowledge on the factors that promote cancer metabolic plasticity, which is exploited from cancer cells to obtain advantages in terms of growth, survival and progression.

    In conclusion, I think that the results shown are new and the manuscript is well presented. Following the short revision process suggested, it will be eligible for a final publication in a medium-high impact factor journal.

  5. Version published to 10.1101/2021.06.09.447520v3 on bioRxiv
  6. ASAPbio crowd review

    This review reflects comments and contributions by Rachel Lau, Claudia Molina, Sónia Gomes Pereira, Pablo Ranea-Robles, Gregory Redpath, Mugda Sathe, Bathia Sonam and Sagar Varankar.

    In this study, Nazemi et al. investigated the role of the extracellular matrix in the metabolic adaptations of breast cancer cells under amino acid starvation. They found that ECM uptake and its lysosomal degradation provide amino acids that support cell growth. They also point to phenylalanine and tyrosine metabolism as an important pathway in this process, leading to the generation of the TCA cycle intermediate fumarate. This study fits well in the context of the broader literature showing that cancer cells upregulate endocytosis to continue proliferating in starvation conditions, and extends it well by identifying catabolism of ECM components as a part of this response and identifying precise metabolic pathways involved. This is a very interesting study, the data are solid and supportive of the claims. The study is well-written and the experiments are well contextualized, making the paper easy to read and understand.

    Some aspects in the preprint require further clarification, major and minor points are outlined below, followed by comments on specific parts of the paper.

    Major points

    • Experimentally, the endocytosis sections could be improved. Filipin is used as an endocytosis inhibitor, despite it being non-specific and not currently accepted as an endocytosis inhibitor. These experiments could be strengthened with well accepted endocytosis inhibitors, and especially macropinocytosis inhibitors to tie the study in with the current literature.
    • The in vitro data is promising, however, the authors could acknowledge in the discussion the limitation of not having in vivo data. The title should specify that the data have been obtained in vitro only.
    • It is not clear when the experiments are completed with Matrigel and Collagen I, or only one of them. Ideally, to make the work more consistent, the two of them could be used for every parameter measured.
    • Some IF experiments lack representative images associated with the quantification.
    • It is not clear why the inhibitor of focal adhesion is tested if there is no change in focal adhesion signaling in cells cultured with collagen-I/Matrigel/Cross-linked matrices.
    • It is not clear that the isotope labelling experiment data support the conclusion that "tyrosine derived from collagen I degradation could contribute to fumarate production." Data show a higher proportion of C13-labelled fumarate on plastic than on Collagen I.
    • Data with HPD and HPDL siRNA show a big effect on cell number and fumarate levels but only with a 10% decrease in protein level by IF. It's hard to reconcile the fact that a siRNA that only decreases 10% of the protein level causes such a big effect. The manuscript should introduce some nuance when describing these data. Experiments with HPD and/or HPDL KO cells would be more conclusive.

    Minor points

    • In the 6-8 days experiment, what was the signal intensity at day 1 when the experiment started? These baseline values may be important to understand this process.
    • It would be informative to include in Figure 1 the values of cells cultured in complete media shown in Fig. S1A-B, but the authors may prefer the current presentation.
    • Can some rationale be provided for using DRAQ5 in some assays in Fig. 1 and Hoescht3342 in others, given that the outcome measured is the same.
    • It may be worth discussing the fact that CDM generated from normal fibroblasts had a remarkable effect on cell growth under Gln starvation, even more than CDM generated from cancer-cells.
    • Colocalization of mTOR with a lysosomal marker would be a nice experiment to support the conclusions.
    • What is the explanation for the seemingly decreased uptake of collagen I upon Aa starvation when compared with complete media?
    • Effect of crosslinking treatment alone should be measured as a control. Does it affect cell number by itself?
    • Fig. S5A: May be worth mentioning in the Results or Discussion the fact that ECM uptake increased when cultured with MMP inhibitor.
    • Fig. 4C: The scale bars look different, the filipin image is lacking a scale bar.
    • Total FAK levels missing in Fig. 5A.
    • Fig. 6A - For each amino acid there is a fold change depending on whether cells were cultured on plastic or collagen I. Is the fold-change collagen I vs plastic? Then why display two fold change bars per amino acid? Are they being compared to the respective controls?
    • It’d be interesting to see if ECM is also incorporated on the MCF10CA1 cell line, and if this leads to an increase in phenylalanine/tyrosine metabolism, similar to that shown for MDA-MB-231 cells.
    • It might be interesting to explore the expression levels and profiles for HPD and HPDL in the MCF10 cell line, or discuss this in the context of publicly available data regarding any correlation with cancer progression.
    • Please add to the reporting of the statistical analyses. Is two-way ANOVA significant per se? Which were the factors compared?
    • Please report in the Methods section or figure legends how many cells were quantified in each experiment, and how many times the experiments were performed.
    • For reproducibility, recommend providing more details about the metabolomic pathway analysis.
    • There are some small spelling or grammar errors in the text.
    • The discussion may benefit from considerations on how ECM internalisation and degradation might alter cellular microenvironment and tissue properties, which might also facilitate cellular migration and invasiveness.

    Additional points

    ‘glutamine and full amino acid starvation' - It is possible to provide the rationale for selecting these conditions as opposed to essential amino acids which cannot be synthesized by human cells, hence need to be supplied to the cells externally.

    ‘the down-regulation of an enzyme in this pathway’- Recommend updating the fragment to clarify which pathway is mentioned and expand the HPDL abbreviation.

    ‘invasive breast cancer’- All the assays were done on MDA-MB-231 cells (with the exception of one assay that was done with MCF10 lines) and the results are occasionally extrapolated to breast cancer. Given the extent of heterogeneity within breast cancers, it is recommended to do a couple of experiments (such as in Fig 1) to ensure that similar ECM-supported growth is observed in more than one line. The results might be specific for this particular line, so accounting for subtype or genetic make up is necessary. Some of the lines to consider might be luminal (MCF7, T47D etc), additional TNBC lines (MDA-MB-468) etc.

    Results

    ‘CAF-CDM provided a more favourable environment for cancer cells’ growth compared to NF-CDM under amino acid deprivation’ - This is outside the scope of this paper, but it would be interesting to see what the differences are in protein composition between CAF-CDM and normal fibroblast CDM and whether these differences have been seen in the different studies referenced.

    Figure 1

    • The figures in general are a bit small, making them difficult to read in the printed version.
    • The colour code to differentiate amino acid starvation and glutamine starvation is good and the legend is in the same order as the line graphs to allow for quick comparison.
    • It is clear in Figure 1 E-F that there is a difference between growing the breast cancer cells on normal fibroblast and CAF cell derived matrices compared to plastic with glutamine starvation whilst only CAF cell derived matrices increased cell growth under amino acid deprivation compared to plastic. What is the rationale for measuring the cell growth by determining cell number by Hoechst whilst in the comparative experiment when growing cells on plastic, collagen or matrigel (Figure 1 A-D, G), DRAQ5 was used instead? Is this due to a technical aspect of the experiments or the availability of the reagents?
    • Figure 1A - Is there a difference between "AA starvation…" vs "AA free starvation…"? ‘2mg/ml collagen I (coll I) or (C-D) 3mg/ml Matrigel (Matr)'*- What is the rationale for using these concentrations? And why is it different for collagen I vs Matrigel? Is there optimization data available that informed the choice of concentrations?
    • Matrigel is a complex mixture of ECMs; is any particular component (for instance, collagen vs laminin), the key player for the observed growth benefit? This could be discussed in the discussion section.
    • ‘Signal intensity’ - As opposed to signal intensity, would it be possible to focus on a more physiological measure like cell growth or proliferation or viability? The intensity data could be part of the Supplementary figures.
    • ‘black dots’ - What do the other lighter colored dots represent?

    ‘This includes normal mammary epithelial cells (MCF10A), non-invasive ductal carcinoma in-situ breast cancer cells (MCF10A-DCIS) and metastatic breast cancer cells (MCF10CA1)’- It would be nice to see if the three cell lines had any growth differences when starved and grown in plastic. Additionally, what was the effect of NF-CDM and CAF-CDM on the growth of these three cell lines which are at different stages of cancer progression. Could these growth curves upon starvation be used for diagnostic purposes for patients?

    Figure 2

    • Suggest annotating n.s. for non-significant results to aid the interpretation of the graphs.
    • ‘The ability to use the ECM to promote cell growth was acquired during carcinoma progression’- Why is the starting intensity for Fig2A and C so different between different samples? If cell numbers had remained the same, would the results be the same or different?

    ‘which passed through DNA synthesis and mitosis’ - As supporting data, was cell cycle analysis performed for these samples? Examining whether starved cells are halted in a specific stage of the cell cycle would provide a great addition to the EdU data. ‘activated caspase-3/7’ - Was any other cell death assay tried?

    ‘Although the apoptosis rate increased between day three and day eight in both complete and amino acid-free media, and amino acid starvation resulted in increased cell death, there were no significant difference between the apoptosis rate on collagen I and Matrigel compared to plastic either at day 3 (Figure S3A) or day 8 (Figure S3B) in amino acid depleted media’- Recommend revising the sentence for length and clarity.

    Figure 3

    • Recommend showing immunofluorescence images, especially for panels C & D.
    • As a suggestion, comparing Figures 1 and 3 would prove to be really helpful in arriving at a conclusion regarding the effects of the ECM on cell growth and proliferation.
    • Figure 3B - The black dots represent the mean of individual experiments, but seem high compared to the other dots in the first two bars (complete media+ matrigel and complete media+ plastic). The black dots also appear slightly above 100% and it is not possible to have more than 100% EdU positive cells. Do the black dots show the means necessary? Do they hide some other dots?
    • Figure 3C-D -The y-axis is integrated intensity instead of average intensity. This is acceptable only in the situations where one knows that cell size is the same between different conditions. Since we are starving the cells, it may not be the case. Additionally, p-S6 should be technically normalised to the total S6 to rule out differences in merely changes in total S6 expression.

    ‘Collagen I and Matrigel rescued mTORC1 activity in starved cells’ - It may make it easier to follow for readers if each result heading refers to one figure. It seems like Fig 3 corresponding to this heading should contain the current Fig 3C-D (and any visualization data).

    ‘MDA-MB-231 cells’ - It would be helpful to provide the rationale for using different cell types for different assays.

    ‘ECM endocytosis’ - At this stage it is still not known whether there is endocytosis or not.

    ‘lysosomal degradation following internalisation’ - Using E64D as a lysosome inhibitor is good, but given that imaging experiments are possible based on what is presented in Fig4/5, verification of this result with co-localisation of ECM components and lysotracker or some other lysosomal marker would be good. In the images presented in the supplementary figures, the ECM localisation appears lysosomal so this result would be easy to get and visually compelling. Also, did these experiments inhibit cell growth? This would further suggest the importance of lysosomal degradation of ECM for cancer cell growth.

    ‘We then wanted to investigate whether the ECM-dependent growth of cancer cells under nutrient deficiency relied on ECM internalisation’ - Suggest to place this first in Fig 4. If EMC components are being degraded in the lysosome, they must be internalised by some endocytic mechanism. Assessing endocytosis and then looking at lysosomal targeting seems like the natural flow of events.

    ‘Interestingly, while the growth of MDA-MB-231 cells was not affected by matrix cross-linking in complete media’ - Is the cell migration affected by cross linking ECM under cell starvation conditions?

    ‘MMP inhibition did not affect cell growth under complete media or amino acid starvation on both plastic and collagen I' - The reduction does not seem so big; there may be another mechanism that explains the reduction in growth?

    ‘lipid raft-mediated endocytosis inhibitor filipin ‘- Filipin is a broad, non-specific endocytosis inhibitor. Filipin is really a cholesterol extracting/disrupting molecule, and cholesterol extraction from the plasma membrane has flow on effects on endocytosis. Filipin is not currently widely used as a bona fide endocytosis inhibitor. The filipin treatment was done for 3 days, after initial cholesterol extraction, it is unclear that filipin can continue to extract cholesterol for over three days. Further, "lipid raft mediated endocytosis" is not an accepted, specific endocytic pathway. The effect of filipin is also modest, so even if it is inhibiting a specific endocytic pathway, it is unlikely to be the predominant one mediating ECM uptake. To draw in an endocytic mechanism here to explain how ECM components are internalised, specific, bona fide endocytic pathways should be investigated. For example, as evidenced in papers cited in the introduction, macropinocytosis is an important endocytic pathway in nutrient scavenging by cancer cells. It would fit perfectly here - cells upregulate fluid phase engulfment by macropinocytosis, which results in increased ECM internalisation and preserves cell proliferation in cell starvation conditions. Alternatively, the filipin results could be replaced by more representative images of the various ECM uptake experiments with crosslinking.

    Some suggestions for studying bona fide endocytic components:

    1. Clathrin pathway can be blocked using pitstop or dynamic shRNA/siRNA. Dynamin inhibitors have off-target effects on actin cytoskeleton, they are not recommended.
    2. Caveolin: can be blocked using CSD peptide
    3. Macropinocytosis: A macropinocytosis inhibitor such as EIPA, RAC1 inhibitor or ctBP1 siRNA,
    4. CLIC/GEEC pathway: CDC42 inhibitor, GBF1 inhibitor or IRSp53 knockdown

    Figure 4

    • (A) 2mg/ml collagen I (coll I) or (B - Please show representative images for these experiments.
    • Panels C-D, ‘​​ECM uptake index was calculated with’ - Please report what the uptake index is.
    • Panels F-G, ‘pH-rodo labelled 0.5mg/ml Matrigel’ - Other panels in the figure use 3mg/ml of labelled Matrigel except for F-G where authors use 0.5mg/ml, can the context for this be outlined?

    ‘predominantly mediated by ECM internalisation’- To strengthen this point, stronger endocytic inhibition studies should be undertaken. As mentioned, filipin is not the most specific or widely accepted endocytosis inhibitor, and its inhibition of ECM uptake is modest in Fig 4F/G. Performing a broader inhibitor screen would support the conclusion that the effects seen in the study are predominantly mediated by ECM endocytosis. An excellent review to help select endocytosis inhibitors is here: https://www.nature.com/articles/s41565-021-00858-8/tables/1

    ‘Given the requirement for HPDL’- Does the MCF10 series of cell lines have variable HPDL expression which may correspond to its ability to grow on ECM under amino acid starvation? Maybe the expression of HPDL in MDA-MB-231 and the MCF10 series of cell lines can be assessed?

    Figure 6

    ‘Working model: invasive breast cancer cells internalised and degraded ECM components. This upregulated phenylalanine/tyrosine catabolism, leading to an increased production of fumarate, supporting cell proliferation under amino acid starvation' - Nice diagram to summarise the proposed mechanism. It would be worth clarifying where integrins come into play, as their uptake was not specifically investigated and the FAK studies ruled out integrin signalling as a factor?

    Discussion

    ‘We showed that the presence of ECM fully rescued [...] suggesting that the ECM supports cell growth via triggering distinct downstream signalling pathways in different cancer types.’ - Recommend revising the paragraph for clarity.

    ‘enodcytosis inhibitor filipin’ - As filipin is not an ideal endocytosis inhibitor, recommend revising the statement to "cholesterol extractor which can have inhibitory effects on endocytosis". Bona fide endocytosis inhibitors should be used to strengthen this part of the manuscript.

    Methods

    Please provide catalogue numbers for the reagents used.

    ‘Telomerase immortalised normal fibroblasts (NFs) and cancer associated fibroblasts (CAFs)’- Is it correct that both the normal fibroblasts and cancer-associated fibroblasts are breast tissue derived as opposed to the normal fibroblasts being from another tissue type (e.g skin)? Are these fibroblasts paired and from the same patient? Can the origin of the normal fibroblasts and cancer-associated fibroblasts be clarified?

    ‘150nM ON TARGET plus Human HPDL and HPD smart pool were added on each well’- It might be useful to provide the siRNA sequences.

  7. Version published to 10.1101/2021.06.09.447520v2 on bioRxiv
  8. Version published to 10.1101/2021.06.09.447520v1 on bioRxiv