Cancer is as unique as the person fighting it. With the exception of a few biomarker-driven therapies, patients go through rounds of trial-and-error approaches to find the best treatment. Using ...patient-derived cell lines, we show that zebrafish larvae xenotransplants constitute a fast and highly sensitive in vivo model for differential therapy response, with resolution to reveal intratumor functional cancer heterogeneity. We screened international colorectal cancer therapeutic guidelines and determined distinct functional tumor behaviors (proliferation, metastasis, and angiogenesis) and differential sensitivities to standard therapy. We observed a general higher sensitivity to FOLFIRI 5-fluorouracil(FU)+irinotecan+folinic acid than to FOLFOX (5-FU+oxaliplatin+folinic acid), not only between isogenic tumors but also within the same tumor. We directly compared zebrafish xenografts with mouse xenografts and show that relative sensitivities obtained in zebrafish are maintained in the rodent model. Our data also illustrate how KRAS mutations can provide proliferation advantages in relation to KRASWT and how chemotherapy can unbalance this advantage, selecting for a minor clone resistant to chemotherapy. Zebrafish xenografts provide remarkable resolution to measure Cetuximab sensitivity. Finally, we demonstrate the feasibility of using primary patient samples to generate zebrafish patient-derived xenografts (zPDX) and provide proof-of-concept experiments that compare response to chemotherapy and biological therapies between patients and zPDX. Altogether, our results suggest that zebrafish larvae xenografts constitute a promising fast assay for precision medicine, bridging the gap between genotype and phenotype in an in vivo setting.
Cancer immunoediting is a dynamic process of crosstalk between tumor cells and the immune system. Herein, we explore the fast zebrafish xenograft model to investigate the innate immune contribution ...to this process. Using multiple breast and colorectal cancer cell lines and zAvatars, we find that some are cleared (regressors) while others engraft (progressors) in zebrafish xenografts. We focus on two human colorectal cancer cells derived from the same patient that show contrasting engraftment/clearance profiles. Using polyclonal xenografts to mimic intra-tumor heterogeneity, we demonstrate that SW620_progressors can block clearance of SW480_regressors. SW480_regressors recruit macrophages and neutrophils more efficiently than SW620_progressors; SW620_progressors however, modulate macrophages towards a pro-tumoral phenotype. Genetic and chemical suppression of myeloid cells indicates that macrophages and neutrophils play a crucial role in clearance. Single-cell-transcriptome analysis shows a fast subclonal selection, with clearance of regressor subclones associated with IFN/Notch signaling and escaper-expanded subclones with enrichment of IL10 pathway. Overall, our work opens the possibility of using zebrafish xenografts as living biomarkers of the tumor microenvironment.
Cell counting is a frequent task in medical research studies. However, it is often performed manually; thus, it is time-consuming and prone to human error. Even so, cell counting automation can be ...challenging to achieve, especially when dealing with crowded scenes and overlapping cells, assuming different shapes and sizes. In this paper, we introduce a deep learning-based cell detection and quantification methodology to automate the cell counting process in the zebrafish xenograft cancer model, an innovative technique for studying tumor biology and for personalizing medicine. First, we implemented a fine-tuned architecture based on the Faster R-CNN using the Inception ResNet V2 feature extractor. Second, we performed several adjustments to optimize the process, paying attention to constraints such as the presence of overlapped cells, the high number of objects to detect, the heterogeneity of the cells' size and shape, and the small size of the data set. This method resulted in a median error of approximately 1% of the total number of cell units. These results demonstrate the potential of our novel approach for quantifying cells in poorly labeled images. Compared to traditional Faster R-CNN, our method improved the average precision from 71% to 85% on the studied data set.
Cancer frequency and prevalence have been increasing in the past decades, with devastating impacts on patients and their families. Despite the great advances in targeted approaches, there is still a ...lack of methods to predict individual patient responses, and therefore treatments are tailored according to average response rates. "Omics" approaches are used for patient stratification and choice of therapeutic options towards a more precise medicine. These methods, however, do not consider all genetic and non-genetic dynamic interactions that occur upon drug treatment. Therefore, the need to directly challenge patient cells in a personalized manner remains. The present review addresses the state of the art of patient-derived
and
models, from organoids to mouse and zebrafish Avatars. The predictive power of each model based on the retrospective correlation with the patient clinical outcome will be considered. Finally, the review is focused on the emerging zebrafish Avatars and their unique characteristics allowing a fast analysis of local and systemic effects of drug treatments at the single-cell level. We also address the technical challenges that the field has yet to overcome.
Abstract Cancer patients often undergo rounds of trial-and-error to find the most effective treatment because there is no test in the clinical practice for predicting therapy response. Here, we ...conduct a clinical study to validate the zebrafish patient-derived xenograft model (zAvatar) as a fast predictive platform for personalized treatment in colorectal cancer. zAvatars are generated with patient tumor cells, treated exactly with the same therapy as their corresponding patient and analyzed at single-cell resolution. By individually comparing the clinical responses of 55 patients with their zAvatar-test, we develop a decision tree model integrating tumor stage, zAvatar-apoptosis, and zAvatar-metastatic potential. This model accurately forecasts patient progression with 91% accuracy. Importantly, patients with a sensitive zAvatar-test exhibit longer progression-free survival compared to those with a resistant test. We propose the zAvatar-test as a rapid approach to guide clinical decisions, optimizing treatment options and improving the survival of cancer patients.
Poly (ADP-ribose) polymerase (PARP) inhibition in BRCA-mutated cells results in an incapacity to repair DNA damage, leading to cell death caused by synthetic lethality. Within the treatment options ...for advanced triple negative breast cancer, the PARP inhibitor olaparib is only given to patients with BRCA1/2 mutations. However, these patients may show resistance to this drug and BRCA1/2 wild-type tumors can show a striking sensitivity, making BRCA status a poor biomarker for treatment choice. Aiming to investigate if the zebrafish model can discriminate sensitivities to olaparib, we developed zebrafish xenografts with different BRCA status and measured tumor response to treatment, as well as its impact on angiogenesis and metastasis. When challenged with olaparib, xenografts revealed sensitivity phenotypes independent of BRCA. Moreover, its combination with ionizing radiation increased the cytotoxic effects, showing potential as a combinatorial regimen. In conclusion, we show that the zebrafish xenograft model may be used as a sensitivity profiling platform for olaparib in monotherapy or in combinatorial regimens. Hence, this model presents as a promising option for the future establishment of patient-derived xenografts for personalized medicine approaches beyond BRCA status.
Somites are formed from the presomitic mesoderm (PSM) and give rise to the axial skeleton and skeletal muscles. The PSM is dynamic; somites are generated at the anterior end, while the posterior end ...is continually renewed with new cells entering from the tailbud progenitor region. Which genes control the conversion of tailbud progenitors into PSM and how is this process coordinated with cell movement? Using loss- and gain-of-function experiments and heat-shock transgenics we show in zebrafish that the transcription factor Mesogenin 1 (Msgn1), acting with Spadetail (Spt), has a central role. Msgn1 allows progression of the PSM differentiation program by switching off the progenitor maintenance genes ntl, wnt3a, wnt8 and fgf8 in the future PSM cells as they exit from the tailbud, and subsequently induces expression of PSM markers such as tbx24. msgn1 is itself positively regulated by Ntl/Wnt/Fgf, creating a negative-feedback loop that might be crucial to regulate homeostasis of the progenitor population until somitogenesis ends. Msgn1 drives not only the changes in gene expression in the nascent PSM cells but also the movements by which they stream out of the tailbud into the PSM. Loss of Msgn1 reduces the flux of cells out of the tailbud, producing smaller somites and an enlarged tailbud, and, by delaying exhaustion of the progenitor population, results in supernumerary tail somites. Through its combined effects on gene expression and cell movement, Msgn1 (with Spt) plays a key role both in genesis of the paraxial mesoderm and in maintenance of the progenitor population from which it derives.
(1) Background: Relapsed HGSOC with ascites and/or pleural effusion is a poor-prognostic population and poorly represented in clinical studies. We questioned if these patients are worth treating. In ...other words, if these patients received the most effective treatment, would it change the course of this disease? To our knowledge this is the first real-life study to evaluate this question in this low-survival population. (2) Methods: To tackle this question we performed a retrospective, multi-centric, real-life study, that reviewed relapsed HGSOC patients with ascites and/or pleural effusion. Our rationale was to compare the OS of two groups of patients: responders, i.e., patients who had an imagological response to treatment (complete/partial response/stable disease, RECIST criteria) versus non-responders (no response/progression upon treatment). We evaluated the predictive value of clinical variables that are available in a real-life setting (e.g., staging, chemotherapy, surgery, platinum-sensitivity). Multivariate logistic regression and survival analysis was conducted. A two-step cluster analysis SPSS tool was used for subgroup analysis. Platinum sensitivity/resistance was also analyzed, as well as multivariate and cluster analysis. (3) Results: We included 57 patients, 41.4% first line responders and 59.6% non-responders. The median OS of responders was 23 months versus 8 months in non-responders (
< 0.001). This difference was verified in platinum-sensitive (mOS 28 months vs. 8 months,
< 0.001) and platinum-resistant populations (mOS 16 months vs. 7 months,
< 0.001). Thirty-one patients reached the second line, of which only 10.3% responded to treatment. Three patients out of thirty-one who did not respond in the first line of relapse, responded in the second line. In the second line, the mOS for the responders' group vs. non-responders was 31 months versus 13 months (
= 0.02). The two step cluster analysis tool found two different subgroups with different prognoses based on overall response rate, according to consolidation chemotherapy, neoadjuvant chemotherapy, FIGO staging and surgical treatment. Cluster analysis showed that even patients with standard clinical and treatment variables associated with poor prognosis might achieve treatment response (the opposite being also true). (4) Conclusions: Our data clearly show that relapsed HGSOC patients benefit from treatment. If given an effective treatment upfront, this can lead to a ~3 times increase in mOS for these patients. Moreover, this was irrespective of patient disease and treatment characteristics. Our results highlight the urgent need for a sensitivity test to tailor treatments and improve efficacy rates in a personalized manner.
Malfunctions of circadian clock trigger abnormal cellular processes and influence tumorigenesis. Using an
and
xenograft model, we show that circadian clock disruption via the downregulation of the ...core-clock genes
,
, and
impacts the circadian phenotype of
,
, and
, and affects proliferation, apoptosis, and cell migration. In particular, both our
and
results suggest an impairment of cell motility and a reduction in micrometastasis formation upon knockdown of
, accompanied by altered expression levels of
and
. Interestingly we show that differential proliferation and reduced tumour growth
may be due to the additional influence of the host-clock and/or to the 3D tumour architecture. Our results raise new questions concerning host-tumour interaction and show that core-clock genes are involved in key cancer properties, including the regulation of cell migration and invasion by
in zebrafish xenografts.
Whereas the role of neoadjuvant radiotherapy in rectal cancer is well-established, the ability to discriminate between radioresistant and radiosensitive tumors before starting treatment is still a ...crucial unmet need. Here we aimed to develop an in vivo test to directly challenge living cancer cells to radiotherapy, using zebrafish xenografts.
We generated zebrafish xenografts using colorectal cancer cell lines and patient biopsies without in vitro passaging, and developed a fast radiotherapy protocol consisting of a single dose of 25 Gy. As readouts of the impact of radiotherapy we analyzed proliferation, apoptosis, tumor size and DNA damage.
By directly comparing isogenic cells that only differ in the KRASG13D allele, we show that it is possible to distinguish radiosensitive from radioresistant tumors in zebrafish xenografts, even in polyclonal tumors, in just 4 days. Most importantly, we performed proof-of-concept experiments using primary rectum biopsies, where clinical response to neoadjuvant chemoradiotherapy correlates with induction of apoptosis in their matching zebrafish Patient-Derived Xenografts-Avatars.
Our work opens the possibility to predict tumor responses to radiotherapy using the zebrafish Avatar model, sparing valuable therapeutic time and unnecessary toxicity.
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