Tumorspheres as In Vitro Model for Identifying Predictive Chemoresistance and Tumor Aggressiveness Biomarkers in Breast and Colorectal Cancer

Abstract

Chemoresistance remains a major challenge in the treatment of breast and colorectal cancer. For this reason, finding reliable predictive biomarkers of response to chemotherapy has become a significant research focus in recent years. However, validating in vitro results may be problematic due to the outcome heterogeneity. In this study, we evaluate the use of tumorspheres as an in vitro model for validating biomarkers of chemoresistance in breast and colorectal cancer. Our investigation highlights the crucial role of inflammation-related pathways in modulating the response to chemotherapy. Using in silico approaches, we identified specific markers elevated in responders versus non-responders patients. These markers were consistently higher in three-dimensional (3D) tumorsphere models compared to traditional adherent cell culture models. Furthermore, the number of tumorspheres from breast and colorectal cancer cells increased in response to cisplatin and oxaliplatin treatment, respectively, whereas cell viability decreased in adherent cell culture. This differential response underscores the importance of the 3D tumorsphere model in mimicking the tumor microenvironment more accurately than adherent cell culture. The enhanced chemoresistance observed in the 3D tumorspheres model and their correlation of data with the in silico study suggest that 3D culture models are a better option to approach the in vivo model and also to validate in silico data. Our findings indicate that tumorspheres are an ideal model for validating chemoresistance biomarkers and exploring the interplay between inflammation and chemoresistance in breast and colon cancer.

Keywords: breast cancer and colorectal cancer; chemoresistance; inflammation; tumorspheres.

Figure 1

Identification of signaling pathways alterations in responders vs. non-responders breast (A) and colorectal (B) cancer patients. Pathways with FDR value ≤ 0.05 are represented. Enrichment plots of matched KEGG pathways are represented, respectively.

Figure 2

mRNA expression levels of inflammation-related markers in MCF7 (A) and SW620 (B) tumorspheres compared to a two-dimensional (2D) culture. Statistical significance was analyzed by Student’s t-test and set at * p ≤ 0.05.

Figure 3

Gene expression of inflammation markers in breast cancer (A) and colorectal cancer (B) patients according to response to chemotherapy treatment. Statistical significance was analyzed by Student’s t-test and set at p ≤ 0.05 (highlighted values).

Figure 4

Viability and tumorsphere formation efficiency of MCF7 (A–D) and SW620 (E–H) cell lines after Cisplatin/Oxaliplatin treatment, respectively. Statistical significance compared to 0 µM (Cisplatin or Oxaliplatin) was analyzed by Student’s t-test and set at * p ≤ 0.05.