BMC Medical Genomics (Sep 2022)

Establishment and genetically characterization of patient-derived xenograft models of cervical cancer

  • Shuangwei Zou,
  • Miaomiao Ye,
  • Jian-an Zhang,
  • Huihui Ji,
  • Yijie Chen,
  • Xueqiong Zhu

DOI
https://doi.org/10.1186/s12920-022-01342-5
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 11

Abstract

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Abstract Purpose Patient-derived xenograft (PDX) models were established to reproduce the clinical situation of original cancers and have increasingly been applied to preclinical cancer research. Our study was designed to establish and genetically characterize cervical cancer PDX models. Methods A total of 91 fresh fragments obtained from 22 surgically resected cervical cancer tissues were subcutaneously engrafted into female NOD-SCID mice. Hematoxylin and eosin (H&E) staining was performed to assess whether the established PDX models conserved the histological features of original patient cervical cancer tissues. Moreover, a Venn diagram was applied to display the overlap of all mutations detected in whole-genome sequencing (WGS) data from patient original cervical cancer (F0) and F2-, F3-PDX models. The whole exome sequencing (WES) and the “maftools” package were applied to determine the somatic mutations among primary cervical cancers and the established PDX models. Results Our study successfully developed a panel of cervical cancer PDX models and the latency time of cervical cancer PDX model establishment was variable with a progressive decrease as the passage number increased, with a mean time to initial growth of 94.71 days in F1 engraftment to 40.65 days in F3 engraftment. Moreover, the cervical cancer PDX models preserved the histological features of their original cervical cancer. WGS revealed that the genome of original cervical cancer was preserved with high fidelity in cervical cancer PDX models throughout the xenografting and passaging process. Furthermore, WES demonstrated that the cervical cancer PDX models maintained the majority somatic mutations of original cervical cancer, of which the KMT2D, LRP1B, NAV3, TP53, FAT1, MKI67 and PKHD1L1 genes were identified as the most frequently mutated genes. Conclusions The cervical cancer PDX models preserved the histologic and genetic characteristics of their original cervical cancer, which helped to gain a deeper insight into the genetic alterations and lay a foundation for further investigation of the molecular targeted therapy of cervical cancer.

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