Chordoma is a rare malignant bone tumor that mainly occurs in the sacrum and the clivus/skull base. Surgical resection is the treatment of choice for chordoma, but the local recurrence rate is high with unsatisfactory prognosis. Compared with other common tumors, there is not much research and individualized treatment for chordoma, partly due to the rarity of the disease and the lack of appropriate disease models, which delay the discovery of therapeutic strategies. Recent advances in modern techniques have enabled gaining a better understanding of a number of rare diseases, including chordoma. Since the beginning of the 21st century, various chordoma cell lines and animal models have been reported, which have partially revealed the intrinsic mechanisms of tumor initiation and progression with the use of next-generation sequencing (NGS) techniques. In this study, we performed a systematic overview of the chordoma models and related sequencing studies in a chronological manner, from the first patient-derived chordoma cell line (U-CH1) to diverse preclinical models such as the patient-derived organoid-based xenograft (PDX) and patient-derived organoid (PDO) models. The use of modern sequencing techniques has discovered mutations and expression signatures that are considered potential treatment targets, such as the expression of Brachyury and overactivated receptor tyrosine kinases (RTKs). Moreover, computational and bioinformatics techniques have made drug repositioning/repurposing and individualized high-throughput drug screening available. These advantages facilitate the research and development of comprehensive and personalized treatment strategies for indicated patients and will dramatically improve their prognoses in the near feature.

Background: Surgery remains the mainstay of treatment for breast cancer spinal metastasis (BCSM) to relieve symptoms and improve the quality of life of BCSM patients. Therefore, it is important to effectively predict the prognosis of patients to determine whether they can undergo surgical operation. However, the prevalent methods for prognosis evaluation lack specificity and sensitivity for indicated malignancies like breast cancer because they are built on a relatively small number of heterogeneous types of primary tumors. The aim of the present study was to explore a novel predictive model based on the clinical, pathological and blood parameters obtained from BCSM patients before they received surgical intervention. Methods: Altogether, 144 patients were included in this study. Univariate and multivariate analyses were performed to investigate the significance of preoperative parameters and identify independent factors for prognostic prediction of BCSM. A nomogram for survival prediction was then established and validated. Time-dependent ROC (TDROC) curves were graphed to evaluate the accuracy of the novel model vs other scoring systems including Tomita Score, revised Tokuhashi Score, modified Bauer Score and New England Spinal Metastasis Score. P values <0.05 were considered statistically significant. Results: Independent factors, including preoperative postmenopausal (P=0.034), visceral metastasis (P=0.021), preoperative Frankel Score (P=0.001), estrogen receptor status (P=0.014), platelet-to-lymphocyte ratio (P=0.012), lymphocyte-monocyte ratio (P<0.001) and albumin-globulin ratio (P=0.017), were selected into the nomogram model with the C-index of 0.834 (95% CI, 0.789-0.890). TDROC curves showed that the Changzheng Hospital (CZ) Score system had the best performance and exhibited the largest IAUC value in comparison with the other scoring systems. Conclusion: We constructed a nomogram model known as CZ Score based on the significant factors to predict the prognosis for BCSM patients. The result showed that CZ Score had a better value for prognostic evaluation and surgical decision-making as compared with the other scoring systems.