Pazopanib as Second-line Antiangiogenic Treatment in Metastatic Renal Cell Carcinoma After Tyrosine Kinase Inhibitor (TKI) Failure: A Phase 2 Trial Exploring Immune-related Biomarkers for Testing in the Post-immunotherapy/TKI Era

Comprehensive Systematic Review of Biomarkers in Metastatic Renal Cell Carcinoma: Predictors, Prognostics, and Therapeutic Monitoring

BACKGROUND

Challenges remain in determining the most effective treatment strategies and identifying patients who would benefit from adjuvant or neoadjuvant therapy in renal cell carcinoma. The objective of this review is to provide a comprehensive overview of biomarkers in metastatic renal cell carcinoma (mRCC) and their utility in prediction of treatment response, prognosis, and therapeutic monitoring in patients receiving systemic therapy for metastatic disease.

METHODS

A systematic literature search was conducted using the PubMed database for relevant studies published between January 2017 and December 2022. The search focused on biomarkers associated with mRCC and their relationship to immune checkpoint inhibitors, targeted therapy, and VEGF inhibitors in the adjuvant, neoadjuvant, and metastatic settings.

RESULTS

The review identified various biomarkers with predictive, prognostic, and therapeutic monitoring potential in mRCC. The review also discussed the challenges associated with anti-angiogenic and immune-checkpoint monotherapy trials and highlighted the need for personalized therapy based on molecular signatures.

CONCLUSION

This comprehensive review provides valuable insights into the landscape of biomarkers in mRCC and their potential applications in prediction of treatment response, prognosis, and therapeutic monitoring. The findings underscore the importance of incorporating biomarker assessment into clinical practice to guide treatment decisions and improve patient outcomes in mRCC.

Identification and validation of a novel cuproptosis-related lncRNA gene signature to predict prognosis and immune response in bladder cancer

PURPOSE

Bladder cancer (BCa) is one of the most common malignant tumors in the urogenital system, characterized by the high recurrence rate, mortality rate and poor prognosis. Based on cuproptosis-related long noncoding RNAs (CRLs), this study set out to create a prediction signature to evaluate the prognosis of patients with BCa.

METHODS

RNA-seq data including CRLs and related clinicopathological data were gathered from The Cancer Genome Atlas (TCGA) database (n = 428). The predictive signature was constructed after correlation analysis. Subsequently, relying on the analyzed data from the TCGA database and our sample collection, we examined and verified the connections between CRLs model and important indexes included prognosis, route and functional enrichment, tumor immune evasion, tumor mutation, and treatment sensitivity.

RESULTS

Patients in the high-risk group had lower overall survival (OS) than that of low-risk group. Compared with clinicopathological variables, CRLs features have better predictive value according to receiver operating characteristic (ROC) curve. The expression level of CRLs was highly associated with the tumor progress, tumor microenvironment and tumor immune escape. Additionally, we identified that the mutation of TP53, TTN, KMT2D and MUC16 gene were founded in patients with BCa. Lapatinib, pazopanib, saracatinib, gemcitabine, paclitaxel and palenolactone had good antitumor effects for BCa patients in the high-risk group (all P < 0.001).

CONCLUSION

This study revealed the effects of CRLs on BCa and further established CRLs model, which can be used in clinic for predicting prognosis, immunological response and treatment sensitivity inpatient with BCa.

Median time to progression with TKI-based therapy after failure of immuno-oncology therapy in metastatic kidney cancer: A systematic review and meta-analysis

BACKGROUND

The efficacy of tyrosine kinase inhibitor (TKI)-based therapy after previous immuno-oncology therapy (IO) failure has been addressed before. However, summary efficacy estimates have never been generated in these reports. We addressed this void.

MATERIAL AND METHODS

We systematically examined TKI efficacy after IO-failure and generated weighted median progression-free survival (PFS) estimates for Pazopanib, Axitinib, Cabozantinib, Sunitinib. A systematic review according to PRISMA was conducted. PubMed and abstracts were queried. Only studies proving median PFS were included. Weighted medians were computed for each TKI alternative.

RESULTS

Of 245 articles, nine eligible studies were included in the current study with 952 analysed patients. Weighted PFS medians after any previous IO-based therapy were respectively 13.7 (range from 4.6 to 24.4), 8.1 (range from 4.7 to 13.2), 8.5 (range from 4.7 to 15.2) and 6.9 months (range from 2.9 to 11.6) for Pazopanib, Axitinib, Cabozantinib, Sunitinib. Specific second-line weighted PFS median was 14.8 months (range from 5.6 to 24.4), 10.1 months (range from 6.4 to 13.2), 8.7 months (range from 4.7 to 15.2) and 6.0 months (range from 2.9 to 8.0) for Pazopanib, Axitinib, Cabozantinib, Sunitinib, respectively, after first-line IO.

CONCLUSION

Pazopanib results in the longest weighted median PFS, after previous IO-failure, regardless of treatment line, as well as in specific second-line, post-first-line IO failure settings. Pending novel studies, Pazopanib appears to represent the most promising treatment option after prior IO.

Hyperprogression to a dual immune blockade followed by subsequent response with cabozantinib in metastatic poor-risk clear cell renal cell carcinoma with NOTCH mutation

Currently, more and more patients receive first-line treatment with immunotherapy combinations and not all patients respond in metastatic renal cell carcinoma. After IO-IO progression, we don’t have a standard of treatment because it is not available prospective data on this setting. We present the case of a patient with metastatic renal cell carcinoma who suffered hyperprogression with IO-IO combination in first line. Second line with cabozantinib results in a deep response of the disease. We performed a Foundation One testing to the patient which showed a mutation in NOTCH. The molecular mechanism to explain patient’s response, it’s the probably crosstalk between MET and NOTCH pathway. Nowadays, there is not clear the subsequent treatment in those patients who progress to IO-IO first line. More efforts in biomarkers development should be made to better selection of patients treatment along the disease.