Use of Biomarkers to Predict Treatment Response and Modify Therapy

The National Institutes of Health Biomarkers Definitions Working Group defines a biomarker as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.” Biomarkers may be used to predict response and modify therapy, such as escalate, de-escalate, or change therapy. At the 5th annual CCA Summit meeting, Kristen Spencer, DO, MPH, discussed the utility of biomarkers to predict treatment response in biliary tract cancers (BTC).¹

Several molecular features have been identified in BTCs that may predict treatment responses or modify therapy. Yoon and colleagues reported that BTCs harboring mutations and chromosomal instability were associated with resistance to PD-1/PD-L1 blockade and low tumor-infiltrating lymphocyte density, indicating immune-suppressive tumor microenvironments.² In contrast, among 65 patients with IDH-mutated pathologically confirmed BTC who had received first-line palliative chemotherapy, overall response rate was significantly longer in patients who received gemcitabine-containing regimens than in those who received non–gemcitabine-containing regimens (39% vs 0%; P =.02).³ Serum carbohydrate antigen 19-9 (s-CA19-9) concentration was identified as a preoperative predictor of lymph node (LN) metastasis, with significantly higher concentrations in N1 versus N0 subgroups. Moreover, high s-CA19-9 (≥100 U/mL, 12 months vs <100 U/mL, 59 months) and LN status (N1, 16 months vs N0, 55 months) predicted worse survival post-hepatectomy.⁴ Strong evidence indicates that multiple point mutations in FGFR confer resistance to FGFR2 inhibitors, which may inform potential treatment changes.^5,6

These data support the concept that emerging biomarkers based on molecular features of BTCs may be useful to predict treatment response and further guide the management of advanced BTCs.

Sources:

1. Spencer K. Use of biomarkers to predict treatment response and modify therapy. Presented at: 5th Annual CCA Summit Meeting, October 19-21, 2023; Scottsdale, AZ.
2. Yoo JG, Kim MH, Jang M, et al. Molecular characterization of biliary tract cancer predicts chemotherapy and programmed death 1/programmed death-ligand 1 blockade responses. Hepatology. 2021;74(4):1914-1931.
3. Wintheiser G, Zemla T, Shi Q, et al. Isocitrate dehydrogenase-mutated cholangiocarcinoma: natural history and clinical outcomes. JCO Precis Oncol. 2022;6:e2100156.
4. Yamada T, Nakanishi Y, Okamura K, et al. Impact of serum carbohydrate antigen 19-9 level on prognosis and prediction of lymph node metastasis in patients with intrahepatic cholangiocarcinoma. J Gastroenterol Hepatol. Published online February 10, 2018.
5. Goyal L, Saha SK, Liu LY, et al. Polyclonal secondary FGFR2 mutations drive acquired resistance to FGFR inhibition in patients with FGFR2 fusion-positive cholangiocarcinoma. Cancer Discov. 2017;7(3):252-263.
6. Goya L, Shi L, Liu LY, et al. TAS-120 overcomes resistance to ATP-competitive FGFR inhibitors in patients with FGFR2 fusion-positive intrahepatic cholangiocarcinoma. Cancer Discov. 2019;9(8):1064-1079.