Browsing by Subject "Predictive biomarker"

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    The Identification of Immunological Biomarkers in Kidney Cancers
    (Frontiers Media, 2018-11-02) Lopez-Beltran, Antonio; Henriques, Vanessa; Cimadamore, Alessia; Santoni, Matteo; Cheng, Liang; Gevaert, Thomas; Blanca, Ana; Massari, Francesco; Scarpelli, Marina; Montironi, Rodolfo; Pathology and Laboratory Medicine, School of Medicine
    The recent approval of several agents have revolutionized the scenario of therapeutic management of metastatic renal cell carcinoma (RCC) allowing us to reach important clinical end points with extended patients' survival. Actually, every new drug approved has represented an important step forward to the improvement of patient's survival. On the other hand, we now understand that RCC includes a large group of tumor entities, each of them with different genetic and mutational alterations, but also showing different clinical behavior; a reason behind the needs of subtype specific personalized approach to therapy of RCC. Immunotherapy is gradually becoming a key factor in the therapeutic algorithm for patients with locally advanced or metastatic RCC. Due to the combination of potent treatment success and potentially deadly adverse effects from immune checkpoint inhibitors (ICI), gathering prognostic and predictive information about FDA-indicated tumors seems to be prudent. Robust and reliable biomarkers are crucial for patient's selection of treatments with immunomodulatory drugs. PD-L1 expression is a poor prognostic factor and predictive of better responses from both PD-1 and PD-L1 inhibitors in a variety of tumor types including RCC. Each FDA approved PD-1/PD-L1 drug is paired with a PD-L1 Immunohistochemistry (IHC) assay. Thus, there is need for improved knowledge and application of PD-1/PD-L1 IHC biomarkers in daily practice. IHC staining appears in membranous fashion. The atezolizumab approved IHC assay is unique in that only immune cell staining is quantified for the use of this assay in RCC. A single biomarker for patient selection may not be feasible, given that immune responses are dynamic and evolve over time. Biomarker development for ICI drugs will likely require integration of multiple biologic components like PD-L1 expression, TILs and mutational load. New methodological approaches based on digital pathology may be relevant since they will allow recognition of the biomarker and to objectively quantitate its expression, and therefore might produce objective and reproducible cut-off assessment. Multidisciplinary approach is very much needed to fully develop the current and future value of ICI in clinical practice.
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    Plasma Protein Biomarkers in Advanced or Metastatic Colorectal Cancer Patients Receiving Chemotherapy With Bevacizumab or Cetuximab: Results from CALGB 80405 (Alliance)
    (American Association for Cancer Research, 2022) Nixon, Andrew B.; Sibley, Alexander B.; Liu, Yingmiao; Hatch, Ace J.; Jiang, Chen; Mulkey, Flora; Starr, Mark D.; Brady, John C.; Niedzwiecki, Donna; Venook, Alan P.; Baez-Diaz, Luis; Lenz, Heinz-Josef; O’Neil, Bert H.; Innocenti, Federico; Meyerhardt, Jeffrey A.; O’Reilly, Eileen M.; Owzar, Kouros; Hurwitz, Herbert I.; Medicine, School of Medicine
    Purpose: CALGB 80405 compared the combination of first-line chemotherapy with cetuximab or bevacizumab in the treatment of advanced or metastatic colorectal cancer (mCRC). Although similar clinical outcomes were observed in the cetuximab-chemotherapy group and the bevacizumab-chemotherapy group, biomarkers could identify patients deriving more benefit from either biologic agent. Patients and methods: In this exploratory analysis, the Angiome, a panel of 24 soluble protein biomarkers were measured in baseline plasma samples in CALGB 80405. Prognostic biomarkers were determined using univariate Cox proportional hazards models. Predictive biomarkers were identified using multivariable Cox regression models including interaction between biomarker level and treatment. Results: In the total population, high plasma levels of Ang-2, CD73, HGF, ICAM-1, IL6, OPN, TIMP-1, TSP-2, VCAM-1, and VEGF-R3 were identified as prognostic of worse progression-free survival (PFS) and overall survival (OS). PlGF was identified as predictive of lack of PFS benefit from bevacizumab [bevacizumab HR, 1.51; 95% confidence interval (CI), 1.10-2.06; cetuximab HR, 0.94; 95% CI, 0.71-1.25; Pinteraction = 0.0298] in the combined FOLFIRI/FOLFOX regimens. High levels of VEGF-D were predictive of lack of PFS benefit from bevacizumab in patients receiving FOLFOX regimen only (FOLFOX/bevacizumab HR, 1.70; 95% CI, 1.19-2.42; FOLFOX/cetuximab HR, 0.92; 95% CI, 0.68-1.24; Pinteraction = 0.0097). Conclusions: In this exploratory, hypothesis-generating analysis, the Angiome identified multiple prognostic biomarkers and two potential predictive biomarkers for patients with mCRC enrolled in CALGB 80405. PlGF and VEGF-D predicted lack of benefit from bevacizumab in a chemo-dependent manner.