scholarly journals Personalized Management of Advanced Kidney Cancer

2018 ◽  
pp. 330-341 ◽  
Author(s):  
Jeffrey Graham ◽  
Daniel Y. C. Heng ◽  
James Brugarolas ◽  
Ulka Vaishampayan
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Kidney Cancer ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Predictive Biomarkers ◽  
Treatment Selection ◽  
Great Success ◽  
Personalized Care ◽  
Oncogenic Pathways

The treatment of renal cell carcinoma represents one of the great success stories in translational cancer research, with the development of novel therapies targeting key oncogenic pathways. These include drugs that target the VEGF and mTOR pathways, as well as novel immuno-oncology agents. Despite the therapeutic advancements, there is a paucity of well-validated prognostic and predictive biomarkers in advanced kidney cancer. With a number of highly effective therapies available across multiple lines, it will become increasingly important to develop a more tailored approach to treatment selection. Prognostic clinical models, such the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model, are routinely used for prognostication in clinical practice. The IMDC model has demonstrated a predictive capability in the context of these treatments including immune checkpoint inhibition. A number of promising molecular markers and gene expression signatures are being explored as prognostic and predictive biomarkers, but none are ready to be widely used for treatment selection. In this review, we will explore the current landscape of personalized care in metastatic renal cell carcinoma. This will include a focus on both prognostic and predictive factors as well as clinical applications of biology in kidney cancer.

scholarly journals Efficacy and Safety of Nivolumab and Ipilimumab for Advanced or Metastatic Renal Cell Carcinoma: A Multicenter Retrospective Cohort Study

2021 ◽  
Vol 28 (2) ◽  
pp. 1402-1411
Author(s):  
Koji Iinuma ◽  
Koji Kameyama ◽  
Kei Kawada ◽  
Shota Fujimoto ◽  
Kimiaki Takagi ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Objective Response ◽  
Predictive Biomarkers ◽  
Progression Free Survival ◽  
Predictive Marker ◽  
Efficacy And Safety ◽  
Lymphocyte Ratio

We conducted a multicenter, retrospective study to evaluate the efficacy and safety of combination nivolumab plus ipilimumab (NIVO+IPI) in 35 patients with advanced or metastatic renal cell carcinoma (mRCC). In this study, we focused on patients who received NIVO+IPI and were stratified into intermediate- or poor-risk disease according to the International Metastatic Renal Cell Carcinoma Database Consortium model at five institutions in Japan. The primary endpoint was overall survival (OS). Secondary endpoints were disease control rate (DCR), best overall response (BOR), objective response rate (ORR), and progression-free survival (PFS). In addition, we evaluated the role of inflammatory cell ratios, namely neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), as predictive biomarkers in patients with mRCC. The median follow-up period was 1 year, and the 1-year OS rate was 95.8%. The ORR and DCR were 34.3% and 80.0%, respectively. According to BOR, four patients (11.4%) achieved complete response. According to NLR stratification, the 1-year PFS rates were 82.6% and 23.7% when the NLR was ≤4.6 and >4.6, respectively (p = 0.04). Based on PLR stratification, the 1-year PFS rates were 81.7% and 34.3% when the PLR was ≤188.1 and >188.1, respectively (p = 0.033). Although 71.4% of the patients experienced treatment-related adverse events (TRAEs) with NIVO+IPI, only four patients discontinued NIVO+IPI due to grade 3/4 TRAEs. Patients treated with NIVO+IPI as a first-line therapy for advanced or mRCC achieved relatively better oncological outcomes. Therefore, NIVO+IPI may have potential advantages and may lead to a treatment effect compared to those receiving targeted therapies. In addition, PLR >188.1 may be a useful predictive marker for mRCC patients who received NIVO+IPI.

A consensus prognostic factor model for survival in patients with metastatic renal cell carcinoma: A Kidney Cancer Association’s International Kidney Cancer Working Group (IKCWG) study

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 5109-5109 ◽  
Author(s):  
P. Royston ◽  
J. Bacik ◽  
P. Elson ◽  
J. B. Manola ◽  
M. Mazumdar
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Kidney Cancer ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Interleukin 2 ◽  
Multivariable Analysis ◽  
Prognostic Index ◽  
The United States ◽  
Model Complexity

5109 Background: Numerous well-designed retrospective studies of prognostic factors (pf) for survival (S) in metastatic renal cell carcinoma (mRCC) patients (pts) have been conducted since 1986. However, no single model for describing S in this population has been universally accepted. Methods: Authors of several existing prognostic indices, and others, formed the IKCWG to develop a single validated S model. The IKCWG has established a comprehensive database of previously reported clinical pf from 3748 previously untreated mRCC pts entered on institution review board approved clinical trials conducted by 11 centers in Europe and the United States from 1975–2002. Results: Median age at study entry was 58, 70% of pts were male, 89% had ECOG performance status (PS) 0 or 1; 75% had prior nephrectomy. 72%, 30%, and 19% of pts had lung, bone, and liver metastases (mets), respectively. 72% received interferon-a and/or interleukin-2 based treatments (tx); 25% were txd with chemotherapy/hormones only; 3% received other tx. 88% of pts have died; median S was 11.1 months (m). All examined factors except sex, age, and histology impacted S at p<.001 in univariable analysis. Multivariable analysis using a log-logistic model stratified by center and multivariable fractional polynomials was performed to identify independent predictors of S. Missing data were handled using multiple imputation methods. Using p=.0044 as the criterion for variable selection to avoid overly complex models, a model comprising tx, PS, number of met sites, interval from diagnosis to tx, and pre-tx hemoglobin, WBC, LDH, alkaline phosphatase and calcium was identified. The 25th and 75th percentiles of the prognostic index formed by multiplying each factor by its regression coefficient were used as cutpoints to form three risk (r) groups with median S times (SE) of: favorable r (n=937; 27.8 (0.4) m), intermediate r (n=1874; 11.4 (0.2) m), and poor r (n=937; 4.1 (0.1) m). Conclusions: 9 clinical factors can be used to model S in mRCC and form 3 distinct prognostic groups. Additional model building to determine if model complexity can be reduced further, validation in independent data and comparison to existing prognostic models are underway. No significant financial relationships to disclose.

A phase I study of BMS-936558 plus sunitinib or pazopanib in patients with metastatic renal cell carcinoma.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. TPS2614-TPS2614
Author(s):  
Hans J. Hammers ◽  
Brian I. Rini ◽  
Gary R. Hudes ◽  
Marc S. Ernstoff ◽  
Christian K. Kollmannsberger ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Phase I ◽  
Cell Carcinoma ◽  
Disease Progression ◽  
Metastatic Renal Cell Carcinoma ◽  
Dose Escalation ◽  
Renal Cell ◽  
Phase I Study ◽  
Predictive Biomarkers ◽  
Treatment Naïve

TPS2614 Background: Standard treatments for metastatic renal cell carcinoma (mRCC) block the vascular endothelial growth factor pathway (eg, sunitinib, pazopanib) or mammalian target of rapamycin pathway (e.g., temsirolimus, everolimus). However, most patients (pts) develop resistance and complete responses are rare. Upregulation of programmed death-1 (PD-1) in tumor infiltrating lymphoctyes, and its ligand PD-L1 in tumors, is associated with more aggressive disease and poor prognosis. Blocking the PD-1/PD-L1 interaction is a novel immunotherapeutic approach for mRCC. In preliminary results of a phase I trial, the anti-PD-1 monoclonal antibody BMS-936558 had antitumor activity in pts with advanced tumors, including objective responses (ORs) in 6 of 18 pts with mRCC. Here we describe a phase I study planned to evaluate the safety, tolerability, and maximum tolerated dose (MTD) of BMS-936558, when combined with sunitinib or pazopanib in pts with mRCC. Methods: This open-label study will have two parallel treatment arms (BMS-936558 plus sunitinib and BMS-936558 plus pazopanib) conducted in two parts (dose escalation and dose expansion). Pts must have received ≥1 prior systemic therapy to be eligible for dose escalation. Only treatment-naïve pts will be eligible for dose expansion. Up to 36 pts (18 per arm) will be treated in the dose-escalation phase. After determining the MTD of BMS-936558, treatment-naïve pts will be enrolled to expansion cohorts allowing 24 pts to be treated at the MTD of each arm. Each treatment cycle will be 6 weeks, with BMS-936558 dosed on Days 1 and 22 and sunitinib or pazopanib given according to product label. Adverse events will be graded according to NCI CTCAE v4.0. Disease will be assessed every 6 weeks for the first four assessments and then every 12 weeks until disease progression. Pts will be treated until unacceptable toxicity, disease progression, or withdrawal of consent. The safety profile in pts treated at the MTD will be used to determine the recommended phase II study dose of BMS-936558 in each combination arm. Secondary objectives will include OR rate and duration of response based on RECIST 1.1. Exploratory analyses will investigate predictive biomarkers of BMS-936558.

Identification and validation of predictive biomarkers (BM) for everolimus (EVE) in metastatic renal cell carcinoma: Analysis of 442 patients on RECORD-3.

2014 ◽  
Vol 32 (15_suppl) ◽  
pp. 4531-4531
Author(s):  
Martin Henner Voss ◽  
David Chen ◽  
Mahtab Marker ◽  
Mark Hamilton ◽  
Creton Kalfoglou ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Predictive Biomarkers

scholarly journals Treatment selection for first‐line metastatic renal cell carcinoma in Australia: Impact of new therapy options

2019 ◽  
Vol 15 (S10) ◽  
pp. 3-10 ◽  
Author(s):  
Andrew Schmidt ◽  
Arun Azad ◽  
Jeffrey Goh ◽  
Carole Harris ◽  
Anthony M. Joshua ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Treatment Selection ◽  
First Line ◽  
Therapy Options ◽  
New Therapy ◽  
Selection For

scholarly journals Exploratory Pilot Study of Circulating Biomarkers in Metastatic Renal Cell Carcinoma

Cancers ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2620
Author(s):  
Ilaria Grazia Zizzari ◽  
Chiara Napoletano ◽  
Alessandra Di Filippo ◽  
Andrea Botticelli ◽  
Alain Gelibter ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cell ◽  
Pilot Study ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Immune Checkpoint ◽  
Renal Cell ◽  
Clinical Decision Making ◽  
Predictive Biomarkers ◽  
T Cell Subsets

With the introduction of immune checkpoint inhibitors (ICIs) and next-generation vascular endothelial growth factor receptor–tyrosine kinase inhibitors (VEGFR–TKIs), the survival of patients with advanced renal cell carcinoma (RCC) has improved remarkably. However, not all patients have benefited from treatments, and to date, there are still no validated biomarkers that can be included in the therapeutic algorithm. Thus, the identification of predictive biomarkers is necessary to increase the number of responsive patients and to understand the underlying immunity. The clinical outcome of RCC patients is, in fact, associated with immune response. In this exploratory pilot study, we assessed the immune effect of TKI therapy in order to evaluate the immune status of metastatic renal cell carcinoma (mRCC) patients so that we could define a combination of immunological biomarkers relevant to improving patient outcomes. We profiled the circulating levels in 20 mRCC patients of exhausted/activated/regulatory T cell subsets through flow cytometry and of 14 immune checkpoint-related proteins and 20 inflammation cytokines/chemokines using multiplex Luminex assay, both at baseline and during TKI therapy. We identified the CD3+CD8+CD137+ and CD3+CD137+PD1+ T cell populations, as well as seven soluble immune molecules (i.e., IFNγ, sPDL2, sHVEM, sPD1, sGITR, sPDL1, and sCTLA4) associated with the clinical responses of mRCC patients, either modulated by TKI therapy or not. These results suggest an immunological profile of mRCC patients, which will help to improve clinical decision-making for RCC patients in terms of the best combination of strategies, as well as the optimal timing and therapeutic sequence.

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