Detection of circulating tumor DNA in patients with metastatic clear cell renal cell carcinoma.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e16105-e16105 ◽  
Author(s):  
Lucia Nappi ◽  
Jack Bacon ◽  
Matti Annala ◽  
Maryam Soleimani ◽  
Jean-Michel Lavoie ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Predictive Biomarkers ◽  
Germline Mutations ◽  
Circulating Tumor Dna ◽  
Ffpe Tissue ◽  
Cell Renal Cell Carcinoma ◽  
Tumor Dna

e16105 Background: Clear cell renal cell carcinoma (ccRCC) represents the most common presentation of kidney cancer. Patient outcomes have significantly improved with the approval of several targeted agents over the past decade. However, the lack of predictive biomarkers has hampered treatment optimization. Circulating tumor DNA (ctDNA) has emerged as an effective, minimally-invasive alternative to tissue for profiling the tumor genome in other tumors. Methods: Blood samples were collected from patients (pts) with metastatic ccRCC for next-generation sequencing of cell free DNA and germline DNA. Targeted sequencing was performed using the Roche Human Oncology Design panel of 981 genes to a median depth of 937x unique reads. Matched FFPE tissue was available from 14 pts and profiled using the same assay. Results: Samples from 52 metastatic, treatment-naïve pts were analyzed. Germline mutations were detected in 6/52 (11%) of the pts with the most frequent abnormalities affecting ATM, PALB2, RAD51D, CHEK2, BRCA1. Median ctDNA fraction was 3.9% (2-40%) with a median of 2 mutations/pt. Somatic mutations were detected in 29/52 (56%) of the samples; of those, 15/29 (51%) of pts harbored RCC-related genes mutations, 3/29 (10%) non-coding mutations and 10/29 (34%) alterations in non RCC-associated genes. Median variant allele frequency was 1.9% (1-22%). Consistent with tissue-based reports, VHL, BAP1, PBRM1, and TP53 were the most frequently altered genes. Lastly, 50% of the patient-matched FFPE tissue samples shared a fully concordant mutation profile. Conclusions: We confirmed a high prevalence of germline mutations in pts with ccRCC. The rate of ctDNA detection in metastatic ccRCC appears to be lower than in other metastatic solid tumors. Furthermore, it is not yet clear whether all the detected somatic alterations are strictly ccRCC-ctDNA dependent. Nevertheless, a quarter of pts exhibited clinically-informative ccRCC associated alterations in their liquid biopsy. These findings suggest that ctDNA is a promising tool for genomic profiling in a subset of patients with metastatic ccRCC.

Comparative genomic profiling from tumor tissue and circulating tumor DNA (ctDNA) in 111 patients (Pts) with metastatic clear cell renal cell carcinoma.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 4565-4565 ◽  
Author(s):  
Ritesh Kotecha ◽  
Erika Gedvilaite ◽  
Samuel J. Murray ◽  
Robert J. Motzer ◽  
Dana Tsui ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Circulating Tumor Dna ◽  
Large Cohort ◽  
Cell Renal Cell Carcinoma ◽  
Primary Tumors ◽  
Primary Tissue ◽  
Tumor Dna

4565 Background: Circulating tumor DNA (ctDNA) assessment is a non-invasive approach for genomic interrogation of solid tumors. As a novel tool, key benchmarks for applications in metastatic clear cell renal cell carcinoma (mccRCC) are yet to be determined. To understand the utility of ctDNA, we performed a large cohort analysis using a comparative genomics approach integrating matched primary tissue and ctDNA genomic data. Methods: Pts with prior tumor mutational profiles generated via next generation sequencing (NGS) from nephrectomy or metastatic specimens underwent single-time point plasma collection. Targeted NGS sequencing with MSK-IMPACT was performed on tumor and ctDNA with subsequent bi-directional cross genotyping using Waltz 2.0. All pts had matched germline comparison from peripheral blood; clinical data was extracted from medical record. Liberal (1-2 reads) and stringent (≥3 reads) filters were applied, with a cut-off of < 30% allele frequency to remove germline mutations. Results: 111 mccRCC pts, of whom available IMDC-risk was favorable (35%), intermediate (60%), and poor-risk (5%) were included for analysis. The median time between tissue and ctDNA collection was 23 months (R: 1-177), and 96% of patients had undergone nephrectomy prior to ctDNA collection. In primary tissue sequencing, 64/111 (58%) from nephrectomy and 42/111 (42%) from metastatic sites, 569 unique alterations were identified across the whole cohort, with a median of 4 mutations/pt (R:1-23). RCC-specific alterations included VHL (88%), PBRM1 (48%), SETD2 (34%), KDM5C (17%), TP53 (14%). Across the cohort, 176 alterations were identified in ctDNA. With cross genotyping, ctDNA alterations concordant with primary tumors were detected in 20% (22/111 pts, 28 unique alterations) using stringent criteria with a median of 1 mutation/pt (R:1-2). Using liberal criteria, concordance with primary tumors was 59% (66/111 pts, 142 unique alterations) with a median of 2 mutations/pt (R: 1-8). Conclusions: This large cohort study matching oncogenomics from tumor and ctDNA highlights complexities and challenges of applying liquid biopsy in biomarker development in mccRCC.

scholarly journals MET Expression in Primary and Metastatic Clear Cell Renal Cell Carcinoma: Implications of Correlative Biomarker Assessment to MET Pathway Inhibitors

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Brian Shuch ◽  
Ryan Falbo ◽  
Fabio Parisi ◽  
Adebowale Adeniran ◽  
Yuval Kluger ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Predictive Biomarkers ◽  
Cell Renal Cell Carcinoma ◽  
Primary Tumors ◽  
Distant Tissue ◽  
Significant Expression ◽  
Metastatic Sites

Aims. Inhibitors of the MET pathway hold promise in the treatment for metastatic kidney cancer. Assessment of predictive biomarkers may be necessary for appropriate patient selection. Understanding MET expression in metastases and the correlation to the primary site is important, as distant tissue is not always available.Methods and Results. MET immunofluorescence was performed using automated quantitative analysis and a tissue microarray containing matched nephrectomy and distant metastatic sites from 34 patients with clear cell renal cell carcinoma. Correlations between MET expressions in matched primary and metastatic sites and the extent of heterogeneity were calculated. The mean expression of MET was not significantly different between primary tumors when compared to metastases (P=0.1). MET expression weakly correlated between primary and matched metastatic sites (R=0.5) and a number of cases exhibited very high levels of discordance between these tumors. Heterogeneity within nephrectomy specimens compared to the paired metastatic tissues was not significantly different (P=0.39).Conclusions. We found that MET expression is not significantly different in primary tumors than metastatic sites and only weakly correlates between matched sites. Moderate concordance of MET expression and significant expression heterogeneity may be a barrier to the development of predictive biomarkers using MET targeting agents.

Prognostic and predictive biomarkers for clear cell renal cell carcinoma utilizing next generation sequencing.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e16070-e16070
Author(s):  
Jamal Zekri ◽  
Abdelrazak Meliti ◽  
Mohammed Abhas Baghdadi ◽  
Turki Sobahy ◽  
Saba Imtiaz
Keyword(s):  
Renal Cell Carcinoma ◽  
Next Generation Sequencing ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Predictive Biomarkers ◽  
High Potential ◽  
Next Generation ◽  
Cell Renal Cell Carcinoma ◽  
Generation Sequencing

e16070 Background: The management of the clear cell renal cell carcinoma (cc-RCC) has evolved over the past decade. Clinical patients’ and tumor characteristics have a limited role in predicting the outcome of these patients. The search for reliable prognostic and predictive biomarkers should be pursued in particular during the current era of next generation sequencing (NGS) technology. Methods: Formalin-Fixed Paraffin-Embedded (FFPE) tissue specimens of cc-RCC were sequenced using NGS and a customized gene panel testing for 72 tumor-related genes. High potential variants were defined by mutation effect (stop-loss, stop-gain, frame-shift substitutions or non-synonymous SNV) and class (pathogenic or likely pathogenic). Cases with identical variants were identified. Results: In total, all 47 cases had 69,052 variants, of which 20,453 were classified as high potential variants. Identical alterations in 15 genes were present in all samples. These genes are: MUC3A, MUC12, MUC7, SRRT, MUC2, MUC5AC, MUC5B, MUC22, MUC6, CR1, MUC4, MUC16, MUC19, MUC17 and MERTK. The numbers of identical and non-identical variants in these 15 genes were counted for each sample. Median number of variants was 377 and was selected as a cut off to define cases with high ( > 377) and low (≤377) variants number (HVN and LVN respectively). For the whole cohort, HVN was associated with shorter overall survival compared to LVN (Median 50 months vs. not reached; Log Rank P = 0.041). In the 11 patients who received anti-angiogenic tyrosine kinase inhibitors (TKIs), HVN was associated with a trend of shorter progression free survival (Median 5 vs. 10 months; Log Rank P = not significant). Conclusions: Alterations in SRRT, CR1, MERTK and MUCIN family genes are very common in RCC. HVN ( > 377) is associated with worse prognosis and may predict decreased benefit from anti-angiogenic TKIs.

Atezolizumab plus bevacizumab in non-clear cell renal cell carcinoma (NccRCC) and clear cell renal cell carcinoma with sarcomatoid differentiation (ccRCCsd): Updated results of activity and predictive biomarkers from a phase II study.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 4583-4583 ◽  
Author(s):  
Ronan Flippot ◽  
Bradley Alexander McGregor ◽  
Abdallah Flaifel ◽  
Kathryn P. Gray ◽  
Sabina Signoretti ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Phase Ii ◽  
Immune Cells ◽  
Renal Cell ◽  
Clear Cell ◽  
Predictive Biomarkers ◽  
Cell Renal Cell Carcinoma ◽  
Immune Infiltrate ◽  
Sarcomatoid Differentiation

4583 Background: NccRCC and ccRCCsd are aggressive tumors associated with poor prognosis and response to therapy. Combination strategies co-targeting VEGF signaling and inhibitory immune checkpoints are highly active in clear-cell renal cell carcinoma, but data is lacking in NccRCC and ccRCCsd. We conducted a multicenter, open-label, single arm phase II trial of atezolizumab plus bevacizumab in NccRCC and ccRCCsd. Methods: Patients with NccRCC and ccRCCsd ( > 20% sarcomatoid differentiation), and ECOG performance status of 0-2 were eligible. Prior systemic treatment was allowed with the exception of prior PD-1/PD-L1-directed therapy. Atezolizumab 1200mg and bevacizumab 15mg/kg were administered every 3 weeks until progression, unacceptable toxicity, or patient withdrawal. Primary endpoint was objective response rate (ORR) per RECIST 1.1. Exploratory biomarker analyses included PD-L1 expression on tumor (TC) and immune cells (IC), and spatial analysis of the immune infiltrate. Results: Sixty patients received at least 1 cycle of treatment, among whom 56 were evaluable for response (17 ccRCCsd and 39 NccRCC). ORR was 34% in the overall population, 53% in ccRCCsd and 26% in NccRCC. Median progression-free survival was 8.4 months (95%CI, 6.9-16.5). Baseline tumor tissue was available for 36 patients. TC PD-L1 expression ≥1% was associated with improved ORR (9/14, 64%) compared to patients with PD-L1 expression < 1% (4/20, 20%). Patients with TC PD-L1 expression ≥1% who experienced progressive disease as best response had shorter average distance between tumor cells and nearest neighboring immune cells at baseline. Further analysis of the immune tumor microenvironment on an expanded cohort, including IC PD-L1 expression and correlation with clinical outcomes, is ongoing and will be updated. Conclusions: The combination of atezolizumab plus bevacizumab is active in NccRCC and ccRCCsd. Candidate predictive biomarkers include PD-L1 expression in TC and topological analysis of the immune infiltrate. Clinical trial information: NCT02724878.

scholarly journals Tumor Microenvironment Features as Predictive Biomarkers of Response to Immune Checkpoint Inhibitors (ICI) in Metastatic Clear Cell Renal Cell Carcinoma (mccRCC)

Cancers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 231
Author(s):  
Audrey Simonaggio ◽  
Nicolas Epaillard ◽  
Cédric Pobel ◽  
Marco Moreira ◽  
Stéphane Oudard ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Immune Checkpoint Inhibitors ◽  
Clear Cell ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Cell Renal Cell Carcinoma ◽  
Genomic Signatures

Renal cell carcinoma (RCC) is the seventh most frequently diagnosed malignancy with an increasing incidence in developed countries. Despite a greater understanding of the cancer biology, which has led to an increase of therapeutic options, metastatic clear cell renal cell carcinoma (mccRCC) still have a poor prognosis with a median five-years survival rate lower than 10%. The standard of care for mccRCC has changed dramatically over the past decades with the emergence of new treatments: anti-VEGFR tyrosine kinase inhibitors, mTOR Inhibitors and immune checkpoint inhibitors (ICI) such as anti-Programmed cell-Death 1 (PD-1) and anti-anti-Programmed Death Ligand-1 (PD-L1) used as monotherapy or as a combination with anti CTLA-4 or anti angiogenic therapies. In the face of these rising therapeutic options, the question of the therapeutic sequences is crucial. Predictive biomarkers are urgently required to provide a personalized treatment for each patient. Disappointingly, the usual ICI biomarkers, PD-L1 expression and Tumor Mutational Burden, approved in melanoma or non-small cell lung cancer (NSCLC) have failed to distinguish good and poor mccRCC responders to ICI. The tumor microenvironment is known to be involved in ICI response. Innovative technologies can be used to explore the immune contexture of tumors and to find predictive and prognostic biomarkers. Recent comprehensive molecular characterization of RCC has led to the development of robust genomic signatures, which could be used as predictive biomarkers. This review will provide an overview of the components of the RCC tumor microenvironment and discuss their role in disease progression and resistance to ICI. We will then highlight the current and future ICI predictive biomarkers assessed in mccRCC with a major focus on immunohistochemistry markers and genomic signatures.

scholarly journals Thrombospondin-2 and LDH Are Putative Predictive Biomarkers for Treatment with Everolimus in Second-Line Metastatic Clear Cell Renal Cell Carcinoma (MARC-2 Study)

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2594
Author(s):  
Philip Zeuschner ◽  
Sebastian Hölters ◽  
Michael Stöckle ◽  
Barbara Seliger ◽  
Anja Mueller ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Unmet Need ◽  
Therapy Response ◽  
Predictive Biomarkers ◽  
Second Line ◽  
Cell Renal Cell Carcinoma ◽  
Therapy Initiation

There is an unmet need for predictive biomarkers in metastatic renal cell carcinoma (mRCC) therapy. The phase IV MARC-2 trial searched for predictive blood biomarkers in patients with predominant clear cell mRCC who benefit from second-line treatment with everolimus. In an exploratory approach, potential biomarkers were assessed employing proteomics, ELISA, and polymorphism analyses. Lower levels of angiogenesis-related protein thrombospondin-2 (TSP-2) at baseline (≤665 parts per billion, ppb) identified therapy responders with longer median progression-free survival (PFS; ≤665 ppb at baseline: 6.9 months vs. 1.8, p = 0.005). Responders had higher lactate dehydrogenase (LDH) levels in serum two weeks after therapy initiation (>27.14 nmol/L), associated with a longer median PFS (3.8 months vs. 2.2, p = 0.013) and improved overall survival (OS; 31.0 months vs. 14.0 months, p < 0.001). Baseline TSP-2 levels had a stronger relation to PFS (HR 0.36, p = 0.008) than baseline patient parameters, including IMDC score. Increased serum LDH levels two weeks after therapy initiation were the best predictor for OS (HR 0.21, p < 0.001). mTOR polymorphisms appeared to be associated with therapy response but were not significant. Hence, we identified TSP-2 and LDH as promising predictive biomarkers for therapy response on everolimus after failure of one VEGF-targeted therapy in patients with clear cell mRCC.

scholarly journals Plasma Extracellular Vesicle-Derived TIMP-1 mRNA as a Prognostic Biomarker in Clear Cell Renal Cell Carcinoma: A Pilot Study

2020 ◽  
Vol 21 (13) ◽  
pp. 4624 ◽  
Author(s):  
Francisca Dias ◽  
Ana Luísa Teixeira ◽  
Inês Nogueira ◽  
Mariana Morais ◽  
Joana Maia ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Prognostic Biomarker ◽  
Predictive Biomarkers ◽  
Tissue Inhibitors Of Metalloproteinases ◽  
Cell Renal Cell Carcinoma ◽  
Localized Disease

The tumor microenvironment has gained a lot of attention from the scientific community since it has a proven impact in the development of tumor progression and metastasis. Extracellular vesicles (EVs) are now considered one of the key players of tumor microenvironment modulation. Clear cell renal cell carcinoma (ccRCC) is the most lethal urological neoplasia and presents a high metastatic potential, which reinforces the need for the development of more effective predictive biomarkers. Our goal was to evaluate the applicability of EV-derived matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) as prognostic biomarkers for ccRCC. To do so, we studied the plasma EV content of 32 patients with localized ccRCC and 29 patients with metastatic ccRCC. We observed that patients with localized disease and tumors larger than 7 cm presented higher levels of plasma EV-derived TIMP-1 mRNA when compared with patients presenting smaller tumors (p = 0.020). Moreover, patients with metastatic disease presented higher levels of EV-derived TIMP-1 mRNA when compared with patients with localized disease (p = 0.002) and when we stratified those patients in high and low levels of TIMP-1 EV-derived mRNA, the ones presenting higher levels had a lower overall survival (p = 0.030). EV-derived TIMP-1 mRNA may be a good prognostic biomarker candidate for ccRCC.

scholarly journals Current Concepts of Non-Coding RNAs in the Pathogenesis of Non-Clear Cell Renal Cell Carcinoma

Cancers ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1580 ◽  
Author(s):  
Dominik A. Barth ◽  
Ondrej Slaby ◽  
Christiane Klec ◽  
Jaroslav Juracek ◽  
Rares Drula ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Current Knowledge ◽  
Predictive Biomarkers ◽  
Treatment Schedule ◽  
Cell Renal Cell Carcinoma ◽  
Non Coding Rnas

Renal cell carcinoma (RCC) is a relatively rare malignancy of the urinary tract system. RCC is a heterogenous disease in terms of underlying histology and its associated underlying pathobiology, prognosis and treatment schedule. The most prevalent histological RCC subtype is clear-cell renal cell carcinoma (ccRCC), accounting for about 70–80% of all RCCs. Though the pathobiology and treatment schedule for ccRCC are well-established, non-ccRCC subtypes account for 20%–30% of RCC altogether, and their underlying molecular biology and treatment options are poorly defined. The class of non-coding RNAs—molecules that are generally not translated into proteins—are new cancer drivers and suppressors in all types of cancer. Of these, small non-coding microRNAs (miRNAs) contribute to carcinogenesis by regulating posttranscriptional gene silencing. Additionally, a growing body of evidence supports the role of long non-coding RNAs (lncRNAs) in cancer development and progression. Most studies on non-coding RNAs in RCC focus on clear-cell histology, and there is a relatively limited number of studies on non-ccRCC subtypes. The aim of this review is to give an overview of the current knowledge regarding the role of non-coding RNAs (including short and long non-coding RNAs) in non-ccRCC and to highlight possible implications as diagnostic, prognostic and predictive biomarkers.

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