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

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.

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The genomic landscape of metastatic non-clear cell renal cell carcinoma.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.6_suppl.474 ◽

2017 ◽

Vol 35 (6_suppl) ◽

pp. 474-474 ◽

Cited By ~ 1

Author(s):

Maria Isabel Carlo ◽

Nabeela Khan ◽

Yingbei Chen ◽

James Hsieh ◽

A. Ari Hakimi ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Mtor Inhibitors ◽

Driver Gene ◽

Cell Renal Cell Carcinoma ◽

Primary Tumors ◽

Targeted Next Generation Sequencing ◽

Metastatic Sites

474 Background: Non-clear cell renal cell carcinoma (nccRCC) encompasses about 20% of RCC cases and includes a number of subtypes that vary clinically and molecularly. Compared to ccRCC, these tumors have more limited sensitivity to conventional anti-VEGF agents and mTOR inhibitors, and there is clear need for better therapies. Analysis of genomic alterations in potentially targetable pathways may lead to novel therapeutic development strategies. Methods: We retrospectively analyzed tumors from 112 patients with metastatic nccRCC with targeted next-generation sequencing (NGS) across a panel of >340 cancer-relevant genes. Matched tumor and normal was used to facilitate somatic calling. We report on recurrent alterations observed for nccRCC variants. Results: Median age was 53 years (range 12-77), 67% were male; 47% presented with metastatic disease and 53% with localized disease that later metastasized. NGS was performed on tissue from primary tumors (57%) or metastatic sites (43%). Subtype classifications included unclassified (44%), papillary (21%), chromophobe (13%), translocation (12%), and other (9%). The most frequently altered genes by subtype are included in table. 36% of unclassified or papillary tumors had a mutation in a putative driver gene amenable to targeted therapies, including MET, NOTCH1, SMARCB1, TSC1, TSC2, PIK3CA, and FGFR3. 3 chromophobe tumors and 1 translocation tumor had a mutation in a potentially targetable pathway. Conclusions: The mutation profiles of metastatic nccRCC vary by papillary, chromophobe, and translocation subtype, with unclassified tumors most approximating papillary subtype. Unclassified and papillary subtypes harbor frequent mutations in potentially targetable pathways that merit further investigation. [Table: see text]

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Abstract 1493: Specific miRNA signatures characterize different metastatic sites in clear cell renal cell carcinoma

10.1158/1538-7445.am2014-1493 ◽

2014 ◽

Author(s):

Joana Heinzelmann ◽

Franzsika Stolzenbach ◽

Robert Schneeweiss ◽

Ulrike Wickmann ◽

Sophie Baumgart ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Cell Renal Cell Carcinoma ◽

Metastatic Sites

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Abstract 1693: Nicotinamide N-methyltransferase in clear cell renal cell carcinoma primary tumors and metastases

10.1158/1538-7445.am2016-1693 ◽

2016 ◽

Author(s):

Anna Reustle ◽

Steffen Rausch ◽

Stefan Winter ◽

Florian Büttner ◽

Stephan Kruck ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Cell Renal Cell Carcinoma ◽

Primary Tumors

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

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.e16070 ◽

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.

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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.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.4583 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. 4583-4583 ◽

Cited By ~ 7

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.

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

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.e16105 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. e16105-e16105 ◽

Cited By ~ 1

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.

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

Cancers ◽

10.3390/cancers13020231 ◽

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.

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