A comprehensive next generation sequencing tissue assay for Asian-prevalent cancers-Analytical validation and performance evaluation with clinical samples.

Introduction: A well-validated diagnostic assay with curated biomarkers complements clinicopathological factors to facilitate early diagnosis and ensure timely treatment delivery. This study focuses on an Asian-centric cancer diagnostic assay designed and thoroughly validated against commercially available standard references and a cohort of over 200 clinical specimens spanning 12 diverse Asian-centric cancer types. Methods: The assay uses hybrid-capture probes capable of profiling DNA aberrations from 572 cancer-related genes and 91 RNA fusion partners. The panel can detect clinically-tractable biomarkers such as microsatellite instability (MSI) and tumor mutation burden (TMB). Results: Analytical evaluation demonstrated 100% specificity and 99.9% sensitivity within a ≥5% VAF limit of detection (LoD) for SNV/Indels. RNA-based fusion features an LoD of ≥5 copies per nanogram input when evaluated against commercial references. Excellent linearity and concordance were observed when benchmarking against orthogonal methods in identifying MSI status, TMB scores and RNA fusions. Actionable genetic alterations were identified in 65% of the clinical samples. Conclusion: These results demonstrate a molecular diagnostic assay that accurately detects genomic alterations and complex biomarkers. The data also supports an excellent performance of this assay for making critical diagnoses and well-informed therapeutic decisions in Asian prevalent cancers.

Analytical and clinical validation of an amplicon-based next generation sequencing assay for ultrasensitive detection of circulating tumor DNA.

Next-generation sequencing of circulating tumor DNA presents a promising approach to cancer diagnostics, complementing conventional tissue-based diagnostic testing by enabling minimally invasive serial testing and broad genomic coverage through a simple blood draw to maximize therapeutic benefit to patients. LiquidHALLMARK® is an amplicon-based next-generation sequencing assay developed for the genomic profiling of plasma-derived cell-free DNA (cfDNA). The comprehensive 80-gene panel profiles point mutations, insertions/deletions, copy number alterations, and gene fusions, and further detects oncogenic viruses (Epstein-Barr virus (EBV) and hepatitis B virus (HBV)) and microsatellite instability (MSI). Here, the analytical and clinical validation of the assay is reported. Analytical validation using reference genetic materials demonstrated a sensitivity of 99.38% for point mutations and 95.83% for insertions/deletions at 0.1% variant allele frequency (VAF), and a sensitivity of 91.67% for gene fusions at 0.5% VAF. In non-cancer samples, a high specificity (≥99.9999% per-base) was observed. The limit of detection for copy number alterations, EBV, HBV, and MSI were also empirically determined. Orthogonal comparison of epidermal growth factor receptor (EGFR) variant calls made by LiquidHALLMARK and a reference allele-specific polymerase chain reaction (AS-PCR) method for 355 lung cancer specimens revealed an overall concordance of 93.80%, while external validation with cobas® EGFR Mutation Test v2 for 50 lung cancer specimens demonstrated an overall concordance of 84.00%, with a 100% concordance rate for EGFR variants above 0.4% VAF. Clinical application of LiquidHALLMARK in 1,592 consecutive patients demonstrated a high detection rate (74.8% circulating tumor DNA (ctDNA)-positive in cancer samples) and broad actionability (50.0% of cancer samples harboring alterations with biological evidence for actionability). Among ctDNA-positive lung cancers, 72.5% harbored at least one biomarker with a guideline-approved drug indication. These results establish the high sensitivity, specificity, accuracy, and precision of the LiquidHALLMARK assay and supports its clinical application for blood-based genomic testing.

Longitudinal Evaluation of Circulating Tumor DNA Using Sensitive Amplicon-Based Next-Generation Sequencing to Identify Resistance Mechanisms to Immune Checkpoint Inhibitors for Advanced Urothelial Carcinoma.

Serial evaluation of circulating tumor DNA may allow noninvasive assessment of drivers of resistance to immune checkpoint inhibitors (ICIs) in advanced urothelial cancer (aUC). We used a novel, amplicon-based next-generation sequencing assay to identify genomic alterations (GAs) pre- and post-therapy in 39 patients with aUC receiving ICI and 6 receiving platinum-based chemotherapy (PBC). One or more GA was seen in 95% and 100% of pre- and post-ICI samples, respectively, commonly in TP53 (54% and 54%), TERT (49% and 59%), and BRCA1/BRCA2 (33% and 33%). Clearance of ≥1 GA was seen in 7 of 9 patients responding to ICI, commonly in TP53 (n = 4), PIK3CA (n = 2), and BRCA1/BRCA2 (n = 2). A new GA was seen in 17 of 20 patients progressing on ICI, frequently in BRCA1/BRCA2 (n = 6), PIK3CA (n = 3), and TP53 (n = 3), which seldom emerged in patients receiving PBC. These findings highlight the potential for longitudinal circulating tumor DNA evaluation in tracking response and resistance to therapy.

Complementing Tissue Testing With Plasma Mutation Profiling Improves Therapeutic Decision-Making for Patients With Lung Cancer.

BACKGROUND: Tissue biopsy is an integral part of the diagnostic approach to lung cancer. It is however invasive and limited by heterogeneity. Liquid biopsies may complement tissue testing by providing additional molecular information and may be particularly helpful in patients from whom obtaining sufficient tissue for genomic profiling is challenging. METHODS: Patients with suspected lung cancer (n = 71) were prospectively recruited. Blood and diagnostic tissue samples were collected within 48 h of each other. Plasma cell-free DNA (cfDNA) testing was done using an ultrasensitive amplicon-based next-generation sequencing (NGS) panel (plasma NGS testing). For cases diagnosed as non-small cell lung carcinoma (NSCLC) via histology or cytology, targeted testing for epidermal growth factor receptor (EGFR) mutations was performed using tissue biopsy samples (tissue EGFR testing), where available. Concordance of clinically actionable mutations between methods and sample types was assessed. RESULTS: For confirmed NSCLC cases (n = 54), tissue EGFR test results were available only for 70.3% (38/54) due to sample inadequacies, compared to blood samples for 98.1% (53/54) cases. Tissue EGFR testing identified sensitizing EGFR (L858R or exon 19 deletion) mutation in 31.6% (12/38) of cases. Plasma NGS identified clinically actionable mutations in 37.7% (20/53) of cases, including EGFR mutations in two cases with no tissue EGFR results, and mutations in KRAS, BRAF, and MET. The overall sensitivity of sensitizing EGFR mutation detection by plasma NGS was 75% (9/12), and specificity was 100% (25/25) in patients tested in both tissue EGFR and plasma NGS (n = 37). In this cohort of patients, tissue EGFR testing alone informed clinical decisions in 22.2% (12/54) of cases. Adding plasma NGS to tissue EGFR testing increased the detection rate of actionable mutations to 42.6% (23/54), representing a 1.9-fold increase in clinically relevant findings. The average turnaround time of plasma NGS was shorter than standard tissue testing (10 vs. 29.9 days, p < 0.05). CONCLUSIONS: In the first-line setting, plasma NGS was highly concordant with tissue EGFR testing. Plasma NGS increases the detection of actionable findings with a shorter time to results. This study outlines the clinical utility of complementary plasma mutation profiling in the routine management of lung cancer patients.

Saliva is more sensitive than nasopharyngeal or nasal swabs for diagnosis of asymptomatic and mild COVID-19 infection.

We aimed to test the sensitivity of naso-oropharyngeal saliva and self-administered nasal (SN) swab compared to nasopharyngeal (NP) swab for COVID-19 testing in a large cohort of migrant workers in Singapore. We also tested the utility of next-generation sequencing (NGS) for diagnosis of COVID-19. Saliva, NP and SN swabs were collected from subjects who presented with acute respiratory infection, their asymptomatic roommates, and prior confirmed cases who were undergoing isolation at a community care facility in June 2020. All samples were tested using RT-PCR. SARS-CoV-2 amplicon-based NGS with phylogenetic analysis was done for 30 samples. We recruited 200 subjects, of which 91 and 46 were tested twice and thrice respectively. In total, 62.0%, 44.5%, and 37.7% of saliva, NP and SN samples were positive. Cycle threshold (Ct) values were lower during the earlier period of infection across all sample types. The percentage of test-positive saliva was higher than NP and SN swabs. We found a strong correlation between viral genome coverage by NGS and Ct values for SARS-CoV-2. Phylogenetic analyses revealed Clade O and lineage B.6 known to be circulating in Singapore. We found saliva to be a sensitive and viable sample for COVID-19 diagnosis.

Computerized Image Analysis of Tumor Cell Nuclear Morphology Can Improve Patient Selection for Clinical Trials in Localized Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clinicopathological scores are used to predict the likelihood of recurrence-free survival for patients with clear cell renal cell carcinoma (ccRCC) after surgery. These are fallible, particularly in the middle range. This inevitably means that a significant proportion of ccRCC patients who will not develop recurrent disease enroll into clinical trials. As an exemplar of using digital pathology, we sought to improve the predictive power of "recurrence free" designation in localized ccRCC patients, by precise measurement of ccRCC nuclear morphological features using computational image analysis, thereby replacing manual nuclear grade assessment. MATERIALS AND METHODS: TNM 8 UICC pathological stage pT1-pT3 ccRCC cases were recruited in Scotland and in Singapore. A Leibovich score (LS) was calculated. Definiens Tissue studio® (Definiens GmbH, Munich) image analysis platform was used to measure tumor nuclear morphological features in digitized hematoxylin and eosin (H&E) images. RESULTS: Replacing human-defined nuclear grade with computer-defined mean perimeter generated a modified Leibovich algorithm, improved overall specificity 0.86 from 0.76 in the training cohort. The greatest increase in specificity was seen in LS 5 and 6, which went from 0 to 0.57 and 0.40, respectively. The modified Leibovich algorithm increased the specificity from 0.84 to 0.94 in the validation cohort. CONCLUSIONS: CcRCC nuclear mean perimeter, measured by computational image analysis, together with tumor stage and size, node status and necrosis improved the accuracy of predicting recurrence-free in the localized ccRCC patients. This finding was validated in an ethnically different Singaporean cohort, despite the different H and E staining protocol and scanner used. This may be a useful patient selection tool for recruitment to multicenter studies, preventing some patients from receiving unnecessary additional treatment while reducing the number of patients required to achieve adequate power within neoadjuvant and adjuvant clinical studies.

Regional registration of whole slide image stacks containing major histological artifacts.

BACKGROUND: High resolution 2D whole slide imaging provides rich information about the tissue structure. This information can be a lot richer if these 2D images can be stacked into a 3D tissue volume. A 3D analysis, however, requires accurate reconstruction of the tissue volume from the 2D image stack. This task is not trivial due to the distortions such as tissue tearing, folding and missing at each slide. Performing registration for the whole tissue slices may be adversely affected by distorted tissue regions. Consequently, regional registration is found to be more effective. In this paper, we propose a new approach to an accurate and robust registration of regions of interest for whole slide images. We introduce the idea of multi-scale attention for registration. RESULTS: Using mean similarity index as the metric, the proposed algorithm (mean ± SD [Formula: see text]) followed by a fine registration algorithm ([Formula: see text]) outperformed the state-of-the-art linear whole tissue registration algorithm ([Formula: see text]) and the regional version of this algorithm ([Formula: see text]). The proposed algorithm also outperforms the state-of-the-art nonlinear registration algorithm (original: [Formula: see text], regional: [Formula: see text]) for whole slide images and a recently proposed patch-based registration algorithm (patch size 256: [Formula: see text] , patch size 512: [Formula: see text]) for medical images. CONCLUSION: Using multi-scale attention mechanism leads to a more robust and accurate solution to the problem of regional registration of whole slide images corrupted in some parts by major histological artifacts in the imaged tissue.

Automated Renal Cancer Grading Using Nuclear Pleomorphic Patterns.

PURPOSE: Nuclear pleomorphic patterns are essential for Fuhrman grading of clear cell renal cell carcinoma (ccRCC). Manual observation of renal histopathologic slides may lead to subjective and inconsistent assessment between pathologists. An automated, image-based system that classifies ccRCC slides by quantifying nuclear pleomorphic patterns in an objective and consistent interpretable fashion can aid pathologists in histopathologic assessment. METHODS: In the current study, histopathologic tissue slides of 59 patients with ccRCC who underwent surgery at Singapore General Hospital were assembled retrospectively. An automated image classification pipeline detects and analyzes prominent nucleoli in ccRCC images to classify them as either low (Fuhrman grade 1 and 2) or high (Fuhrman grade 3 and 4). The pipeline uses machine learning and image pixel intensity-based feature extraction techniques for nuclear analysis. We trained classification systems that concurrently analyze different permutations of multiple prominent nucleoli image patches. RESULTS: Given the parameters for feature combination and extraction, we present experimental results across various configurations for the classification of a given ccRCC histopathologic image. We also demonstrate that the image score used by the pipeline, termed fraction value, is correlated ( R = 0.59) with an existing multigene assay-based scoring system that has previously been demonstrated to be a strong indicator of prognosis in patients with ccRCC. CONCLUSION: The current method provides an objective and fully automated way by which to process pathologic slides. The correlation study with a multigene assay-based scoring system also allows us to provide quantitative interpretation for already established nuclear pleomorphic patterns in ccRCC. This method can be extended to other cancers whose corresponding grading systems use nuclear pattern information.

Recognizing the Continuous Nature of Expression Heterogeneity and Clinical Outcomes in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) has been previously classified into putative discrete prognostic subtypes by gene expression profiling. To investigate the robustness of these proposed subtype classifications, we evaluated 12 public datasets, together with a new dataset of 265 ccRCC gene expression profiles. Consensus clustering showed unstable subtype and principal component analysis (PCA) showed a continuous spectrum both within and between datasets. Considering the lack of discrete delineation and continuous spectrum observed, we developed a continuous quantitative prognosis score (Continuous Linear Enhanced Assessment of RCC, or CLEAR score). Prognostic performance was evaluated in independent cohorts from The Cancer Genome Atlas (TCGA) (n = 414) and EMBL-EBI (n = 53), CLEAR score demonstrated both superior prognostic estimates and inverse correlation with anti-angiogenic tyrosine-kinase inhibition in comparison to previously proposed discrete subtyping classifications. Inverse correlation with high-dose interleukin-2 outcomes was also observed for the CLEAR score. Multiple somatic mutations (VHL, PBRM1, SETD2, KDM5C, TP53, BAP1, PTEN, MTOR) were associated with the CLEAR score. Application of the CLEAR score to independent expression profiling of intratumoral ccRCC regions demonstrated that average intertumoral heterogeneity exceeded intratumoral expression heterogeneity. Wider investigation of cancer biology using continuous approaches may yield insights into tumor heterogeneity; single cell analysis may provide a key foundation for this approach.

Metformin Inhibits Cellular Proliferation and Bioenergetics in Colorectal Cancer Patient-Derived Xenografts.

There is increasing preclinical evidence suggesting that metformin, an antidiabetic drug, has anticancer properties against various malignancies, including colorectal cancer. However, the majority of evidence, which was derived from cancer cell lines and xenografts, was likely to overestimate the benefit of metformin because these models are inadequate and require supraphysiologic levels of metformin. Here, we generated patient-derived xenograft (PDX) lines from 2 colorectal cancer patients to assess the properties of metformin and 5-fluorouracil (5-FU), the first-line drug treatment for colorectal cancer. Metformin (150 mg/kg) as a single agent inhibits the growth of both PDX tumors by at least 50% (P < 0.05) when administered orally for 24 days. In one of the PDX models, metformin given concurrently with 5-FU (25 mg/kg) leads to an 85% (P = 0.054) growth inhibition. Ex vivo culture of organoids generated from PDX demonstrates that metformin inhibits growth by executing metabolic changes to decrease oxygen consumption and activating AMPK-mediated pathways. In addition, we also performed genetic characterizations of serial PDX samples with corresponding parental tissues from patients using next-generation sequencing (NGS). Our pilot NGS study demonstrates that PDX represents a useful platform for analysis in cancer research because it demonstrates high fidelity with parental tumor. Furthermore, NGS analysis of PDX may be useful to determine genetic identifiers of drug response. This is the first preclinical study using PDX and PDX-derived organoids to investigate the efficacy of metformin in colorectal cancer. Mol Cancer Ther; 16(9); 2035-44. ©2017 AACR.

Patient-specific hepatocyte-like cells derived from induced pluripotent stem cells model pazopanib-mediated hepatotoxicity.

Idiosyncratic drug-induced hepatotoxicity is a major cause of liver damage and drug pipeline failure, and is difficult to study as patient-specific features are not readily incorporated in traditional hepatotoxicity testing approaches using population pooled cell sources. Here we demonstrate the use of patient-specific hepatocyte-like cells (HLCs) derived from induced pluripotent stem cells for modeling idiosyncratic hepatotoxicity to pazopanib (PZ), a tyrosine kinase inhibitor drug associated with significant hepatotoxicity of unknown mechanistic basis. In vitro cytotoxicity assays confirmed that HLCs from patients with clinically identified hepatotoxicity were more sensitive to PZ-induced toxicity than other individuals, while a prototype hepatotoxin acetaminophen was similarly toxic to all HLCs studied. Transcriptional analyses showed that PZ induces oxidative stress (OS) in HLCs in general, but in HLCs from susceptible individuals, PZ causes relative disruption of iron metabolism and higher burden of OS. Our study establishes the first patient-specific HLC-based platform for idiosyncratic hepatotoxicity testing, incorporating multiple potential causative factors and permitting the correlation of transcriptomic and cellular responses to clinical phenotypes. Establishment of patient-specific HLCs with clinical phenotypes representing population variations will be valuable for pharmaceutical drug testing.

A five-gene reverse transcription-PCR assay for pre-operative classification of breast fibroepithelial lesions.

BACKGROUND: Breast fibroepithelial lesions are biphasic tumors and include fibroadenomas and phyllodes tumors. Preoperative distinction between fibroadenomas and phyllodes tumors is pivotal to clinical management. Fibroadenomas are clinically benign while phyllodes tumors are more unpredictable in biological behavior, with potential for recurrence. Differentiating the tumors may be challenging when they have overlapping clinical and histological features especially on core biopsies. Current molecular and immunohistochemical techniques have a limited role in the diagnosis of breast fibroepithelial lesions. We aimed to develop a practical molecular test to aid in distinguishing fibroadenomas from phyllodes tumors in the pre-operative setting. METHODS: We profiled the transcriptome of a training set of 48 formalin-fixed, paraffin-embedded fibroadenomas and phyllodes tumors and further designed 43 quantitative polymerase chain reaction (qPCR) assays to verify differentially expressed genes. Using machine learning to build predictive regression models, we selected a five-gene transcript set (ABCA8, APOD, CCL19, FN1, and PRAME) to discriminate between fibroadenomas and phyllodes tumors. We validated our assay in an independent cohort of 230 core biopsies obtained pre-operatively. RESULTS: Overall, the assay accurately classified 92.6 % of the samples (AUC = 0.948, 95 % CI 0.913-0.983, p = 2.51E-19), with a sensitivity of 82.9 % and specificity of 94.7 %. CONCLUSIONS: We provide a robust assay for classifying breast fibroepithelial lesions into fibroadenomas and phyllodes tumors, which could be a valuable tool in assisting pathologists in differential diagnosis of breast fibroepithelial lesions.

Substrate Stiffness Modulates the Maturation of Human Pluripotent Stem-Cell-Derived Hepatocytes.

Obtaining functional hepatocytes from human pluripotent stem cells (hPSCs) holds great potential for applications in drug safety testing, as well in the field of regenerative medicine. However, developing functionally mature hPSC-derived hepatocytes (hPSC-Heps) remains a challenge. We hypothesized that the cellular microenvironment plays a vital role in the maturation of immature hepatocytes. In this study, we examined the role of mechanical stiffness, a key component of the cellular microenvironment, in the maturation of hPSC-Heps. We cultured hPSC-Heps on collagen-coated polyacrylamide hydrogels with varying elastic moduli. On softer substrates the hPSC-Heps formed compact colonies while on stiffer substrates they formed a diffuse monolayer. We observed an inverse correlation between albumin production and substrate stiffness. The expression of key cytochrome enzymes, which are expressed at higher levels in the adult liver compared to the fetal liver, also correlated inversely with substrate stiffness, whereas fetal markers such as Cyp3A7 and AFP showed no correlation with stiffness. Culture of hPSC-Heps on soft substrates for 12 days led to 10-30 fold increases in the expression of drug-metabolizing enzymes. These results demonstrate that substrate stiffness similar to that of the liver enables aspects of the maturation of hPSC-Heps.

Fumarate Hydratase-deficient Cell Line NCCFH1 as a New In Vitro Model of Hereditary Papillary Renal Cell Carcinoma Type 2.

BACKGROUND/AIM: Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) is a rare autosomal dominant disorder characterized by fumarate hydratase (FH) gene mutation. It is associated with the development of very aggressive kidney tumors, characterized by early onset and high metastatic potential, and has no effective therapy. The aim of the study was to establish a new preclinical platform for investigating morphogenetic and metabolic features, and alternative therapy of metastatic hereditary papillary renal cell carcinoma type 2 (PRCC2). MATERIALS AND METHODS: Fresh cells were collected from pleural fluid of a patient with metastatic hereditary PRCC2. Morphogenetic and functional characteristics were evaluated via microscopy, FH gene sequencing analysis, real-time polymerase chaine reaction and enzymatic activity measurement. We performed bioenergetic analysis, gene-expression profiling, and cell viability assay with 19 anti-neoplastic drugs. RESULTS: We established a new in vitro model of hereditary PRCC2 - the NCCFH1 cell line. The cell line possesses a c.1162 delA - p.Thr375fs frameshift mutation in the FH gene. Our findings indicate severe attenuation of oxidative phosphorylation and glucose-dependent growth of NCCFH1 cells that is consistent with the Warburg effect. Furthermore, gene-expression profiling identified that the most prominent molecular features reflected a high level of apoptosis, cell adhesion, and cell signaling. Drug screening revealed a marked sensitivity of FH(-/-) cells to mitoxantrone, epirubicin, topotecan and a high sensitivity to bortezomib. CONCLUSION: We demonstrated that the NCCFH1 cell line is a very interesting preclinical model for studying the metabolic features and testing new therapies for hereditary PRCC2, while bortezomib may be a potential efficient therapeutic option.

Association of ABCB1 and FLT3 Polymorphisms with Toxicities and Survival in Asian Patients Receiving Sunitinib for Renal Cell Carcinoma.

Sunitinib is a tyrosine kinase inhibitor used as first-line treatment for metastatic renal cell carcinoma (mRCC). Asian ethnicity has been previously associated with lower clearance and greater toxicities for sunitinib treatment, relative to Caucasian ethnicity. Research focusing on identifying corresponding biomarkers of efficacy and toxicity has been hitherto conducted in Caucasian populations, and few of the reported associations have been externally validated. Our work thus aims to investigate candidate biomarkers in Asian patients receiving sunitinib, comparing the observed genotype effects with those reported in Caucasian populations. Using data from 97 Asian mRCC patients treated with sunitinib, we correlated 7 polymorphisms in FLT3, ABCB1, VEGFR2, ABCG2 and BIM with patient toxicities, response, and survival. We observed a stronger association of FLT3 738T genotype with leucopenia in our Asian dataset than that previously reported in Caucasian mRCC patients (odds ratio [OR]=8.0; P=0.03). We observed significant associations of FLT3 738T (OR=2.7), ABCB1 1236T (OR=0.3), ABCB1 3435T (OR=0.1), ABCB1 2677T (OR=0.4), ABCG2 421A (OR=0.3) alleles and ABCB1 3435, 1236, 2677 TTT haplotype (OR=0.1) on neutropenia. Primary resistance (OR=0.1, P=0.004) and inferior survival (progression-free: hazard ratio [HR]=5.5, P=0.001; overall: HR=5.0, P=0.005) were associated with the ABCB1 3435, 1236, 2677 TTT haplotype. In conclusion, ABCB1 and FLT3 polymorphisms may be helpful in predicting sunitinib toxicities, response and survival benefit in Asian mRCC patients. We have also validated the association between FLT3 738T and sunitinib-induced leucopenia previously reported in Caucasian populations, but have not validated other reported genetic associations.

Predictive molecular biomarkers to guide clinical decision making in kidney cancer: current progress and future challenges.

Although the past decade has seen a surfeit of new targeted therapies for renal cell carcinoma (RCC), no predictive molecular biomarker is currently used in routine clinical practice to guide personalized therapy as a companion diagnostic. Many putative biomarkers have been suggested, but none have undergone rigorous validation. There have been considerable advances in the biological understanding of RCC in recent years, with the development of accompanying molecular diagnostics that with additional validation, may be helpful for routine clinical decision making. In this review, we summarize the current understanding of predictive biomarkers in RCC management and also highlight upcoming developments of interest in biomarker research for personalizing RCC diagnostics and therapeutics.