NOVEL USE OF CTDNA TO IDENTIFY LOCALLY ADVANCED AND METASTATIC UPPER TRACT UROTHELIAL CARCINOMA

Disclosed are compositions and methods for detecting, prognosing, grading, and treating a cancer such as, for example a bladder cancer including, but not limited to upper tract urothelial carcinoma (UTUC) using circulating tumor DNA (ctDNA).

Upper tract urothelial carcinoma (UTUC) is an aggressive cancer for which use of neoadjuvant chemotherapy (NAC) is limited by suboptimal clinical staging prior to nephroureterectomy. Detection of circulating tumor DNA (ctDNA) associated with locally advanced and nodally metastatic urothelial carcinoma of the bladder may help identify UTUC patients who would benefit from NAC. Optimal patient selection for neoadjuvant chemotherapy prior to surgical extirpation is limited by the inaccuracy of contemporary clinical staging methods in high-risk upper tract urothelial carcinoma (UTUC). What are needed are new methods to detect cancers and assess cancer risk so appropriate treatments can be applied to patients and thereby increase cancer survivability.

Disclosed are methods and compositions related detecting, prognosing, grading, and treating a cancer such as, for example a bladder using circulating tumor DNA (ctDNA).

Also disclosed herein are methods of detecting the presence of a cancer and/or metastasis of any preceding aspect, further comprising extracting DNA from the tissue sample.

In one aspect, disclosed herein are methods of detecting the presence of a cancer and/or metastasis of any preceding aspect, further comprising measuring plasma copy number burden (CNB); wherein a CNB of >6.5 indicates the presence of a cancer.

Also disclosed herein are methods of detecting the presence of a cancer and/or metastasis of any preceding aspect, further comprising administering to the subject an anti-cancer treatment (such as, for example a cisplatin-based neoadjuvant chemotherapy or nephroureterectomy (RNU)) when a cancer is detected.

Also disclosed herein are methods of predicting survival (including overall survival and/or progression free survival) of any preceding aspect, further comprising extracting DNA from the tissue sample.

In one aspect, disclosed herein are methods of predicting survival (including overall survival and/or progression free survival) of any preceding aspect, further comprising measuring plasma copy number burden (CNB); wherein a CNB of >6.5 indicates the presence of a cancer.

Also disclosed herein are methods of predicting survival (including overall survival and/or progression free survival) of any preceding aspect, further comprising administering to the subject an anti-cancer treatment (such as, for example a cisplatin-based neoadjuvant chemotherapy) when cancer survival is low.

Also disclosed herein are methods of staging cancer and/or metastasis (such as, for example, a bladder or urinary tract cancer including, but not limited to upper tract urothelial carcinoma (UTUC) such as muscle-invasive (MI)/non-organ confined (NOC) (MI/NOC) UTUC or non-muscle invasive (NMI) UTUC) of any preceding aspect, further comprising extracting DNA from the tissue sample.

In one aspect, disclosed herein are methods of staging cancer and/or metastasis (such as, for example, a bladder or urinary tract cancer including, but not limited to upper tract urothelial carcinoma (UTUC) such as muscle-invasive (MI)/non-organ confined (NOC) (MI/NOC) UTUC or non-muscle invasive (NMI) UTUC) of any preceding aspect, further comprising measuring plasma copy number burden (CNB); wherein a CNB of >6.5 indicates the presence of a cancer.

Also disclosed herein are methods of staging cancer and/or metastasis (such as, for example, a bladder or urinary tract cancer including, but not limited to upper tract urothelial carcinoma (UTUC) such as muscle-invasive (MI)/non-organ confined (NOC) (MI/NOC) UTUC or non-muscle invasive (NMI) UTUC) of any preceding aspect, further comprising administering to the subject an anti-cancer treatment (such as, for example, a cisplatin-based neoadjuvant chemotherapy or nephroureterectomy (RNU)) when an aggressive cancer is detected.

Also disclosed herein are methods of treating, inhibiting, reducing, decreasing, ameliorating, and/or preventing a cancer and/or metastasis of any preceding aspect, further comprising extracting DNA from the tissue sample.

In one aspect, disclosed herein are methods of treating, inhibiting, reducing, decreasing, ameliorating, and/or preventing a cancer and/or metastasis of any preceding aspect, further comprising measuring plasma copy number burden (CNB); wherein a CNB of >6.5 indicates the presence of a cancer.

V. DETAILED DESCRIPTION

An “increase” can refer to any change that results in a greater amount of a symptom, disease, composition, condition or activity. An increase can be any individual, median, or average increase in a condition, symptom, activity, composition in a statistically significant amount. Thus, the increase can be a 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100% increase so long as the increase is statistically significant.

A “decrease” can refer to any change that results in a smaller amount of a symptom, disease, composition, condition, or activity. A substance is also understood to decrease the genetic output of a gene when the genetic output of the gene product with the substance is less relative to the output of the gene product without the substance. Also for example, a decrease can be a change in the symptoms of a disorder such that the symptoms are less than previously observed. A decrease can be any individual, median, or average decrease in a condition, symptom, activity, composition in a statistically significant amount. Thus, the decrease can be a 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100% decrease so long as the decrease is statistically significant.

By “reduce” or other forms of the word, such as “reducing” or “reduction,” is meant lowering of an event or characteristic (e.g., tumor growth). It is understood that this is typically in relation to some standard or expected value, in other words it is relative, but that it is not always necessary for the standard or relative value to be referred to. For example, “reduces tumor growth” means reducing the rate of growth of a tumor relative to a standard or a control.

The term “subject” refers to any individual who is the target of administration or treatment. The subject can be a vertebrate, for example, a mammal. In one aspect, the subject can be human, non-human primate, bovine, equine, porcine, canine, or feline. The subject can also be a guinea pig, rat, hamster, rabbit, mouse, or mole. Thus, the subject can be a human or veterinary patient. The term “patient” refers to a subject under the treatment of a clinician, e.g., physician.

“Biocompatible” generally refers to a material and any metabolites or degradation products thereof that are generally non-toxic to the recipient and do not cause significant adverse effects to the subject.

A “control” is an alternative subject or sample used in an experiment for comparison purposes. A control can be “positive” or “negative.”

“Effective amount” of an agent refers to a sufficient amount of an agent to provide a desired effect. The amount of agent that is “effective” will vary from subject to subject, depending on many factors such as the age and general condition of the subject, the particular agent or agents, and the like. Thus, it is not always possible to specify a quantified “effective amount.” However, an appropriate “effective amount” in any subject case may be determined by one of ordinary skill in the art using routine experimentation. Also, as used herein, and unless specifically stated otherwise, an “effective amount” of an agent can also refer to an amount covering both therapeutically effective amounts and prophylactically effective amounts. An “effective amount” of an agent necessary to achieve a therapeutic effect may vary according to factors such as the age, sex, and weight of the subject. Dosage regimens can be adjusted to provide the optimum therapeutic response. For example, several divided doses may be administered daily or the dose may be proportionally reduced as indicated by the exigencies of the therapeutic situation.

A “pharmaceutically acceptable” component can refer to a component that is not biologically or otherwise undesirable, i.e., the component may be incorporated into a pharmaceutical formulation provided by the disclosure and administered to a subject as described herein without causing significant undesirable biological effects or interacting in a deleterious manner with any of the other components of the formulation in which it is contained. When used in reference to administration to a human, the term generally implies the component has met the required standards of toxicological and manufacturing testing or that it is included on the Inactive Ingredient Guide prepared by the U.S. Food and Drug Administration.

“Pharmaceutically acceptable carrier” (sometimes referred to as a “carrier”) means a carrier or excipient that is useful in preparing a pharmaceutical or therapeutic composition that is generally safe and non-toxic and includes a carrier that is acceptable for veterinary and/or human pharmaceutical or therapeutic use. The terms “carrier” or “pharmaceutically acceptable carrier” can include, but are not limited to, phosphate buffered saline solution, water, emulsions (such as an oil/water or water/oil emulsion) and/or various types of wetting agents. As used herein, the term “carrier” encompasses, but is not limited to, any excipient, diluent, filler, salt, buffer, stabilizer, solubilizer, lipid, stabilizer, or other material well known in the art for use in pharmaceutical formulations and as described further herein.

“Pharmacologically active” (or simply “active”), as in a “pharmacologically active” derivative or analog, can refer to a derivative or analog (e.g., a salt, ester, amide, conjugate, metabolite, isomer, fragment, etc.) having the same type of pharmacological activity as the parent compound and approximately equivalent in degree.

“Therapeutic agent” refers to any composition that has a beneficial biological effect. Beneficial biological effects include both therapeutic effects, e.g., treatment of a disorder or other undesirable physiological condition, and prophylactic effects, e.g., prevention of a disorder or other undesirable physiological condition (e.g., a non-immunogenic cancer). The terms also encompass pharmaceutically acceptable, pharmacologically active derivatives of beneficial agents specifically mentioned herein, including, but not limited to, salts, esters, amides, proagents, active metabolites, isomers, fragments, analogs, and the like. When the terms “therapeutic agent” is used, then, or when a particular agent is specifically identified, it is to be understood that the term includes the agent per se as well as pharmaceutically acceptable, pharmacologically active salts, esters, amides, proagents, conjugates, active metabolites, isomers, fragments, analogs, etc.

“Therapeutically effective amount” or “therapeutically effective dose” of a composition (e.g. a composition comprising an agent) refers to an amount that is effective to achieve a desired therapeutic result. In some embodiments, a desired therapeutic result is the control of type I diabetes. In some embodiments, a desired therapeutic result is the control of obesity. Therapeutically effective amounts of a given therapeutic agent will typically vary with respect to factors such as the type and severity of the disorder or disease being treated and the age, gender, and weight of the subject. The term can also refer to an amount of a therapeutic agent, or a rate of delivery of a therapeutic agent (e.g., amount over time), effective to facilitate a desired therapeutic effect, such as pain relief. The precise desired therapeutic effect will vary according to the condition to be treated, the tolerance of the subject, the agent and/or agent formulation to be administered (e.g., the potency of the therapeutic agent, the concentration of agent in the formulation, and the like), and a variety of other factors that are appreciated by those of ordinary skill in the art. In some instances, a desired biological or medical response is achieved following administration of multiple dosages of the composition to the subject over a period of days, weeks, or years.

Disclosed herein are kits that are drawn to reagents that can be used in practicing the methods disclosed herein. The kits can include any reagent or combination of reagent discussed herein or that would be understood to be required or beneficial in the practice of the disclosed methods. For example, the kits could include primers to perform the amplification reactions discussed in certain embodiments of the methods, as well as the buffers and enzymes required to use the primers as intended.

C. METHOD OF TREATING CANCER

Upper tract urothelial carcinoma (UTUC) is an aggressive disease with up to 70% incidence of high-grade histology and 60% muscle-invasive staging at the time of radical nephroureterectomy (RNU). Patients with muscle-invasive UTUC (≥pT2) have a poor prognosis, with 5-year cancer-specific mortality rates ranging between 21-59%. Fortunately, there is emerging evidence that cisplatin-based neoadjuvant chemotherapy (NAC) can be safely delivered to achieve pathologic down-staging and improved survival. However, a major challenge preventing optimal patient selection for NAC rests with the difficulty of accurate clinical staging due to UTUC's cloistered anatomical location. Tumor biopsies by ureteroscopy under-stage UTUC up to 46% of the time. Efforts to improve clinical risk stratification using nomograms incorporating ureteroscopic findings, histologic features and cross-sectional imaging yielded only incremental gains. Moreover, clinical under-staging causes missed opportunities for systemic therapy, as those patients who develop renal insufficiency after surgery can no longer qualify for chemotherapy. Given the high stakes for accurate preoperative risk stratification, predictive biomarkers for invasive UTUC are critically needed.

The detection of circulating tumor DNA (ctDNA), that is, plasma cell-free DNA with tumor-specific alterations, is increasingly adopted for numerous clinical applications including cancer diagnosis, assessment of treatment response, and detection of residual disease and/or recurrence ctDNA can be detected in up to 35% of patients with localized urothelial carcinoma of the bladder and 83% with metastatic urothelial cancer. Saliently, higher levels of ctDNA have been shown to correlate with disease burden and portend worse outcomes. It was demonstrated higher levels of ctDNA in patients with muscle invasive bladder cancer than those with recurrent non-muscle invasive disease. Based on these findings, we hypothesized that the detection of plasma ctDNA can be used to refine clinical staging in high-risk UTUC patients undergoing extirpative surgery. In this study, we demonstrate the feasibility of preoperative ctDNA collection and correlate its accuracy in the prediction of muscle-invasive and non-organ confined UTUC (MI/NOC UTUC).

Also disclosed herein are methods of detecting the presence of a cancer and/or metastasis of any preceding aspect, further comprising extracting DNA from the tissue sample.

In one aspect, disclosed herein are methods of detecting the presence of a cancer and/or metastasis of any preceding aspect, further comprising measuring plasma copy number burden (CNB); wherein a CNB of >6.5 indicates the presence of a cancer.

Also disclosed herein are methods of detecting the presence of a cancer and/or metastasis of any preceding aspect, further comprising administering to the subject an anti-cancer treatment (such as, for example a cisplatin-based neoadjuvant chemotherapy or nephroureterectomy (RNU)) when a cancer is detected.

Also disclosed herein are methods of staging cancer and/or metastasis (such as, for example, a bladder or urinary tract cancer including, but not limited to upper tract urothelial carcinoma (UTUC) such as muscle-invasive (MI)/non-organ confined (NOC) (MI/NOC) UTUC or non-muscle invasive (NMI) UTUC) of any preceding aspect, further comprising extracting DNA from the tissue sample.

In one aspect, disclosed herein are methods of staging cancer and/or metastasis (such as, for example, a bladder or urinary tract cancer including, but not limited to upper tract urothelial carcinoma (UTUC) such as muscle-invasive (MI)/non-organ confined (NOC) (MI/NOC) UTUC or non-muscle invasive (NMI) UTUC) of any preceding aspect, further comprising measuring plasma copy number burden (CNB); wherein a CNB of >6.5 indicates the presence of a cancer.

Also disclosed herein are methods of staging cancer and/or metastasis (such as, for example, a bladder or urinary tract cancer including, but not limited to upper tract urothelial carcinoma (UTUC) such as muscle-invasive (MI)/non-organ confined (NOC) (MI/NOC) UTUC or non-muscle invasive (NMI) UTUC) of any preceding aspect, further comprising administering to the subject an anti-cancer treatment (such as, for example, a cisplatin-based neoadjuvant chemotherapy or nephroureterectomy (RNU)) when an aggressive cancer is detected.

Also disclosed herein are methods of predicting survival (including overall survival and/or progression free survival) of any preceding aspect, further comprising extracting DNA from the tissue sample.

In one aspect, disclosed herein are methods of predicting survival (including overall survival and/or progression free survival) of any preceding aspect, further comprising measuring plasma copy number burden (CNB); wherein a CNB of >6.5 indicates the presence of a cancer.

Also disclosed herein are methods of predicting survival (including overall survival and/or progression free survival) of any preceding aspect, further comprising administering to the subject an anti-cancer treatment (such as, for example a cisplatin-based neoadjuvant chemotherapy) when cancer survival is low.

The disclosed compositions can be used to treat any disease where uncontrolled cellular proliferation occurs such as cancers. A representative but non-limiting list of cancers that the disclosed compositions can be used to treat is the following: lymphomas such as B cell lymphoma and T cell lymphoma; mycosis fungoides; Hodgkin's Disease; myeloid leukemia (including, but not limited to acute myeloid leukemia (AML) and/or chronic myeloid leukemia (CML)); bladder cancer (including, but not limited to upper tract urothelial carcinoma (UTUC) such as muscle-invasive (MI)/non-organ confined (NOC) (MI/NOC) UTUC or non-muscle invasive (NMI) UTUC); urinary tract cancer; brain cancer; nervous system cancer; head and neck cancer; squamous cell carcinoma of head and neck; renal cancer; lung cancers such as small cell lung cancer, non-small cell lung carcinoma (NSCLC), lung squamous cell carcinoma (LUSC), and Lung Adenocarcinomas (LUAD); neuroblastoma/glioblastoma; ovarian cancer; pancreatic cancer; prostate cancer; skin cancer; hepatic cancer; melanoma; squamous cell carcinomas of the mouth, throat, larynx, and lung; cervical cancer; cervical carcinoma; breast cancer including, but not limited to triple negative breast cancer; genitourinary cancer; pulmonary cancer; esophageal carcinoma; head and neck carcinoma; large bowel cancer; hematopoietic cancers; testicular cancer; and colon and rectal cancers.

Also disclosed herein are methods of treating, inhibiting, reducing, decreasing, ameliorating, and/or preventing a cancer and/or metastasis of any preceding aspect, further comprising extracting DNA from the tissue sample.

In one aspect, disclosed herein are methods of treating, inhibiting, reducing, decreasing, ameliorating, and/or preventing a cancer and/or metastasis of any preceding aspect, further comprising measuring plasma copy number burden (CNB); wherein a CNB of >6.5 indicates the presence of a cancer.

Patients with high-grade cTa-T2 UTUC without radiographic evidence of metastatic disease undergoing up-front radical nephroureterectomy (RNU) were prospectively accrued.

Blood was collected preoperatively on the day of surgery, and plasma and buffy coat were processed for extraction of ctDNA. FFPE samples from RNU were used for tissue genomic DNA extraction. Next-generation sequencing (NGS) was used for variant profiling.

Detection of cancer variants with a mutation allele frequency (MAF)≥0.25% and hotspot variants with a MAF down to 0.1% were reported for plasma samples targeted by a NGS panel (PredicineCARE™). Variants with MAF≥5% and hotspot variants with a MAF down to 2% were reported for FFPE samples.

Five patients (33%) had detectable plasma ctDNA mutations concordant with tumor-based genotypes using the targeted NGS panel.

Baseline clinicopathologic information

Location

Pathologic Grading

T Stage

N Stage

Margins

All patients with detectable preoperative ctDNA had advanced staging (≥pT2 or ≥pN1) and lymphovascular invasion

Prospective ctDNA analysis using a targeted NGS panel is a feasible nonsurgical approach to predict high-risk UTUC and has the potential to identify patients that may benefit from NAC.

2. Example 2: Novel Use of ctDNA to Identify Muscle-Invasive and Non-Organ Confined Upper Tract Urothelial Carcinoma

Upper tract urothelial carcinoma (UTUC) is an aggressive disease with up to 70% incidence of high-grade histology and 60% muscle-invasive staging at the time of radical nephroureterectomy (RNU). Patients with muscle-invasive UTUC (≥pT2) have a poor prognosis, with 5-year cancer-specific mortality rates ranging between 21-59%. Fortunately, there is emerging evidence that cisplatin-based neoadjuvant chemotherapy (NAC) can be safely delivered to achieve pathologic down-staging and improved survival. However, a major challenge preventing optimal patient selection for NAC rests with the difficulty of accurate clinical staging due to UTUC's cloistered anatomical location. Tumor biopsies by ureteroscopy under-stage UTUC up to 46% of the time. Efforts to improve clinical risk stratification using nomograms incorporating ureteroscopic findings, histologic features and cross-sectional imaging yielded only incremental gains. Moreover, clinical under-staging causes missed opportunities for systemic therapy, as those patients who develop renal insufficiency after surgery can no longer qualify for chemotherapy. Given the high stakes for accurate preoperative risk stratification, predictive biomarkers for invasive UTUC are critically needed.

The detection of circulating tumor DNA (ctDNA), that is, plasma cell-free DNA with tumor-specific alterations, is increasingly adopted for numerous clinical applications including cancer diagnosis, assessment of treatment response, and detection of residual disease and/or recurrence ctDNA can be detected in up to 35% of patients with localized urothelial carcinoma of the bladder and 83% with metastatic urothelial cancer. Saliently, higher levels of ctDNA have been shown to correlate with disease burden and portend worse outcomes. It was demonstrated higher levels of ctDNA in patients with muscle invasive bladder cancer than those with recurrent non-muscle invasive disease. Based on these findings, we hypothesized that the detection of plasma ctDNA can be used to refine clinical staging in high-risk UTUC patients undergoing extirpative surgery. In this study, we demonstrate the feasibility of preoperative ctDNA collection and correlate its accuracy in the prediction of muscle-invasive and non-organ confined UTUC (MI/NOC UTUC).

a) Patients and Methods

(1) Study Design, Patient Selection, and Clinical Sample Collection

Following IRB approval, 32 patients diagnosed with clinically respectable, high-risk UTUC and planning up-front RNU or ureterectomy at H. Lee Moffitt Cancer Center were prospectively enrolled from October 2020 to April 2022. All patients provided written informed consent and the study was approved by the institutional review board. Treatment and surveillance were performed in accordance with the NCCN and EAU guidelines on UTUC. Recommendations to forego neoadjuvant chemotherapy, the performance of template-based lymphadenectomy, and administration of adjuvant treatment were made by the multidisciplinary treatment team. Pathologic specimens were reviewed by board-certified genitourinary pathology specialists and classified according to the AJCC Cancer Staging Manual, 8th edition. Postsurgical surveillance consisted of cross-sectional imaging, cystoscopy, and urine cytology every 3-6 mo in the first two years and every 6-12 mo thereafter according to the pathologic stage and grade.

Peripheral blood (10 ml) was collected in EDTA-containing tubes (Streck cell-free DNA BCT, La Vista, Nebraska, USA) 1-2 hours prior to surgery. Two-step centrifugation of whole blood was performed at 1600×g for 10 minutes followed by 3200×g for 10 minutes at 10° C. Plasma, buffy coat, and cell pellet were stored at −80° C. From the nephroureterectomy specimen, thick 20 μm sections of formalin-fixed paraffin embedded (FFPE) tumor tissue with ≥50% tumor cellularity were microdissected for

Peripheral blood mononuclear cell (PBMC)-derived germline DNA (gDNA), tumor tissue DNA, and plasma cell-free DNA (cfDNA) were extracted using a combination of established proprietary kits and in-house column-based methods. Thirty of 32 patients had adequate preoperative plasma samples for ctDNA extraction. After quality assessment and quantification, up to 250 ng of gDNA, 50-100 ng of tumor DNA, and 5-30 ng of cfDNA were used for next-generation sequencing library preparation, panel-based hybridization (152-gene PredicineCARE® panel) (FIG. 7), and enrichment prior to ˜20,000X, 150 bp paired-end sequencing on the Illumina NovaSeq 6000 platform (Illumina, San Diego, CA). In parallel, plasma samples were also sequenced using low-pass (1-3×) whole-genome sequencing (WGS).

A proprietary machine learning bioinformatics pipeline (Predicine DeepSEA®) was used to identify single nucleotide variations (SNVs), insertions/deletions (indels), gene-level copy number changes (CNAs), and targeted gene fusions. This algorithm incorporates customized probabilistic control for sequencing errors, detects and eliminates mutations potentially resulting from clonal hematopoiesis of indeterminate potential (CHIP), and calls mutations passing validated allele frequency thresholds of 0.25% (or 0.1% for hotspot mutations) in plasma and 5% (or 2% for hotspot mutations) in FFPE. Additionally, germline mutations detected in matched PBMCs or at high frequency in population genomic databases were filtered out. Pathogenicity of mutations was annotated according to the Clinvar data base. Tumor mutation burden (TMB) was calculated using high-confidence mutations and adjusted for the panel size. In parallel, the low-pass WGS data from plasma cfDNA was used to conduct chromosomal-level copy number analysis using a modified version of the ichorCNA algorithm. Genome-wide copy number burden (CNB) was calculated as an aggregate score across significant copy number changes detected in 1 MB windows throughout the autosomal genome. Using low-pass WGS data, we tested for evidence of somatic chromosomal arm copy number changes in the plasma cfDNA.

(3) Outcomes and Statistical Analyses

The primary objective was to investigate the ability of plasma ctDNA to distinguish between muscle-invasive/non-organ confined (MI/NOC) and non-muscle invasive (NMI) UTUC. The predictive performance of ctDNA for preoperative identification of MI/NOC UTUC was summarized across preoperative variant count thresholds by calculating the area under the receiver-operating characteristic curve (AUC). The optimal variant count threshold for best sensitivity and specificity was determined using Youden's J statistic implemented in the R package pROC. Based on this method, preoperative ctDNA positivity was defined as the detection of at least two plasma variants, coinciding with other published analyses. The Kaplan-Meier method was used to estimate survival and Mantel-Cox log-rank testing to assess associations between preoperative ctDNA positivity and clinical outcomes including 1) overall survival (OS, time from surgery until UC-related death) and 2) progression-free survival (PFS, time from surgery until progression to metastatic UC). Differences between NMI and MI/NOC patient groups were tested using the Wilcoxon test for continuous variables and the Fisher Exact test for categorical variables. Univariate analysis of each variable was done using logistic regression, and elastic-net regularization was imposed for multivariate models (R packages glm, caret and glmnet). All tests were conducted in R version 4.1.3.

(4) cfDNA and Genomic DNA Extraction

Whole blood samples were shipped to Predicine on ice and later centrifuged in the lab. Circulating cell-free DNA was extracted from the plasma fraction by QIAamp circulating nucleic acid kit. Quantity and quality of the purified cfDNA was checked using Qubit fluorimeter and Bioanalyzer 2100. For samples with severe genomic contamination from peripheral blood cells, a bead-based size selection was performed to remove large genomic fragments. Genomic DNA (gDNA) was also extracted from the matched buffy coat fraction (PBMCs) from each blood sample and matched patient FFPE tumor sample. Up to 250 ng genomic DNA from PBMC and up to 100 ng gDNA was then enzymatically fragmented and purified.

(5) Library Preparation, Capture and Sequencing

Five to thirty nanograms of extracted cfDNA were used for plasma cfDNA library construction including end-repair, dA-tailing, and ligation of unique molecular identifiers (UMIs) and sequencing adapters. Ligated fragments were amplified via PCR. The amplified DNA libraries were then further checked using Bioanalyzer 2100 and samples with sufficient yield were used for hybrid capture. When available, a subsample of material was reserved for later low-pass WGS.

Library capture was conducted using Biotin labeled DNA probes. In brief, the library was hybridized overnight with the PredicineCARE panel and paramagnetic beads. The unbound fragments were washed away, and the enriched fragments were amplified via PCR. The purified product was checked using a Bioanalyzer 2100 and then loaded onto the Illumina NovaSeq 6000 for NGS sequencing with paired-end 2×150 bp sequencing kits.

(6) Analyses of NGS Data

Data was analyzed using the Predicine DeepSea analysis pipeline, which starts from the raw sequencing data (BCL files) and outputs final variant calls. Briefly, the pipeline first does adapter trim, barcode checking, and correction followed by paired FASTQ read alignment to human reference genome build hg19 using the BWA. Candidate variants, consisting of point mutations, small insertions and deletions, are identified across the targeted regions covered in the panel.

(7) Variant Calling and Annotation

Candidate variants with low base quality, mapping scores, and other quality metrics are filtered. Sequencing and PCR errors are also corrected using the algorithm described in (Newman et al. 2016). In general, a variant identified in cfDNA was considered a somatic mutation only when (i) at least three distinct fragments (at least one of them double-stranded) contained the mutation; and (ii) the mutant allele frequency was higher than 0.25%, or 0.1% for hotspot mutations; and (iii) the ctDNA variant containing fragments are significantly over-represented in comparison with the matched PBMC sample using a fisher-exact test (p-value<0.01 and odds-ratio>3). Non-hotspot variants with high variant frequency (>30%) were considered as suspicious germline variants. For FFPE samples we included variants with >5% MAF, >2% MAF in hotspots.

Candidate somatic mutations were annotated for their effect on protein coding genes as well as probable pathogenicity using the Clin Var database and annotation tool Varsome [ref]. Intronic and silent changes were excluded from our analyses, while missense mutations, nonsense mutations, frameshifts, or splice site alterations were retained. We also excluded common germline variants annotated in the 1000 genomes, ExAC, gnomAD and KAVIAR databases with population allele frequency>0.5%. Finally, we excluded hematopoietic expansion (CHIP) related variants, including those in DNMT3A, ASXL1, TET2.

(8) Copy Number Alterations and Copy Number Burden

Copy number variation was first estimated at the gene level using the NGS panel data. The in-house pipeline calculates the on-target unique fragment coverage based on consensus bam files, which are first corrected for GC bias and then adjusted for probe-level bias (estimated from a pooled reference). Each adjusted coverage profile is self-normalized (assuming diploid status of each sample) and then compared against correspondingly adjusted coverages from a group of normal reference samples to estimate the significance of each copy number variant. To call an amplification or deletion of a gene, we required the absolute z-score and copy number change to pass minimum thresholds.

We measured genome-wide copy-number burden with PredicineCNB™ (ref). The ichorCNA algorithm [Adalsteinsson V A, et al.] was applied to GC and mappability-normalized reads to estimate plasma and tissue copy number variations using a hidden Markov model (HMM). Firstly, we measured segment level (1 MB) copy number deviation as the log 2 ratio of the normalized reads between a sample and normal plasma background (or used a normal gDNA background for tissue CNB), then we quantified arm-level CNV deviation as the average of segment CNVs across each chromosome arm. Our method also takes into account local cfDNA fragment-size distributions. Finally, we calculated sample-level copy number burden (CNB score) as the sum of absolute zscore of arm-level CNV deviation, where higher CNB score indicates greater absolute CNV abnormality compared with normal background.

DNA rearrangement was detected by identifying the alignment break points based on the BAM files before consensus filtering. Suspicious alignments were filtered based on repeat regions, local entropy calculation and similarity between reference and alternative alignments. Larger than 3 unique alignments (at least one of them double stranded) were required to report a DNA fusion.

ctDNA fraction was estimated based on the mutant allele fraction of autosomal somatic mutations. Briefly, under the conservative assumption that each SNV may have loss of heterozygosity, the mutant allele fraction (MAF) and ctDNA fraction are related as MAF=(ctDNA*1)/[(1−ctDNA)*2+ctDNA*1], and so ctDNA=2/((1/MAF)+1). Somatic mutations in genes with a detectable copy number change were omitted from ctDNA fraction estimation, thus only a subset of samples could have ctDNA fraction accurately estimated from mutation data.

Blood-based tumor mutational burden (bTMB) was defined as the number of somatic coding SNVs, including synonymous and nonsynonymous variants, within panel target regions. Because TMB estimation considers all variants (including synonymous and non-whitelist variants), higher variant call specificity is required. More stringent cut-offs were used for variant calls, and only variants with allele frequency≥0.35% were used in score calculation. The bTMB score was weighted and normalized by the total effective targeted panel size within the coding region. 43 samples with the maximum somatic allelic frequency (MSAF)<0.7% were excluded for bTMB estimation.

(1) Patient Characteristics and UTUC Staging

Overall, 30/32 patients with clinically high-risk UTUC undergoing surgical extirpation had preoperative plasma ctDNA passing quality control (QC). Of the two samples failing QC, one was due to processing error and another due to insufficient DNA yield. Of the remaining 30 patients, median age was 74 years (IQR 67, 77.8) and 21 (70%) were male (Table 2). The tumor was located in the renal pelvis in 10 (33%), the ureter in 9 (30%), and both in 11 (37%). Twenty-seven (90%) patients underwent nephroureterectomy, 3 (10%) segmental ureterectomy, and 12 (40%) concomitant regional lymphadenectomy. Two (7%) patients received topical therapy before definitive surgical extirpation and 6 (20%) received adjuvant/salvage chemotherapy. On surgical pathology, 24 (80%) were high grade and 13 (43%) were MI UTUC (≥pT2). Six (20%) patients were found to harbor nodal metastases. Interestingly, one patient with pT1 HG ureteral tumor was found to have occult nodal metastasis, resulting in 14/30 (47%) patients with MI/NOC UTUC (FIG. 3).

Age, median
74
years
range 67-77.8 years

Gender

Smoking Status

History of bladder cancer
13
43

hydronephrosis Tumor

location

Pathologic grading

Pathologic tumor stage

Pathologic node stage

(2) Somatic Mutations and CNAs

The 152-gene PredicineCARE™ panel covers 81.2% of the commonly altered genes (≥10% incidence) in UTUC. To investigate the concordance between plasma and tumor tissue-derived DNA, targeted sequencing was performed on matching plasma and surgical UTUC samples. Overall, molecular alterations (MA) including SNVs/indels (66%) and gene-level CNAs (34%) were detected in 29 out of 30 (97%) tumor samples, spanning 75 of the 152 paneled-genes (FIG. 3a). In addition, 1 FGFR3-TACC3 fusion was found. Of the SNVs and indels, 29% were classified as Pathogenic. Each tumor contained a median of 6 (range 0-18) MAs and a mean TMB of 8.8 mutations/Mb (range 0-35.1), similar to levels (FIG. 8). One (3.3%) hypermutated tumor was found within our cohort, consistent with the 5.5% incidence described by others. Interestingly, this patient did not have germline mismatch repair gene alterations or prior cancer history. The most common tumor derived variants included TERT promoter (63%), TP53 (40%), MYC (37%), FGFR3 (33%), and CDKN2A (30%) (FIG. 4b). Although there was no significant difference in the total number of variants detected between NMI vs MI/NOC tumor tissue (8.3 vs 7, p=0.5, FIG. 4a), important distinctions exist at the gene level. TP53 (57% vs. 25%, p=0.1) was more commonly mutated in MI/NOC UTUC though this difference did not reach statistical significance. In contrast, a similar prevalence of FGFR3 (31% vs. 31%) and TERT promoter (69% vs. 57%) alterations were found in NMI and MI/NOC tumors (FIG. 4b).

At least one MA was detected within the cfDNA from 21/30 (70%) preoperative plasma samples, with each patient carrying a median of 1 ctDNA variant (range 0-8) (FIG. 3a). The most commonly detected alterations in the plasma cfDNA were TP53 (27%), ATM (17%), and ARIDIA (13%) (FIG. 4d). Overall, 52% of the detected plasma ctDNA variants corroborated alterations detected in the matching tumor samples. On the other hand, 88% of the tumor variants were not detected within the plasma (FIG. 1b). In particular, alterations in TP53, ARIDIA, and PIK3CA were frequently detected concomitantly in paired plasma and tissue samples. Importantly, a significantly higher number of plasma variants were detected within the plasma from MI/NOC (mean 3.4, range 1-8) vs. NMI UTUC (mean 0.5, range 0-2, p<0.0001) (FIG. 4c).

(3) Clinical Utility of Preoperative ctDNA Detection and Staging

The detection of ctDNA has been utilized in the preoperative setting to estimate tumor burden and refine prognosis in patients with stage III cutaneous melanoma. Similarly, we evaluated the utility of preoperative ctDNA to predict clinical staging in our cohort. Following summarization of predictive performance for optimal sensitivity and specificity of preoperative identification of MI/NOC UTUC across variant count thresholds, the presence of pre-surgical ctDNA was defined as the detection of at least two panel-based plasma MAs. Detection of ctDNA at this threshold was strongly predictive of MI/NOC UTUC at the time of surgery, achieving a sensitivity of 71% and specificity of 94% for detecting MI/NOC UTUC stage with an AUC of 0.92 (0.85-1.0, 95% CI) (FIG. 9). From 14 MI/NOC patients, four false negatives occurred, in patients with HG-UTUC staged pT1N1, pT3Nx, pT4Nx, and pT4N1. The one false positive occurred in a patient with multifocal HG pTaNO with a large 6.1 cm renal pelvic tumor.

(4) Utility of Copy Number Changes and Staging

There is a dichotomy between UTUCs with highly complex karyotypes containing frequent focal CNAs, aneuploidy, and chromothripsis compared to those with simple arm-level aberrations most commonly involving chromosome 1q, 3, 8, and 9. Furthermore, those with complex CNAs were frequently found to have TP53 alterations, and more likely to be staged as muscle-invasive and exhibit aggressive phenotypes. We hypothesized that high CNB correlates with pathologic staging and can be used to complement ctDNA positivity to improve the prediction model for MI/NOC UTUC. Evidence of somatic chromosomal arm gain and/or loss was found in all tumors. TP53-altered tumors had numerically higher number of CNAs than other subtypes (3.5 vs. 2.1, p=0.09) (FIG. 10). Overall, there was a marginal difference in preoperative plasma CNB score (4.5 vs. 5.2, p=0.06) between NMI and MI/NOC UTUC patients (FIG. 11A). Imposing a threshold of plasma CNB score>6.5 to confirm MI/NOC UTUC when at least two plasma variants were detected increased the sensitivity of prediction to 79%, without compromising the specificity (FIG. 11B).

The inability to accurately stage tumors prior to surgical extirpation has severely hampered customization of treatment for patients with high risk UTUC. As evidenced herein, despite adherence to clinical guidelines, 30% of the patients suffered rapid disease progression and/or cancer-specific death within two years following surgery with curative intent. With emerging evidence supporting the use of neoadjuvant chemotherapy, clinical tools to enhance the identification of potential beneficiaries with invasive, micrometastatic disease prior to surgery are critically needed. The inherent loss of renal function from surgical extirpation renders a subset of patients ineligible for adjuvant cisplatin-based chemotherapy, which makes this unmet need even more dire. Against this backdrop, our study provides encouraging evidence that plasma ctDNA collected at diagnosis estimates tumor burden and can be leveraged to distinguish between patients with MI/NOC from those with NMI UTUC. Equally important, ctDNA was strongly prognostic for disease progression and death following surgery, making it a promising biomarker for selecting patients to undergo chemotherapy in the neoadjuvant setting.

When treating high risk UTUC, more emphasis should be placed on minimizing missed opportunities to provide life-prolonging systemic treatment to patients with MI/NOC UTUC undergoing extirpative surgery. To that end, the sensitivity of preoperative ctDNA to define MI/NOC UTUC reached 79% in our model based on the detection of at least 2 panel-based plasma variants and a minimal threshold of plasma CNB score of 6.5. Although needing validation, this level of sensitivity represents a clear improvement over the more modest sensitivities between 42-48% achieved using available clinical nomograms.

On top of its clinical relevance, the 152-gene PredicineCARE™ ctDNA platform provided ease of clinical application and high genomic fidelity. Of the 31 plasma samples appropriately processed, only 1 failed to yield sufficient cfDNA for analysis. From the analysis of tumor tissue samples, MAs were detected in all but one of the samples (97%), validating the broad coverage of the frequently altered genes in UTUC.

Due to the rare incidence of UTUC, scant data exists on the application of ctDNA in the localized UTUC setting. Using a 73-gene panel, ctDNA were defined as one or more tumor-derived MAs and reported detection of ctDNA in 95% of 75 metastatic UTUC patients from 13 academic institutions, with an average of 6.8 Mas per patient. The higher plasma MA rates can reflect higher disease burden in patients with metastatic disease, though sporadic UTUC has also been shown to have a lower mutational burden than urothelial carcinoma of the bladder. Similar to our study, the most frequently encountered plasma MAs were TP53 (51%), PIK3CA (23%), ARIDIA (20%), and TERT (17%), albeit at higher detection frequencies. Likewise, frequent chromosomal arm-level gains and losses in addition to focal CNAs at the 9p24.3 region (CD274, JAK2, and PDCD1LG2) and 1q21.3-1q23.3 (PVRL4) were detected in our study. These genome-wide measures of plasma cfDNA CNB were also associated with advanced staging (5.2 vs. 4.5, p=0.06). Adding CNB as a secondary predictor of MI/NOC UTUC to our model increased the sensitivity from 71% to 79% (FIG. 11B). Our study represents the first investigation at scale of the ctDNA landscape in localized, high-risk UTUC and its concordance with somatic mutations found from matched tumor specimens.

117. In this prospective observational study, we demonstrate the clinical utility of ctDNA managing high risk, localized UTUC. Preoperative ctDNA positivity based on the detection of at least 2 plasma variants and a minimal threshold of CNB score of 6.5 was highly predictive of MI/NOC UTUC staging and strongly prognostic of progression and overall survival. Preoperative ctDNA analysis is feasible and can be used to select high risk UTUC patients benefiting from neoadjuvant chemotherapy.