PURPOSEAdvances in the systemic treatment for advanced clear cell renal cell carcinoma (ccRCC) have led to improvements in survival time. Globally, access to therapies with proven benefit, such as immune checkpoint inhibitors (ICPIs) and tyrosine kinase inhibitors, varies. Our investigation assessed whether patients from New Zealand have differential outcomes compared with their Australian counterparts.METHODSIn this retrospective cohort study, outcomes for patients treated with systemic therapy for advanced ccRCC in New Zealand (Auckland and Waikato) and Australia (Melbourne) were compared. Overall survival (OS) was the primary outcome. Key secondary outcomes included number of lines of systemic therapy received and the proportion of patients receiving an ICPI.RESULTSOne hundred and eighty-three, 101, and 66 patients were eligible for inclusion from Auckland, Waikato, and Australia, respectively, between 2010 and 2019. Median OS time was longer for the Australian cohort compared with the combined New Zealand cohort (56 v 17 months, hazard ratio, 0.40, P < .0001). Increased receipt of subsequent-line therapies was observed in the Australian cohort (24% v 11% received third line). A higher proportion of patients in the Australian cohort received an ICPI-containing regimen (41% v 13%).CONCLUSIONClinically meaningful differences in survival time were seen for patients treated with systemic therapy for advanced ccRCC between the New Zealand and Australian cohorts. These differences were greater than anticipated, with shorter survival time for patients in New Zealand. This analysis supports efforts to improve access to systemic therapies for patients with advanced ccRCC in New Zealand.

Supplementary Figure 2. Mutations in selected genes.

Supplementary Figure S1 shows independent estimation of circulating tumor DNA fraction using whole exome sequencing.

Supplementary Table 1: Somatic mutation count across all samples within meta-cohort. Counts of mutations in all ctDNA positive samples. 95th and 90th percentile are highlighted. Samples are named as a function of their relative mutation count. Supplementary Table 2: Evidence for mismatch repair deficiency by patient. See also Figure 2 Supplementary Table 3: Somatic mismatch repair gene alterations detected in patients with hypermutation. The status of key mismatch repair genes with respect to mutations and copynumber events. ClinVar version 20180603 annotations are included. *Clinvar annotation absent; **Diploid or lack of evidence for deviation from diploid ploidy; blue colour indicates the patients without MMRd etiology Supplementary Table 4: Whole exome sequencing summary statistics. Read depth and subsequent frequency calculations are based on unique read depth, post duplicate removal. Supplementary Table 5: Frequency of mutation and copy number changes in key genes. Comparison of gene and copy number frequencies in mimsatch repair cohort compared to control. P value and odds ratio generated using scipy.stats.fisher_exact verion 1.2.1 Supplementary Table 6: Somatic coding region altering mutations detected through targeted DNA sequencing (all cases in 95th percentile). Mutation annotation format with refseq protein change annotation. Supplementary Table 7: AR and other oncogene mutations detected across serial cfDNA collections. Protein changes are annotated with all refseq isoform amino acid changes. Variant allele frequency (VAF) is provided for each mutation. Supplementary Table 8: Distribution of variant allele frequencies for somatic mutations in each sample. Column D indicates the proportion of mutations in each sample that are considered subclonal. Predicted ctDNA fractions are calculated on max allele frequency of mutations in gene panel. Other columns contain descriptive statistics that summarize the central tendency, dispersion and shape of the distribution of variant allele frequencies per sample. Supplementary Table 9: CtDNA fraction by sample. The highest allele frequency mutation from each sample which does not belong to copy altered segment of the genome is used in the calculation of ctDNA fraction. Supplementary Table 10: Comparison of variant allele frequencies between tissue and ctDNA samples from patients P04 and P10. Supplementary Table 11: Clinical characteristics and PSA response to first-line AR-pathway inhibitor in the MMRd and control (MMR intact) cohort.

Supplementary Figure S7 shows the concordance of gene coverage logratios between 72-gene targeted sequencing and whole exome sequencing

Supplementary Figure 5. Somatic mutation trinucleotide contexts.

<p>Supplementary Figure S17 provides whole exome somatic mutation profiles in patients that did not show temporal changes in 72-gene panel mutation profiles</p>

Supplementary Figure 12. Swimmer plot showing overall patient survival from initial cancer diagnosis.

Supplementary Figure S8 shows that exome-wide sequencing supports ctDNA fraction estimates inferred with the 72-gene panel

Supplementary Figure S13 shows temporal changes in copy number profiles detected via 72-gene targeted sequencing

Supplementary Figure S10 provides Kaplan-Meier plots showing duration of treatment response in patients with different baseline circulating tumor DNA fractions

Supplementary Figure 3. Representative copy number profiles of samples harboring MSH2 and MSH6 deletions.

Supplementary Figure 9. Comparison of tumor mutation burden between primary tissue and cfDNA collections.

Supplementary Figure S25 shows concordant identification of intragenic copy number changes inside the androgen receptor (AR) gene based on a coverage-based approach and breakpoint-based approach

Supplementary Figure S24 shows that amplification of the enhancer region 640 kb upstream of the androgen receptor (AR) is common.

Supplementary Figure S12 shows the re-detection rate for somatic mutations identified in an earlier cfDNA sample

Supplementary Figure S14 shows temporal changes in whole exome somatic mutation profiles in patients that had evidence for somatic mutation profile change based on 72-gene targeted sequencing.

Supplementary Figure 1 Consort diagram of patient selection and analysis performed.

<p>Supplementary Figure S17 provides whole exome somatic mutation profiles in patients that did not show temporal changes in 72-gene panel mutation profiles</p>

Supplementary Figure S19 shows the complete switch of circulating tumor DNA profile in patient 026 between baseline and first progression timepoints