Purpose The main objective of this preliminary analysis of the IMaging PAtients for Cancer drug selecTion (IMPACT)-renal cell cancer (RCC) study is to evaluate the lesion detection of baseline contrast-enhanced CT, [⁸⁹Zr]Zr-DFO-girentuximab-PET/CT and [¹⁸F]FDG-PET/CT in detecting ccRCC lesions in patients with a good or intermediate prognosis metastatic clear cell renal cell carcinoma (mccRCC) according to the International Metastatic Database Consortium (IMDC) risk model. Methods Between February 2015 and March 2018, 42 newly diagnosed mccRCC patients with good or intermediate prognosis, eligible for watchful waiting, were included. Patients underwent CT, [⁸⁹Zr]Zr-DFO-girentuximab-PET/CT and [¹⁸F]FDG-PET/CT at baseline. Scans were independently reviewed and lesions of ≥10 mm and lymph nodes of ≥15 mm at CT were analyzed. For lesions with [⁸⁹Zr]Zr-DFO-girentuximab or [¹⁸F]FDG-uptake visually exceeding background uptake, maximum standardized uptake values (SUV_max) were measured. Results A total of 449 lesions were detected by ≥1 modality (median per patient: 7; ICR 4.25–12.75) of which 42% were in lung, 22% in lymph nodes and 10% in bone. Combined [⁸⁹Zr]Zr-DFO-girentuximab-PET/CT and CT detected more lesions than CT alone: 91% (95%CI: 87–94) versus 56% (95%CI: 50–62, p = 0.001), respectively, and more than CT and [¹⁸F]FDG-PET/CT combined (84% (95%CI:79–88, p < 0.005). Both PET/CTs detected more bone and soft tissue lesions compared to CT alone. Conclusions The addition of [⁸⁹Zr]Zr-DFO-girentuximab-PET/CT and [¹⁸F]FDG-PET/CT to CT increases lesion detection compared to CT alone in newly diagnosed good and intermediate prognosis mccRCC patients eligible for watchful waiting.

In contrast to primary colorectal cancer (CRC) little is known about the genomic landscape of metastasized CRC. Here we present whole genome sequencing data of metastases of 429 CRC patients participating in the pan-cancer CPCT-02 study (NCT01855477). Unsupervised clustering using mutational signature patterns highlights three major patient groups characterized by signatures known from primary CRC, signatures associated with received prior treatments, and metastasis-specific signatures. Compared to primary CRC, we identify additional putative (non-coding) driver genes and increased frequencies in driver gene mutations. In addition, we identify specific genes preferentially affected by microsatellite instability. CRC-specific 1kb-10Mb deletions, enriched for common fragile sites, and LINC00672 mutations are associated with response to treatment in general, whereas FBXW7 mutations predict poor response specifically to EGFR-targeted treatment. In conclusion, the genomic landscape of mCRC shows defined changes compared to primary CRC, is affected by prior treatments and contains features with potential clinical relevance.

Mutations in the gene coding for the estrogen receptor (ER), ESR1, have been associated with acquired endocrine resistance in patients with ER-positive metastatic breast cancer (MBC). Functional studies revealed that these ESR1 mutations lead to constitutive activity of the ER, meaning that the receptor is active in absence of its ligand estrogen, conferring resistance against several endocrine agents. While recent clinical studies reported that the occurrence of ESR1 mutations is rare in primary breast cancer tumors, these mutations are more frequently observed in metastatic tissue and circulating cell-free DNA of MBC patients pretreated with endocrine therapy. Given the assumed impact that the presence of ESR1 mutations has on outcome to endocrine therapy, assessing ESR1 mutations in MBC patients is likely to be of significant interest to further individualize treatment for MBC patients. Here, ESR1 mutation detection methods and the most relevant pre-clinical and clinical studies on ESR1 mutations regarding endocrine resistance are reviewed, with particular interest in the ultimate goal of guiding treatment decision-making based on ESR1 mutations.

Quantification of tumor‐specific variants (TSVs) in cell‐free DNA is rapidly evolving as a prognostic and predictive tool in patients with cancer. Currently, both variant allele frequency (VAF) and number of mutant molecules per mL plasma are used as units of measurement to report those TSVs. However, it is unknown to what extent both units of measurement agree and what are the factors underlying an existing disagreement. To study the agreement between VAF and mutant molecules in current clinical studies, we analyzed 1116 TSVs from 338 patients identified with next‐generation sequencing (NGS) or digital droplet PCR (ddPCR). On different study cohorts, a Deming regression analysis was performed and its 95% prediction interval was used as surrogate for the limits of agreement between VAF and number of mutant molecules per mL and to identify outliers. VAF and number of mutant molecules per mL plasma yielded greater agreement when using ddPCR than NGS. In case of discordance between VAF and number of mutant molecules per mL, insufficient molecular coverage in NGS and high cell‐free DNA concentration were the main responsible factors. We propose several optimization steps needed to bring monitoring of TSVs in cell‐free DNA to its full potential.