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Shows supplementary methods

shows an estimation of copanlisib exposure variables following first infusion or at first tumor size assessment

shows plasma biomarkers with decreased levels compared to baseline following copanlisib infusion

shows copanlisib plasma concentration over time following infusion during the first week

shows the correlation between different PK parameters and percentage change in tumor size from baseline

shows plasma analytes associated with the maximum change in tumor area

shows baseline PI3K isoform and PTEN data for lymphoma and solid tumor cohorts

Table 1: samples included in the RNAseq analysis Figure 1: consort flow diagram Table 2: Comparison of patients' characteristics of the subset of patients included in the RNA-seq analysis and patients recruited in the DECISION study Figure 2: Progression-free survival of the subgroup of patients included in the RNA-seq analysis. Table 3: Pathways_GO_analysis Figure 3: Kaplan-Meyer curves of the three RNA expression groups regarding treatment group in DECISION trial. Figure 4: A,B,C: PFS in papillary, follicular and poorly differentiated histologies, respectively; D,E,F: OS in papillary, follicular and poorly differentiated histologies, respectively Figure 5: Overall survival (OS) analysis based on RNA expression profile from TCGA data of papillary thyroid cancer (Cell, 2014) Figure 6: Analyses based on 121 angiogenesisrelated genes

shows changes in plasma levels of metabolic and immune cell markers following treatment with copanlisib

shows mean systolic blood pressure in patients receiving copanlisib over the first 24 hours

Several biomarkers have been suggested to have prognostic value in differentiated thyroid carcinomas (DTC) with no validation in the refractory setting, including all tumor subtypes. We aim to correlate RNA expression profiles with survival based on patients included in the DECISION trial. We obtained 247 samples from the 417 patients included in the DECISION study and performed RNAseq analysis (77 million paired-end reads for each sample on HiSeq2000). After quality control, 125 samples were included in the secondary analysis and mapped against the human reference genome (GRCh38) with STAR (v2.5.1b) using ENCODE parameter. Survival analysis was calculated using the Kaplan–Meier method and log-rank test was used for statistical comparison. In this post hoc analysis, we identified three groups of tumors based on their gene expression profile: BRAF-like, RAS-like, and non-BRAF-non-RAS-like (NoBRaL). No significant correlation with sorafenib responders was observed. However, we identified a statistically significant correlation between the RNA-expression profiles and progression-free survival. The BRAF-like profile had a significantly better outcome compared with RAS-like and NoBRaL (11.8, 6.2, and 5.5 months, respectively) [HR: 0.31, 95% confidence interval (CI), 0.17–0.60; P < 0.001 and HR: 0.36 (95% CI, 0.21–0.63); P < 0.001] and HR: 0.36 (95% CI, 0.21–0.63; P < 0.001) and maintained significance as an independent prognostic factor for overall survival in the multivariate analysis for papillary thyroid cancers. To our knowledge, this is the first comprehensive RNA-seq analysis of all histologic subtypes of DTC. The RNA expression profiles identified may suggest a new prognostic parameter to be considered before recommendation of systemic therapies or the design of stratification factors for future clinical trials.

The PI3K inhibitor copanlisib has efficacy and manageable safety in patients with indolent lymphoma and solid tumors. Pharmacodynamic effects relative to copanlisib dose and plasma exposure were evaluated. Patients with lymphoma or solid tumors received copanlisib 0.4 or 0.8 mg/kg on days 1, 8, and 15 of a 28-day cycle. Primary variables were maximum changes in phosphorylated AKT (pAKT) levels in platelet-rich plasma (PRP) and plasma glucose. Other evaluations included PI3K signaling markers and T-lymphocytes in paired tumor biopsies, the relationship between estimated plasma exposure and pharmacodynamic markers, response, and safety. Sixty-three patients received copanlisib. PRP pAKT levels showed sustained reductions from baseline following copanlisib [median inhibition: 0.4 mg/kg, 73.8% (range −94.9 to 144.0); 0.8 mg/kg, 79.6% (range −96.0 to 408.0)]. Tumor pAKT was reduced versus baseline with copanlisib 0.8 mg/kg in paired biopsy samples (P < 0.05). Dose-related transient plasma glucose elevations were observed. Estimated copanlisib plasma exposure significantly correlated with changes in plasma pAKT and glucose metabolism markers. There were two complete responses and six partial responses; seven of eight responders received copanlisib 0.8 mg/kg. Adverse events (all grade) included hyperglycemia (52.4%), fatigue (46.0%), and hypertension (41.3%). Copanlisib demonstrated dose-dependent pharmacodynamic evidence of target engagement and PI3K pathway modulation/inhibition in tumor and immune cells. Results support the use of copanlisib 0.8 mg/kg (or flat-dose equivalent of 60 mg) in solid tumors and lymphoma, and provide a biomarker hypothesis for studies of copanlisib combined with immune checkpoint inhibitors (NCT03711058).

Molecular markers of sorafenib efficacy in patients with metastatic renal cell carcinoma (mRCC) are not available. The purpose of this study was to discover genetic markers of survival in patients with mRCC treated with sorafenib. Germline variants from 56 genes were genotyped in 295 patients with mRCC. Variant-overall survival (OS) associations were tested in multivariate regression models. Mechanistic studies were conducted to validate clinical associations. VEGFA rs1885657, ITGAV rs3816375, and WWOX rs8047917 (sorafenib arm), and FLT4 rs307826 and VEGFA rs3024987 (sorafenib and placebo arms combined) were associated with shorter OS. FLT4 rs307826 increased VEGFR-3 phosphorylation, membrane trafficking, and receptor activation. VEGFA rs1885657 and rs58159269 increased transcriptional activity of the constructs containing these variants in endothelial and RCC cell lines, and VEGFA rs58159269 increased endothelial cell proliferation and tube formation. FLT4 rs307826 and VEGFA rs58159269 led to reduced sorafenib cytotoxicity. Genetic variation in VEGFA and FLT4 could affect survival in sorafenib-treated patients with mRCC. These markers should be examined in additional malignancies treated with sorafenib and in other angiogenesis inhibitors used in mRCC.Significance:Clinical and mechanistic data identify germline genetic variants in VEGFA and FLT4 as markers of survival in patients with metastatic renal cell carcinoma.

Genotyped genes.

Expression of WT and T494A VEGFR-3 in HUVECs (A) and replication of phosphorylation experiments testing the effect of FLT4 rs307826 (A>G, T494A) on VEGFR-3 phosphorylation (B).

Study schematic for patients genotyped in this study.

SNP selection criteria, imputation and bioinformatic analyses

Kaplan-Meier plots of genetic variants versus PFS.

Bioinformatic analyses.

Effects of VEGFA rs58159269 (T>C) on endothelial cell proliferation in sunitinib.

T494A is located in the 5th Ig-like domain of VEGFR-3.

No biomarkers are available to predict toxicities induced by VEGFR TKIs. This study aimed to identify markers of toxicities induced by these drugs using a discovery-validation approach. The discovery set included 140 sorafenib-treated cancer patients (TARGET study) genotyped for SNPs in 56 genes. The most significant SNPs associated with grade ≥2 hypertension, diarrhea, dermatologic toxicities, and composite toxicity (any one of the toxicities) were tested for association with grade ≥2 toxicity in a validation set of 201 sorafenib-treated patients (Alliance/CALGB 80802). The validated SNP was tested for association with grade ≥2 toxicity in 107 (LCCC 1029) and 82 (Italian cohort) regorafenib-treated patients. SNP-toxicity associations were evaluated using logistic regression, and a meta-analysis between the studies was performed by inverse variance. Variant rs4864950 in KDR increased the risk of grade ≥2 composite toxicity in TARGET, Alliance/CALGB 80802, and the Italian cohort (meta-analysis p=6.79×10(−4), OR=2.01, 95% CI 1.34–3.01). We identified a predictor of toxicities induced by VEGFR TKIs.

Molecular markers of sorafenib efficacy in metastatic renal cell carcinoma (mRCC) patients are not available. The purpose of this study was to discover genetic markers of survival in mRCC patients treated with sorafenib. Germline variants from 56 genes were genotyped in 295 mRCC patients. Variant-overall survival (OS) associations were tested in multivariate regression models. Mechanistic studies were conducted to validate clinical associations. VEGFA rs1885657, ITGAV rs3816375, and WWOX rs8047917 (sorafenib arm), and FLT4 rs307826 and VEGFA rs3024987 (sorafenib and placebo arms combined) were associated with shorter OS. FLT4 rs307826 increased VEGFR-3 phosphorylation, membrane trafficking and receptor activation. VEGFA rs1885657 and rs58159269 increased transcriptional activity of the constructs containing these variants in endothelial and RCC cell lines, and VEGFA rs58159269 increased endothelial cell proliferation and tube formation. FLT4 rs307826 and VEGFA rs58159269 led to reduced sorafenib cytotoxicity. Genetic variation in VEGFA and FLT4 could affect survival in sorafenib-treated mRCC patients. These markers should be examined in additional malignancies treated with sorafenib, and in other angiogenesis inhibitors used in mRCC.