Additional file 4: of Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

Figure S3. Distributions of background error values by mutation type. Panels (a), (b), (c) and (d) refers to mutations from reference allele A, C, G and T respectively. Mutations are split by alternative allele and strand, (+) and (−). Note the higher error values for A > G (T > C) and C > T (G > A) mutations. Plots are bound to error values of 0.005 on the y-axis for visual clarity. (PPTX 201 kb

Additional file 1: of Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

Supplementary Methods. Details of the MutPlat pipeline. (DOCX 15 kb

Additional file 2: of Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

Figure S1. Variant allele frequency (VAF) distributions for the A, T, C, G nucleotides as calculated from 30 randomly chosen normal samples across our custom AmpliSeq panel. Only VAFs < 60% are displayed. The red lines mark VAF = 20%. (PPTX 278 kb

Additional file 6: of Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

Figure S5. Fraction of sites in our custom AmpliSeq panel sequenced at a given coverage or more. The values are calculated over 30 randomly selected ctDNA samples. Note that positions with depth of coverage less than 200 are not considered for calculating the total number of positions. The red lines represent the upper and lower bounds of coverage used in the synthetic variant test. (PPTX 64 kb

Additional file 5: of Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

Figure S4. Position-specific, allele-specific and strand-specific frequency of alternative alleles in 100 consecutive positions in the AR gene. (PPTX 116 kb

Additional file 3: of Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

Figure S2. Fraction of sites in a normal sample sequenced at a given coverage or more across our custom AmpliSeq panel. The values are calculated over 30 randomly selected samples. (PPTX 59 kb

sj-docx-1-tam-10.1177_17588359231177018 – Supplemental material for Safety of Lutetium-177 prostate-specific membrane antigen-617 (PSMA-617) radioligand therapy in the setting of severe renal impairment: a case report and literature review

Supplemental material, sj-docx-1-tam-10.1177_17588359231177018 for Safety of Lutetium-177 prostate-specific membrane antigen-617 (PSMA-617) radioligand therapy in the setting of severe renal impairment: a case report and literature review by Duncan E. K. Sutherland, Raghava Kashyap, Price Jackson, James P. Buteau, Declan G. Murphy, Brian Kelly, Lavinia Spain, Shahneen Sandhu, Arun A. Azad, Elizabeth Medhurst, Grace Kong and Michael S. Hofman in Therapeutic Advances in Medical Oncology</p

Table_4_Utomilumab in Patients With Immune Checkpoint Inhibitor-Refractory Melanoma and Non-Small-Cell Lung Cancer.pdf

Section HeadClinical/translational cancer immunotherapyBackgroundThe goal of this study was to estimate the objective response rate for utomilumab in adults with immune checkpoint inhibitor (ICI)-refractory melanoma and non–small-cell lung cancer (NSCLC).MethodsUtomilumab was dosed intravenously every 4 weeks (Q4W) and adverse events (AEs) monitored. Tumor responses by RECIST1.1 were assessed by baseline and on-treatment scans. Tumor biopsies were collected for detection of programmed cell death ligand 1, CD8, 4-1BB, perforin, and granzyme B, and gene expression analyzed by next-generation sequencing. CD8+ T cells from healthy donors were stimulated with anti-CD3 ± utomilumab and compared with control.ResultsPatients with melanoma (n=43) and NSCLC (n=20) received utomilumab 0.24 mg/kg (n=36), 1.2 mg/kg (n=26), or 10 mg/kg (n=1). Treatment-emergent AEs (TEAEs) occurred in 55 (87.3%) patients and serious TEAEs in 18 (28.6%). Five (7.9%) patients discontinued owing to TEAEs. Thirty-two (50.8%) patients experienced treatment-related AEs, mostly grade 1–2. Objective response rate: 2.3% in patients with melanoma; no confirmed responses for patients with NSCLC. Ten patients each with melanoma (23.3%) or NSCLC (50%) had stable disease; respective median (95% confidence interval, CI) progression-free survival was 1.8 (1.7–1.9) and 3.6 (1.6–6.5) months. Utomilumab exposure increased with dose. The incidences of antidrug and neutralizing antibodies were 46.3% and 19.4%, respectively. Efficacy was associated with immune-active tumor microenvironments, and pharmacodynamic activity appeared to be blunted at higher doses.ConclusionsUtomilumab was well tolerated, but antitumor activity was low in patients who previously progressed on ICIs. The potential of 4-1BB agonists requires additional study to optimize efficacy while maintaining the tolerable safety profile.</p

Supplementary Figures from The Dual Inhibition of RNA Pol I Transcription and PIM Kinase as a New Therapeutic Approach to Treat Advanced Prostate Cancer

Fig S1: Generation and characterisation of an androgen-dependent Hi-MYC epithelial line from 5-month Hi-MYC lateral prostate adenocarcinoma. Fig S2: CX-6258 does not inhibit Ribosomal RNA transcription. Fig S3: CX-6258 does not induce p53, but does induce low level p21 expression Fig S4: CX-5461 co-operates with Everolimus (RAD001) in vitro, but this does not suppress Hi-MYC tumorigenesis Fig S5: 5 month old Hi-MYC mouse prostate and body weight Fig S6: Influence of the androgen receptor on growth inhibition sensitivity</p

Supplementary text from The Dual Inhibition of RNA Pol I Transcription and PIM Kinase as a New Therapeutic Approach to Treat Advanced Prostate Cancer

Supplementary Materials and methods</p