Phase I dose-escalation study of copanlisib in combination with gemcitabine or cisplatin plus gemcitabine in patients with advanced cancer.

BACKGROUND: Copanlisib is a pan-class I phosphatidylinositol 3-kinase (PI3K) inhibitor with predominant PI3K-α/δ activity that has demonstrated clinical activity and manageable safety when administered as monotherapy in a phase II study. Combination therapy may overcome compensatory signalling that could occur with PI3K pathway inhibition, resulting in enhanced inhibitory activity, and preclinical studies of copanlisib with gemcitabine have demonstrated potent anti-tumour activity in vivo. METHODS: A phase I, open-label, dose-escalation study to evaluate the safety, tolerability and recommended phase II dose (RP2D) of copanlisib with gemcitabine or with cisplatin plus gemcitabine (CisGem) in patients with advanced malignancies, including an expansion cohort in patients with biliary tract cancer (BTC) at the RP2D of copanlisib plus CisGem. Copanlisib and gemcitabine were administered on days 1, 8 and 15 of a 28-day cycle; maximum tolerated dose (MTD) and RP2D of copanlisib were determined. Copanlisib plus CisGem was administered on days 1 and 8 of a 21-day cycle; pharmacokinetics and biomarkers were assessed. RESULTS: Fifty patients received treatment as follows: dose-escalation cohorts, n=16; copanlisib plus CisGem cohort, n=14; and BTC expansion cohort, n=20. Copanlisib 0.8 mg kg-1 plus gemcitabine was the MTD and RP2D for both combinations. Common treatment-emergent adverse events included nausea (86%), hyperglycaemia (80%) and decreased platelet count (80%). Copanlisib exposure displayed a dose-proportional increase. No differences were observed upon co-administration of CisGem. Response rates were as follows: copanlisib plus gemcitabine, 6.3% (one partial response in a patient with peritoneal carcinoma); copanlisib plus CisGem, 12% (one complete response and three partial responses all in patients with BTC (response rate 17.4% in patients with BTC)). Mutations were detected in PIK3CA (1 out of 43), KRAS (10 out of 43) and BRAF (2 out of 22), with phosphate and tensin homologue protein loss in 41% (12 out of 29). CONCLUSIONS: Copanlisib plus CisGem demonstrated a manageable safety profile, favourable pharmacokinetics, and potentially promising clinical response.

A phase Ib dose-escalation study of the MEK inhibitor trametinib in combination with the PI3K/mTOR inhibitor GSK2126458 in patients with advanced solid tumors.

Introduction This Phase Ib trial investigated the safety, tolerability, and recommended phase 2 dose for the pan-PI3K/mTOR inhibitor, GSK2126458 (GSK458), and trametinib combination when administered to patients with advanced solid tumors. Patients and Methods Patients with advanced solid tumors received escalating doses of GSK458 (once or twice daily, and continuous or intermittent) and trametinib following a zone-based 3 + 3 design to determine the maximum tolerated dose (MTD). Assessments included monitoring for adverse events and response, and evaluating pharmacokinetic (PK) measures. Archival tissue and circulating free DNA samples were collected to assess biomarkers of response in the PI3K and RAS pathways. Results 57 patients were enrolled onto the continuous dosing cohort and 12 patients onto an intermittent BID dosing cohort. Two MTDs were established for the continuous daily dosing: 2 mg of GSK458 with 1.0 mg of trametinib or 1.0 mg of GSK458 with 1.5 mg of trametinib; no MTD was determined in the intermittent dosing cohort. The most frequent adverse events were rash (74 %) and diarrhea (61 %). Dose interruptions due to adverse events occurred in 42 % of patients. No significant PK interaction was observed. One patient achieved partial response and 12 patients had stable disease >16 weeks. Mutations in RAS/RAF/PI3K were detected in 70 % of patients, but no pattern emerged between response and mutational status. Conclusion GSK458 plus trametinib is poorly tolerated, due to skin and GI-related toxicities. Responses were minimal, despite enrichment for PI3K/RAS pathway driven tumors, which may be due to overlapping toxicities precluding sufficient dose exposure.

Biobanks and personalized medicine.

We provide a mini-review of how biobanks can support clinical genetics in the era of personalized medicine. We discuss types of biobanks, including disease specific and general biobanks not focused on one disease. We present considerations in setting up a biobank, including consenting and governance, biospecimens, risk factor and related data, informatics, and linkage to electronic health records for phenotyping. We also discuss the uses of biobanks and ongoing considerations, including genotype-driven recruitment, investigations of gene-environment associations, and the re-use of data generated from studies. Finally, we present a brief discussion of some of the unresolved issues, such as return of research results and sustaining biobanks over time. In summary, carefully designed biobanks can provide critical research and infrastructure support for clinical genetics in the era of personalized medicine.

A phase Ib/II dose expansion study of subcutaneous sasanlimab in patients with locally advanced or metastatic non-small-cell lung cancer and urothelial carcinoma.

BACKGROUND: Sasanlimab is an antibody to the programmed cell death protein 1 receptor. We report updated data of subcutaneous sasanlimab in non-small-cell lung cancer (NSCLC) and urothelial carcinoma dose expansion cohorts from a first-in-human phase Ib/II study. PATIENTS AND METHODS: Patients were ≥18 years of age with NSCLC or urothelial carcinoma, and no prior immunotherapies, who progressed on or were intolerant to systemic therapy, or for whom systemic therapy was refused or unavailable. Patients received subcutaneous sasanlimab at 300 mg every 4 weeks (q4w). Primary objectives were to evaluate safety, tolerability, and clinical efficacy by objective response rate (ORR). RESULTS: Sixty-eight and 38 patients with NSCLC and urothelial carcinoma, respectively, received subcutaneous sasanlimab. Overall, sasanlimab was well tolerated; 13.2% of patients experienced grade ≥3 treatment-related adverse events. Confirmed ORR was 16.4% and 18.4% in the NSCLC and urothelial carcinoma cohorts, respectively. ORR was generally higher in patients with high programmed death-ligand 1 (PD-L1) expression (≥25%) and high tumor mutational burden (TMB; >75%). In the NSCLC and urothelial carcinoma cohorts, median progression-free survival (PFS) was 3.7 and 2.9 months, respectively; corresponding median overall survival (OS) was 14.7 and 10.9 months. Overall, longer median PFS and OS correlated with high PD-L1 expression and high TMB. Longer median PFS and OS were also associated with T-cell inflamed gene signature in the urothelial carcinoma cohort. CONCLUSIONS: Subcutaneous sasanlimab at 300 mg q4w was well tolerated with promising clinical efficacy observed. Phase II and III clinical trials of sasanlimab are ongoing to validate clinical benefit. Subcutaneous sasanlimab may be a potential treatment option for patients with NSCLC or urothelial carcinoma.

Different cellular p16(INK4a) localisation may signal different survival outcomes in head and neck cancer.

BACKGROUND: Recently, the management of head and neck squamous cell carcinoma (HNSCC) has focused considerable attention on biomarkers, which may influence outcomes. Tests for human papilloma infection, including direct assessment of the virus as well as an associated tumour suppressor gene p16, are considered reproducible. Tumours from familial melanoma syndromes have suggested that nuclear localisation of p16 might have a further role in risk stratification. We hypothesised p16 staining that considered nuclear localisation might be informative for predicting outcomes in a broader set of HNSCC tumours not limited to the oropharynx, human papilloma virus (HPV) status or by smoking status. METHODS: Patients treated for HNSCC from 2002 to 2006 at UNC (University of North Carolina at Chapel Hill) hospitals that had banked tissue available were eligible for this study. Tissue microarrays (TMA) were generated in triplicate. Immunohistochemical (IHC) staining for p16 was performed and scored separately for nuclear and cytoplasmic staining. Human papilloma virus staining was also carried out using monoclonal antibody E6H4. p16 expression, HPV status and other clinical features were correlated with progression-free (PFS) and overall survival (OS). RESULTS: A total of 135 patients had sufficient sample for this analysis. Median age at diagnosis was 57 years (range 20-82), with 68.9% males, 8.9% never smokers and 32.6% never drinkers. Three-year OS rate and PFS rate was 63.0% and 54.1%, respectively. Based on the p16 staining score, patients were divided into three groups: high nuclear, high cytoplasmic staining group (HN), low nuclear, low cytoplasmic staining group (LS) and high cytoplasmic, low nuclear staining group (HC). The HN and the LS groups had significantly better OS than the HC group with hazard ratios of 0.10 and 0.37, respectively, after controlling for other factors, including HPV status. These two groups also had significantly better PFS than the HC staining group. This finding was consistent for sites outside the oropharynx and did not require adjustment for smoking status. CONCLUSION: Different p16 protein localisation suggested different survival outcomes in a manner that does not require limiting the biomarker to the oropharynx and does not require assessment of smoking status.

PREDICT Plus: development and validation of a prognostic model for early breast cancer that includes HER2.

BACKGROUND: Predict (www.predict.nhs.uk) is an online, breast cancer prognostication and treatment benefit tool. The aim of this study was to incorporate the prognostic effect of HER2 status in a new version (Predict+), and to compare its performance with the original Predict and Adjuvant!. METHODS: The prognostic effect of HER2 status was based on an analysis of data from 10 179 breast cancer patients from 14 studies in the Breast Cancer Association Consortium. The hazard ratio estimates were incorporated into Predict. The validation study was based on 1653 patients with early-stage invasive breast cancer identified from the British Columbia Breast Cancer Outcomes Unit. Predicted overall survival (OS) and breast cancer-specific survival (BCSS) for Predict+, Predict and Adjuvant! were compared with observed outcomes. RESULTS: All three models performed well for both OS and BCSS. Both Predict models provided better BCSS estimates than Adjuvant!. In the subset of patients with HER2-positive tumours, Predict+ performed substantially better than the other two models for both OS and BCSS. CONCLUSION: Predict+ is the first clinical breast cancer prognostication tool that includes tumour HER2 status. Use of the model might lead to more accurate absolute treatment benefit predictions for individual patients.

Centrosome-related genes, genetic variation, and risk of breast cancer.

Centrosome amplification has been detected in premalignant lesions and in situ tumors in the breast and in over 70% of invasive breast tumors, and has been associated with aneuploidy and tumor development. Based on these observations, the contribution of commonly inherited genetic variation in candidate genes related to centrosome structure and function to breast cancer risk was evaluated in an association study. Seven-hundred and 82 single nucleotide polymorphisms (SNPs) from 101 centrosomal genes were analyzed in 798 breast cancer cases and 843 controls from the Mayo Clinic Breast Cancer Study to assess the association between these SNPs (both individually and combined) and risk of breast cancer in this population. Eleven SNPs out of 782 from six genes displayed associations with breast cancer risk (P < 0.01). Haplotypes in five genes also displayed significant associations with risk. A two SNP combination of rs10145182 in NIN and rs2134808 in the TUBG1 locus (P-interaction = 0.00001), suggested SNPs in mediators of microtubule nucleation from the centrosome contribute to breast cancer. Evaluation of the simultaneous significance of all SNPs in the centrosome pathway suggested that the centrosome pathway is highly enriched (P = 4.76 × 10(-50)) for SNPs that are associated with breast cancer risk. Collections of weakly associated genetic variants in the centrosome pathway, rather than individual highly significantly associated SNPs, may account for a putative role for the centrosome pathway in predisposition to breast cancer.

Variation in genes required for normal mitosis and risk of breast cancer.

The down-regulation of genes involved in normal cell division can cause aberrant mitoses and increased cell death. Surviving cells exhibit aneuploidy and/or polyploidy. Since mitotic disruption has been linked with tumor development and progression, alterations in the expression or activity of these mitotic regulators may contribute to breast tumor formation. We evaluated associations between common inherited variation in these genes and breast cancer risk. Two hundred and five tagging and candidate functional single nucleotide polymorphisms in 30 genes required for normal cell division were genotyped in 798 breast cancer cases and 843 controls from the Mayo Clinic breast cancer study. Two variants in EIF3A (rs10787899 and rs3824830; P < 0.01) and four variants in SART1 (rs660118, rs679581, rs754532, and rs735942; P(trend) < or = 0.02) were significantly associated with an altered risk of breast cancer along with single variants in RRM2, PSCD3, C11orf51, CDC16, SNW1, MFAP1, and CDC2 (P < 0.05). Variation in both SART1 (P = 0.009) and EIF3A (P = 0.02) was also significant at the gene level. Analyses suggested that SART1 SNPs rs660118 and rs679581 accounted for the majority of the association of that gene with breast cancer. The observed associations between breast cancer risk and genetic variation in the SART1 and EIF3A genes that are required for maintenance of normal mitosis suggest a direct role for these genes in the development of breast cancer.

Regression analysis for comparing protein samples with 16O/18O stable-isotope labeled mass spectrometry.

MOTIVATION: Using stable isotopes in global proteome scans, labeled molecules from one sample are pooled with unlabeled molecules from another sample and subsequently subjected to mass-spectral analysis. Stable-isotope methodologies make use of the fact that identical molecules of different stable-isotope compositions are differentiated in a mass spectrometer and are represented in a mass spectrum as distinct isotopic clusters with a known mass shift. We describe two multivariable linear regression models for (16)O/(18)O stable-isotope labeled data that jointly model pairs of resolved isotopic clusters from the same peptide and quantify the abundance present in each of the two biological samples while concurrently accounting for peptide-specific incorporation rates of the heavy isotope. The abundance measure for each peptide from the two biological samples is then used in down-stream statistical analyses, e.g. differential expression analysis. Because the multivariable regression models are able to correct for the abundance of the labeled peptide that appear as an unlabeled peptide due to the inability to exchange the natural C-terminal oxygen for the heavy isotope, they are particularly advantageous for a two-step digestion/labeling procedure. We discuss how estimates from the regression model are used to quantify the variability of the estimated abundance measures for the paired samples. Although discussed in the context of (16)O/(18)O stable-isotope labeled data, the multivariable regression models are generalizable to other stable-isotope labeled technologies.