Fc γ receptor IIB (FcγRIIB) is an inhibitory molecule capable of reducing antibody immunotherapy efficacy. We hypothesized its expression could confer resistance in patients with diffuse large B-cell lymphoma (DLBCL) treated with anti-CD20 monoclonal antibody (mAb) chemoimmunotherapy, with outcomes varying depending on mAb (rituximab [R]/obinutuzumab [G]) because of different mechanisms of action. We evaluated correlates between FCGR2B messenger RNA and/or FcγRIIB protein expression and outcomes in 3 de novo DLBCL discovery cohorts treated with R plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) reported by Arthur, Schmitz, and Reddy, and R-CHOP/G-CHOP-treated patients in the GOYA trial (NCT01287741). In the discovery cohorts, higher FCGR2B expression was associated with significantly shorter progression-free survival (PFS; Arthur: hazard ratio [HR], 1.09; 95% confidence interval [CI], 1.01-1.19; P = .0360; Schmitz: HR, 1.13; 95% CI, 1.02-1.26; P = .0243). Similar results were observed in GOYA with R-CHOP (HR, 1.26; 95% CI, 1.00-1.58; P = .0455), but not G-CHOP (HR, 0.91; 95% CI, 0.69-1.20; P = .50). A nonsignificant trend that high FCGR2B expression favored G-CHOP over R-CHOP was observed (HR, 0.67; 95% CI, 0.44-1.02; P = .0622); however, low FCGR2B expression favored R-CHOP (HR, 1.58; 95% CI, 1.00-2.50; P = .0503). In Arthur and GOYA, FCGR2B expression was associated with tumor FcγRIIB expression; correlating with shorter PFS for R-CHOP (HR, 2.17; 95% CI, 1.04-4.50; P = .0378), but not G-CHOP (HR, 1.37; 95% CI, 0.66-2.87; P = .3997). This effect was independent of established prognostic biomarkers. High FcγRIIB/FCGR2B expression has prognostic value in R-treated patients with DLBCL and may confer differential responsiveness to R-CHOP/G-CHOP.
The management of metastatic urothelial cancer is rapidly evolving since immune checkpoint inhibitors were introduced. We present the case of a patient with metastatic upper tract urothelial cancer who had a complete response to durvalumab and tremelimumab. This patient then developed multiple non-invasive papillary bladder tumours. Next-generation sequencing revealed that the tumours shared ancestry with the upper tract cancer, although there were key differences, most notably the presence of a TP53 missense mutation in the upper tract disease that was absent in the bladder tumours. This illustrates an important practice point in the management of exceptional responders to checkpoint inhibitors.
This study examined associations between childhood maltreatment, colonial harms and sex/drug-related risks for HIV and hepatitis C virus (HCV) infection among young Indigenous people who use drugs.
Cyclin-dependent kinase 10 (CDK10) is a CDC2-related serine/threonine kinase involved in cellular processes including cell proliferation, transcription regulation and cell cycle regulation. CDK10 has been identified as both a candidate tumor suppressor in hepatocellular carcinoma, biliary tract cancers and gastric cancer, and a candidate oncogene in colorectal cancer (CRC). CDK10 has been shown to be specifically involved in modulating cancer cell proliferation, motility and chemosensitivity. Specifically, in CRC, it may represent a viable biomarker and target for chemoresistance. The development of therapeutics targeting CDK10 has been hindered by lack a specific small molecule inhibitor for CDK10 kinase activity, due to a lack of a high throughput screening assay. Recently, a novel CDK10 kinase activity assay has been developed, which will aid in the development of small molecule inhibitors targeting CDK10 activity. Discovery of a small molecular inhibitor for CDK10 would facilitate further exploration of its biological functions and affirm its candidacy as a therapeutic target, specifically for CRC.
Prostate cancer is a significant cause of cancer mortality. It has been well-established that certain germline pathogenic variants confer both an increased risk of being diagnosed with prostate cancer and dying of prostate cancer.1 There are exciting developments in both the availability of genetic testing and opportunities for improved treatment of patients. On August 19, 2020, the Princess Margaret Cancer Centre in Toronto, Ontario, hosted a virtual retreat, bringing together international experts in urology, medical oncology, radiation oncology, medical genetics, and translational research, as well as a patient representative. We are pleased to provide this manuscript as a review of those proceedings for Canadian clinicians.
Progress in defining genomic fitness landscapes in cancer, especially those defined by copy number alterations (CNAs), has been impeded by lack of time-series single-cell sampling of polyclonal populations and temporal statistical models. Here we generated 42,000 genomes from multi-year time-series single-cell whole-genome sequencing of breast epithelium and primary triple-negative breast cancer (TNBC) patient-derived xenografts (PDXs), revealing the nature of CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy. Using a new Wright-Fisher population genetics model to infer clonal fitness, we found that TP53 mutation alters the fitness landscape, reproducibly distributing fitness over a larger number of clones associated with distinct CNAs. Furthermore, in TNBC PDX models with mutated TP53, inferred fitness coefficients from CNA-based genotypes accurately forecast experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDXs resulted in cisplatin-resistant clones emerging from low-fitness phylogenetic lineages in the untreated setting. Conversely, high-fitness clones from treatment-naive controls were eradicated, signalling an inversion of the fitness landscape. Finally, upon release of drug, selection pressure dynamics were reversed, indicating a fitness cost of treatment resistance. Together, our findings define clonal fitness linked to both CNA and therapeutic resistance in polyclonal tumours.
Purpose: In the placebo-controlled SPARTAN study, apalutamide added to androgen-deprivation therapy (ADT) improved metastasis-free survival, second progression-free survival, and overall survival (OS) in patients with nonmetastatic castration-resistant prostate cancer (nmCRPC). Mechanisms of resistance to apalutamide in nmCRPC require evaluation.
Experimental design: In a subset of patients from SPARTAN, aberrations were assessed at baseline and end of study treatment (EOST) using targeted next-generation sequencing or quantitative reverse transcription PCR. Circulating tumor (ct)DNA levels were assessed qualitatively. Select aberrations in androgen receptor (AR) and other common PC-driving genes were detected and summarized by treatment group; genomic aberrations were summarized in ctDNA-positive samples. Association between detection of aberrations in all patients and outcomes was assessed using Cox proportional-hazards models and multivariate analysis.
Results: In 247 patients, the overall prevalence of ctDNA, AR aberrations, and TP53 inactivation increased from baseline (40.6%, 13.6%, 22.2%) to EOST (57.1%, 25.4%, 35.0%) and was comparable between treatment groups at EOST. In patients who received subsequent androgen signaling inhibition after study treatment, detectable biomarkers at EOST were significantly associated with poor outcomes: ctDNA with PFS2 or OS [HR = 2.01 or 2.17, respectively; P < 0.0001 for both], any AR aberration with PFS2 [1.74; P = 0.024], and TP53 or BRCA2 inactivation with OS [2.06; P = 0.003; or 3.1; P <0.0001].
Conclusions: Apalutamide plus ADT did not increase detectable AR/non-AR aberrations over ADT alone. Detectable ctDNA, AR aberrations, and TP53/BRCA2 inactivation at EOST were associated with poor outcomes in patients treated with first subsequent androgen signaling inhibitor.
Sarcomatoid mesothelioma is an aggressive malignancy that can be challenging to distinguish from benign spindle cell mesothelial proliferations based on biopsy, and this distinction is crucial to patient treatment and prognosis. A novel deep learning based classifier may be able to aid pathologists in making this critical diagnostic distinction. SpindleMesoNET was trained on cases of malignant sarcomatoid mesothelioma and benign spindle cell mesothelial proliferations. Performance was assessed through cross-validation on the training set, on an independent set of challenging cases referred for expert opinion ('referral' test set), and on an externally stained set from outside institutions ('externally stained' test set). SpindleMesoNET predicted the benign or malignant status of cases with AUC's of 0.932, 0.925, and 0.989 on the cross-validation, referral and external test sets, respectively. The accuracy of SpindleMesoNET on the referral set cases (92.5%) was comparable to the average accuracy of 3 experienced pathologists on the same slide set (91.7%). We conclude that SpindleMesoNET can accurately distinguish sarcomatoid mesothelioma from benign spindle cell mesothelial proliferations. A deep learning system of this type holds potential for future use as an ancillary test in diagnostic pathology.
Single-arm trials are common in precision oncology. Owing to the lack of randomized counterfactual, resultant data are not amenable to comparative outcomes analyses. Difference-in-difference (DID) methods present an opportunity to generate causal estimates of time-varying treatment outcomes. Using DID, our study estimates within-cohort effects of genomics-informed treatment versus standard care on clinical and cost outcomes.
As the year 2020 came to a close, several new strains have been reported of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the agent responsible for the coronavirus disease 2019 (COVID-19) pandemic that has afflicted us all this past year. However, it is difficult to comprehend the scale, in sequence space, geographical location and time, at which SARS-CoV-2 mutates and evolves in its human hosts. To get an appreciation for the rapid evolution of the coronavirus, we built interactive scalable vector graphics maps that show daily nucleotide variations in genomes from the six most populated continents compared to that of the initial, ground-zero SARS-CoV-2 isolate sequenced at the beginning of the year.