Fragmentomic analysis of circulating tumor DNA-targeted cancer panels.

BACKGROUND: The isolation of cell-free DNA (cfDNA) from the bloodstream can be used to detect and analyze somatic alterations in circulating tumor DNA (ctDNA), and multiple cfDNA-targeted sequencing panels are now commercially available for Food and Drug Administration (FDA)-approved biomarker indications to guide treatment. More recently, cfDNA fragmentation patterns have emerged as a tool to infer epigenomic and transcriptomic information. However, most of these analyses used whole-genome sequencing, which is insufficient to identify FDA-approved biomarker indications in a cost-effective manner. PATIENTS AND METHODS: We used machine learning models of fragmentation patterns at the first coding exon in standard targeted cancer gene cfDNA sequencing panels to distinguish between cancer and non-cancer patients, as well as the specific tumor type and subtype. We assessed this approach in two independent cohorts: a published cohort from GRAIL (breast, lung, and prostate cancers, non-cancer, n = 198) and an institutional cohort from the University of Wisconsin (UW; breast, lung, prostate, bladder cancers, n = 320). Each cohort was split 70%/30% into training and validation sets. RESULTS: In the UW cohort, training cross-validated accuracy was 82.1%, and accuracy in the independent validation cohort was 86.6% despite a median ctDNA fraction of only 0.06. In the GRAIL cohort, to assess how this approach performs in very low ctDNA fractions, training and independent validation were split based on ctDNA fraction. Training cross-validated accuracy was 80.6%, and accuracy in the independent validation cohort was 76.3%. In the validation cohort where the ctDNA fractions were all <0.05 and as low as 0.0003, the cancer versus non-cancer area under the curve was 0.99. CONCLUSIONS: To our knowledge, this is the first study to demonstrate that sequencing from targeted cfDNA panels can be utilized to analyze fragmentation patterns to classify cancer types, dramatically expanding the potential capabilities of existing clinically used panels at minimal additional cost.

Cabazitaxel versus abiraterone or enzalutamide in poor prognosis metastatic castration-resistant prostate cancer: a multicentre, randomised, open-label, phase II trial.

BACKGROUND: Treatment of poor prognosis metastatic castration-resistant prostate cancer (mCRPC) includes taxane chemotherapy and androgen receptor pathway inhibitors (ARPI). We sought to determine optimal treatment in this setting. PATIENTS AND METHODS: This multicentre, randomised, open-label, phase II trial recruited patients with ARPI-naive mCRPC and poor prognosis features (presence of liver metastases, progression to mCRPC after <12 months of androgen deprivation therapy, or ≥4 of 6 clinical criteria). Patients were randomly assigned 1 : 1 to receive cabazitaxel plus prednisone (group A) or physician's choice of enzalutamide or abiraterone plus prednisone (group B) at standard doses. Patients could cross over at progression. The primary endpoint was clinical benefit rate for first-line treatment (defined as prostate-specific antigen response ≥50%, radiographic response, or stable disease ≥12 weeks). RESULTS: Ninety-five patients were accrued (median follow-up 21.9 months). First-line clinical benefit rate was greater in group A versus group B (80% versus 62%, P = 0.039). Overall survival was not different between groups A and B (median 37.0 versus 15.5 months, hazard ratio (HR) = 0.58, P = 0.073) nor was time to progression (median 5.3 versus 2.8 months, HR = 0.87, P = 0.52). The most common first-line treatment-related grade ≥3 adverse events were neutropenia (cabazitaxel 32% versus ARPI 0%), diarrhoea (9% versus 0%), infection (9% versus 0%), and fatigue (7% versus 5%). Baseline circulating tumour DNA (ctDNA) fraction above the cohort median and on-treatment ctDNA increase were associated with shorter time to progression (HR = 2.38, P < 0.001; HR = 4.03, P < 0.001). Patients with >30% ctDNA fraction at baseline had markedly shorter overall survival than those with undetectable ctDNA (HR = 38.22, P < 0.001). CONCLUSIONS: Cabazitaxel was associated with a higher clinical benefit rate in patients with ARPI-naive poor prognosis mCRPC. ctDNA abundance was prognostic independent of clinical features, and holds promise as a stratification biomarker.

HSD3B1 (1245A>C) germline variant and clinical outcomes in metastatic castration-resistant prostate cancer patients treated with abiraterone and enzalutamide: results from two prospective studies.

BACKGROUND: A common polymorphism (1245A>C) in the HSD3B1 gene is associated with increased de novo synthesis of androgens and worse outcomes in men treated with androgen-deprivation therapy for metastatic castration-sensitive prostate cancer. The objective of the study was to determine whether this polymorphism is associated with outcomes for metastatic castration-resistant prostate cancer (mCRPC) treated with abiraterone or enzalutamide. PATIENTS AND METHODS: A total of 547 patients treated with abiraterone or enzalutamide from two prospective cohorts were evaluated. The HSD3B1 genotype was determined by targeted sequencing and/or TaqMan single-nucleotide polymorphism genotyping. In cohort 1, patients were randomized to receive abiraterone + prednisone or enzalutamide. In cohort 2, patients received either agent according to investigator's choice. Prostate-specific antigen (PSA) response rate, time to PSA progression (TTPP), time to progression (TTP) and overall survival were determined. Associations between HSD3B1 genotypes and outcomes were evaluated via univariate Cox regression. Multivariable Cox model was used to determine the independent association of each covariate. RESULTS: The HSD3B1 variant genotype (CC) was present in 15% of patients and was associated with worse TTP [hazard ratio (HR) 1.31, 95% confidence interval (CI) 1.02-1.67, P = 0.032] and PSA response rates (48% for CC versus 62% and 65% for AA and AC, respectively [P = 0.019]), with no significant difference in TTPP (HR 1.28, 95% CI 0.99-1.66, P = 0.064). The effect of genotype was similar for treatment with abiraterone or enzalutamide with a negative test for interaction for TTPP (P = 0.997) and TTP (P = 0.749). Multivariable analysis did not show a significant association between genotype and TTP or TTPP. CONCLUSIONS: The HSD3B1 (CC) genotype was associated with shorter TTP and lower PSA response rate in patients with mCRPC treated with abiraterone or enzalutamide. However, the CC genotype did not provide prognostic information beyond that conferred by standard clinical variables, suggesting that it may not be a suitable stand-alone biomarker in mCRPC.

Multi-stressor impacts on fungal diversity and ecosystem functions in streams: natural vs. anthropogenic stress.

Biological assemblages are often subjected to multiple stressors emerging from both anthropogenic activities and naturally stressful conditions, and species' responses to simultaneous stressors may differ from those predicted based on the individual effects of each stressor alone. We studied the influence of land-use disturbance (forest drainage) on fungal decomposer assemblages and leaf decomposition rates in naturally harsh (low pH caused by black-shale dominated geology) vs. circumneutral streams. We used pyrosequencing to determine fungal richness and assemblage structure. Decomposition rates did not differ between circumneutral and naturally acidic reference sites. However, the effect of forest drainage on microbial decomposition was more pronounced in the naturally acidic streams than in circumneutral streams. Single-effect responses of fungal assemblages were mainly related to geology. Community similarity was significantly higher in the naturally acidic disturbed sites than in corresponding reference sites, suggesting that land-use disturbance simplifies fungal assemblages in naturally stressful conditions. Naturally acidic streams supported distinct fungal assemblages with many OTUs (operational taxonomic unit) unique to these streams. Our results indicate that fungal assemblages in streams are sensitive to both structural and functional impairment in response to multiple stressors. Anthropogenic degradation of naturally acidic streams may decrease regional fungal diversity and impair ecosystem functions, and these globally occurring environments therefore deserve special attention in conservation planning.

Are biological communities in naturally unproductive streams resistant to additional anthropogenic stressors?

Studies on the interactive responses to multiple simultaneously acting stressors have focused on individual or population-level responses in laboratory microcosms, while field-based studies on community-level responses are rare. We examined the influence of a natural (non-anthropogenic acidity) vs. human-induced stress (land drainage) and their interaction on species richness and spatial turnover (ß diversity) of stream diatom, bryophyte, and benthic invertebrate communities. Our four stream categories were: circumneutral reference, circumneutral impacted, naturally acidic, and naturally acidic impacted streams. We expected the most sensitive species to be present only in the circumneutral reference streams. Therefore, species richness should be highest in these streams and lowest in the naturally acidic streams additionally stressed by forest drainage. Alternatively, communities in acidic streams may consist of the most tolerant taxa that are unaffected by further stressors, species richness in these streams remaining unaffected by drainage. We also expected spatial turnover to be highest in the circumneutral near-pristine streams and lowest in the drainage-impacted acidic streams. In all three taxonomic groups, α diversity was lower in the naturally acidic than in circumneutral streams. The additional impact of the anthropogenic stress on species richness varied between groups, having no effect on diatoms, antagonistic effect on bryophytes, and additive effect on invertebrates. We also found differences in how each stressor modified ß diversity of each taxonomic group. For diatoms, ß diversity showed an overall tendency to decrease with increasing stress level, while bryophyte ß diversity responded mainly to forest drainage. Benthic invertebrate ß diversity did not differ between treatments. Our results suggest that non-additive effects among stressors need special attention to improve the understanding and management of multifactor responses in streams. Our results also argue for the primacy of a multi-taxon approach to environmental impact detection, and for the inclusion of a wide array of ecological responses, particularly community turnover, in bioassessment programs to detect responses that may go unnoticed by conventional richness-based measures.

An ancestral molecular response to nanomaterial particulates.

The varied transcriptomic response to nanoparticles has hampered the understanding of the mechanism of action. Here, by performing a meta-analysis of a large collection of transcriptomics data from various engineered nanoparticle exposure studies, we identify common patterns of gene regulation that impact the transcriptomic response. Analysis identifies deregulation of immune functions as a prominent response across different exposure studies. Looking at the promoter regions of these genes, a set of binding sites for zinc finger transcription factors C2H2, involved in cell stress responses, protein misfolding and chromatin remodelling and immunomodulation, is identified. The model can be used to explain the outcomes of mechanism of action and is observed across a range of species indicating this is a conserved part of the innate immune system.

IGFBP2 potentiates nuclear EGFR-STAT3 signaling.

Insulin-like growth factor binding protein 2 (IGFBP2) is a pleiotropic oncogenic protein that has both extracellular and intracellular functions. Despite a clear causal role in cancer development, the tumor-promoting mechanisms of IGFBP2 are poorly understood. The contributions of intracellular IGFBP2 to tumor development and progression are also unclear. Here we present evidence that both exogenous IGFBP2 treatment and cellular IGFBP2 overexpression lead to aberrant activation of epidermal growth factor receptor (EGFR), which subsequently activates signal transducer and activator of transcription factor 3 (STAT3) signaling. Furthermore, we demonstrate that IGFBP2 augments the nuclear accumulation of EGFR to potentiate STAT3 transactivation activities, via activation of the nuclear EGFR signaling pathway. Nuclear IGFBP2 directly influences the invasive and migratory capacities of human glioblastoma cells, providing a direct link between intracellular (and particularly nuclear) IGFBP2 and cancer hallmarks. These activities are also consistent with the strong association between IGFBP2 and STAT3-activated genes derived from The Cancer Genome Atlas database for human glioma. A high level of all three proteins (IGFBP2, EGFR and STAT3) was strongly correlated with poorer survival in an independent patient data set. These results identify a novel tumor-promoting function for IGFBP2 of activating EGFR/STAT3 signaling and facilitating EGFR accumulation in the nucleus, thereby deregulating EGFR signaling by two distinct mechanisms. As targeting EGFR in glioma has been relatively unsuccessful, this study suggests that IGFBP2 may be a novel therapeutic target.

Fusion genes and their discovery using high throughput sequencing.

Fusion genes are hybrid genes that combine parts of two or more original genes. They can form as a result of chromosomal rearrangements or abnormal transcription, and have been shown to act as drivers of malignant transformation and progression in many human cancers. The biological significance of fusion genes together with their specificity to cancer cells has made them into excellent targets for molecular therapy. Fusion genes are also used as diagnostic and prognostic markers to confirm cancer diagnosis and monitor response to molecular therapies. High-throughput sequencing has enabled the systematic discovery of fusion genes in a wide variety of cancer types. In this review, we describe the history of fusion genes in cancer and the ways in which fusion genes form and affect cellular function. We also describe computational methodologies for detecting fusion genes from high-throughput sequencing experiments, and the most common sources of error that lead to false discovery of fusion genes.