The level of copy number alteration (CNA), termed CNA burden, in the tumor genome is associated with recurrence of primary prostate cancer Whether CNA burden is associated with prostate cancer survival or outcomes in other cancers is unknown We analyzed the CNA landscape of conservatively treated prostate cancer in a biopsy and transurethral resection cohort, reflecting an increasingly common treatment approach We find that CNA burden is prognostic for cancer-specific death, independent of standard clinical prognosticators More broadly, we find CNA burden is significantly associated with disease-free and overall survival in primary breast, endometrial, renal clear cell, thyroid, and colorectal cancer in TCGA cohorts To assess clinical applicability, we validated these findings in an independent pan-cancer cohort of patients whose tumors were sequenced using a clinically-certified next generation sequencing assay (MSK-IMPACT), where prognostic value varied based on cancer type This prognostic association was affected by incorporating tumor purity in some cohorts Overall, CNA burden of primary and metastatic tumors is a prognostic factor, potentially modulated by sample purity and measurable by current clinical sequencing

Tumor copy number alteration burden is a pan-cancer prognostic factor associated with recurrence and death.

Purpose: Neuroblastoma (NB) is a heterogeneous disease characterized by distinct clinical features and by the presence of typical copy-number alterations (CNAs). Given the strong association of these CNA profiles with prognosis, analysis of the CNA profile at diagnosis is mandatory. Therefore, we tested whether the analysis of circulating cell-free DNA (cfDNA) present in plasma samples of patients with NB could offer a valuable alternative to primary tumor DNA for CNA profiling.Experimental Design: In 37 patients with NB, cfDNA analysis using shallow whole genome sequencing (sWGS) was compared with arrayCGH analysis of primary tumor tissue.Results: Comparison of CNA profiles on cfDNA showed highly concordant patterns, particularly in high-stage patients. Numerical chromosome imbalances as well as large and focal structural aberrations including MYCN and LIN28B amplification and ATRX deletion could be readily detected with sWGS using a low input of cfDNA.Conclusions: In conclusion, sWGS analysis on cfDNA offers a cost-effective, noninvasive, rapid, robust and sensitive alternative for tumor DNA copy-number profiling in most patients with NB. Clin Cancer Res; 23(20); 6305-14. ©2017 AACR.

/pdf/shallow-whole-genome-sequencing-on-circulating-cell-free-dna-2iz8a1cotf.pdf

Shallow Whole Genome Sequencing on Circulating Cell-Free DNA Allows Reliable Noninvasive Copy-Number Profiling in Neuroblastoma Patients

https://minerva-access.unimelb.edu.au/bitstream/handle/11343/244295/PMC7186589.pdf

Clinical and genomic insights into circulating tumor DNA-based alterations across the spectrum of metastatic hormone-sensitive and castrate-resistant prostate cancer

// Bo Ai 1 , Huiquan Liu 2 , Yu Huang 2 , Ping Peng 2 1 Department of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei, Wuhan 430030, People’s Republic of China 2 Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei, Wuhan 430030, People’s Republic of China Correspondence to: Ping Peng, email: pengpingtjh@163.com Keywords: circulating cell-free DNA, non-small cell lung cancer, prognosis, biomarker, meta-analysis Received: February 28, 2016      Accepted: May 29, 2016      Published: June 15, 2016 ABSTRACT Circulating cell-free DNA (cfDNA), which can be obtained from plasma or serum by non-invasive procedures, has showed great potential to predict treatment response and survival for cancer patients. Several studies have assessed the prognostic and predictive value of cfDNA in non-small cell lung cancer (NSCLC). However, these studies were often small and reported varying results. To address this issue, a meta-analysis was carried out. A total of 22 studies involving 2518 patients were subjected to the final analysis. Our results indicated that NSCLC patients with higher cfDNA concentration had shorter median progression-free survival (PFS) and overall survival (OS) time. In addition, high levels of cfDNA were significantly associated with poor PFS (hazard ratio or HR, 1.32; 95% CI, 1.02-1.71) and OS (HR, 1.64; 95% CI, 1.26-2.15). With respect to tumor specific mutations, we failed to reveal significant differences for PFS (HR, 1.30; 95% CI, 0.66-2.56) and OS (HR, 1.05; 95% CI, 0.49-2.25) when NSCLC patients were grouped according to KRAS genotype detected in cfDNA. However, NSCLC patients which harbored EGFR activating mutation in cfDNA had a greater chance of response to EGFR-TKIs (odds ratio or OR, 1.96; 95% CI, 1.59-2.42). No significant publication bias was detected in this study. In conclusion, cfDNA could act as a prognostic and predictive biomarker for patients with NSCLC.

/pdf/circulating-cell-free-dna-as-a-prognostic-and-predictive-4f8oao657j.pdf

Circulating cell-free DNA as a prognostic and predictive biomarker in non-small cell lung cancer.

Background The main cause of cancer death is lung cancer (LC) which usually presents at an advanced stage, but its early detection would increase the benefits of treatment. Blood is particularly favored in clinical research given the possibility of using it for relatively noninvasive analyses. Copy number variation (CNV) is a common genetic change in tumor genomes, and many studies have indicated that CNV-derived cell-free DNA (cfDNA) from plasma could be feasible as a biomarker for cancer diagnosis. Methods In this study, we determined the possibility of using chromosomal arm-level CNV from cfDNA as a biomarker for lung cancer diagnosis in a small cohort of 40 patients and 41 healthy controls. Arm-level CNV distributions were analyzed based on z score, and the machine-learning algorithm Extreme Gradient Boosting (XGBoost) was applied for cancer prediction. Results The results showed that amplifications tended to emerge on chromosomes 3q, 8q, 12p, and 7q. Deletions were frequently detected on chromosomes 22q, 3p, 5q, 16q, 10q, and 15q. Upon applying a trained XGBoost classifier, specificity and sensitivity of 100% were finally achieved in the test group (12 patients and 13 healthy controls). In addition, five-fold cross-validation proved the stability of the model. Finally, our results suggested that the integration of four arm-level CNVs and the concentration of cfDNA into the trained XGBoost classifier provides a potential method for detecting lung cancer. Conclusion Our results suggested that the integration of four arm-level CNVs and the concentration from of cfDNA integrated withinto the trained XGBoost classifier could become provides a potentially method for detecting lung cancer detection. Key points Significant findings of the study: Healthy individuals have different arm-level CNV profiles from cancer patients. Amplifications tend to emerge on chromosome 3q, 8q, 12p, 7q and deletions tend to emerge on chromosome 22q, 3p, 5q, 16q, 10q, 15q. What this study adds CfDNA concentration, arm 10q, 3q, 8q, 3p, and 22q are key features for prediction. Trained XGBoost classifier is a potential method for lung cancer detection.

https://onlinelibrary.wiley.com/doi/epdf/10.1111/1759-7714.13204

Copy number variation in plasma as a tool for lung cancer prediction using Extreme Gradient Boosting (XGBoost) classifier

Liquid biopsies, examinations of tumor components in body fluids, have shown promise for predicting clinical outcomes. To evaluate tumor-associated genomic and genetic variations in plasma cell-free DNA (cfDNA) and their associations with treatment response and overall survival, we applied whole genome and targeted sequencing to examine the plasma cfDNAs derived from 20 patients with advanced prostate cancer. Sequencing-based genomic abnormality analysis revealed locus-specific gains or losses that were common in prostate cancer, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. To estimate tumor burden in cfDNA, we developed a Plasma Genomic Abnormality (PGA) score by summing the most significant copy number variations. Cox regression analysis showed that PGA scores were significantly associated with overall survival (p < 0.04). After androgen deprivation therapy or chemotherapy, targeted sequencing showed significant mutational profile changes in genes involved in androgen biosynthesis, AR activation, DNA repair, and chemotherapy resistance. These changes may reflect the dynamic evolution of heterozygous tumor populations in response to these treatments. These results strongly support the feasibility of using non-invasive liquid biopsies as potential tools to study biological mechanisms underlying therapy-specific resistance and to predict disease progression in advanced prostate cancer.

/pdf/plasma-genetic-and-genomic-abnormalities-predict-treatment-2ylpop4qr3.pdf

Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer

Genomic variations in plasma cell free DNA differentiate early stage lung cancers from normal controls.

Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA

Androgen deprivation therapy (ADT) for hormone-sensitive prostate cancer (HSPC) and chemotherapy for castration-resistant prostate cancer (CRPC) are considered standard of care. However, there are no clinical tests or factors that can reliably predict treatment responses for the advanced prostate cancer patients. Examination of tumor component in circulation, also known as liquid biopsy, has shown promise for predicting treatment outcomes and survival. To capture the tumor-derived genomic alterations and decrease the surrogacy of using PSA measurements as is currently performed, we propose a Plasma Genomic Abnormality (PGA) score and Treatment Efficacy (TEff) index based on copy number variations as estimated by cell free DNA (cfDNA) in plasma. We first performed whole genome and targeted sequencing (NimbleGen comprehensive cancer panel) to examine plasma cfDNA for tumor-associated genetic and genomic aberrations in 10 HSPC patients receiving ADT and 10 CRPC patients receiving chemotherapy. For each patient, we tested plasma from two time points: pre-treatment and 4 months post-treatment. We then calculated the PGA score by summing the most significant genomic abnormalities with higher PGA score indicating greater tumor DNA content in cfDNA. TEff index was derived from comparison of PGA score difference between treatments with higher TEff index reflecting a better treatment response. The sequencing-based copy number analysis revealed locus-specific gains or losses including those previously reported in prostate cancers, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. We found that overall PGA score was significantly higher in CRPC patients than in HSPC patients (p<0.0005), possibly reflecting increased tumor burden during the disease progression. Patients with low TEff index often demonstrated poor response to treatments, and patients with high initial PGA score or low TEff index tended to have poor overall survival. As examples of the PGA-based TEff associations with outcome we presented three CRPC patients including two with neuro-endocrine origin (small cell carcinoma). Comparison of mutational profiles between pre- and post-treatments showed that treatments caused more diverse gene mutations, in particular, in the genes involving androgen biosynthesis, AR activation, DNA repair and chemotherapy resistance, suggesting subclonal evolution of heterogeneous tumor genomes in response to these treatments. Our results strongly support the feasibility of using non-invasive liquid biopsy as a potential powerful tool to study biological mechanisms underlying therapy-specific resistance and monitor disease progression in the advanced prostate cancer. Further studies are needed to develop and validate the genomics-based PGA score and TEff index for clinical applications.

Citation Format: Liang Wang, Shu Xia, Meijun Du, Rachel Ditmar, Tiezheng Yuan, Yongchen Guo, Yuan Wang, Adam Lee, Michael Tschannen, Elizabeth Worthey, Howard Jacobs, Chiang-Ching Huang, Manish Kohli. Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5231. doi:10.1158/1538-7445.AM2015-5231

Abstract 5231: Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer

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Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer

Genomic variations in plasma cell free DNA differentiate early stage lung cancers from normal controls.

Abstract 5231: Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer