Molecular analysis of archival diagnostic prostate cancer biopsies identifies genomic similarities in cases with progression post‐radiotherapy, and those with de novo metastatic disease
Background It is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin‐fixed paraffin‐embedded (FFPE) prostate biopsies from cohorts with post‐radiotherapy (R...
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| Published in: | The Prostate Vol. 84; no. 10; pp. 977 - 990 |
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| Abstract | Background
It is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin‐fixed paraffin‐embedded (FFPE) prostate biopsies from cohorts with post‐radiotherapy (RT) long‐term clinical follow‐up has been limited. Utilizing parallel sequencing modalities, we performed a proof‐of‐principle sequencing analysis of historical diagnostic FFPE prostate biopsies. We compared patients with (i) stable PCa (sPCa) postprimary or salvage RT, (ii) progressing PCa (pPCa) post‐RT, and (iii) de novo metastatic PCa (mPCa).
Methods
A cohort of 19 patients with diagnostic prostate biopsies (n = 6 sPCa, n = 5 pPCa, n = 8 mPCa) and mean 4 years 10 months follow‐up (diagnosed 2009–2016) underwent nucleic acid extraction from demarcated malignancy. Samples underwent 3′RNA sequencing (3′RNAseq) (n = 19), nanoString analysis (n = 12), and Illumina 850k methylation (n = 8) sequencing. Bioinformatic analysis was performed to coherently identify differentially expressed genes and methylated genomic regions (MGRs).
Results
Eighteen of 19 samples provided useable 3′RNAseq data. Principal component analysis (PCA) demonstrated similar expression profiles between pPCa and mPCa cases, versus sPCa. Coherently differentially methylated probes between these groups identified ~600 differentially MGRs. The top 50 genes with increased expression in pPCa patients were associated with reduced progression‐free survival post‐RT (p < 0.0001) in an external cohort.
Conclusions
3′RNAseq, nanoString and 850k‐methylation analyses are each achievable from historical FFPE diagnostic pretreatment prostate biopsies, unlocking the potential to utilize large cohorts of historic clinical samples. Profiling similarities between individuals with pPCa and mPCa suggests biological similarities and historical radiological staging limitations, which warrant further investigation. |
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| AbstractList | Background
It is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin‐fixed paraffin‐embedded (FFPE) prostate biopsies from cohorts with post‐radiotherapy (RT) long‐term clinical follow‐up has been limited. Utilizing parallel sequencing modalities, we performed a proof‐of‐principle sequencing analysis of historical diagnostic FFPE prostate biopsies. We compared patients with (i) stable PCa (sPCa) postprimary or salvage RT, (ii) progressing PCa (pPCa) post‐RT, and (iii) de novo metastatic PCa (mPCa).
Methods
A cohort of 19 patients with diagnostic prostate biopsies (n = 6 sPCa, n = 5 pPCa, n = 8 mPCa) and mean 4 years 10 months follow‐up (diagnosed 2009–2016) underwent nucleic acid extraction from demarcated malignancy. Samples underwent 3′RNA sequencing (3′RNAseq) (n = 19), nanoString analysis (n = 12), and Illumina 850k methylation (n = 8) sequencing. Bioinformatic analysis was performed to coherently identify differentially expressed genes and methylated genomic regions (MGRs).
Results
Eighteen of 19 samples provided useable 3′RNAseq data. Principal component analysis (PCA) demonstrated similar expression profiles between pPCa and mPCa cases, versus sPCa. Coherently differentially methylated probes between these groups identified ~600 differentially MGRs. The top 50 genes with increased expression in pPCa patients were associated with reduced progression‐free survival post‐RT (p < 0.0001) in an external cohort.
Conclusions
3′RNAseq, nanoString and 850k‐methylation analyses are each achievable from historical FFPE diagnostic pretreatment prostate biopsies, unlocking the potential to utilize large cohorts of historic clinical samples. Profiling similarities between individuals with pPCa and mPCa suggests biological similarities and historical radiological staging limitations, which warrant further investigation. It is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin-fixed paraffin-embedded (FFPE) prostate biopsies from cohorts with post-radiotherapy (RT) long-term clinical follow-up has been limited. Utilizing parallel sequencing modalities, we performed a proof-of-principle sequencing analysis of historical diagnostic FFPE prostate biopsies. We compared patients with (i) stable PCa (sPCa) postprimary or salvage RT, (ii) progressing PCa (pPCa) post-RT, and (iii) de novo metastatic PCa (mPCa).BACKGROUNDIt is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin-fixed paraffin-embedded (FFPE) prostate biopsies from cohorts with post-radiotherapy (RT) long-term clinical follow-up has been limited. Utilizing parallel sequencing modalities, we performed a proof-of-principle sequencing analysis of historical diagnostic FFPE prostate biopsies. We compared patients with (i) stable PCa (sPCa) postprimary or salvage RT, (ii) progressing PCa (pPCa) post-RT, and (iii) de novo metastatic PCa (mPCa).A cohort of 19 patients with diagnostic prostate biopsies (n = 6 sPCa, n = 5 pPCa, n = 8 mPCa) and mean 4 years 10 months follow-up (diagnosed 2009-2016) underwent nucleic acid extraction from demarcated malignancy. Samples underwent 3'RNA sequencing (3'RNAseq) (n = 19), nanoString analysis (n = 12), and Illumina 850k methylation (n = 8) sequencing. Bioinformatic analysis was performed to coherently identify differentially expressed genes and methylated genomic regions (MGRs).METHODSA cohort of 19 patients with diagnostic prostate biopsies (n = 6 sPCa, n = 5 pPCa, n = 8 mPCa) and mean 4 years 10 months follow-up (diagnosed 2009-2016) underwent nucleic acid extraction from demarcated malignancy. Samples underwent 3'RNA sequencing (3'RNAseq) (n = 19), nanoString analysis (n = 12), and Illumina 850k methylation (n = 8) sequencing. Bioinformatic analysis was performed to coherently identify differentially expressed genes and methylated genomic regions (MGRs).Eighteen of 19 samples provided useable 3'RNAseq data. Principal component analysis (PCA) demonstrated similar expression profiles between pPCa and mPCa cases, versus sPCa. Coherently differentially methylated probes between these groups identified ~600 differentially MGRs. The top 50 genes with increased expression in pPCa patients were associated with reduced progression-free survival post-RT (p < 0.0001) in an external cohort.RESULTSEighteen of 19 samples provided useable 3'RNAseq data. Principal component analysis (PCA) demonstrated similar expression profiles between pPCa and mPCa cases, versus sPCa. Coherently differentially methylated probes between these groups identified ~600 differentially MGRs. The top 50 genes with increased expression in pPCa patients were associated with reduced progression-free survival post-RT (p < 0.0001) in an external cohort.3'RNAseq, nanoString and 850k-methylation analyses are each achievable from historical FFPE diagnostic pretreatment prostate biopsies, unlocking the potential to utilize large cohorts of historic clinical samples. Profiling similarities between individuals with pPCa and mPCa suggests biological similarities and historical radiological staging limitations, which warrant further investigation.CONCLUSIONS3'RNAseq, nanoString and 850k-methylation analyses are each achievable from historical FFPE diagnostic pretreatment prostate biopsies, unlocking the potential to utilize large cohorts of historic clinical samples. Profiling similarities between individuals with pPCa and mPCa suggests biological similarities and historical radiological staging limitations, which warrant further investigation. It is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin-fixed paraffin-embedded (FFPE) prostate biopsies from cohorts with post-radiotherapy (RT) long-term clinical follow-up has been limited. Utilizing parallel sequencing modalities, we performed a proof-of-principle sequencing analysis of historical diagnostic FFPE prostate biopsies. We compared patients with (i) stable PCa (sPCa) postprimary or salvage RT, (ii) progressing PCa (pPCa) post-RT, and (iii) de novo metastatic PCa (mPCa). A cohort of 19 patients with diagnostic prostate biopsies (n = 6 sPCa, n = 5 pPCa, n = 8 mPCa) and mean 4 years 10 months follow-up (diagnosed 2009-2016) underwent nucleic acid extraction from demarcated malignancy. Samples underwent 3'RNA sequencing (3'RNAseq) (n = 19), nanoString analysis (n = 12), and Illumina 850k methylation (n = 8) sequencing. Bioinformatic analysis was performed to coherently identify differentially expressed genes and methylated genomic regions (MGRs). Eighteen of 19 samples provided useable 3'RNAseq data. Principal component analysis (PCA) demonstrated similar expression profiles between pPCa and mPCa cases, versus sPCa. Coherently differentially methylated probes between these groups identified ~600 differentially MGRs. The top 50 genes with increased expression in pPCa patients were associated with reduced progression-free survival post-RT (p < 0.0001) in an external cohort. 3'RNAseq, nanoString and 850k-methylation analyses are each achievable from historical FFPE diagnostic pretreatment prostate biopsies, unlocking the potential to utilize large cohorts of historic clinical samples. Profiling similarities between individuals with pPCa and mPCa suggests biological similarities and historical radiological staging limitations, which warrant further investigation. BackgroundIt is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin‐fixed paraffin‐embedded (FFPE) prostate biopsies from cohorts with post‐radiotherapy (RT) long‐term clinical follow‐up has been limited. Utilizing parallel sequencing modalities, we performed a proof‐of‐principle sequencing analysis of historical diagnostic FFPE prostate biopsies. We compared patients with (i) stable PCa (sPCa) postprimary or salvage RT, (ii) progressing PCa (pPCa) post‐RT, and (iii) de novo metastatic PCa (mPCa).MethodsA cohort of 19 patients with diagnostic prostate biopsies (n = 6 sPCa, n = 5 pPCa, n = 8 mPCa) and mean 4 years 10 months follow‐up (diagnosed 2009–2016) underwent nucleic acid extraction from demarcated malignancy. Samples underwent 3′RNA sequencing (3′RNAseq) (n = 19), nanoString analysis (n = 12), and Illumina 850k methylation (n = 8) sequencing. Bioinformatic analysis was performed to coherently identify differentially expressed genes and methylated genomic regions (MGRs).ResultsEighteen of 19 samples provided useable 3′RNAseq data. Principal component analysis (PCA) demonstrated similar expression profiles between pPCa and mPCa cases, versus sPCa. Coherently differentially methylated probes between these groups identified ~600 differentially MGRs. The top 50 genes with increased expression in pPCa patients were associated with reduced progression‐free survival post‐RT (p < 0.0001) in an external cohort.Conclusions3′RNAseq, nanoString and 850k‐methylation analyses are each achievable from historical FFPE diagnostic pretreatment prostate biopsies, unlocking the potential to utilize large cohorts of historic clinical samples. Profiling similarities between individuals with pPCa and mPCa suggests biological similarities and historical radiological staging limitations, which warrant further investigation. |
| Author | O'Reilly, Dawn Philippou, Yiannis Buffa, Francesca Meteora Bryant, Richard John Higgins, Geoff Stuart Lamb, Alastair David Gordon Verrill, Clare Charlton, Philip Vincent Rao, Srinivasa Rao Mills, Ian Geoffrey Hamdy, Freddie Charles |
| AuthorAffiliation | 5 Department of Pathology Oxford University Hospitals NHS Foundation Trust Oxford UK 3 Department of Urology Oxford University Hospitals NHS Foundation Trust Oxford UK 4 Nuffield Department of Surgical Sciences University of Oxford Oxford UK 2 Department of Oncology Oxford University Hospitals NHS Foundation Trust Oxford UK 1 Department of Oncology University of Oxford Oxford UK |
| AuthorAffiliation_xml | – name: 5 Department of Pathology Oxford University Hospitals NHS Foundation Trust Oxford UK – name: 2 Department of Oncology Oxford University Hospitals NHS Foundation Trust Oxford UK – name: 1 Department of Oncology University of Oxford Oxford UK – name: 3 Department of Urology Oxford University Hospitals NHS Foundation Trust Oxford UK – name: 4 Nuffield Department of Surgical Sciences University of Oxford Oxford UK |
| Author_xml | – sequence: 1 givenname: Philip Vincent surname: Charlton fullname: Charlton, Philip Vincent organization: Oxford University Hospitals NHS Foundation Trust – sequence: 2 givenname: Dawn surname: O'Reilly fullname: O'Reilly, Dawn organization: University of Oxford – sequence: 3 givenname: Yiannis surname: Philippou fullname: Philippou, Yiannis organization: Oxford University Hospitals NHS Foundation Trust – sequence: 4 givenname: Srinivasa Rao surname: Rao fullname: Rao, Srinivasa Rao organization: University of Oxford – sequence: 5 givenname: Alastair David Gordon surname: Lamb fullname: Lamb, Alastair David Gordon organization: University of Oxford – sequence: 6 givenname: Ian Geoffrey orcidid: 0000-0001-5347-5083 surname: Mills fullname: Mills, Ian Geoffrey organization: University of Oxford – sequence: 7 givenname: Geoff Stuart surname: Higgins fullname: Higgins, Geoff Stuart organization: Oxford University Hospitals NHS Foundation Trust – sequence: 8 givenname: Freddie Charles surname: Hamdy fullname: Hamdy, Freddie Charles organization: University of Oxford – sequence: 9 givenname: Clare surname: Verrill fullname: Verrill, Clare organization: Oxford University Hospitals NHS Foundation Trust – sequence: 10 givenname: Francesca Meteora surname: Buffa fullname: Buffa, Francesca Meteora email: francesca.buffa@oncology.ox.ac.uk organization: University of Oxford – sequence: 11 givenname: Richard John orcidid: 0000-0002-8330-9251 surname: Bryant fullname: Bryant, Richard John email: richard.bryant@nds.ox.ac.uk organization: University of Oxford |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38654435$$D View this record in MEDLINE/PubMed |
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| Keywords | radiotherapy prostate cancer metastasis molecular analysis diagnostic biopsies |
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| Snippet | Background
It is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent.... It is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular... BackgroundIt is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent.... |
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| SubjectTerms | Aged Biopsy Cohort Studies diagnostic biopsies Disease Progression DNA probes Genomics Humans Male Malignancy Metastases Metastasis Middle Aged molecular analysis Neoplasm Metastasis Original Patients Principal components analysis Prostate - pathology Prostate cancer Prostatic Neoplasms - genetics Prostatic Neoplasms - pathology Prostatic Neoplasms - radiotherapy Radiation therapy radiotherapy Sequence analysis |
| Title | Molecular analysis of archival diagnostic prostate cancer biopsies identifies genomic similarities in cases with progression post‐radiotherapy, and those with de novo metastatic disease |
| URI | https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fpros.24715 https://www.ncbi.nlm.nih.gov/pubmed/38654435 https://www.proquest.com/docview/3063369639 https://www.proquest.com/docview/3046513381 https://pubmed.ncbi.nlm.nih.gov/PMC11253896 |
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