Publications by authors named "Siri H Strand"

Article Synopsis
  • A study using single-cell RNA sequencing analyzed ductal carcinoma in situ (DCIS) to understand its growth mechanisms and how it may progress to invasive cancer.
  • Researchers identified a mix of cancerous and normal epithelial cells, uncovering significant genetic diversity and different cell states driven by estrogen receptor expression.
  • The findings suggest that changes in specific cell states and loss of basement membrane integrity are linked to the transition from DCIS to invasive breast cancer, highlighting the biological complexity of preinvasive breast diseases.
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Background: Ductal carcinoma in situ (DCIS) is a non-obligate precursor to invasive breast cancer (IBC). Studies have indicated differences in DCIS outcome based on race or ethnicity, but molecular differences have not been investigated.

Methods: We examined the molecular profile of DCIS by self-reported race (SRR) and outcome groups in Black (n = 99) and White (n = 191) women in a large DCIS case-control cohort study with longitudinal follow up.

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Background: Triple-negative breast cancer (TNBC) is an aggressive subtype that exhibits a high incidence of distant metastases and lacks targeted therapeutic options. Here we explored how the epigenome contributes to matrix metalloprotease (MMP) dysregulation impacting tumor invasion, which is the first step of the metastatic process.

Methods: We combined RNA expression and chromatin interaction data to identify insulator elements potentially associated with MMP gene expression and invasion.

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Article Synopsis
  • Ductal carcinoma in situ (DCIS) is the leading precursor to invasive breast cancer (IBC) and varies in its likelihood of progressing.
  • Researchers analyzed 774 DCIS samples over 7.3 years, identifying 812 genes tied to recurrent cancer and creating a predictive classifier for recurrence.
  • The study uncovered important biological pathways related to recurrence, including proliferation and immune response, using advanced methods to create a detailed atlas of breast precancer changes.
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Ductal carcinoma in situ (DCIS) is a pre-invasive lesion that is thought to be a precursor to invasive breast cancer (IBC). To understand the changes in the tumor microenvironment (TME) accompanying transition to IBC, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) and a 37-plex antibody staining panel to interrogate 79 clinically annotated surgical resections using machine learning tools for cell segmentation, pixel-based clustering, and object morphometrics. Comparison of normal breast with patient-matched DCIS and IBC revealed coordinated transitions between four TME states that were delineated based on the location and function of myoepithelium, fibroblasts, and immune cells.

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Available tools for prostate cancer (PC) prognosis are suboptimal but may be improved by better knowledge about genes driving tumor aggressiveness. Here, we identified FRMD6 (FERM domain-containing protein 6) as an aberrantly hypermethylated and significantly downregulated gene in PC. Low FRMD6 expression was associated with postoperative biochemical recurrence in two large PC patient cohorts.

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Improved prostate cancer prognostic biomarkers are urgently needed. We previously identified the four-miRNA prognostic biomarker panel MiCaP ((miR-23a-3p × miR-10b-5p)/(miR-133a-3p × miR-374b-5p)) for prediction of biochemical recurrence (BCR) after radical prostatectomy (RP). Here, we identified an optimal numerical cut-off for MiCaP dichotomisation using a training cohort of 475 RP patients and tested this in an independent cohort of 281 RP patients (PCA281).

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Novel and minimally-invasive prostate cancer (PCa)-specific biomarkers are needed to improve diagnosis and risk stratification. Here, we investigated the biomarker potential in localized and metastatic PCa (mPCa) of methylated circulating tumor DNA (ctDNA) in plasma. Using the Marmal-aid database and in-house datasets, we identified three top candidates specifically hypermethylated in PCa tissue: and (specificity/sensitivity: 80%-100%/75-94%).

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miR-615-3p has previously been described as up-regulated in prostate cancer (PC) tissue samples compared with nonmalignant controls; however, its prognostic potential and functional role in PC remain largely unknown. In this study, we investigated the clinical and biological relevance of miR-615-3p in PC. The expression of miR-615-3p was measured in PC tissue specimens from 239 men who underwent radical prostatectomy (RP), and it was investigated if miR-615-3p could predict postoperative biochemical recurrence (BCR).

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Improved prognostic biomarkers are needed to guide personalized prostate cancer (PC) treatment decisions. Due to the prominent molecular heterogeneity of PC, multimarker panels may be more robust. Here, 25 selected top-candidate miRNA and methylation markers for PC were profiled by qPCR in malignant radical prostatectomy (RP) tissue specimens from 198 PC patients (Cohort 1, training).

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Prostate cancer (PCa) is a clinically heterogeneous disease and currently, accurate diagnostic and prognostic molecular biomarkers are lacking. This study aimed to identify novel DNA hypermethylation markers for PCa with future potential for blood-based testing. Accordingly, to search for genes specifically hypermethylated in PCa tissue samples and not in blood cells or other cancer tissue types, we performed a systematic analysis of genome-wide DNA methylation data (Infinium 450K array) available in the Marmal-aid database for 4072 malignant/normal tissue samples of various types.

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This study aimed to validate whether 5-hydroxymethylcytosine (5hmC) level in combination with ERG expression is a predictive biomarker for biochemical failure (BF) in men undergoing radical prostatectomy (RP) for prostate cancer (PCa). The study included 592 PCa patients from two consecutive Danish RP cohorts. 5hmC level and ERG expression were analyzed using immunohistochemistry in RP specimens.

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Background: The current inability to predict whether a primary prostate cancer (PC) will progress to metastatic disease leads to overtreatment of indolent PCs as well as undertreatment of aggressive PCs. Here, we explored the transcriptional changes associated with metastatic progression of multifocal hormone-naive PC.

Methods: Using total RNA-sequencing, we analysed laser micro-dissected primary PC foci (n = 23), adjacent normal prostate tissue samples (n = 23) and lymph node metastases (n = 9) from ten hormone-naive PC patients.

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Background: Prognostic tools for prostate cancer (PC) are inadequate and new molecular biomarkers may improve risk stratification. The epigenetic mark 5-hydroxymethylcytosine (5hmC) has recently been proposed as a novel candidate prognostic biomarker in several malignancies including PC. 5hmC is an oxidized derivative of 5-methylcytosine (5mC) and can be further oxidized to 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC).

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Current diagnostic and prognostic tools for prostate cancer (PC) are suboptimal, leading to overdiagnosis and overtreatment. Aberrant promoter hypermethylation of specific genes has been suggested as novel candidate biomarkers for PC that may improve diagnosis and prognosis. We here analyzed ST6GALNAC3 and ZNF660 promoter methylation in prostate tissues, and ST6GALNAC3, ZNF660, CCDC181, and HAPLN3 promoter methylation in liquid biopsies.

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Article Synopsis
  • Prostate cancer diagnosis relies on needle biopsies, which often miss cancer cases, leading to false negatives.
  • The study examined nine epigenetically altered genes in non-cancerous prostate tissue to see if they could improve cancer detection rates.
  • A four-gene methylation signature was identified that can distinguish between non-malignant tissues of patients with and without prostate cancer, showing promise for enhancing diagnostic sensitivity.
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Purpose: The lack of biomarkers that can distinguish aggressive from indolent prostate cancer has caused substantial overtreatment of clinically insignificant disease. Here, by genome-wide DNA methylome profiling, we sought to identify new biomarkers to improve the accuracy of prostate cancer diagnosis and prognosis.

Experimental Design: Eight novel candidate markers, COL4A6, CYBA, TCAF1 (FAM115A), HLF, LINC01341 (LOC149134), LRRC4, PROM1, and RHCG, were selected from Illumina Infinium HumanMethylation450 BeadChip analysis of 21 tumor (T) and 21 non-malignant (NM) prostate specimens.

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Two independent regions within HNF1B are consistently identified in prostate and ovarian cancer genome-wide association studies (GWAS); their functional roles are unclear. We link prostate cancer (PC) risk SNPs rs11649743 and rs3760511 with elevated HNF1B gene expression and allele-specific epigenetic silencing, and outline a mechanism by which common risk variants could effect functional changes that increase disease risk: functional assays suggest that HNF1B is a pro-differentiation factor that suppresses epithelial-to-mesenchymal transition (EMT) in unmethylated, healthy tissues. This tumor-suppressor activity is lost when HNF1B is silenced by promoter methylation in the progression to PC.

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Background: Prostate cancer (PC) can be stratified into distinct molecular subtypes based on TMPRSS2-ERG gene fusion status, but its potential prognostic value remains controversial. Likewise, routine clinicopathological features cannot clearly distinguish aggressive from indolent tumors at the time of diagnosis; thus, new prognostic biomarkers are urgently needed. The DNA methylation variant 5-hydroxymethylcytosine (5hmC, an oxidized derivative of 5-methylcytosine) has recently emerged as a new diagnostic and/or prognostic biomarker candidate for several human malignancies.

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Article Synopsis
  • Prostate cancer (PC) is the most common cancer diagnosed in men and a leading cause of cancer deaths in the Western world, making accurate management a significant challenge due to its wide variability in aggressiveness.
  • Current diagnostic methods lack reliable biomarkers to predict tumor progression, amplifying the need for better prognostic tools.
  • This review highlights the potential of DNA methylation biomarkers, such as PITX2 and C1orf114, showing promise in predicting PC outcomes, with ongoing research to validate their effectiveness further.*
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