Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers

Rantalainen, Mattias; Klevebring, Daniel; Lindberg, Johan; Ivansson, Emma; Rosin, Gustaf; Kis, Lóránd; Celebioglu, Fuat; Fredriksson, Irma; Czene, Kamila; Frisell, Jan; Hartman, Johan; Bergh, Jonas; Grönberg, Henrik

doi:10.1038/srep38037

Cited by 17 publications

(26 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…No new gene expression or RNA microarray data have been added for this study. Lists of genes and coefficients for the models are quoted in the previous publications …”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Digital image analysis of Ki67 in hot spots is superior to both manual Ki67 and mitotic counts in breast cancer

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…No new gene expression or RNA microarray data have been added for this study. Lists of genes and coefficients for the models are quoted in the previous publications …”

Section: Methodsmentioning

confidence: 99%

“…The cohort has been published previously. 16,20,21 For this study, additional data on therapy, relapse and survival status were collected between 27 December 2016 and 22 January 2017, providing up to 15 years of survival data.…”

Section: Materials and Methods P A T I E N T S A N D S A M P L E Smentioning

confidence: 99%

Digital image analysis of Ki67 in hot spots is superior to both manual Ki67 and mitotic counts in breast cancer

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…The breast cancer pilot study consisted of women with a primary breast cancer diagnosed in 2001 to 2012 in the Stockholm/Gotland regions. A subset of 307 breast tumors was successfully sequenced (12). The validation study is a nested case-control study consisting of women diagnosed with a primary breast cancer in 1997 to 2005 in the same regions and has been described in detail previously (13,14).…”

Section: Study Populationsmentioning

confidence: 99%

“…Details on methods for this section are described in the study by Rantalainen and colleagues (12) and our complete analysis pipeline is described in Supplementary Methods in the Supplement.…”

Section: Bioinformatic Processing Of Sequencing Data In Parent Clinsementioning

confidence: 99%

Molecular Differences between Screen-Detected and Interval Breast Cancers Are Largely Explained by PAM50 Subtypes

Ivansson

Klevebring

et al. 2017

Clinical Cancer Research

Self Cite

View full text Add to dashboard Cite

Interval breast cancer is of clinical interest, as it exhibits an aggressive phenotype and evades detection by screening mammography. A comprehensive picture of somatic changes that drive tumors to become symptomatic in the screening interval can improve understanding of the biology underlying these aggressive tumors. Initiated in April 2013, Clinical Sequencing of Cancer in Sweden (Clinseq) is a scientific and clinical platform for the genomic profiling of cancer. The breast cancer pilot study consisted of women diagnosed with breast cancer between 2001 and 2012 in the Stockholm/Gotland regions. A subset of 307 breast tumors was successfully sequenced, of which 113 were screen-detected and 60 were interval cancers. We applied targeted deep sequencing of cancer-related genes; low-pass, whole-genome sequencing; and RNA sequencing technology to characterize somatic differences in the genomic and transcriptomic architecture by interval cancer status. Mammographic density and PAM50 molecular subtypes were considered. In the univariate analyses, , and were significantly more frequently mutated in interval cancers than in screen-detected cancers. Acquired somatic copy number aberrations with a frequency difference of at least 15% between the two groups included gains in 17q23-q25.3 and losses in 16q24.2. Gene expression analysis identified 447 significantly differentially expressed genes, of which 120 were replicated in an independent microarray dataset. After adjusting for PAM50, most differences were no longer significant. Molecular differences by interval cancer status were observed, but they were largely explained by PAM50 subtypes. This work offers new insights into the biological differences between the two tumor groups. .

show abstract

“…Various commercially available gene signature panels, such as Oncotype DX [ 6 ] Prosigna ® [ 7 ] and MammaPrint [ 8 , 9 ] are currently available for prognostic purposes, which can predict therapy response and the likelihood of cancer recurrence. Recently, we have determined the histological grade of breast cancer using the RNA-sequencing data from 275 breast cancer patients [ 10 ]. In that study, by using RNA sequencing data, we managed to reclassify the transcriptomic grade (TG) [ 11 ] for grade 2 tumors, which is a clinically challenging group for making clinical decisions regarding therapy [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Intra-tumor heterogeneity in breast cancer has limited impact on transcriptomic-based molecular profiling

et al. 2017

Self Cite

View full text Add to dashboard Cite

BackgroundTranscriptomic profiling of breast tumors provides opportunity for subtyping and molecular-based patient stratification. In diagnostic applications the specimen profiled should be representative of the expression profile of the whole tumor and ideally capture properties of the most aggressive part of the tumor. However, breast cancers commonly exhibit intra-tumor heterogeneity at molecular, genomic and in phenotypic level, which can arise during tumor evolution. Currently it is not established to what extent a random sampling approach may influence molecular breast cancer diagnostics.MethodsIn this study we applied RNA-sequencing to quantify gene expression in 43 pieces (2-5 pieces per tumor) from 12 breast tumors (Cohort 1). We determined molecular subtype and transcriptomic grade for all tumor pieces and analysed to what extent pieces originating from the same tumors are concordant or discordant with each other. Additionally, we validated our finding in an independent cohort consisting of 19 pieces (2-6 pieces per tumor) from 6 breast tumors (Cohort 2) profiled using microarray technique. Exome sequencing was also performed on this cohort, to investigate the extent of intra-tumor genomic heterogeneity versus the intra-tumor molecular subtype classifications.ResultsMolecular subtyping was consistent in 11 out of 12 tumors and transcriptomic grade assignments were consistent in 11 out of 12 tumors as well. Molecular subtype predictions revealed consistent subtypes in four out of six patients in this cohort 2. Interestingly, we observed extensive intra-tumor genomic heterogeneity in these tumor pieces but not in their molecular subtype classifications.ConclusionsOur results suggest that macroscopic intra-tumoral transcriptomic heterogeneity is limited and unlikely to have an impact on molecular diagnostics for most patients.Electronic supplementary materialThe online version of this article (10.1186/s12885-017-3815-2) contains supplementary material, which is available to authorized users.

show abstract

Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers

Cited by 17 publications

References 46 publications

Digital image analysis of Ki67 in hot spots is superior to both manual Ki67 and mitotic counts in breast cancer

Digital image analysis of Ki67 in hot spots is superior to both manual Ki67 and mitotic counts in breast cancer

Molecular Differences between Screen-Detected and Interval Breast Cancers Are Largely Explained by PAM50 Subtypes

Intra-tumor heterogeneity in breast cancer has limited impact on transcriptomic-based molecular profiling

Contact Info

Product

Resources

About