Study design requirements for RNA sequencing-based breast cancer diagnostics

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.NonePublishe

A Nordic initiative for a more personal and accurate diagnostic pathway for prostate cancer

Non peer reviewe

Determining breast cancer histological grade from RNA-sequencing data

BACKGROUND: The histologic grade (HG) of breast cancer is an established prognostic factor. The grade is usually reported on a scale ranging from 1 to 3, where grade 3 tumours are the most aggressive. However, grade 2 is associated with an intermediate risk of recurrence, and carries limited information for clinical decision-making. Patients classified as grade 2 are at risk of both under- and over-treatment. METHODS: RNA-sequencing analysis was conducted in a cohort of 275 women diagnosed with invasive breast cancer. Multivariate prediction models were developed to classify tumours into high and low transcriptomic grade (TG) based on gene- and isoform-level expression data from RNA-sequencing. HG2 tumours were reclassified according to the prediction model and a recurrence-free survival analysis was performed by the multivariate Cox proportional hazards regression model to assess to what extent the TG model could be used to stratify patients. The prediction model was validated in N=487 breast cancer cases from the The Cancer Genome Atlas (TCGA) data set. Differentially expressed genes and isoforms associated with HGs were analysed using linear models. RESULTS: The classification of grade 1 and grade 3 tumours based on RNA-sequencing data achieved high accuracy (area under the receiver operating characteristic curve = 0.97). The association between recurrence-free survival rate and HGs was confirmed in the study population (hazard ratio of grade 3 versus 1 was 2.62 with 95 % confidence interval = 1.04-6.61). The TG model enabled us to reclassify grade 2 tumours as high TG and low TG gene or isoform grade. The risk of recurrence in the high TG group of grade 2 tumours was higher than in low TG group (hazard ratio = 2.43, 95 % confidence interval = 1.13-5.20). We found 8200 genes and 13,809 isoforms that were differentially expressed between HG1 and HG3 breast cancer tumours. CONCLUSIONS: Gene- and isoform-level expression data from RNA-sequencing could be utilised to differentiate HG1 and HG3 tumours with high accuracy. We identified a large number of novel genes and isoforms associated with HG. Grade 2 tumours could be reclassified as high and low TG, which has the potential to reduce over- and under-treatment if implemented clinically.NonePublishe

MUC1 as a Putative Prognostic Marker for Prostate Cancer

MUC1 is expressed on the apical surface of glandular epithelium. With functions including protection, adhesion and signaling, MUC1 has been implicated in prostate cancer. There are many splice variants, the best characterized of which are MUC1/1 and MUC1/2 which are determined by a SNP (rs4072037, 3506G>A)

The Nordic Nutrition Recommendations and prostate cancer risk in the Cancer of the Prostate in Sweden (CAPS) study.

AbstractObjectiveThe Nordic Nutrition Recommendations (NNR) aim at preventing diet-associated diseases such as cancer in the Nordic countries. We evaluated adherence to the NNR in relation to prostate cancer (PC) in Swedish men, including potential interaction with a genetic risk score and with lifestyle factors.DesignPopulation-based case–control study (Cancer of the Prostate in Sweden (CAPS), 2001–2002). Using data from a semi-quantitative FFQ, we created an NNR adherence score and estimated relative risks of PC by unconditional logistic regression. Individual score components were modelled separately and potential modifying effects were assessed on the multiplicative scale.SettingFour regions in the central and northern parts of Sweden.SubjectsIncident PC patients (n 1386) and population controls (n 940), frequency-matched on age and region.ResultsNo overall association with PC was found, possibly due to the generally high adherence to the NNR score and its narrow distribution in the study population. Among individual NNR score components, high compared with low intakes of polyunsaturated fat were associated with an increased relative risk of localized PC. No formal interaction with genetic or lifestyle factors was observed, although in stratified analysis a positive association between the NNR and PC was suggested among men with a high genetic risk score but not among men with a medium or low genetic risk score.ConclusionsOur findings do not support an association between NNR adherence and PC. The suggestive interaction with the genetic risk score deserves further investigations in other study populations

Mediterranean Diet Score and prostate cancer risk in a Swedish population-based case–control study

Several individual components of the Mediterranean diet have been shown to offer protection against prostate cancer. The present study is the first to investigate the association between adherence to the Mediterranean diet and the relative risk of prostate cancer. We also explored the usefulness of the Mediterranean Diet Score (MDS) in a non-Mediterranean population. FFQ data were obtained from 1482 incident prostate cancer patients and 1108 population-based controls in the Cancer of the Prostate in Sweden (CAPS) study. We defined five MDS variants with different components or using either study-specific intakes or intakes in a Greek reference population as cut-off values between low and high intake of each component. Unconditional logistic regression was used to estimate the relative risk of prostate cancer for high and medium v. low MDS, as well as potential associations with the individual score components. No statistically significant association was found between adherence to the Mediterranean diet based on any of the MDS variants and prostate cancer risk (OR range: 0·96–1·19 for total prostate cancer, comparing high with low adherence). Overall, we found little support for an association between the Mediterranean diet and prostate cancer in this Northern European study population. Despite potential limitations inherent in the study or in the build-up of a dietary score, we suggest that the original MDS with study-specific median intakes as cut-off values between low and high intake is useful in assessing the adherence to the Mediterranean diet in non-Mediterranean populations

Efektifitas metode bervariasi terhadap hasil belajar siswa pada bidang studi PAI Di SMP Zainuddin Waru Sidoarjo

Dalam skripsi ini penulis membahas tentang Efektifitas penggunaan Metode Bervariasi Terhadap Hasil Belajar Siswa Pada Bidang Studi PAI Di SMP Zainuddin Waru Sidoarjo dengan tiga rumusan masalah sebagai berikut : 1. Bagaimana penggunaan metode bervariasi di SMP Zainuddin Waru Sidoarjo ? 2. Bagaimana hasil belajar siswa SMP Zainuddin Waru Sidoarjo ? 3. Sejauh mana efektifitas penggunaan metode bervariasi terhadap basil belajar siswa pada bidang studi PAI di SMP Zainuddin Waru Sidoarjo ? Penelitian ini merupakan penelitian kuantitatif dengan populasi berjumlah 108 siswa, yaitu siswa kelas VIII. Dalam hal ini penulis mengambil sampel 30% dari seluruh populasi yang berjumlah 108 siswa sehingga menjadi 30 siswa. Dalam menjawab permasalahan di atas, penulis menggunakan metode pengumpulan data berupa metode observasi, dokumentasi, wawancara atau interview, dan metode angket atau quesioner. Sedangkan untuk analisa data penulis menggunakan analisa data statistik product moment. Berdasarkan hasil penelitian kemudian dapat disimpulkan bahwa penggunaan metode bervariasi di SMP Zainuddin Waru Sidoarjo terbilang baik. Dan hasil belajar siswa pada bidang studi Pendidikan Agama Islam di SMP Zainuddin Waru Sidoarjo terbilang sangat baik. Kemudian dari hasil akhir statistik menunjukkan bahwa ada pengaruh yang terbilang kuat atau tinggi antara efektifitas metode bervariasi terhadaP. basil belajar siswa pada bidang studi Pendidikan Agama Islam di SMP Zainuddin Waru Sidoarjo dengan hasil 0,836

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

Sequencing-based breast cancer diagnostics have the potential to replace routine biomarkers and provide molecular characterization that enable personalized precision medicine. Here we investigate the concordance between sequencing-based and routine diagnostic biomarkers and to what extent tumor sequencing contributes clinically actionable information. We applied DNA- and RNA-sequencing to characterize tumors from 307 breast cancer patients with replication in up to 739 patients. We developed models to predict status of routine biomarkers (ER, HER2,Ki-67, histological grade) from sequencing data. Non-routine biomarkers, including mutations in BRCA1, BRCA2 and ERBB2(HER2), and additional clinically actionable somatic alterations were also investigated. Concordance with routine diagnostic biomarkers was high for ER status (AUC = 0.95;AUC(replication) = 0.97) and HER2 status (AUC = 0.97;AUC(replication) = 0.92). The transcriptomic grade model enabled classification of histological grade 1 and histological grade 3 tumors with high accuracy (AUC = 0.98;AUC(replication) = 0.94). Clinically actionable mutations in BRCA1, BRCA2 and ERBB2(HER2) were detected in 5.5% of patients, while 53% had genomic alterations matching ongoing or concluded breast cancer studies. Sequencing-based molecular profiling can be applied as an alternative to histopathology to determine ER and HER2 status, in addition to providing improved tumor grading and clinically actionable mutations and molecular subtypes. Our results suggest that sequencing-based breast cancer diagnostics in a near future can replace routine biomarkersNonePublishe