Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome

Background: Breast cancer is a heterogeneous disease at the clinical and molecular level. In this study we integrate classifications extracted from five different molecular levels in order to identify integrated subtypes. Methods: Tumor tissue from 425 patients with primary breast cancer from the Oslo2 study was cut and blended, and divided into fractions for DNA, RNA and protein isolation and metabolomics, allowing the acquisition of representative and comparable molecular data. Patients were stratified into groups based on their tumor characteristics from five different molecular levels, using various clustering methods. Finally, all previously identified and newly determined subgroups were combined in a multilevel classification using a "cluster-of-clusters" approach with consensus clustering. Results: Based on DNA copy number data, tumors were categorized into three groups according to the complex arm aberration index. mRNA expression profiles divided tumors into five molecular subgroups according to PAM50 subtyping, and clustering based on microRNA expression revealed four subgroups. Reverse-phase protein array data divided tumors into five subgroups. Hierarchical clustering of tumor metabolic profiles revealed three clusters. Combining DNA copy number and mRNA expression classified tumors into seven clusters based on pathway activity levels, and tumors were classified into ten subtypes using integrative clustering. The final consensus clustering that incorporated all aforementioned subtypes revealed six major groups. Five corresponded well with the mRNA subtypes, while a sixth group resulted from a split of the luminal A subtype; these tumors belonged to distinct microRNA clusters. Gain-of-function studies using MCF-7 cells showed that microRNAs differentially expressed between the luminal A clusters were important for cancer cell survival. These microRNAs were used to validate the split in luminal A tumors in four independent breast cancer cohorts. In two cohorts the microRNAs divided tumors into subgroups with significantly different outcomes, and in another a trend was observed. Conclusions: The six integrated subtypes identified confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing knowledge of the heterogeneity of the luminal A subtype may add pivotal information to guide therapeutic choices, evidently bringing us closer to improved treatment for this largest subgroup of breast cancer.Peer reviewe

Individual and combined effects of DNA methylation and copy number alterations on miRNA expression in breast tumors

Peer reviewe

In Silico Ascription of Gene Expression Differences to Tumor and Stromal Cells in a Model to Study Impact on Breast Cancer Outcome

Breast tumors consist of several different tissue components. Despite the heterogeneity, most gene expression analyses have traditionally been performed without prior microdissection of the tissue sample. Thus, the gene expression profiles obtained reflect the mRNA contribution from the various tissue components. We utilized histopathological estimations of area fractions of tumor and stromal tissue components in 198 fresh-frozen breast tumor tissue samples for a cell type-associated gene expression analysis associated with distant metastasis. Sets of differentially expressed gene-probes were identified in tumors from patients who developed distant metastasis compared with those who did not, by weighing the contribution from each tumor with the relative content of stromal and tumor epithelial cells in their individual tumor specimen. The analyses were performed under various assumptions of mRNA transcription level from tumor epithelial cells compared with stromal cells. A set of 30 differentially expressed gene-probes was ascribed solely to carcinoma cells. Furthermore, two sets of 38 and five differentially expressed gene-probes were mostly associated to tumor epithelial and stromal cells, respectively. Finally, a set of 26 differentially expressed gene-probes was identified independently of cell type focus. The differentially expressed genes were validated in independent gene expression data from a set of laser capture microdissected invasive ductal carcinomas. We present a method for identifying and ascribing differentially expressed genes to tumor epithelial and/or stromal cells, by utilizing pathologic information and weighted t-statistics. Although a transcriptional contribution from the stromal cell fraction is detectable in microarray experiments performed on bulk tumor, the gene expression differences between the distant metastasis and no distant metastasis group were mostly ascribed to the tumor epithelial cells of the primary breast tumors. However, the gene PIP5K2A was found significantly elevated in stroma cells in distant metastasis group, compared to stroma in no distant metastasis group. These findings were confirmed in gene expression data from the representative compartments from microdissected breast tissue. The method described was also found to be robust to different histopathological procedures

Penggunaan Media Gambar Dalam Meningkatkan Kemampuan Membaca Permulaan Siswa Kelas I SDN Uwedaka Kecamatan Pagimana Kabupaten Banggai

Pokok permasalahan dalam penelitian ini adalah rendahnya tingkat kemampuan membaca permulaan siswa kelas I SDN Uwedaka dalam pembelajaran Bahasa Indonesia. Tujuan Penelitian adalah untuk meningkatkan kemampuan membaca permulaan siswa kelas I SDN Uwedaka Kecamatan Pagimana Kabupaten Banggai. Berdasarkan hasil observasi yang didapatkan masih terdapat beberapa siswa yang sama sekali belum bisa membaca. Pembelajaran membaca permulaan di SDN Uwedaka selama ini hanya menggunakan media pembelajaran yang konvensional yaitu dengan menggunakan papan tulis, pembelajaran yang hanya berpusat pada guru, penggunaan media dalam pembelajaran sebagai alat bantu masih sangat terbatas, hal ini menyebabkan kemampuan membaca permulaan yang masih rendah dan terlihat hampir 65% siswa masih mengalami kesulitan membaca dalam proses belajar mengajar. Metode yang digunakan adalah metode deskriptif kualitatif dan kuantitatif. Data kualitatif didapatkan dari hasil tes dan observasi siswa dan guru. data kuantitatif didapatkan dari hasil tes belajar. Desain penelitian ini mengacu pada desain oleh Kemmis dan Mc Taggart yang terdiri dari empat tahapan, yaitu perencanaan, pelaksanaan tindakan, observasi dan refleksi. Data dikumpulkan melalui penilaian proses dan penilaian hasil setiap akhir tindakan. Penelitian ini dilakukan dalam dua siklus. Pada siklus I diperoleh nilai rata-rata siswa yaitu sebesar 67 dengan ketuntasan belajar klasikal sebesar 40% serta daya serap 66,6%. Pada siklus II, nilai rata-rata meningkat menjadi 83 dengan ketuntasan klasikal sebesar 100% serta daya serap klasikal sebesar 83,3%. Bersarkan hasil penelitian maka dapat disimpulkan bahwa penggunaan media gambar dapat meningkatkan kemampuan membaca permulaan terhadap siswa kelas I SDN Uwedaka Kecamatan Pagimana Kabupaten Banggai

Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: a report of the international immuno‐oncology biomarker working group

The clinical significance of the tumor-immune interaction in breast cancer (BC) has been well established, and tumor-infiltrating lymphocytes (TILs) have emerged as a predictive and prognostic biomarker for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2 negative) breast cancer (TNBC) and HER2-positive breast cancer. How computational assessment of TILs can complement manual TIL-assessment in trial- and daily practices is currently debated and still unclear. Recent efforts to use machine learning (ML) for the automated evaluation of TILs show promising results. We review state-of-the-art approaches and identify pitfalls and challenges by studying the root cause of ML discordances in comparison to manual TILs quantification. We categorize our findings into four main topics; (i) technical slide issues, (ii) ML and image analysis aspects, (iii) data challenges, and (iv) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns, or design choices in the computational implementation. To aid the adoption of ML in TILs assessment, we provide an in-depth discussion of ML and image analysis including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial- and routine clinical management of patients with TNBC

Optimising post-operative radiation therapy after oncoplastic and reconstructive procedures

Surgical techniques for breast cancer have been refined over the past decades to deliver an aesthetic outcome as close as possible to the contralateral intact breast. Current surgery further allows excellent aesthetic outcome even in case of mastectomy, by performing skin sparing or nipple sparing mastectomy in combination with breast reconstruction. In this review we discuss how to optimise post-operative radiation therapy after oncoplastic and breast reconstructive procedures, including dose, fractionation, volumes, surgical margins, and boost application

Expression of C-KIT, CD24, CD44s, and COX2 in benign and non-invasive apocrine lesions of the breast

Benign apocrine metaplasia (AM) of the adult breast is a very common, but enigmatic lesion. It has been speculated that AM might be a precursor of malignancy or an indicator of a susceptibility of the breast tissue to develop neoplasia, mainly based on comparing the frequency of AM in breast cancer and non-breast cancer patients [1]. Studies using comparative genomic hybridization have supported this by showing similar molecular alterations in benign and malignant apocrine lesions [2]. Few studies, however, have compared expression of biomarkers involved in tumor progression in AM and progressively more advanced atypical apocrine lesions. The expression of C-KIT, COX2, CD24, and CD44s was evaluated by immunohistochemistry in formalin-fixed, paraffin-embedded material of 9 AM, 20 apocrine ductal intraepithelial neoplasia (DIN1c-3) and 40 atypical apocrine lesions (not qualifying for DIN1c-3) and compared to expression of the same biomarkers in adjacent normal ductal epithelium. Of the 66 apocrine lesions, 62 (94 %) did not express C-KIT compared to 4/63 (6 %) of the normal glands (Fisher's exact, p < 0.001). COX2 was expressed in a significantly higher proportion of apocrine lesions than of normal glands (49 vs. 14 %, p < 0.001), and the number of apocrine lesions positive for CD24 was found to be higher with increasing aggressiveness of the lesions (Spearman, p < 0.001). In conclusion, benign and non-invasive proliferative apocrine lesions of the breast display immuno-phenotypical characteristics previously ascribed mainly to malignant transformation. This could lend support to the theory that AM is an early step towards malignant transformation, albeit associated with slow progression to carcinoma