Project description:BackgroundBreast 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.MethodsTumor 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.ResultsBased 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.ConclusionsThe 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.

Project description: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 primary breast cancer patients of the Oslo2 study was cut and blended before being divided into fractions for DNA-, RNA- and protein isolation, and metabolomics, allowing for 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 scored 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 using integrative clustering, tumors were classified into ten subtypes. The final consensus clustering incorporating all the 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 where 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 significant different outcome, and in another a trend was observed. Conclusions: The herein identified six integrated subtypes confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing the knowledge of the luminal A subtype heterogeneity may add pivotal information guiding therapeutic choices, evidently bringing us closer to more personalized treatment for this largest subgroup of breast cancer.

Project description:Recent studies identified Midkine (MDK) as playing a key role in immune regulation. In this study, we aimed to discover the clinical significance and translational relevance in prostate cancer (PCa). We retrospectively analyzed 759 PCa patients who underwent radical prostatectomy from Huashan Hospital, Fudan University (training cohort, n = 369) and Chinese Prostate Cancer Consortium (validation cohort, n = 390). A total of 325 PCa patients from The Cancer Genome Atlas (TCGA) database (external cohort) were analyzed for exploration. Immune landscape and antitumor immunity were assessed through immunohistochemistry and flow cytometry. Patient-derived explant culture system was applied for evaluating the targeting potential of MDK. We found that intratumoral MDK expression correlated with PCa progression, which indicated an unfavorable biochemical recurrence (BCR)-free survival for postoperative PCa patients. Addition of MDK expression to the postoperative risk assessment tool CAPRA-S could improve its prognostic value. Tumors with MDK abundance characterized the tumor-infiltrating CD8+ T cells with less cytotoxicity production and increased immune checkpoint expression, which were accompanied by enriched immunosuppressive contexture. Moreover, MDK inhibition could reactivate CD8+ T cell antitumor immunity. MDK mRNA expression negatively correlated with androgen receptor activity signature and positively associated with radiotherapy-related signature. In conclusion, intratumoral MDK expression could serve as an independent prognosticator for BCR in postoperative PCa patients. MDK expression impaired the antitumor function of CD8+ T cells through orchestrating an immunoevasive microenvironment, which could be reversed by MDK inhibition. Moreover, tumors with MDK enrichment possessed potential sensitivity to postoperative radiotherapy while resistance to adjuvant hormonal therapy of PCa. MDK could be considered as a potential therapeutic target for PCa.

Project description:Genetic subtypes of acute lymphoblastic leukaemia (ALL) are used to determine risk and treatment in children. 25% of precursor B-ALL cases are genetically unclassified and have intermediate prognosis. We aimed to use a genome-wide study to improve prognostic classification of ALL in children.We constructed a classifier based on gene expression in 190 children with newly diagnosed ALL (German Cooperative ALL [COALL] discovery cohort) by use of double-loop cross-validation and validated this in an independent cohort of 107 newly diagnosed patients (Dutch Childhood Oncology Group [DCOG] independent validation cohort). Hierarchical cluster analysis with classifying gene-probe sets revealed a new ALL subtype, the underlying genetic abnormalities of which were characterised by comparative genomic hybridisation-arrays and molecular cytogenetics.Our classifier predicted ALL subtype with a median accuracy of 90.0% (IQR 88.3-91.7) in the discovery cohort and correctly identified 94 of 107 patients (accuracy 87.9%) in the independent validation cohort. Without our classifier, 44 children in the COALL cohort and 33 children in the DCOG cohort would have been classified as B-other. However, hierarchical clustering showed that many of these genetically unclassified cases clustered with BCR-ABL1-positive cases: 30 (19%) of 154 children with precursor B-ALL in the COALL cohort and 14 (15%) of 92 children with precursor B-ALL in the DCOG cohort had this BCR-ABL1-like disease. In the COALL cohort, these patients had unfavourable outcome (5-year disease-free survival 59.5%, 95% CI 37.1-81.9) compared with patients with other precursor B-ALL (84.4%, 76.8-92.1%; p=0.012), a prognosis similar to that of patients with BCR-ABL1-positive ALL (51.9%, 23.1-80.6%). In the DCOG cohort, the prognosis of BCR-ABL1-like disease (57.1%, 31.2-83.1%) was worse than that of other precursor B-ALL (79.2%, 70.2-88.3%; p=0.026), and similar to that of BCR-ABL1-positive ALL (32.5%, 2.3-62.7%). 36 (82%) of the patients with BCR-ABL1-like disease had deletions in genes involved in B-cell development, including IKZF1, TCF3, EBF1, PAX5, and VPREB1; only nine (36%) of 25 patients with B-other ALL had deletions in these genes (p=0.0002). Compared with other precursor B-ALL cells, BCR-ABL1-like cells were 73 times more resistant to L-asparaginase (p=0.001) and 1.6 times more resistant to daunorubicin (p=0.017), but toxicity of prednisolone and vincristine did not differ.New treatment strategies are needed to improve outcome for this newly identified high-risk subtype of ALL.Dutch Cancer Society, Sophia Foundation for Medical Research, Paediatric Oncology Foundation Rotterdam, Centre of Medical Systems Biology of the Netherlands Genomics Initiative/Netherlands Organisation for Scientific Research, American National Institute of Health, American National Cancer Institute, and American Lebanese Syrian Associated Charities.

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Integrated Classification of Prostate Cancer Reveals a Novel Luminal Subtype with Poor Outcome.

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Integrated Classification of Prostate Cancer Reveals a Novel Luminal Subtype with Poor Outcome.

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