| 41. |
- Jönsson, Göran B, et al.
(författare)
-
The retinoblastoma gene undergoes rearrangements in BRCA1-deficient basal-like breast cancer.
- 2012
-
Ingår i: Cancer Research. - 1538-7445. ; 72:16, s. 4028-4036
-
Tidskriftsartikel (refereegranskat)abstract
- Breast tumors from BRCA1 germ line mutation carriers typically exhibit features of the basal-like molecular subtype. However, the specific genes recurrently mutated as a consequence of BRCA1 dysfunction have not been fully elucidated. In this study, we utilized gene expression profiling to molecularly subtype 577 breast tumors, including 72 breast tumors from BRCA1/2 mutation carriers. Focusing on the RB1 locus, we analyzed 33 BRCA1-mutated, 36 BRCA2-mutated and 48 non-BRCA1/2-mutated breast tumors using a custom-designed high-density oligomicroarray covering the RB1 gene. We found a strong association between the basal-like subtype and BRCA1-mutated breast tumors and the luminal B subtype and BRCA2-mutated breast tumors. RB1 was identified as a major target for genomic disruption in tumors arising in BRCA1 mutation carriers and in sporadic tumors with BRCA1 promoter-methylation, but rarely in other breast cancers. Homozygous deletions, intragenic breaks, or microdeletions were found in 33% of BRCA1-mutant tumors, 36% of BRCA1 promoter-methylated basal-like tumors, 13% of non-BRCA1 deficient basal-like tumors, and 3% of BRCA2-mutated tumors. In conclusion, RB1 was frequently inactivated by gross gene disruption in BRCA1-related hereditary breast cancer and BRCA1-methylated sporadic basal-like breast cancer, but rarely in BRCA2-hereditary breast cancer and non-BRCA1-deficient sporadic breast cancers. Together, our findings demonstrate the existence of genetic heterogeneity within the basal-like breast cancer subtype that is based upon BRCA1-status.
|
|
| 42. |
- Khan, J, et al.
(författare)
-
Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks
- 2001
-
Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1546-170X .- 1078-8956. ; 7:6, s. 673-679
-
Tidskriftsartikel (refereegranskat)abstract
- The purpose of this study was to develop a method of classifying cancers to specific diagnosticcategories based on their gene expression signatures using artificial neural networks (ANNs).We trained the ANNs using the small, round blue-cell tumors (SRBCTs) as a model. These cancersbelong to four distinct diagnostic categories and often present diagnostic dilemmas in clinicalpractice. The ANNs correctly classified all samples and identified the genes most relevant to theclassification. Expression of several of these genes has been reported in SRBCTs, but most havenot been associated with these cancers. To test the ability of the trained ANN models to recognizeSRBCTs, we analyzed additional blinded samples that were not previously used for the trainingprocedure, and correctly classified them in all cases. This study demonstrates the potentialapplications of these methods for tumor diagnosis and the identification of candidate targets fortherapy.
|
|
| 43. |
- Khan, J, et al.
(författare)
-
Expression profiling in cancer using cDNA microarrays
- 1999
-
Ingår i: Electrophoresis. - 0173-0835. ; 20:2, s. 223-229
-
Forskningsöversikt (refereegranskat)abstract
- Currently there are over 1,000,000 human expressed sequence tag (EST) sequences available on the public database, representing perhaps 50-90% of all human genes. The cDNA microarray technique is a recently developed tool that exploits this wealth of information for the analysis of gene expression. In this method, DNA probes representing cDNA clones are arrayed onto a glass slide and interrogated with fluorescently labeled cDNA targets. The power of the technology is the ability to perform a genome-wide expression profile of thousands of genes in one experiment. In our review we describe the principles of the microarray technology as applied to cancer research, summarize the literature on its use so far, and speculate on the future application of this powerful technique.
|
|
| 44. |
- Larsson, Christer, et al.
(författare)
-
Prognostic implications of the expression levels of different immunoglobulin heavy chain-encoding RNAs in early breast cancer
- 2020
-
Ingår i: npj Breast Cancer. - : Springer Science and Business Media LLC. - 2374-4677. ; 6:1
-
Tidskriftsartikel (refereegranskat)abstract
- The extent and composition of the immune response in a breast cancer is one important prognostic factor for the disease. The aim of the current work was to refine the analysis of the humoral component of an immune response in breast tumors by quantifying mRNA expression of different immunoglobulin classes and study their association with prognosis. We used RNA-Seq data from two local population-based breast cancer cohorts to determine the expression of IGJ and immunoglobulin heavy (IGH) chain-encoding RNAs. The association with prognosis was investigated and public data sets were used to corroborate the findings. Except for IGHE and IGHD, mRNAs encoding heavy chains were generally detected at substantial levels and correlated with other immune-related genes. High IGHG1 mRNA was associated with factors related to poor prognosis such as estrogen receptor negativity, HER2 amplification, and high grade, whereas high IGHA2 mRNA levels were primarily associated with lower age at diagnosis. High IGHA2 and IGJ mRNA levels were associated with a more favorable prognosis both in univariable and multivariable Cox models. When adjusting for other prognostic factors, high IGHG1 mRNA levels were positively associated with improved prognosis. To our knowledge, these results are the first to demonstrate that expression of individual Ig class types has prognostic implications in breast cancer.
|
|
| 45. |
- Lasič, Samo, et al.
(författare)
-
Apparent exchange rate for breast cancer characterization.
- 2016
-
Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 29:5, s. 631-639
-
Tidskriftsartikel (refereegranskat)abstract
- Although diffusion MRI has shown promise for the characterization of breast cancer, it has low specificity to malignant subtypes. Higher specificity might be achieved if the effects of cell morphology and molecular exchange across cell membranes could be disentangled. The quantification of exchange might thus allow the differentiation of different types of breast cancer cells. Based on differences in diffusion rates between the intra- and extracellular compartments, filter exchange spectroscopy/imaging (FEXSY/FEXI) provides non-invasive quantification of the apparent exchange rate (AXR) of water between the two compartments. To test the feasibility of FEXSY for the differentiation of different breast cancer cells, we performed experiments on several breast epithelial cell lines in vitro. Furthermore, we performed the first in vivo FEXI measurement of water exchange in human breast. In cell suspensions, pulsed gradient spin-echo experiments with large b values and variable pulse duration allow the characterization of the intracellular compartment, whereas FEXSY provides a quantification of AXR. These experiments are very sensitive to the physiological state of cells and can be used to establish reliable protocols for the culture and harvesting of cells. Our results suggest that different breast cancer subtypes can be distinguished on the basis of their AXR values in cell suspensions. Time-resolved measurements allow the monitoring of the physiological state of cells in suspensions over the time-scale of hours, and reveal an abrupt disintegration of the intracellular compartment. In vivo, exchange can be detected in a tumor, whereas, in normal tissue, the exchange rate is outside the range experimentally accessible for FEXI. At present, low signal-to-noise ratio and limited scan time allows the quantification of AXR only in a region of interest of relatively large tumors. © 2016 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.
|
|
| 46. |
- Li, Yanni, et al.
(författare)
-
Mitochondrial heteroplasmic shifts reveal a positive selection of breast cancer
- 2023
-
Ingår i: Journal of Translational Medicine. - 1479-5876. ; 21:1
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Breast cancer is, despite screening, not always detected early enough and is together with other tumor types known to shed genetic information in circulation. Unlike single-copy nuclear DNA, mitochondrial DNA (mtDNA) copies range from 100s to 10,000s per cell, thus providing a potentially alternative to identify potential missing cancer information in circulation at an early stage.METHODS: To characterize mitochondrial mutation landscapes in breast cancer, whole mtDNA sequencing and bioinformatics analyses were performed on 86 breast cancer biopsies and 50 available matched baseline cancer-free whole blood samples from the same individuals, selected from a cohort of middle-aged women in Sweden. To determine whether the mutations can be detected in blood plasma prior to cancer diagnosis, we further designed a nested case-control study (n = 663) and validated the shortlisted mutations using droplet digital PCR.RESULTS: We detected different mutation landscapes between biopsies and matched whole blood samples. Compared to whole blood samples, mtDNA from biopsies had higher heteroplasmic mutations in the D-loop region (P = 0.02), RNR2 (P = 0.005), COX1 (P = 0.037) and CYTB (P = 0.006). Furthermore, the germline mtDNA mutations had higher heteroplasmy level than the lost (P = 0.002) and de novo mutations (P = 0.04). The nonsynonymous to synonymous substitution ratio (dN/dS) was higher for the heteroplasmic mutations (P = 7.25 × 10 -12) than that for the homoplasmic mutations, but the de novo (P = 0.06) and lost mutations (P = 0.03) had lower dN/dS than the germline mutations. Interestingly, we found that the critical regions for mitochondrial transcription: MT-HSP1 (odds ratio [OR]: 21.41), MT-TFH (OR: 7.70) and MT-TAS2 (OR: 3.62), had significantly higher heteroplasmic mutations than the rest of the D-loop sub-regions. Finally, we found that the presence of mt.16093T > C mutation increases 67% risk of developing breast cancer. CONCLUSIONS: Our findings show that mitochondrial genetic landscape changes during cancer pathogenesis and positive selection of mtDNA heteroplasmic mutations in breast cancer. Most importantly, the mitochondrial mutations identified in biopsies can be traced back in matched plasma samples and could potentially be used as early breast cancer diagnostic biomarkers.
|
|
| 47. |
- Loman, Niklas, et al.
(författare)
-
Abstract P2-02-09: Breast cancer subtype distribution and circulating tumor DNA in response to neoadjuvant chemotherapy: Experiences from a preoperative cohort within SCAN-B
- 2018
-
Ingår i: Cancer research. Supplement. - 1538-7445. ; 78:4
-
Konferensbidrag (refereegranskat)abstract
- Introduction: Preoperative chemotherapy in early breast cancer increases the rate of breast preservation and provides prognostic information. In the case of residual disease, a change in subtypes may be observed. Sensitive and reproducible biomarkers predicting treatment response early during the treatment course are needed in order to better exploit the potential benefit of an individualized preoperative treatment.Material and Methods: In an ongoing prospective study within the population-based SCAN-B project (NCT02306096), patients undergoing preoperative chemotherapy for early or locally recurrent breast cancer have been treated with iv Epirubicin and Cyclophosphamide q3w x 3 in sequence with either Docetaxel q3w x 3 or Paclitaxel q1w x 9 with a preoperative intent. HER2-positive cases also received HER2-directed treatment. At baseline, patients were staged using sentinel node biopsy for clinically node-negative patients and CT scan for cytologically confirmed node-positive cases. A clinical core needle biopsy as well as tissue from the surgical specimen was collected for determination of conventional biomarkers including ER, PgR, HER2 and Ki67. Tumor biopsies for biomolecule-extraction and RNA-sequencing were taken using ultrasound guidance and collected fresh in RNAlater at baseline, after 2 treatment cycles, as well as at surgery. Blood plasma samples were collected at baseline, after one-, three-, and six- 3w treatment cycles, and post-surgery. Using RNA-sequencing data, somatic mutations were identified in the tumor biopsies and personalized analyses for circulating tumor DNA (ctDNA) were performed. A pathological complete remission (pCR) was defined as the complete disappearance of invasive breast cancer in the breast and axilla at time of definitive surgery. Subtyping was performed using modified St Gallen criteria (2013).Results: Thus far, 45 patients aged 24-74 years have been included, of which 34 (76 %) were clinical stage 2 and 11 (24%) were stage 3. The subtype distribution at baseline was five Luminal A-like (11 %), 21 Luminal B-like (HER2 negative) (47 %), 8 HER2-positive (18 %) and 11 Triple-negative (ductal) (24 %). The rates of pCR in 38 operated cases to date were 0/3 Luminal A-like, 3/19 Luminal B-like (HER2 negative), 2/8 HER2-positive, and 4/7 Triple-negative (overall 24 % pCR rate). One patient did not undergo surgery due to clinically progressive disease. In 25 cases with evaluable residual disease at surgery, there was a shift in the subtype in 13 (52 %), the majority of which represented a transition from Luminal B to Luminal A. No Triple-negative cases underwent a change in subtype during treatment. Results of the ctDNA analyses will be presented at the meeting.Discussion: We have established an infrastructure allowing for an extensive evaluation of preoperative chemotherapy in early breast cancer. The goal is to develop methods to refine response-guided treatment in early breast cancer using molecular responses in the tumor as well as in the blood circulation. The patients continue to be prospectively monitored with iterative ctDNA analyses during follow-up.
|
|
| 48. |
|
|
| 49. |
- Lundgren, Christine, et al.
(författare)
-
Agreement between molecular subtyping and surrogate subtype classification : a contemporary population-based study of ER-positive/HER2-negative primary breast cancer
- 2019
-
Ingår i: Breast Cancer Research and Treatment. - : SPRINGER. - 0167-6806 .- 1573-7217. ; 178:2, s. 459-467
-
Tidskriftsartikel (refereegranskat)abstract
- Purpose: Oestrogen receptor-positive (ER+) and human epidermal receptor 2-negative (HER2-) breast cancers are classified as Luminal A or B based on gene expression, but immunohistochemical markers are used for surrogate subtyping. The aims of this study were to examine the agreement between molecular subtyping (MS) and surrogate subtyping and to identify subgroups consisting mainly of Luminal A or B tumours.Methods: The cohort consisted of 2063 patients diagnosed between 2013-2017, with primary ER+/HER2- breast cancer, analysed by RNA sequencing. Surrogate subtyping was performed according to three algorithms (St. Gallen 2013, Maisonneuve and our proposed Grade-based classification). Agreement (%) and kappa statistics (kappa) were used as concordance measures and ROC analysis for luminal distinction. Ki67, progesterone receptor (PR) and histological grade (HG) were further investigated as surrogate markers.Results: The agreement rates between the MS and St. Gallen 2013, Maisonneuve and Grade-based classifications were 62% (kappa = 0.30), 66% (kappa = 0.35) and 70% (kappa = 0.41), respectively. PR did not contribute to distinguishing Luminal A from B tumours (auROC = 0.56). By classifying HG1-2 tumours as Luminal A-like and HG3 as Luminal B-like, agreement with MS was 80% (kappa = 0.46). Moreover, by combining HG and Ki67 status, a large subgroup of patients (51% of the cohort) having > 90% Luminal A tumours could be identified.Conclusions: Agreement between MS and surrogate classifications was generally poor. However, a post hoc analysis showed that a combination of HG and Ki67 could identify patients very likely to have Luminal A tumours according to MS.
|
|
| 50. |
|
|
