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Jan Budczies

Bio: Jan Budczies is an academic researcher from University Hospital Heidelberg. The author has contributed to research in topics: Breast cancer & Cancer. The author has an hindex of 48, co-authored 166 publications receiving 12762 citations. Previous affiliations of Jan Budczies include German Cancer Research Center & Humboldt University of Berlin.


Papers
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Journal ArticleDOI
TL;DR: An online tool to draw survival plots, which can be used to assess the relevance of the expression levels of various genes on the clinical outcome both in untreated and treated breast cancer patients, and which validated the capability of microarrays to determine estrogen receptor status in 1,231 patients.
Abstract: Validating prognostic or predictive candidate genes in appropriately powered breast cancer cohorts are of utmost interest. Our aim was to develop an online tool to draw survival plots, which can be used to assess the relevance of the expression levels of various genes on the clinical outcome both in untreated and treated breast cancer patients. A background database was established using gene expression data and survival information of 1,809 patients downloaded from GEO (Affymetrix HGU133A and HGU133+2 microarrays). The median relapse free survival is 6.43 years, 968/1,231 patients are estrogen-receptor (ER) positive, and 190/1,369 are lymph-node positive. After quality control and normalization only probes present on both Affymetrix platforms were retained (n = 22,277). In order to analyze the prognostic value of a particular gene, the cohorts are divided into two groups according to the median (or upper/lower quartile) expression of the gene. The two groups can be compared in terms of relapse free survival, overall survival, and distant metastasis free survival. A survival curve is displayed, and the hazard ratio with 95% confidence intervals and logrank P value are calculated and displayed. Additionally, three subgroups of patients can be assessed: systematically untreated patients, endocrine-treated ER positive patients, and patients with a distribution of clinical characteristics representative of those seen in general clinical practice in the US. Web address: www.kmplot.com . We used this integrative data analysis tool to confirm the prognostic power of the proliferation-related genes TOP2A and TOP2B, MKI67, CCND2, CCND3, CCNDE2, as well as CDKN1A, and TK2. We also validated the capability of microarrays to determine estrogen receptor status in 1,231 patients. The tool is highly valuable for the preliminary assessment of biomarkers, especially for research groups with limited bioinformatic resources.

2,395 citations

Journal ArticleDOI
18 Dec 2013-PLOS ONE
TL;DR: An integrated database and an online tool capable of uni- and multivariate analysis for in silico validation of new biomarker candidates in non-small cell lung cancer are established.
Abstract: In the last decade, optimized treatment for non-small cell lung cancer had lead to improved prognosis, but the overall survival is still very short. To further understand the molecular basis of the disease we have to identify biomarkers related to survival. Here we present the development of an online tool suitable for the real-time meta-analysis of published lung cancer microarray datasets to identify biomarkers related to survival. We searched the caBIG, GEO and TCGA repositories to identify samples with published gene expression data and survival information. Univariate and multivariate Cox regression analysis, Kaplan-Meier survival plot with hazard ratio and logrank P value are calculated and plotted in R. The complete analysis tool can be accessed online at: www.kmplot.com/lung. All together 1,715 samples of ten independent datasets were integrated into the system. As a demonstration, we used the tool to validate 21 previously published survival associated biomarkers. Of these, survival was best predicted by CDK1 (p<1E-16), CD24 (p<1E-16) and CADM1 (p = 7E-12) in adenocarcinomas and by CCNE1 (p = 2.3E-09) and VEGF (p = 3.3E-10) in all NSCLC patients. Additional genes significantly correlated to survival include RAD51, CDKN2A, OPN, EZH2, ANXA3, ADAM28 and ERCC1. In summary, we established an integrated database and an online tool capable of uni- and multivariate analysis for in silico validation of new biomarker candidates in non-small cell lung cancer.

1,413 citations

Journal ArticleDOI
TL;DR: The presence of tumor-associated lymphocytes in breast cancer is a new independent predictor of response to anthracycline/taxane neoadjuvant chemotherapy and provides useful information for oncologists to identify a subgroup of patients with a high benefit from this type of chemotherapy.
Abstract: PURPOSE Preclinical data suggest a contribution of the immune system to chemotherapy response. In this study, we investigated the prespecified hypothesis that the presence of a lymphocytic infiltrate in cancer tissue predicts the response to neoadjuvant chemotherapy. METHODS We investigated intratumoral and stromal lymphocytes in a total of 1,058 pretherapeutic breast cancer core biopsies from two neoadjuvant anthracycline/taxane-based studies (GeparDuo, n = 218, training cohort; and GeparTrio, n = 840, validation cohort). Molecular parameters of lymphocyte recruitment and activation were evaluated by kinetic polymerase chain reaction in 134 formalin-fixed, paraffin-embedded tumor samples. Results In a multivariate regression analysis including all known predictive clinicopathologic factors, the percentage of intratumoral lymphocytes was a significant independent parameter for pathologic complete response (pCR) in both cohorts (training cohort: P = .012; validation cohort: P = .001). Lymphocyte-predominant breast cancer responded, with pCR rates of 42% (training cohort) and 40% (validation cohort). In contrast, those tumors without any infiltrating lymphocytes had pCR rates of 3% (training cohort) and 7% (validation cohort). The expression of inflammatory marker genes and proteins was linked to the histopathologic infiltrate, and logistic regression showed a significant association of the T-cell-related markers CD3D and CXCL9 with pCR. CONCLUSION The presence of tumor-associated lymphocytes in breast cancer is a new independent predictor of response to anthracycline/taxane neoadjuvant chemotherapy and provides useful information for oncologists to identify a subgroup of patients with a high benefit from this type of chemotherapy.

1,412 citations

Journal ArticleDOI
TL;DR: The hypothesis that breast cancer is immunogenic and might be targetable by immune-modulating therapies is supported and increased TIL concentration predicted response to neoadjuvant chemotherapy in all molecular subtypes assessed.
Abstract: Summary Background Tumour-infiltrating lymphocytes (TILs) are predictive for response to neoadjuvant chemotherapy in triple-negative breast cancer (TNBC) and HER2-positive breast cancer, but their role in luminal breast cancer and the effect of TILs on prognosis in all subtypes is less clear. Here, we assessed the relevance of TILs for chemotherapy response and prognosis in patients with TNBC, HER2-positive breast cancer, and luminal–HER2-negative breast cancer. Methods Patients with primary breast cancer who were treated with neoadjuvant combination chemotherapy were included from six randomised trials done by the German Breast Cancer Group. Pretherapeutic core biopsies from 3771 patients included in these studies were assessed for the number of stromal TILs by standardised methods according to the guidelines of the International TIL working group. TILs were analysed both as a continuous parameter and in three predefined groups of low (0–10% immune cells in stromal tissue within the tumour), intermediate (11–59%), and high TILs (≥60%). We used these data in univariable and multivariable statistical models to assess the association between TIL concentration and pathological complete response in all patients, and between the amount of TILs and disease-free survival and overall survival in 2560 patients from five of the six clinical trial cohorts. Findings In the luminal–HER2-negative breast cancer subtype, a pathological complete response (pCR) was achieved in 45 (6%) of 759 patients with low TILs, 48 (11%) of 435 with intermediate TILs, and 49 (28%) of 172 with high TILs. In the HER2-positive subtype, pCR was observed in 194 (32%) of 605 patients with low TILs, 198 (39%) of 512 with intermediate TILs, and 127 (48%) of 262 with high TILs. Finally, in the TNBC subtype, pCR was achieved in 80 (31%) of 260 patients with low TILs, 117 (31%) of 373 with intermediate TILs, and 136 (50%) of 273 with high TILs (p 2 test for trend). In the univariable analysis, a 10% increase in TILs was associated with longer disease-free survival in TNBC (hazard ratio [HR] 0·93 [95% CI 0·87–0·98], p=0·011) and HER2-positive breast cancer (0·94 [0·89–0·99], p=0·017), but not in luminal–HER2-negative tumours (1·02 [0·96–1·09], p=0·46). The increase in TILs was also associated with longer overall survival in TNBC (0·92 [0·86–0·99], p=0·032), but had no association in HER2-positive breast cancer (0·94 [0·86–1·02], p=0·11), and was associated with shorter overall survival in luminal–HER2-negative tumours (1·10 [1·02–1·19], p=0·011). Interpretation Increased TIL concentration predicted response to neoadjuvant chemotherapy in all molecular subtypes assessed, and was also associated with a survival benefit in HER2-positive breast cancer and TNBC. By contrast, increased TILs were an adverse prognostic factor for survival in luminal–HER2-negative breast cancer, suggesting a different biology of the immunological infiltrate in this subtype. Our data support the hypothesis that breast cancer is immunogenic and might be targetable by immune-modulating therapies. In light of the results in luminal breast cancer, further research investigating the interaction of the immune system with different types of endocrine therapy is warranted. Funding Deutsche Krebshilfe and European Commission.

1,154 citations

Journal ArticleDOI
14 Dec 2012-PLOS ONE
TL;DR: The functionality of Cutoff Finder is illustrated by the analysis of the gene expression of estrogen receptor and progesterone receptor in breast cancer tissues, which is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival.
Abstract: Gene or protein expression data are usually represented by metric or at least ordinal variables. In order to translate a continuous variable into a clinical decision, it is necessary to determine a cutoff point and to stratify patients into two groups each requiring a different kind of treatment. Currently, there is no standard method or standard software for biomarker cutoff determination. Therefore, we developed Cutoff Finder, a bundle of optimization and visualization methods for cutoff determination that is accessible online. While one of the methods for cutoff optimization is based solely on the distribution of the marker under investigation, other methods optimize the correlation of the dichotomization with respect to an outcome or survival variable. We illustrate the functionality of Cutoff Finder by the analysis of the gene expression of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer tissues. This distribution of these important markers is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival. Cutoff Finder is expected to fill a relevant gap in the available biometric software repertoire and will enable faster optimization of new diagnostic biomarkers. The tool can be accessed at http://molpath.charite.de/cutoff.

934 citations


Cited by
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Journal ArticleDOI
04 Mar 2011-Cell
TL;DR: Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer.

51,099 citations

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5,680 citations

01 Jan 2016
TL;DR: The modern applied statistics with s is universally compatible with any devices to read, and is available in the digital library an online access to it is set as public so you can download it instantly.
Abstract: Thank you very much for downloading modern applied statistics with s. As you may know, people have search hundreds times for their favorite readings like this modern applied statistics with s, but end up in harmful downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some harmful virus inside their laptop. modern applied statistics with s is available in our digital library an online access to it is set as public so you can download it instantly. Our digital library saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the modern applied statistics with s is universally compatible with any devices to read.

5,249 citations

Journal ArticleDOI
TL;DR: In this Opinion article, the context-specific nature of infiltrating immune cells can affect the prognosis of patients is discussed.
Abstract: Tumours grow within an intricate network of epithelial cells, vascular and lymphatic vessels, cytokines and chemokines, and infiltrating immune cells. Different types of infiltrating immune cells have different effects on tumour progression, which can vary according to cancer type. In this Opinion article we discuss how the context-specific nature of infiltrating immune cells can affect the prognosis of patients.

3,759 citations