Partial PTEN deletion is linked to poor prognosis in breast cancer

Lebok, Patrick; Kopperschmidt, Valerie; Kluth, Martina; Hube‐Magg, Claudia; Özden, Cüneyt; Taskin, Berivan; Hussein, Khakan; Mittenzwei, Anja; Lebeau, Annette; Witzel, Isabell; Wölber, Linn; Mahner, Sven; Jänicke, F.; Geist, Stefan; Paluchowski, Peter; Wilke, Christian; Heilenkötter, Uwe; Simon, Ronald; Sauter, Guido; Terracciano, Luigi; Krech, Rainer; Assen, Albert von der; Müller, V; Burandt, Eike-Christian

doi:10.1186/s12885-015-1770-3

Cited by 34 publications

(40 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The density of CD8 + TILs and other clinical factors including patient age and the number of metastatic axillary lymph nodes were also independent predictive factors for OS and/or DFS in patients with EBC (Table ), consistent with previous clinical evidence . In addition, we found that PTEN expression (PTEN loss) was significantly associated with tumor size, tumor nuclear grade, and ER negativity (Table ); similar results have been previously reported elsewhere . Notably in this study, PTEN expression was a significant prognostic factor for favorable OS in HER2‐postive patients who were without adjuvant anti‐HER2 therapy (trastuzumab), which was not true for other intrinsic EBC subtypes.…”

Section: Discussionsupporting

confidence: 89%

Predictive factors of the tumor immunological microenvironment for long‐term follow‐up in early stage breast cancer

et al. 2017

View full text Add to dashboard Cite

The aim of this research was to investigate the correlation of immunologic factors in the tumor environment of breast cancer, using immunohistological staining to evaluate the expression of programmed death 1/programmed death ligand 1 (PD‐1/PD‐L1), phosphatase and tensin homolog (PTEN), tumor infiltrating lymphocytes (TILs), and macrophages, and to analyze the association between the immunologic factors and clinical outcome for patients with early stage breast cancer (EBC). A total of 97 EBC patients who underwent standard surgery were investigated. Expression of PD‐1/PD‐L1 and PTEN and the density of CD3+ TILs, CD8+ TILs, and CD163+ macrophages were evaluated by immunohistochemical analysis. The association between the immunologic factors and clinical outcome was statistically analyzed. The density of CD3+ TILs, CD8+ TILs, and CD163+ macrophages and non‐expression of PTEN was significantly higher in cases of triple negative breast cancer. CD8+ TIL density and CD8+/PD‐L1+ expression were predictive factors for disease‐free survival and overall survival (OS). Human epidermal growth factor 2 (HER2)‐positive patients with PTEN expression and luminal/HER2‐negative patients without PD‐L1 expression had significantly longer OS compared to patients without PTEN expression (P = 0.049) and with PD‐L1 expression (P = 0.036), respectively. Furthermore, patients with PD‐L1+/CD8+ expression had worse median progression‐free survival (P = 0.022) and median OS (P = 0.037) compared with patients without PD‐L1+/CD8+ expression. The CD3+ TILs, CD8+ TILs, and CD163+ macrophages were shown to infiltrate the tumor area of EBC. In particular, triple negative breast cancer had a higher rate of TIL infiltration within the tumor environment. Expression of PTEN and lack of PD‐L1 expression were associated with favorable survival in HER2‐positive and luminal/HER2‐negative EBC patients, respectively. The PD‐L1 expression combined with CD8+ density was significantly associated with an aggressive clinical outcome.

show abstract

Section: Discussionsupporting

confidence: 89%

Predictive factors of the tumor immunological microenvironment for long‐term follow‐up in early stage breast cancer

et al. 2017

View full text Add to dashboard Cite

show abstract

“…This finding is related to our previous observation in a different cohort of patients treated in the pre-trastuzumab era (16), where PIK3CA mutation types interacted with PTEN status and affected outcome in opposite directions. Further in breast cancer, TP53 mutation status may influence the prognostic CANCER GENOMICS & PROTEOMICS 16: 195-206 (2019) 202 effect of PIK3CA mutations (25) and of preserved PTEN (34), while the unfavourable effect of PTEN-loss may be augmented in the presence of additional alterations interfering with the activation of the PI3K pathway (35). All this argumentation suggests that we need to shift our view from single oncogenic drivers to a molecular environment that certainly interferes with-and may alter the effects of these drivers (36).…”

Section: Discussionmentioning

confidence: 99%

Opposite Prognostic Impact of Single PTEN-loss andPIK3CAMutations in Early High-risk Breast Cancer

Lazaridis

Kotoula

Vrettou

et al. 2019

Cancer Genomics Proteomics

View full text Add to dashboard Cite

Background/Aim: PTEN-loss and PIK3CA mutations have been addressed as markers of PI3K activation in breast cancer. We evaluated these markers in early high-risk breast cancer (EBC) focusing on PTEN immunohistochemistry (IHC) issues, particularly in HER2-positive disease. Materials and Methods: We examined PTEN-loss and PIK3CA mutations in 1265 EBC patients treated with adjuvant chemotherapy within two clinical trials. Two different methods for the evaluation of PTEN IHC were used, one upfront binary (loss; no-loss) and the other initially multi-scale allowing for the classification of "grey zone" tumors with low and very low PTEN protein expression. Results: PTEN-loss (33.4% and 22.1%, depending on the IHC method) and PIK3CA mutations (29.6%) were associated with ER/PgR/HER2-negative and ER/PgR-positive disease, respectively. Concordance of the two IHC methods was moderate (Cohen's kappa 0.624). PTEN-loss discrepancy and intra-tumor heterogeneity concerned "grey zone" tumors that were prevalent among HER2-positive cancers. PTEN-loss independently conferred higher risk for relapse and death. Compared to single PIK3CA mutations, 195 This article is freely accessible online.

show abstract

“…Among these, we found the amplification of ERBB2/HER2 (17q12, AUC=0.7, CI=[0.56-0.83], predictions based on histopathological subtypes yield an AUC=0.59, CI=[0.49, 0.68], Figure 2d ), similar to previous reports 19 , and deletion of a segment containing PTEN (10q23.31, AUC=0.69 CI=[0.56-0.81], predictions based on histopathological subtypes yield an AUC=0.56, CI=[0.46, 0.66]). Importantly, both alterations are prognostically and therapeutically relevant for treatment with targeted therapies such as Herceptin 20,21 .…”

Section: Focal Amplifications and Deletionsmentioning

confidence: 99%

Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis

Jung

Torné

et al. 2019

Preprint

110

166

View full text Add to dashboard Cite

Key points• Pan-cancer computational histopathology analysis with deep learning extracts histopathological patterns and accurately discriminates 28 cancer and 14 normal tissue types • Computational histopathology predicts whole genome duplications, focal amplifications and deletions, as well as driver gene mutations • Wide-spread correlations with gene expression indicative of immune infiltration and proliferation • Prognostic information augments conventional grading and histopathology subtyping in the majority of cancers AbstractHere we use deep transfer learning to quantify histopathological patterns across 17,396 H&E stained histopathology image slides from 28 cancer types and correlate these with underlying genomic and transcriptomic data. Pan-cancer computational histopathology (PC-CHiP) classifies the tissue origin across organ sites and provides highly accurate, spatially resolved tumor and normal distinction within a given slide. The learned computational histopathological features correlate with a large range of recurrent genetic aberrations, including whole genome duplications (WGDs), arm-level copy number gains and losses, focal amplifications and deletions as well as driver gene mutations within a range of cancer types. WGDs can be predicted in 25/27 cancer types (mean AUC=0.79) including those that were not part of model training. Similarly, we observe associations with 25% of mRNA transcript levels, which enables to learn and localise histopathological patterns of molecularly defined cell types on each slide. Lastly, we find that computational histopathology provides prognostic information augmenting histopathological subtyping and grading in the majority of cancers assessed, which pinpoints prognostically relevant areas such as necrosis or infiltrating lymphocytes on each tumour section. Taken together, these findings highlight the large potential of PC-CHiP to discover new molecular and prognostic associations, which can augment diagnostic workflows and lay out a rationale for integrating molecular and histopathological data.

show abstract

Partial PTEN deletion is linked to poor prognosis in breast cancer

Cited by 34 publications

References 74 publications

Predictive factors of the tumor immunological microenvironment for long‐term follow‐up in early stage breast cancer

Predictive factors of the tumor immunological microenvironment for long‐term follow‐up in early stage breast cancer

Opposite Prognostic Impact of Single PTEN-loss andPIK3CAMutations in Early High-risk Breast Cancer

Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis

Contact Info

Product

Resources

About