Selection of bone metastasis seeds by mesenchymal signals in the primary tumor stroma.

How organ-specific metastatic traits arise in primary tumors remains unknown. Here, we show a role of the breast tumor stroma in selecting cancer cells that are primed for metastasis in bone. Cancer-associated fibroblasts (CAFs) in triple-negative (TN) breast tumors skew heterogeneous cancer cell populations toward a predominance of clones that thrive on the CAF-derived factors CXCL12 and IGF1. Limiting concentrations of these factors select for cancer cells with high Src activity, a known clinical predictor of bone relapse and an enhancer of PI3K-Akt pathway activation by CXCL12 and IGF1. Carcinoma clones selected in this manner are primed for metastasis in the CXCL12-rich microenvironment of the bone marrow. The evidence suggests that stromal signals resembling those of a distant organ select for cancer cells that are primed for metastasis in that organ, thus illuminating the evolution of metastatic traits in a primary tumor and its distant metastases.

Author Correction: Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

In the Methods section of this Article, 'greater than' should have been 'less than' in the sentence 'Putative regions of clustered rearrangements were identified as having an average inter-rearrangement distance that was at least 10 times greater than the whole-genome average for the individual sample. '. The Article has not been corrected.

Integrative whole-genome and transcriptome analysis of HER2-amplified metastatic breast cancer.

BACKGROUND: In breast cancer, the advent of anti-HER2 therapies has made HER2+ tumors a highly relevant subgroup. However, the exact characteristics which prohibit clinical response to anti-HER2 therapies and drive disease progression are not yet fully known. Integrative whole-genome and transcriptomic sequencing data from both primary and metastatic HER2-positive breast cancer will enhance our understanding of underlying biological processes. METHODS: Here, we used WGS and RNA sequencing data of 700 metastatic breast tumors, of which 68 being HER2+, to search for specific genomic features of HER2+ disease and therapy resistance. Furthermore, we integrated results with transcriptomic data to associate tumors exhibiting a HER2+-specific gene expression profile with ERBB2 mutation status, prior therapy and relevant gene expression signatures. RESULTS: Overall genomic profiles of primary and metastatic HER2+ breast cancers were similar, and no specific acquired genomics traits connected to prior anti-HER2 treatment were observed. However, specific genomic features were predictive of progression-free survival on post-biopsy anti-HER2 treatment. Furthermore, a HER2-driven expression profile grouped HER2-amplified tumors with ERBB2-mutated cases and cases without HER2 alterations. The latter were reported as ER positive in primary disease, but the metastatic biopsy showed low ESR1 expression and upregulation of the MAPK pathway, suggesting transformation to ER independence. CONCLUSIONS: In summary, although the quantity of variants increased throughout HER2-positive breast cancer progression, the genomic composition remained largely consistent, thus yielding no new major processes beside those already operational in primary disease. Our results suggest that integrated genomic and transcriptomic analyses may be key in establishing therapeutic options.

Breast cancer genomes from CHEK2 c.1100delC mutation carriers lack somatic TP53 mutations and display a unique structural variant size distribution profile.

BACKGROUND: CHEK2 c.1100delC was the first moderate-risk breast cancer (BC) susceptibility allele discovered. Despite several genomic, transcriptomic and functional studies, however, it is still unclear how exactly CHEK2 c.1100delC promotes tumorigenesis. Since the mutational landscape of a tumor reflects the processes that have operated on its development, the aim of this study was to uncover the somatic genomic landscape of CHEK2-associated BC. METHODS: We sequenced primary BC (pBC) and normal genomes of 20 CHEK2 c.1100delC mutation carriers as well as their pBC transcriptomes. Including pre-existing cohorts, we exhaustively compared CHEK2 pBC genomes to those from BRCA1/2 mutation carriers, those that displayed homologous recombination deficiency (HRD) and ER- and ER+ pBCs, totaling to 574 pBC genomes. Findings were validated in 517 metastatic BC genomes subdivided into the same subgroups. Transcriptome data from 168 ER+ pBCs were used to derive a TP53-mutant gene expression signature and perform cluster analysis with CHEK2 BC transcriptomes. Finally, clinical outcome of CHEK2 c.1100delC carriers was compared with BC patients displaying somatic TP53 mutations in two well-described retrospective cohorts totaling to 942 independent pBC cases. RESULTS: BC genomes from CHEK2 mutation carriers were most similar to ER+ BC genomes and least similar to those of BRCA1/2 mutation carriers in terms of tumor mutational burden as well as mutational signatures. Moreover, CHEK2 BC genomes did not show any evidence of HRD. Somatic TP53 mutation frequency and the size distribution of structural variants (SVs), however, were different compared to ER+ BC. Interestingly, BC genomes with bi-allelic CHEK2 inactivation lacked somatic TP53 mutations and transcriptomic analysis indicated a shared biology with TP53 mutant BC. Moreover, CHEK2 BC genomes had an increased frequency of > 1 Mb deletions, inversions and tandem duplications with peaks at specific sizes. The high chromothripsis frequency among CHEK2 BC genomes appeared, however, not associated with this unique SV size distribution profile. CONCLUSIONS: CHEK2 BC genomes are most similar to ER+ BC genomes, but display unique features that may further unravel CHEK2-driven tumorigenesis. Increased insight into this mechanism could explain the shorter survival of CHEK2 mutation carriers that is likely driven by intrinsic tumor aggressiveness rather than endocrine resistance.

GRHL2-controlled gene expression networks in luminal breast cancer.

Grainyhead like 2 (GRHL2) is an essential transcription factor for development and function of epithelial tissues. It has dual roles in cancer by supporting tumor growth while suppressing epithelial to mesenchymal transitions (EMT). GRHL2 cooperates with androgen and estrogen receptors (ER) to regulate gene expression. We explore genome wide GRHL2 binding sites conserved in three ER⍺/GRHL2 positive luminal breast cancer cell lines by ChIP-Seq. Interaction with the ER⍺/FOXA1/GATA3 complex is observed, however, only for a minor fraction of conserved GRHL2 peaks. We determine genome wide transcriptional dynamics in response to loss of GRHL2 by nascent RNA Bru-seq using an MCF7 conditional knockout model. Integration of ChIP- and Bru-seq pinpoints candidate direct GRHL2 target genes in luminal breast cancer. Multiple connections between GRHL2 and proliferation are uncovered, including transcriptional activation of ETS and E2F transcription factors. Among EMT-related genes, direct regulation of CLDN4 is corroborated but several targets identified in other cells (including CDH1 and ZEB1) are ruled out by both ChIP- and Bru-seq as being directly controlled by GRHL2 in luminal breast cancer cells. Gene clusters correlating positively (including known GRHL2 targets such as ErbB3, CLDN4/7) or negatively (including TGFB1 and TGFBR2) with GRHL2 in the MCF7 knockout model, display similar correlation with GRHL2 in ER positive as well as ER negative breast cancer patients. Altogether, this study uncovers gene sets regulated directly or indirectly by GRHL2 in luminal breast cancer, identifies novel GRHL2-regulated genes, and points to distinct GRHL2 regulation of EMT in luminal breast cancer cells. Video Abstract.

The circular RNome of primary breast cancer.

Circular RNAs (circRNAs) are a class of RNAs that is under increasing scrutiny, although their functional roles are debated. We analyzed RNA-seq data of 348 primary breast cancers and developed a method to identify circRNAs that does not rely on unmapped reads or known splice junctions. We identified 95,843 circRNAs, of which 20,441 were found recurrently. Of the circRNAs that match exon boundaries of the same gene, 668 showed a poor or even negative (R < 0.2) correlation with the expression level of the linear gene. In silico analysis showed only a minority (8.5%) of circRNAs could be explained by known splicing events. Both these observations suggest that specific regulatory processes for circRNAs exist. We confirmed the presence of circRNAs of CNOT2, CREBBP, and RERE in an independent pool of primary breast cancers. We identified circRNA profiles associated with subgroups of breast cancers and with biological and clinical features, such as amount of tumor lymphocytic infiltrate and proliferation index. siRNA-mediated knockdown of circCNOT2 was shown to significantly reduce viability of the breast cancer cell lines MCF-7 and BT-474, further underlining the biological relevance of circRNAs. Furthermore, we found that circular, and not linear, CNOT2 levels are predictive for progression-free survival time to aromatase inhibitor (AI) therapy in advanced breast cancer patients, and found that circCNOT2 is detectable in cell-free RNA from plasma. We showed that circRNAs are abundantly present, show characteristics of being specifically regulated, are associated with clinical and biological properties, and thus are relevant in breast cancer.

Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

Lost by Transcription: Fork Failures, Elevated Expression, and Clinical Consequences Related to Deletions in Metastatic Colorectal Cancer.

Among the structural variants observed in metastatic colorectal cancer (mCRC), deletions (DELs) show a size preference of ~10 kb-1 Mb and are often found in common fragile sites (CFSs). To gain more insight into the biology behind the occurrence of these specific DELs in mCRC, and their possible association with outcome, we here studied them in detail in metastatic lesions of 429 CRC patients using available whole-genome sequencing and corresponding RNA-seq data. Breakpoints of DELs within CFSs are significantly more often located between two consecutive replication origins compared to DELs outside CFSs. DELs are more frequently located at the midpoint of genes inside CFSs with duplications (DUPs) at the flanks of the genes. The median expression of genes inside CFSs was significantly higher than those of similarly-sized genes outside CFSs. Patients with high numbers of these specific DELs showed a shorter progression-free survival time on platinum-containing therapy. Taken together, we propose that the observed DEL/DUP patterns in expressed genes located in CFSs are consistent with a model of transcription-dependent double-fork failure, and, importantly, that the ability to overcome the resulting stalled replication forks decreases sensitivity to platinum-containing treatment, known to induce stalled replication forks as well. Therefore, we propose that our DEL score can be used as predictive biomarker for decreased sensitivity to platinum-containing treatment, which, upon validation, may augment future therapeutic choices.

Intratumoral heterogeneity of second-harmonic generation scattering from tumor collagen and its effects on metastatic risk prediction.

BACKGROUND: Metastases are the leading cause of breast cancer-related deaths. The tumor microenvironment impacts cancer progression and metastatic ability. Fibrillar collagen, a major extracellular matrix component, can be studied using the light scattering phenomenon known as second-harmonic generation (SHG). The ratio of forward- to backward-scattered SHG photons (F/B) is sensitive to collagen fiber internal structure and has been shown to be an independent prognostic indicator of metastasis-free survival time (MFS). Here we assess the effects of heterogeneity in the tumor matrix on the possible use of F/B as a prognostic tool. METHODS: SHG imaging was performed on sectioned primary tumor excisions from 95 untreated, estrogen receptor-positive, lymph node negative invasive ductal carcinoma patients. We identified two distinct regions whose collagen displayed different average F/B values, indicative of spatial heterogeneity: the cellular tumor bulk and surrounding tumor-stroma interface. To evaluate the impact of heterogeneity on F/B's prognostic ability, we performed SHG imaging in the tumor bulk and tumor-stroma interface, calculated a 21-gene recurrence score (surrogate for OncotypeDX®, or S-ODX) for each patient and evaluated their combined prognostic ability. RESULTS: We found that F/B measured in tumor-stroma interface, but not tumor bulk, is prognostic of MFS using three methods to select pixels for analysis: an intensity threshold selected by a blinded observer, a histogram-based thresholding method, and an adaptive thresholding method. Using both regression trees and Random Survival Forests for MFS outcome, we obtained data-driven prediction rules that show F/B from tumor-stroma interface, but not tumor bulk, and S-ODX both contribute to predicting MFS in this patient cohort. We also separated patients into low-intermediate (S-ODX < 26) and high risk (S-ODX ≥26) groups. In the low-intermediate risk group, comprised of patients not typically recommended for adjuvant chemotherapy, we find that F/B from the tumor-stroma interface is prognostic of MFS and can identify a patient cohort with poor outcomes. CONCLUSIONS: These data demonstrate that intratumoral heterogeneity in F/B values can play an important role in its possible use as a prognostic marker, and that F/B from tumor-stroma interface of primary tumor excisions may provide useful information to stratify patients by metastatic risk.

Cancer-associated fibroblast-derived Gremlin 1 promotes breast cancer progression.

BACKGROUND: Bone morphogenetic proteins (BMPs) have been reported to maintain epithelial integrity and to antagonize the transforming growth factor ß (TGFß)-induced epithelial to mesenchymal transition. The expression of soluble BMP antagonists is dysregulated in cancers and interrupts proper BMP signaling in breast cancer. METHODS: In this study, we mined the prognostic role of BMP antagonists GREMLIN 1 (GREM1) in primary breast cancer tissues using in-house and publicly available datasets. We determined which cells express GREM1 RNA using in situ hybridization (ISH) on a breast cancer tissue microarray. The effects of Grem1 on the properties of breast cancer cells were assessed by measuring the mesenchymal/stem cell marker expression and functional cell-based assays for stemness and invasion. The role of Grem1 in breast cancer-associated fibroblast (CAF) activation was measured by analyzing the expression of fibroblast markers, phalloidin staining, and collagen contraction assays. The role of Grem1 in CAF-induced breast cancer cell intravasation and extravasation was studied by utilizing xenograft zebrafish breast cancer (co-) injection models. RESULTS: Expression analysis of clinical breast cancer datasets revealed that high expression of GREM1 in breast cancer stroma is correlated with a poor prognosis regardless of the molecular subtype. The large majority of human breast cancer cell lines did not express GREM1 in vitro, but breast CAFs did express GREM1 both in vitro and in vivo. Transforming growth factor ß (TGFß) secreted by breast cancer cells, and also inflammatory cytokines, stimulated GREM1 expression in CAFs. Grem1 abrogated bone morphogenetic protein (BMP)/SMAD signaling in breast cancer cells and promoted their mesenchymal phenotype, stemness, and invasion. Moreover, Grem1 production by CAFs strongly promoted the fibrogenic activation of CAFs and promoted breast cancer cell intravasation and extravasation in co-injection xenograft zebrafish models. CONCLUSIONS: Our results demonstrated that Grem1 is a pivotal factor in the reciprocal interplay between breast cancer cells and CAFs, which promotes cancer cell invasion. Targeting Grem1 could be beneficial in the treatment of breast cancer patients with high Grem1 expression.

A kinase inhibitor screen identifies a dual cdc7/CDK9 inhibitor to sensitise triple-negative breast cancer to EGFR-targeted therapy.

BACKGROUND: The effective treatment of triple-negative breast cancer (TNBC) remains a profound clinical challenge. Despite frequent epidermal growth factor receptor (EGFR) overexpression and reliance on downstream signalling pathways in TNBC, resistance to EGFR-tyrosine kinase inhibitors (TKIs) remains endemic. Therefore, the identification of targeted agents, which synergise with current therapeutic options, is paramount. METHODS: Compound-based, high-throughput, proliferation screening was used to profile the response of TNBC cell lines to EGFR-TKIs, western blotting and siRNA transfection being used to examine the effect of inhibitors on EGFR-mediated signal transduction and cellular dependence on such pathways, respectively. A kinase inhibitor combination screen was used to identify compounds that synergised with EGFR-TKIs in TNBC, utilising sulphorhodamine B (SRB) assay as read-out for proliferation. The impact of drug combinations on cell cycle arrest, apoptosis and signal transduction was assessed using flow cytometry, automated live-cell imaging and western blotting, respectively. RNA sequencing was employed to unravel transcriptomic changes elicited by this synergistic combination and to permit identification of the signalling networks most sensitive to co-inhibition. RESULTS: We demonstrate that a dual cdc7/CDK9 inhibitor, PHA-767491, synergises with multiple EGFR-TKIs (lapatinib, erlotinib and gefitinib) to overcome resistance to EGFR-targeted therapy in various TNBC cell lines. Combined inhibition of EGFR and cdc7/CDK9 resulted in reduced cell proliferation, accompanied by induction of apoptosis, G2-M cell cycle arrest, inhibition of DNA replication and abrogation of CDK9-mediated transcriptional elongation, in contrast to mono-inhibition. Moreover, high expression of cdc7 and RNA polymerase II Subunit A (POLR2A), the direct target of CDK9, is significantly correlated with poor metastasis-free survival in a cohort of breast cancer patients. RNA sequencing revealed marked downregulation of pathways governing proliferation, transcription and cell survival in TNBC cells treated with the combination of an EGFR-TKI and a dual cdc7/CDK9 inhibitor. A number of genes enriched in these downregulated pathways are associated with poor metastasis-free survival in TNBC. CONCLUSIONS: Our results highlight that dual inhibition of cdc7 and CDK9 by PHA-767491 is a potential strategy for targeting TNBC resistant to EGFR-TKIs.

Comprehensive evaluation of methods to assess overall and cell-specific immune infiltrates in breast cancer.

BACKGROUND: Breast cancer (BC) immune infiltrates play a critical role in tumor progression and response to treatment. Besides stromal tumor infiltrating lymphocytes (sTILs) which have recently reached level 1B evidence as a prognostic marker in triple negative BC, a plethora of methods to assess immune infiltration exists, and it is unclear how these compare to each other and if they can be used interchangeably. METHODS: Two experienced pathologists scored sTIL, intra-tumoral TIL (itTIL), and 6 immune cell types (CD3+, CD4+, CD8+, CD20+, CD68+, FOXP3+) in the International Cancer Genomics Consortium breast cancer cohort using hematoxylin and eosin-stained (n = 243) and immunohistochemistry-stained tissue microarrays (n = 254) and whole slides (n = 82). The same traits were evaluated using transcriptomic- and methylomic-based deconvolution methods or signatures. RESULTS: The concordance correlation coefficient (CCC) between pathologists for sTIL was very good (0.84) and for cell-specific immune infiltrates slightly lower (0.63-0.66). Comparison between tissue microarray and whole slide pathology scores revealed systematically higher values in whole slides (ratio 2.60-5.98). The Spearman correlations between microscopic sTIL and transcriptomic- or methylomic-based assessment of immune infiltrates were highly variable (r = 0.01-0.56). Similar observations were made for cell type-specific quantifications (r = 0.001-0.54). We observed a strong inter-method variability between the omics-derived estimations, which is further cell type dependent. Finally, we demonstrated that most methods more accurately identify highly infiltrated (sTIL ≥ 60%; area under the curve, AUC, 0.64-0.99) as compared to lowly infiltrated tumors (sTIL ≤ 10%; AUC 0.52-0.82). CONCLUSIONS: There is a lower inter-pathologist concordance for cell-specific quantification as compared to overall infiltration quantification. Microscopic assessments are underestimated when considering small cores (tissue microarray) instead of whole slides. Results further highlight considerable differences between the microscopic-, transcriptomic-, and methylomic-based methods in the assessment of overall and cell-specific immune infiltration in BC. We therefore call for extreme caution when assessing immune infiltrates using current methods and emphasize the need for standardized immune characterization beyond TIL.

Androgen receptor expression in circulating tumor cells of patients with metastatic breast cancer.

The androgen receptor (AR) has potential clinical relevance in metastatic breast cancer (mBC) since it might be a treatment target and has been associated with endocrine resistance. A minimal-invasive way to determine AR expression on metastatic tumor cells is by characterization of circulating tumor cells (CTCs). Here, we assessed AR mRNA expression in CTCs (CTC-AR) and in matched primary tumor samples from mBC patients representing different breast cancer subtypes. In addition, we explored CTC-AR-status in relation to outcome on endocrine therapy. AR, and 92 AR or estrogen receptor (ER) related genes, were measured in CellSearch-enriched CTCs from 124 mBC patients and in 52 matched FFPE primary tissues using quantitative reverse-transcriptase PCR. AR in CTCs was considered positive if the expression was 1 standard deviation higher than the expression measured in 11 healthy blood donors. A total of 31% of the mBC patients had AR-positive (AR+) CTCs. 58% of the matched CTC and primary tumor samples were discordant with respect to AR status, observing both switches from AR+ to AR-negative (AR-) and vice versa. There was no statistically significant difference in progression-free survival for patients treated with ER-targeting drugs and CTC-AR-status (13 AR+/ 37 AR- cases, p = 0.28). Thus, AR can be determined in RNA isolated from CTCs, with in our set 31% AR-positive samples. Given the discordance between AR status in CTC samples and corresponding primary tumors, determination of AR expression in CTCs might be a promising tool to select mBC patients for AR inhibiting agents.

Gene length corrected trimmed mean of M-values (GeTMM) processing of RNA-seq data performs similarly in intersample analyses while improving intrasample comparisons.

BACKGROUND: Current normalization methods for RNA-sequencing data allow either for intersample comparison to identify differentially expressed (DE) genes or for intrasample comparison for the discovery and validation of gene signatures. Most studies on optimization of normalization methods typically use simulated data to validate methodologies. We describe a new method, GeTMM, which allows for both inter- and intrasample analyses with the same normalized data set. We used actual (i.e. not simulated) RNA-seq data from 263 colon cancers (no biological replicates) and used the same read count data to compare GeTMM with the most commonly used normalization methods (i.e. TMM (used by edgeR), RLE (used by DESeq2) and TPM) with respect to distributions, effect of RNA quality, subtype-classification, recurrence score, recall of DE genes and correlation to RT-qPCR data. RESULTS: We observed a clear benefit for GeTMM and TPM with regard to intrasample comparison while GeTMM performed similar to TMM and RLE normalized data in intersample comparisons. Regarding DE genes, recall was found comparable among the normalization methods, while GeTMM showed the lowest number of false-positive DE genes. Remarkably, we observed limited detrimental effects in samples with low RNA quality. CONCLUSIONS: We show that GeTMM outperforms established methods with regard to intrasample comparison while performing equivalent with regard to intersample normalization using the same normalized data. These combined properties enhance the general usefulness of RNA-seq but also the comparability to the many array-based gene expression data in the public domain.

T lymphocytes facilitate brain metastasis of breast cancer by inducing Guanylate-Binding Protein 1 expression.

The discovery of genes and molecular pathways involved in the formation of brain metastasis would direct the development of therapeutic strategies to prevent this deadly complication of cancer. By comparing gene expression profiles of Estrogen Receptor negative (ER-) primary breast tumors between patients who developed metastasis to brain and to organs other than brain, we found that T lymphocytes promote the formation of brain metastases. To functionally test the ability of T cells to promote brain metastasis, we used an in vitro blood-brain barrier (BBB) model. By co-culturing T lymphocytes with breast cancer cells, we confirmed that T cells increase the ability of breast cancer cells to cross the BBB. Proteomics analysis of the tumor cells revealed Guanylate-Binding Protein 1 (GBP1) as a key T lymphocyte-induced protein that enables breast cancer cells to cross the BBB. The GBP1 gene appeared to be up-regulated in breast cancer of patients who developed brain metastasis. Silencing of GBP1 reduced the ability of breast cancer cells to cross the in vitro BBB model. In addition, the findings were confirmed in vivo in an immunocompetent syngeneic mouse model. Co-culturing of ErbB2 tumor cells with activated T cells induced a significant increase in Gbp1 expression by the cancer cells. Intracardial inoculation of the co-cultured tumor cells resulted in preferential seeding to brain. Moreover, intracerebral outgrowth of the tumor cells was demonstrated. The findings point to a role of T cells in the formation of brain metastases in ER- breast cancers, and provide potential targets for intervention to prevent the development of cerebral metastases.

Proteomic characterization of microdissected breast tissue environment provides a protein-level overview of malignant transformation.

Both healthy and cancerous breast tissue is heterogeneous, which is a bottleneck for proteomics-based biomarker analysis, as it obscures the cellular origin of a measured protein. We therefore aimed at obtaining a protein-level interpretation of malignant transformation through global proteome analysis of a variety of laser capture microdissected cells originating from benign and malignant breast tissues. We compared proteomic differences between these tissues, both from cells of epithelial origin and the stromal environment, and performed string analysis. Differences in protein abundances corresponded with several hallmarks of cancer, including loss of cell adhesion, transformation to a migratory phenotype, and enhanced energy metabolism. Furthermore, despite enriching for (tumor) epithelial cells, many changes to the extracellular matrix were detected in microdissected cells of epithelial origin. The stromal compartment was heterogeneous and richer in the number of fibroblast and immune cells in malignant sections, compared to benign tissue sections. Furthermore, stroma could be clearly divided into reactive and nonreactive based on extracellular matrix disassembly proteins. We conclude that proteomics analysis of both microdissected epithelium and stroma gives an additional layer of information and more detailed insight into malignant transformation.

The mTORC1 Complex Is Significantly Overactivated in SDHX-Mutated Paragangliomas.

AIM: We aimed at exploring the activation pattern of the mTOR pathway in sporadic and hereditary pheochromocytomas (PCCs) and paragangliomas (PGLs). METHODS: A total of 178 PCCs and 44 PGLs, already characterized for the presence of germline mutations in VHL, RET, NF1, MAX, SDHA, SDHB, SDHC, and SDHD as well as somatic mutations in VHL, RET, H-RAS, and MAX, were included in 5 tissue microarrays and tested using immunohistochemistry for mTOR and Rictor as well as the phosphorylated forms of mTOR, p70S6K, AMPK, AKT, 4EBP1, S6, and Raptor. RESULTS: The positive correlation among most of the molecules investigated proved the functional activation of the mTOR pathway in PCCs/PGLs. Total mTOR, p-S6K and p-S6, and mTORC1-associated molecules p-Raptor and p-AMPK were all significantly overexpressed in PGLs rather than in PCCs, and in the head and neck rather than in abdominal locations. None of the markers, except for the low expression of p-mTOR, was associated with malignancy. Cluster 1 PCCs/PGLs had higher total mTOR, p-Raptor, and p-S6 expression than cluster 2 PCCs/PGLs. In contrast, p-mTOR and mTORC2-associated molecule Rictor were significantly overexpressed in cluster 2 tumors. Within cluster 1, molecules active in the mTORC1 complex were significantly overexpressed in SDHX- as compared to VHL-mutated tumors. CONCLUSION: In summary, the mTOR pathway is activated in a high proportion of PCCs/PGLs, with a preferential overactivation of the mTORC1 complex in PGLs of the head and neck and/or harboring SDHX mutations.

The advantage of laser-capture microdissection over whole tissue analysis in proteomic profiling studies.

Laser-capture microdissection (LCM) offers a reliable cell population enrichment tool and has been successfully coupled to MS analysis. Despite this, most proteomic studies employ whole tissue lysate (WTL) analysis in the discovery of disease biomarkers and in profiling analyses. Furthermore, the influence of tissue heterogeneity in WTL analysis, nor its impact in biomarker discovery studies have been completely elucidated. In order to address this, we compared previously obtained high resolution MS data from a cohort of 38 breast cancer tissues, of which both LCM enriched tumor epithelial cells and WTL samples were analyzed. Label-free quantification (LFQ) analysis through MaxQuant software showed a significantly higher number of identified and quantified proteins in LCM enriched samples (3404) compared to WTLs (2837). Furthermore, WTL samples displayed a higher amount of missing data compared to LCM both at peptide and protein levels (p-value < 0.001). 2D analysis on co-expressed proteins revealed discrepant expression of immune system and lipid metabolisms related proteins between LCM and WTL samples. We hereby show that LCM better dissected the biology of breast tumor epithelial cells, possibly due to lower interference from surrounding tissues and highly abundant proteins. All data have been deposited in the ProteomeXchange with the dataset identifier PXD002381 (http://proteomecentral.proteomexchange.org/dataset/PXD002381).

Molecular characterization of irinotecan (SN-38) resistant human breast cancer cell lines.

BACKGROUND: Studies in taxane and/or anthracycline refractory metastatic breast cancer (mBC) patients have shown approximately 30% response rates to irinotecan. Hence, a significant number of patients will experience irinotecan-induced side effects without obtaining any benefit. The aim of this study was to lay the groundwork for development of predictive biomarkers for irinotecan treatment in BC. METHODS: We established BC cell lines with acquired or de novo resistance to SN-38, by exposing the human BC cell lines MCF-7 and MDA-MB-231 to either stepwise increasing concentrations over 6 months or an initial high dose of SN-38 (the active metabolite of irinotecan), respectively. The resistant cell lines were analyzed for cross-resistance to other anti-cancer drugs, global gene expression, growth rates, TOP1 and TOP2A gene copy numbers and protein expression, and inhibition of the breast cancer resistance protein (ABCG2/BCRP) drug efflux pump. RESULTS: We found that the resistant cell lines showed 7-100 fold increased resistance to SN-38 but remained sensitive to docetaxel and the non-camptothecin Top1 inhibitor LMP400. The resistant cell lines were characterized by Top1 down-regulation, changed isoelectric points of Top1 and reduced growth rates. The gene and protein expression of ABCG2/BCRP was up-regulated in the resistant sub-lines and functional assays revealed BCRP as a key mediator of SN-38 resistance. CONCLUSIONS: Based on our preclinical results, we suggest analyzing the predictive value of the BCRP in breast cancer patients scheduled for irinotecan treatment. Moreover, LMP400 should be tested in a clinical setting in breast cancer patients with resistance to irinotecan.

An 8-gene mRNA expression profile in circulating tumor cells predicts response to aromatase inhibitors in metastatic breast cancer patients.

BACKGROUND: Molecular characterization of circulating tumor cells (CTC) is promising for personalized medicine. We aimed to identify a CTC gene expression profile predicting outcome to first-line aromatase inhibitors in metastatic breast cancer (MBC) patients. METHODS: CTCs were isolated from 78 MBC patients before treatment start. mRNA expression levels of 96 genes were measured by quantitative reverse transcriptase polymerase chain reaction. After applying predefined exclusion criteria based on lack of sufficient RNA quality and/or quantity, the data from 45 patients were used to construct a gene expression profile to predict poor responding patients, defined as disease progression or death <9 months, by a leave-one-out cross validation. RESULTS: Of the 45 patients, 19 were clinically classified as poor responders. To identify them, the 75% most variable genes were used to select genes differentially expressed between good and poor responders. An 8-gene CTC predictor was significantly associated with outcome (Hazard Ratio [HR] 4.40, 95% Confidence Interval [CI]: 2.17-8.92, P < 0.001). This predictor identified poor responding patients with a sensitivity of 63% and a positive predictive value of 75%, while good responding patients were correctly predicted in 85% of the cases. In multivariate Cox regression analysis, including CTC count at baseline, the 8-gene CTC predictor was the only factor independently associated with outcome (HR 4.59 [95% CI: 2.11-9.56], P < 0.001). This 8-gene signature was not associated with outcome in a group of 71 MBC patients treated with systemic treatments other than AI. CONCLUSIONS: An 8-gene CTC predictor was identified which discriminates good and poor outcome to first-line aromatase inhibitors in MBC patients. Although results need to be validated, this study underscores the potential of molecular characterization of CTCs.