Background: For most early-stage aggressive breast cancers (BC), neoadjuvant therapy (NAT) with chemotherapy (CT), with/without HER2 blockade or immune checkpoint blockade (ICB), is the current standard of care. However, around half of them will not respond to NAT and have a higher risk of recurrence. This study aims to provide insights into the cellular and molecular heterogeneity, potential resistance mechanisms, and predictive biomarkers for NAT response by analyzing the tumor and immune landscape using single-cell RNA sequencing (scRNA-seq). Methods: Tissue samples were prospectively collected from pre-treatment biopsies, post-treatment tumor beds, and normal adjacent tissue of patients treated with NAT for luminal B-like (LumB), HER2-positive (HER2+), and triple-negative breast cancer (TNBC). Cells were processed using the 10x Genomics Chromium Next GEM Single Cell 5’ platform and analyzed for gene expression and T-cell and B-cell repertoire profiling. Following data pre-processing, cell clusters were annotated using unsupervised clustering and canonical marker genes. Comprehensive analyses involving copy number variation (CNV), pathway analysis, pseudotime trajectory, and ligand-receptor (LR) interactions were conducted. Differences in gene expression and cell proportions were assessed using t-tests and Wilcoxon rank-sum tests. Results: We obtained high-quality scRNA-seq data from 30 patients across various time points, totaling 286,346 cells. NAT responders were 1/4 in LumB, 5/5 in HER2+, 7/14 in TNBC with CT alone, and 5/7 in TNBC treated with CT-ICB. After annotation, tumor tissue was enriched in immune cells and specific cancer-associated fibroblasts (CAFs) compared to normal adjacent tissue. Across BC subtypes, we observed differences in tumor cell origins, tumor microenvironment (TME) composition, and its dynamics under NAT. TNBC tumor cells indicated a basal/luminal progenitor origin, while LumB and HER2+ tumor cells displayed a luminal hormone-responsive origin. Also, LumB had lower levels of immune cells compared to TNBC and HER2+, especially tumor-reactive CXCL13+ and effector T cells. NAT influenced cell subtype dynamics, decreasing T and B cells and increasing CAFs in all BC subtypes. Post-NAT, there was a reduction in naïve CD4 and CD8 T cells and Tregs, but an increase in resident memory and T helper cells. Of interest, responders showed a significant increase in the CD8 effector/Treg ratio post-NAT compared to non-responders (p<0.001), likely due to the higher cytotoxic effect of CT on Tregs, which contributes to its antitumor efficacy. Response to NAT also correlated with higher proportions of proliferating T cells in the G2/M cell cycle phase (p<0.01), while higher levels of T cells in the G1 phase were associated with non-responders. Of interest, a granular analysis of the T cell compartment revealed clonotypic variations and CXCL13+ CD8+ T cell expansion in pre-treatment samples linked to NAT response. Cell-cell interaction analyses further highlighted LR interactions specific to responders between tumor cells and CXCL13+ CD4+/CD8+ T cells, NK cells, proliferative T cells, and B cells. On the other hand, LR interactions specific to response to CT-ICB versus CT alone in TNBC were primarily observed among immune cell subsets, particularly between CXCL13+ CD4/CD8+ T cells and T regs and B cells (via CXCL13/CXCR5, TNFSF4/TNFRSF4, CCL5/CR5, CCL3/CCR5 or TNF/ICOS LR pairs), suggesting the necessity of immune cell communication in lymphoid aggregates for an effective immune response. Finally, tumor cell sub-clonal analysis by inferred CNV revealed distinct patterns of genomic and transcriptomic heterogeneity among epithelial cells and TMEs. Conclusions: Our findings underscore tumor-immune landscape complexity and offer insights into cellular dynamics, potentially unveiling predictive biomarkers of response to NAT in BC. Citation Format: Marcela Carausu, David Gacquer, Xiaoxiao Wang, Samira Majjaj, Delphine Vincent, Laurence Buisseret, Michail Ignatiadis, Jérémy Blanc, Daphne T’Kint de Roodenbeke, Isabelle Veys, Filip De Neubourg, Denis Larsimont, Françoise Rothé, and Christos Sotiriou. Deciphering the Tumor-Immune Landscape and Mechanisms of Response and Resistance to Neoadjuvant Therapy in Early-Stage Breast Cancer Using Single-Cell RNA Sequencing [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr PS1-08.

Abstract Background Tertiary lymphoid structures (TLS) are ectopic lymphoid organs playing a role in adaptive antitumor immune response. They were shown to be associated with favorable outcome and appears to be a promising biomarker for response to immune checkpoint inhibitors (ICI). Yet, there is no consensus for their detection and quantification. Here we aimed to derive a specific TLS signature using high resolution spatial transcriptomics data from a large series of triple negative breast cancer (TNBC) samples and to assess its clinical relevance including response to ICI. Methods Spatial transcriptomics (ST) was performed on a series of 94 early-stage TNBC surgical samples with detailed clinicopathological and outcome data. TLS and tumor infiltrating lymphocytes (TILs) were scored using hematoxylin and eosin and double immunohistochemistry (CD3/CD20) stained slides by a dedicated breast pathologist. Regression based on morphological annotations and deconvolution methods estimated the fraction of gene expression related to TLS in each ST spot allowing to derive specific TLS signature. Its prognostic and predictive value of response to ICI was assessed using publicly available breast cancer (METABRIC, SCAN-B, and I-SPY2) and other tumor type datasets treated with ICI (Bareche et al. Ann Oncol, 2022) from bulk gene expression data. Results Deconvolution of the TLS compartments using the ST gene expression data showed that TLS are enriched in all B cell subsets, CD4+ (central) memory and naïve T cells, as well as mast cells. A functional analysis showed an enrichment of ‘vascular endothelial cell proliferation’, ‘mitotic G2/M transition checkpoint’, ‘V/D/J recombination’ and ‘regulation of cell chemotaxis to fibroblast growth factor’ suggesting that TLS aggregates are associated with angiogenesis, immune cell proliferation, adaptative humoral response and tissue remodeling. A comparison of gene expression data between TLS and non-aggregated TILs led to the development of a specific TLS gene signature comprising B and T cell-specific genes, immunoglobulin genes as well as genes associated with TLS initiation. Its projection on tumor slides overlapped with the regions annotated as TLS by the pathologist, demonstrating its specificity for TLS detection. As expected, the highest levels of the TLS signature were observed in the immunomodulatory TNBC molecular subtype and fully inflamed tumors, whereas the lowest levels were observed in the mesenchymal molecular subtype and immune desert tumors (p< 0.05). Of note, high levels of the TLS signature were associated with better prognosis in TNBC patients from METABRIC (p=6.5 10−5) and SCAN-B datasets (p=1.6 10−3) as well as with higher pathological complete response rates in all breast cancer patients treated with neoadjuvant pembrolizumab in the I-SPY2 study (p=0.026). Similar results were found in other tumor types treated with immunotherapy in the metastatic setting including metastatic melanoma, pancreatic and bladder cancers (PFS, p=6 10−6). Of interest, the TLS signature outperformed the predictive value of other immune-related signatures including TILs suggesting a key role of TLS in obtaining a sustainable, adaptive antitumor immune response in the vicinity of the tumor area. Conclusion By leveraging the potential of spatial transcriptomics, we have successfully developed a unique TLS gene signature that demonstrates a strong correlation with the response to ICI in breast cancer and various other tumor types. This TLS gene signature outperforms other immune biomarkers, underscoring the pivotal role of TLS in eliciting a robust antitumor immune response. The universality of this TLS signature makes it a potent biomarker capable of identifying patients who would benefit from immunotherapy, pending further validation. Citation Format: Xiaoxiao Wang, David Venet, Frédéric Lifrange, Denis Larsimont, Mattia Rediti, Linnea Stenbeck, Floriane Dupont, Ghizlane Rouas, Andrea Joaquin Garcia, David Gacquer, Ligia Craciun, Laurence Buisseret, Nayanika Bhalla, Yuvarani Masarapu, Kim Thrane, Eva Gracia Villacampa, Lovisa Franzén, Sami Saarenpää, Linda Kvastad, Joakim Lundeberg, Françoise Rothé, Christos Sotiriou. Characterization of tertiary lymphoid structures and its association with response to immune checkpoint inhibitors in triple negative breast cancer using spatial transcriptomics [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-25-07.

Introduction: Invasive lobular breast cancer (ILC) is the most frequent special type of breast cancer. Recent studies showed the impact of intratumor heterogeneity (ITH) on patient outcome. Here, we aimed to better characterize ITH in ILC using spatial transcriptomics (ST) together with high-resolution morphological annotation. Methods: Spatial transcriptomics (Visium 10x Genomics) was performed on frozen tumor samples from 15 primary estrogen receptor positive, HER2-negative ILCs with 4 patients developing disease relapse. For each sample, we annotated hematoxylin/eosin sections (QuPath software) in two steps: manual annotation of specific histomorphological structures (e.g. normal breast ducts, fat tissue, vessels) and machine learning annotation of stroma and tumor cells at the single cell level. Proportion of each specific tissue type per sample was defined by pixel percentage computed within each ST spot. For each sample, the proportion of a given tissue type was defined as the proportion of pixels annotated with this specific type averaged across all spots within the tissue section. Spatially variable genes were used as input for non-negative matrix factorization and the reduced expression matrix was clustered with the Louvain algorithm implemented in Seurat. A cluster of spots was defined as tumoral if the average proportion of pixels annotated as tumor across its constitutive spots was higher than the average proportion of tumor pixels across all spots from the tissue section. Cluster characterization was performed using gene set enrichment analysis based on hallmarks (Molecular Signature Database) with a false discovery rate < 0.05. Spatial heterogeneity and tumor organization within each sample were assessed according to the number and type of cluster interactions, homo-contacts being defined as interactions between spots belonging to the same cluster and hetero-contacts between spots from two different clusters. Comparisons between groups were assessed using Wilcoxon test. Results: A total of 45 tumor clusters were identified among the 15 patients, with a range of 2-4 tumor clusters per sample highlighting intra-tumor heterogeneity. Cluster characterization revealed the presence of clusters enriched in different biological pathways within a given sample. These analyses also showed inter-patient heterogeneity as witnessed by distinct tumor clusters only present in a subset of tissue samples. In particular, 66% (N=10/15) of the tissue samples harbored clusters enriched in oxidative phosphorylation, 53% (N=8/15) in epithelial-mesenchymal transition, 33% (N=5/15) in interferon gamma response, 27% (N=4/15) in TNF-alpha via NFkB, 27% (N=4/15) in androgen response and 13% (N=2/15) in protein secretion hallmarks. All samples shared at least one tumor cluster enriched in estrogen early and late response.Although the number of tumor clusters was similar between samples from patients with or without relapse (median of 3, range 2-4), the presence of clusters enriched in protein secretion was associated with disease recurrence (p = 0.02). Of note, higher number of hetero-contacts mirroring tumor disorganization was associated with poor outcome although not significant (p= 0.08). Conclusions: Here, we showed for the first time a substantial inter- and intra-tumor heterogeneity of ILC at an unprecedented level, characterized by the presence of specific tumor clusters and distinct tumor organization patterns associated with outcome. We also. uncovered potentially targetable clusters missed by bulk analysis, offering novel perspectives for optimized ILC care. Further validation is warranted. Citation Format: Laetitia Collet, Matteo Serra, Mattia Rediti, Frédéric Lifrange, David Venet, XiaoXiao Wang, Delphine Vincent, Ghizlane Rouas, Danai Fimereli, David Gacquer, Andrea Joaquin Garcia, Isabelle Veys, Ligia Craciun, Denis Larsimont, Miikka Vikkula, François Duhoux, Françoise Rothé, Christos Sotiriou. Unravelling spatial tumor organization and heterogeneity in lobular breast cancer using spatial transcriptomics [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD14-02.

Background: Invasive lobular breast carcinoma (ILC) represents 5 to 15% of all invasive breast cancers (BCs). Here, we aim to investigate inter- and intra-tumor heterogeneity in terms of microenvironment composition, PAM50 molecular classification and proliferation (genomic grade index [GGI]) by combining spatial transcriptomics (ST) and accurate morphological annotation. Methods: Spatial RNA sequencing (Visium - 10X Genomics) was performed on frozen tumor samples from 15 primary estrogen receptor positive, HER2-negative ILC patients with long-term follow up. Hematoxylin/eosin slides were morphologically annotated integrating manual and machine learning-based approaches reaching single-cell resolution (QuPath software). The relative histomorphological categories (HC) composition of each spot across the ST slide was computed as percentage of pixels, while the level of proximity of different HC was evaluated computing the proportion of co-occurring HC at each spot. The PAM50 subtypes (AIMS R package) and GGI were computed on spots containing at least 40% of tumor (merging all the spots belonging to each sample [pseudo-bulk] for PAM50, while calculating mean and standard deviation [SD] across spots for GGI). PAM50 was also computed on the pseudo-bulk of the whole set of spots per sample. Wilcoxon and Spearman rank tests were used to compare continuous variables and assess correlations. Results: Out of 15 tumors, 7 were T2 or T3, 6 were node positive at diagnosis and 14 were grade 2. Four patients experienced disease relapse. Morphological annotation revealed that an average (per patient) of 20.3% (5.6-46.7%), 65.9% (45.5-83.5%) and 6.5% (0.0-27.1%) of the spots corresponded to tumor, stroma and fat tissue respectively. Larger tumors (T2-3 vs T1) presented a higher proportion of fat tissue and tumor cells, although these differences did not reach statistical significance. The levels and spatial variability of proliferation, measured using GGI, were higher in T2-3 compared to T1 tumors (p = 0.072 and 0.040, respectively). Of note, higher spatial variability of proliferation was also associated with node-positive tumors (p = 0.066). By computing the PAM50 classification using the pseudo-bulk, 9 samples were classified as luminal A, 1 as luminal B and 5 as normal-like. Of interest, when focusing on the tumor enriched spots, 60% of the samples previously classified as normal-like were re-classified as luminal A. Samples from patients who relapsed showed a higher fraction of fat tissue at the level of the whole slide (14.4% vs 3.5%; p = 0.018), with an increased co-localization of fat tissue and tumor cells at the spot level as well as higher proliferation values, although not significant. Conclusions: High proportion of fat tissue together with higher co-localization of fat tissue with tumor cells are associated with poor outcome in ILC. Higher spatial variability of proliferation is associated with larger tumors, lymph node positivity and recurrence. The proportion of stroma and fat tissue affected substantially the PAM50 classification of the tumors. Further validation is needed. Citation Format: Matteo Serra, Laetitia Collet, Mattia Rediti, Frédéric Lifrange, David Venet, Xiaoxiao Wang, Delphine Vincent, Ghizlane Rouas, Danai Fimereli, David Gacquer, Andrea Joaquin Garcia, Isabelle Veys, Ligia Craciun, Denis Larsimont, Miikka Vikkula, François Duhoux, Françoise Rothé, Christos Sotiriou. Integrating spatial transcriptomics and high-resolution morphological annotation to investigate tumor heterogeneity and PAM50 molecular subtyping in lobular breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-05-03.

Abstract Background Triple negative breast cancer (TNBC) is a heterogeneous disease characterized by at least five molecular subtypes, namely basal like (BL), immunomodulatory (IM), luminal androgen receptor (LAR), mesenchymal (M) and mesenchymal stem like (MSL), associated with distinct gene expression, genomic and tumor microenvironment (TME) profiles. Recent technological advances allow to investigate intratumor geographic heterogeneity ignored by bulk tumor analyses. Here, we deployed spatial transcriptomics (ST) to interrogate tumor and stroma compartments heterogeneity and assess its association with clinical outcome. Methods Spatial transcriptomics (Visium® Spatial Gene Expression, 10X Genomics) was performed on a retrospective series of 94 case-control TNBC samples matched for known clinic-pathological parameters with available long term outcome. Detailed morphological annotations spanning 11 histomorphological categories were performed by a breast dedicated pathologist assisted by the automated QuPath digital pathology software. Bioinformatic analyses were performed using in house pipelines. Results We investigated the distribution of each morphological category across the five TNBC molecular subtypes. We found that LAR, M and MSL, even though they had less tumor cells, had more patches of very small size (p< 0.0001). On the other hand, BL and IM had few large and dense patches. Stroma had an opposite distribution compared to tumor, with LAR and MSL being enriched with stroma (p< 00001). Tumor infiltrating lymphocytes were specific of the IM (p< 0.0001) and to a lesser extent the BL subtype. Normal structures, like fat tissue (p< 0.008), lactiferous ducts (p< 0.03) and vessels (p< 0.02), were more present in MSL and LAR. The differences between the molecular subtypes are mirrored at the level of their cell composition and tumor organization, suggesting the possibility to assess TNBC molecular subtypes from imaging data alone. At the gene expression level, spatial deconvolution analyses revealed the co-existence of tumor and stroma compartments from different TNBC subtypes within a tumor sample of a given subtype as defined by bulk tumor analysis. Interestingly, these different tumor-stroma combinations were associated with prognosis. For example, M tumors associated with MSL stroma seem to have a better prognosis than M tumors with an M stroma (p=0.001). Furthermore, spatial resolution of the gene expression identified 418 individual clusters (median 4 clusters per sample) associated with specific molecular and cellular features highlighting a substantial intra-patient heterogeneity. These clusters were further grouped into 11 ecotypes associated with distinct hallmarks and pathways, including EMT, angiogenesis, DNA repair and immune profiles revealing an important inter-patient heterogeneity beyond TNBC classification. Interestingly, 2 ecotypes were identified within the IM subtype associated with distinct clinical outcome, with ecotype 6 characterized by high EMT, mesenchymal stroma and worse prognosis (p = 0,021). Conclusion To our knowledge, this is the largest study demonstrating the substantial intra- and inter-patient heterogeneity characterizing TNBC at an unprecedented level, with differences both in tumor and stroma composition as well as spatial organization and clinical outcome. Our results hightlight the need to consider TNBC heterogeneity for patient care and future clinical development including immunotherapy. Citation Format: Xiaoxiao Wang, David Venet, Frédéric Lifrange, Denis Larsimont, Mattia Rediti, Linnea Stenbeck, David Gacquer, Floriane Dupont, Ghizlane Rouas, Matteo Serra, Joakim Lundeberg, Françoise Rothé, Christos Sotiriou. PD4-01 Spatial transcriptomics reveals a substantial heterogeneity in TNBC tumor and stroma compartments with potential clinical implications [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD4-01.

Background: The early molecular events in human thyrocytes after I-131 exposure have not yet been unravelled. Therefore, we investigated the role of TSH in the I-131-induced DNA damage response and gene expression in primary cultured human thyrocytes. Methods: Following exposure of thyrocytes, in the presence or absence of TSH, to I-131 (beta radiation), gamma radiation (3 Gy), and hydrogen peroxide (H2O2), we assessed DNA damage, proliferation, and cell-cycle status. We conducted RNA sequencing to profile gene expression after each type of exposure and evaluated the influence of TSH on each transcriptomic response. Results: Overall, the thyrocyte responses following exposure to beta or gamma radiation and to H2O2 were similar. However, TSH increased I-131-induced DNA damage, an effect partially diminished after iodide uptake inhibition. Specifically, TSH increased the number of DNA double-strand breaks in nonexposed thyrocytes and thus predisposed them to greater damage following I-131 exposure. This effect most likely occurred via G alpha(q) cascade and a rise in intracellular reactive oxygen species (ROS) levels. beta and gamma radiation prolonged thyroid cell-cycle arrest to a similar extent without sign of apoptosis. The gene expression profiles of thyrocytes exposed to beta/gamma radiation or H2O2 were overlapping. Modulations in genes involved in inflammatory response, apoptosis, and proliferation were observed. TSH increased the number and intensity of modulation of differentially expressed genes after I-131 exposure. Conclusions: TSH specifically increased (131I)-induced DNA damage probably via a rise in ROS levels and produced a more prominent transcriptomic response after exposure to I-131.

The cerebral cortex underwent rapid expansion and increased complexity during recent hominid evolution. Gene duplications constitute a major evolutionary force, but their impact on human brain development remains unclear. Using tailored RNA sequencing (RNA-seq), we profiled the spatial and temporal expression of hominid-specific duplicated (HS) genes in the human fetal cortex and identified a repertoire of 35 HS genes displaying robust and dynamic patterns during cortical neurogenesis. Among them NOTCH2NL, human-specific paralogs of the NOTCH2 receptor, stood out for their ability to promote cortical progenitor maintenance. NOTCH2NL promote the clonal expansion of human cortical progenitors, ultimately leading to higher neuronal output. At the molecular level, NOTCH2NL function by activating the Notch pathway through inhibition ofcisDelta/Notch interactions. Our study uncovers a large repertoire of recently evolved genes active during human corticogenesis and reveals how human-specific NOTCH paralogs may have contributed to the expansion of the human cortex.

The advent of next generation sequencing technologies has boosted the interest in exploring the role of fusion genes in the development and progression of solid tumors. In breast cancer, most of the detected gene fusions seem to be "passenger" events while the presence of recurrent and driver fusions is still under study. We performed RNA sequencing in 55 well-characterized breast cancer samples and 10 adjacent normal breast tissues, complemented by an analysis of SNP array data. We explored the presence of fusion genes and defined their association with breast cancer subtypes, clinical-pathologic characteristics and copy number aberrations. Overall, 370 fusions were detected across the majority of the samples. HER2+ samples had significantly more fusions than triple negative and luminal subtypes. The number of fusions was correlated with histological grade, Ki67 and tumor size. Clusters of fusion genes were observed across the genome and a significant correlation of fusions with copy number aberrations and more specifically amplifications was also revealed. Despite the large number of fusion events, only a few were recurrent, while recurrent individual genes forming fusions with different partners were also detected including the estrogen receptor 1 gene in the previously detected ESR1-CCDC170 fusion. Overall we detected novel gene fusion events while we confirmed previously reported fusions. Genomic hotspots of fusion genes, differences between subtypes and small number of recurrent fusions are the most relevant characteristics of these events in breast cancer. Further investigation is necessary to comprehend the biological significance of these fusions.

Textbooks suggest that cancers are compact balls with an inner core and an invasive front in contact with non-cancerous cells, and that tumor growth is driven by tumor cell proliferation subsequent to oncogenic genome mutations. We reconstructed at histological scale the 3D volume occupied by tumor cells in two regions of a BRAFV600E-mutated papillary thyroid carcinoma (PTC) with low tumor purity, as determined by sequencing, but initially considered high purity during pathology review. In contrast with a compact ball, tumor cells formed a sparse mesh deeply embedded within the stroma. The concepts of inner core and invasive front broke down in this morphology: all tumor cells were within short distance from the stroma. The fibrous stroma was highly cellular and proliferative, a result confirmed in an independent series. This case was not unique: 3.5% of The Cancer Genome Atlas PTCs had purities <25%, 27% were below the 60% purity inclusion criterion. Moreover, the presence of BRAFV600E was associated with extensive fibrosis, high stromal activation, and dedifferentiation. Thus, non-tumor cells make most of the tumor mass and contribute to its expansion in a significant fraction of BRAFV600E PTCs. Therapeutics targeting the tumor-stroma crosstalk could be beneficial in this context.

Background Papillary Thyroid Cancer (PTC) is the most prevalent type of endocrine cancer. Its incidence has rapidly increased in recent decades but little is known regarding its complete microRNA transcriptome (miRNome). In addition, there is a need for molecular biomarkers allowing improved PTC diagnosis. Methods We performed small RNA deep-sequencing of 3 PTC, their matching normal tissues and lymph node metastases (LNM). We designed a new bioinformatics framework to handle each aspect of the miRNome: whole expression profiles, isomiRs distribution, non-templated additions distributions, RNA-editing or mutation. Results were validated experimentally by qRT-PCR on normal samples, tumors and LNM from 14 independent patients and in silico using the dataset from The Cancer Genome Atlas (small RNA deepsequencing of 59 normal samples, 495 PTC, and 8 LNM). Results We performed small RNA deep-sequencing of 3 PTC, their matching normal tissues and lymph node metastases (LNM). We designed a new bioinformatics framework to handle each aspect of the miRNome: whole expression profiles, isomiRs distribution, non-templated additions distributions, RNA-editing or mutation. Results were validated experimentally by qRT-PCR on normal samples, tumors and LNM from 14 independent patients and in silico using the dataset from The Cancer Genome Atlas (small RNA deep-sequencing of 59 normal samples, 495 PTC, and 8 LNM). We confirmed already described up-regulations of microRNAs in PTC, such as miR-146b-5p or miR-222-3p, but we also identified down-regulated microRNAs, such as miR-7-5p or miR-30c-2-3p. We showed that these down-regulations are linked to the tumorigenesis process of thyrocytes. We selected the 14 most down-regulated microRNAs in PTC and we showed that they are potential biomarkers of PTC samples. Nevertheless, they can distinguish histological classical variants and follicular variants of PTC in the TCGA dataset. In addition, 12 of the 14 down-regulated microRNAs are significantly less expressed in aggressive PTC compared to non-aggressive PTC. We showed that the associated aggressive expression profile is mainly due to the presence of the BRAF V600E mutation. In general, primary tumors and LNM presented similar microRNA expression profiles but specific variations like the down-regulation of miR-7-2-3p and miR-30c-2-3p in LNM were observed. Investigations of the 5p-to-3p arm expression ratios, non-templated additions or isomiRs distributions revealed no major implication in PTC tumorigenesis process or LNM appearance. Conclusions Our results showed that down-regulated microRNAs can be used as new potential common biomarkers of PTC and to distinguish main subtypes of PTC. MicroRNA expressions can be linked to the development of LNM of PTC. The bioinformatics framework that we have developed can be used as a starting point for the global analysis of any microRNA deep-sequencing data in an unbiased way.

BACKGROUND:Studies evaluating the presence of viral sequences in breast cancer (BC), including various strains of human papillomavirus and human herpes virus, have yielded conflicting results. Most were based on RT-PCR and in situ hybridization.METHODS:In this report we searched for expressed viral sequences in 58 BC transcriptomes using five distinct in silico methods. In addition, we complemented our RNA sequencing results with exome sequencing, PCR and immunohistochemistry (IHC) analyses. A control sample was used to test our in silico methods.RESULTS:All of the computational methods correctly detected viral sequences in the control sample. We identified a small number of viral sequences belonging to human herpesvirus 4 and 6 and Merkel cell polyomavirus. The extremely low expression levels-two orders of magnitude lower than in a typical hepatitis B virus infection in hepatocellular carcinoma-did not suggest active infections. The presence of viral elements was confirmed in sample-matched exome sequences, but could not be confirmed by PCR or IHC.CONCLUSIONS:Our results show that no viral sequences are expressed in significant amounts in the BC investigated. The presence of non-transcribed viral DNA cannot be excluded.

The contribution of intratumor heterogeneity to thyroid metastatic cancers is still unknown. The clonal relationships between the primary thyroid tumors and lymph nodes (LN) or distant metastases are also poorly understood. The objective of this study was to determine the phylogenetic relationships between matched primary thyroid tumors and metastases. We searched for non-synonymous single-nucleotide variants (nsSNVs), gene fusions, alternative transcripts, and loss of heterozygosity (LOH) by paired-end massively parallel sequencing of cDNA (RNA-Seq) in a patient diagnosed with an aggressive papillary thyroid cancer (PTC). Seven tumor samples from a stage IVc PTC patient were analyzed by RNA-Seq: two areas from the primary tumor, four areas from two LN metastases, and one area from a pleural metastasis (PLM). A large panel of other thyroid tumors was used for Sanger sequencing screening. We identified seven new nsSNVs. Some of these were early events clonally present in both the primary PTC and the three matched metastases. Other nsSNVs were private to the primary tumor, the LN metastases and/or the PLM. Three new gene fusions were identified. A novel cancer-specific KAZN alternative transcript was detected in this aggressive PTC and in dozens of additional thyroid tumors. The PLM harbored an exclusive whole-chromosome 19 LOH. We have presented the first, to our knowledge, deep sequencing study comparing the mutational spectra in a PTC and both LN and distant metastases. This study has yielded novel findings concerning intra-tumor heterogeneity, clonal evolution and metastases dissemination in thyroid cancer.

Little is known about how RNA editing operates in cancer. Transcriptome analysis of 68 normal and cancerous breast tissues revealed that the editing enzyme ADAR acts uniformly, on the same loci, across tissues. In controlled ADAR expression experiments, the editing frequency increased at all loci with ADAR expression levels according to the logistic model. Loci-specific "editabilities," i.e., propensities to be edited by ADAR, were quantifiable by fitting the logistic function to dose-response data. The editing frequency was increased in tumor cells in comparison to normal controls. Type I interferon response and ADAR DNA copy number together explained 53% of ADAR expression variance in breast cancers. ADAR silencing using small hairpin RNA lentivirus transduction in breast cancer cell lines led to less cell proliferation and more apoptosis. A-to-I editing is a pervasive, yet reproducible, source of variation that is globally controlled by 1q amplification and inflammation, both of which are highly prevalent among human cancers.

Background Microarrays have revolutionized breast cancer (BC) research by enabling studies of gene expression on a transcriptome-wide scale. Recently, RNA-Sequencing (RNA-Seq) has emerged as an alternative for precise readouts of the transcriptome. To date, no study has compared the ability of the two technologies to quantify clinically relevant individual genes and microarray-derived gene expression signatures (GES) in a set of BC samples encompassing the known molecular BC’s subtypes. To accomplish this, the RNA from 57 BCs representing the four main molecular subtypes (triple negative, HER2 positive, luminal A, luminal B), was profiled with Affymetrix HG-U133 Plus 2.0 chips and sequenced using the Illumina HiSeq 2000 platform. The correlations of three clinically relevant BC genes, six molecular subtype classifiers, and a selection of 21 GES were evaluated. Results 16,097 genes common to the two platforms were retained for downstream analysis. Gene-wise comparison of microarray and RNA-Seq data revealed that 52% had a Spearman’s correlation coefficient greater than 0.7 with highly correlated genes displaying significantly higher expression levels. We found excellent correlation between microarray and RNA-Seq for the estrogen receptor (ER; r s = 0.973; 95% CI: 0.971-0.975), progesterone receptor (PgR; r s = 0.95; 0.947-0.954), and human epidermal growth factor receptor 2 (HER2; r s = 0.918; 0.912-0.923), while a few discordances between ER and PgR quantified by immunohistochemistry and RNA-Seq/microarray were observed. All the subtype classifiers evaluated agreed well (Cohen’s kappa coefficients >0.8) and all the proliferation-based GES showed excellent Spearman correlations between microarray and RNA-Seq (all r s >0.965). Immune-, stroma- and pathway-based GES showed a lower correlation relative to prognostic signatures (all r s >0.6). Conclusions To our knowledge, this is the first study to report a systematic comparison of RNA-Seq to microarray for the evaluation of single genes and GES clinically relevant to BC. According to our results, the vast majority of single gene biomarkers and well-established GES can be reliably evaluated using the RNA-Seq technology.