The Repertoire of Serous Ovarian Cancer Non-genetic Heterogeneity Revealed by Single-Cell Sequencing of Normal Fallopian Tube Epithelial Cells

Hu, Zhiyuan; Artibani, Mara; Alsaadi, Abdulkhaliq; Wietek, Nina; Morotti, Matteo; Shi, Tingyan; Zhong, Zhe; González, Laura Santana; El-Sahhar, Salma; KaramiNejadRanjbar, Mohammad; Mallett, Garry; Feng, Yun; Masuda, Kenta; Zheng, Yiyan; Chong, Kay Y.; Damato, Stephen; Dhar, Sunanda; Campo, Leticia; Campanile, Riccardo Garruto; Majd, Hooman Soleymani; Rai, Vikram; Maldonado-Pérez, David; Jones, Stephanie; Cerundolo, Vincenzo; Sauka‐Spengler, Tatjana; Yau, Christopher; Ahmed, Ahmed A.

doi:10.1016/j.ccell.2020.01.003

Cited by 129 publications

(115 citation statements)

References 125 publications

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“…However, most of the studies are based on laboratory models instead of human tumors. The stressed-related profile has been found in other single cell studies in muscle stem cells (van den Brink et al, 2017) and HGSOC (Hu et al, 2020) . Hu et al suggest several genes belonging to the stress-related transcriptional profile to be artifacts due to sample preparation for scRNA-seq experiments.…”

Section: Discussionsupporting

confidence: 64%

“…However, the analyses using bulk transcriptomes can be severely biased by cell type compositions and have limited ability to capture the heterogeneity within a tumor as multiple subtypes can co-exist in the same tumor. A recent work using single-cell RNA sequencing (scRNA-seq) has characterized six cell subtypes of fallopian tube epithelium and identified a epithelial-mesenchymal transition (EMT)-high subtype of HGSOC with poor prognosis (Hu et al, 2020) . However, the transcriptional changes due to chemotherapy have remained elusive.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of single-cell RNA-seq data from ovarian cancer samples before and after chemotherapy links stress-related transcriptional profile with chemotherapy resistance

Zhang

Erkan

Dai

et al. 2020

Preprint

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The authors declare no potential conflicts of interest. 1 Translational relevanceWe discovered a stress-related transcriptional profile that is significantly enriched in fresh tissue samples after chemotherapy and is significantly associated with poor progression-free survival in an independent patient cohort. The survival association is independent of age, tumor purity or BRCAness. Therefore, this chemotherapy resistance associated profile is intrinsic and could thus be targeted already in treatment-naive patients. The translation potential of the stress-related transcriptomics profile was further supported by pan-cancer cell line analysis that showed that cell lines with high stress-related transcriptional profile are not affected by platinum, corroborating our results, whereas they were more sensitive to MEK1/2 inhibitors. Taken together, the stress-related transcriptional profile, quantifiable with a set of 35 marker genes, provides a basis for improved prediction of platinum response as well as novel avenues to treat this patient group more effectively.2 Abstract Chemotherapy resistance is the greatest contributor to cancer mortality and the most urgent unmet challenge in oncology. In order to reveal transcriptomics changes due to platinum-based chemotherapy we analyzed single-cell RNA-seq data from fresh tissue samples taken at the time of diagnosis and after neoadjuvant chemotherapy from 11 high-grade serous ovarian cancer (HGSOC) patients. With a novel clustering method accounting for patient-specific variability and technical confounders, we identified 12 clusters. Of these, a stress-related transcriptional profile was enriched during chemotherapy and associated significantly to poor progression-free survival (PFS) and disease-free interval (DFI) in deconvoluted bulk RNA-seq data analysis of treatment-naive samples in TCGA cohort. Pan-cancer cell line analysis suggests that patients with high stress-related transcriptional profile may benefit from MEK1/2 inhibitors instead of platinum. Further, h igh proportion of stromal components and high interaction score between tumor and stromal suggest the tumor cells with high-stress profile actively interact with and potentially recruit stromal cells to their microenvironment already prior to chemotherapy, potentially facilitating protection from chemotherapeutic treatments. In summary, we have identified a stress-related transcriptional profile , which is present at the time of diagnosis, enriched during platinum treatment, independent predictor for poor PFS and DFI, and, based on in vitro data, targetable with MEK1/2 inhibitors.3

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Section: Discussionsupporting

confidence: 64%

Section: Introductionmentioning

confidence: 99%

Analysis of single-cell RNA-seq data from ovarian cancer samples before and after chemotherapy links stress-related transcriptional profile with chemotherapy resistance

Zhang

Erkan

Dai

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…This cluster was characterized by decreasing expression of OVGP1 and mitotic pathways and genes were strongly enriched ( Figure 3E, Figure S4B), even though we regressed out cell cycle phase scores during pre-processing to minimize the impact of cell cycle heterogeneity on cluster calls. This cluster likely corresponds to cluster C9 from Hu et al (2020). Cells in this cluster appeared to represent an early transitioning cell population at the point of losing OVGP1 expression.…”

Section: Reconstructing Differentiation Trajectories In the Human Falmentioning

confidence: 88%

Single-cell Transcriptomics Identifies Gene Expression Networks Driving Differentiation and Tumorigenesis in the Human Fallopian Tube

Dinh

Lin

Abbasi

et al. 2020

Preprint

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The human fallopian tube harbors the cell-of-origin for the majority of high-grade serous 'ovarian' cancers (HGSCs), but its cellular composition, particularly the epithelial component, is poorly characterized. We performed single-cell transcriptomic profiling in 12 primary fallopian specimens from 8 patients, analyzing around 53,000 individual cells to map the major immune, fibroblastic and epithelial cell types present in this organ. We identified 10 epithelial sub-populations, characterized by diverse transcriptional programs including SOX17 (enriched in secretory epithelial cells), TTF3 and RFX3 (enriched in ciliated cells) and NR2F2 (enriched in early, partially differentiated secretory cells). Based on transcriptional signatures, we reconstructed a trajectory whereby secretory cells differentiate into ciliated cells via a RUNX3 high intermediate. Computational deconvolution of the cellular composition of advanced HGSCs based on epithelial subset signatures identified the 'early secretory' population as a likely precursor state for the majority of HGSCs. The signature of this rare population of cells comprised both epithelial (EPCAM, KRT) and mesenchymal (THY1, ACTA2) features, and was enriched in mesenchymal-type HGSCs (P = 6.7 x 10 -27 ), a group known to have particularly poor prognoses. This cellular and molecular compendium of the human fallopian tube in cancer-free women is expected to advance our understanding of the earliest stages of fallopian epithelial neoplasia.

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“…scRNA-seq of dissociated tumors has identified (partial-)EMT states in some carcinomas (41,42) but not others (55). EMT-like transcriptional profiles also arise normally in the cell type of origin for serous ovarian cancer (56). For breast cancer, changes along the EMT spectrum are mostly described in hormone-negative cell lines, but more-recent work reports EMT-like activation patterns in 65-85% of primary luminal breast cancers (57).…”

Section: Rhegs Are Enriched For Emt Signatures and Correlate With Canmentioning

confidence: 99%

Pan-cancer Drivers are Recurrent Transcriptional Regulatory Heterogeneities in Early-stage Luminal Breast Cancer

Singh

Sutcliffe

Repich

et al. 2020

Preprint

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The authors declare no potential conflicts of interest. Running title: Stochastic profiling of luminal breast cancer by 10cRNA-seqThe heterogeneous composition of solid tumors is known to impact disease progression and response to therapy. Malignant cells coexist in different regulatory states that can be accessed transcriptomically by single-cell RNA sequencing, but these methods have many caveats related to sensitivity, noise, and sample handling. We revised a statistical fluctuation analysis called stochastic profiling to combine with 10-cell RNA sequencing, which was designed for laser-capture microdissection (LCM) and extended here for immuno-LCM. When applied to a cohort of late-onset, early-stage luminal breast cancers, the integrated approach identified thousands of candidate regulatory heterogeneities. Intersecting the candidates from different tumors yielded a relatively stable set of 710 recurrent heterogeneously expressed genes (RHEGs) that were significantly variable in >50% of patients. RHEGs were not confounded by dissociation artifacts, cell cycle oscillations, or driving mutations for breast cancer. Rather, we detected RHEG enrichments for epithelial-to-mesenchymal transition genes and, unexpectedly, the latest pan-cancer assembly of driver genes across cancer types other than breast.Heterogeneous transcriptional regulation conceivably provides a faster, reversible mechanism for malignant cells to sample the effects of potential oncogenes or tumor suppressors on cancer hallmarks. Statement of significanceProfiling intratumor heterogeneity of luminal breast carcinoma cells identifies a recurrent set of genes suggesting sporadic activation of pathways known to drive other types of cancer.

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The Repertoire of Serous Ovarian Cancer Non-genetic Heterogeneity Revealed by Single-Cell Sequencing of Normal Fallopian Tube Epithelial Cells

Cited by 129 publications

References 125 publications

Analysis of single-cell RNA-seq data from ovarian cancer samples before and after chemotherapy links stress-related transcriptional profile with chemotherapy resistance

Analysis of single-cell RNA-seq data from ovarian cancer samples before and after chemotherapy links stress-related transcriptional profile with chemotherapy resistance

Single-cell Transcriptomics Identifies Gene Expression Networks Driving Differentiation and Tumorigenesis in the Human Fallopian Tube

Pan-cancer Drivers are Recurrent Transcriptional Regulatory Heterogeneities in Early-stage Luminal Breast Cancer

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