Genetic intra-tumour heterogeneity in epithelial ovarian cancer and its implications for molecular diagnosis of tumours

Overview of Tumor Heterogeneity in High-Grade Serous Ovarian Cancers

Ovarian cancers encompass a group of neoplasms originating from germinal tissues and exhibiting distinct clinical, pathological, and molecular features. Among these, epithelial ovarian cancers (EOCs) are the most prevalent, comprising five distinct tumor histotypes. Notably, high-grade serous ovarian cancers (HGSOCs) represent the majority, accounting for over 70% of EOC cases. Due to their silent and asymptomatic behavior, HGSOCs are generally diagnosed in advanced stages with an evolved and complex genomic state, characterized by high intratumor heterogeneity (ITH) due to chromosomal instability that distinguishes HGSOCs. Histologically, these cancers exhibit significant morphological diversity both within and between tumors. The histologic patterns associated with solid, endometrioid, and transitional (SET) and classic subtypes of HGSOCs offer prognostic insights and may indicate specific molecular profiles. The evolution of HGSOC from primary to metastasis is typically characterized by clonal ITH, involving shared or divergent mutations in neoplastic sub-clones within primary and metastatic sites. Disease progression and therapy resistance are also influenced by non-clonal ITH, related to interactions with the tumor microenvironment and further genomic changes. Notably, significant alterations occur in nonmalignant cells, including cancer-associated fibroblast and immune cells, during tumor progression. This review provides an overview of the complex nature of HGSOC, encompassing its various aspects of intratumor heterogeneity, histological patterns, and its dynamic evolution during progression and therapy resistance.

Application of a 3D hydrogel-based model to replace use of animals for passaging patient-derived xenografts

Purpose

This 3D in vitro cancer model for propagation of patient-derived cells, using a synthetic self-assembling peptide gel, allows the formation of a fully characterised, tailorable tumour microenvironment. Unlike many existing 3D cancer models, the peptide gel is inert, apart from molecules and motifs deliberately added or produced by cells within the model.

Methods

Breast cancer patient-derived xenografts (PDXs) were disaggregated and embedded in a peptide hydrogel. Growth was monitored by microscopic examination and at intervals, cells were extracted from the gels and passaged on into fresh gels. Passaged cells were assessed by qPCR and immunostaining techniques for the retention of characteristic markers.

Results

Breast cancer PDXs were shown to be capable of expansion over four or more passages in the peptide gel. Contaminating mouse cells were found to be rapidly removed by successive passages. The resulting human cells were shown to be compatible with a range of common assays useful for assessing survival, growth and maintenance of heterogeneity.

Conclusions

Based on these findings, the hydrogel has the potential to provide an effective and practical breast cancer model for the passage of PDXs which will have the added benefits of being relatively cheap, fully-defined and free from the use of animals or animal products. Encapsulated cells will require further validation to confirm the maintenance of cell heterogeneity, genotypes and phenotypes across passage, but with further development, including the addition of bespoke cell and matrix components of the tumour microenvironment, there is clear potential to model other cancer types.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44164-023-00048-x.

Characterizing morphologic subtypes of high-grade serous ovarian cancer by CT: a retrospective cohort study

OBJECTIVE

A novel classification system of high-grade serous ovarian carcinoma based on gross morphology observed at pre-treatment laparoscopy was recently defined. The purpose of this study was to identify radiographic features unique to each morphologic subtype.

METHODS

This retrospective study included 109 patients with high-grade serous ovarian cancer who underwent pre-operative computed tomography (CT) scanning and laparoscopic assessment of disease burden between 1 April 2013 and 5 August 2015. Gross morphologic subtype had been previously assigned by laparoscopy. Two radiologists independently reviewed CT images for each patient, categorized disease at eight anatomic sites, and assessed for radiographic characteristics of interest: large infiltrative plaques, mass-like metastases, enhancing peritoneal lining, architectural distortion, fat stranding, calcifications, and lymph node involvement. Demographic and clinical information was summarized with descriptive statistics and compared using Student's t-tests, χ² tests, or Fisher exact tests as appropriate; kappa statistics were used to assess inter-reader agreement.

RESULTS

Certain radiographic features were found to be associated with gross morphologic subtype. Large infiltrative plaques were more common in type 1 disease (88.7% (47/53) vs 71.4% (25/35), p=0.04), while mass-like metastases were more often present in type 2 disease (48.6% (17/35) vs 22.6% (12/53), p=0.01). Additionally, radiographic presence of disease at the falciform ligament was more common in type 1 morphology (33.9% (19/56) vs 13.2% (5/38), p=0.02).

CONCLUSION

Morphologic subtypes of high-grade serous ovarian cancer were associated with specific CT findings, including the presence of large infiltrative plaques, mass-like metastases, and falciform ligament involvement.

Evolutionary perspectives, heterogeneity and ovarian cancer: a complicated tale from past to present

Ovarian cancer is composed of a complex system of cells best described by features such as clonal evolution, spatial and temporal genetic heterogeneity, and development of drug resistance, thus making it the most lethal gynecologic cancer. Seminal work on cancer as an evolutionary process has a long history; however, recent cost-effective large-scale molecular profiling has started to provide novel insights coupled with the development of mathematical algorithms. In the current review, we have systematically searched for articles that focused on the clonal evolution of ovarian cancer to offer the whole landscape of research that has been done and highlight future research avenues given its characteristic features and connections to evolutionary biology.

Interpatient Heterogeneity in Drug Response and Protein Biomarker Expression of Recurrent Ovarian Cancer

Recurrent ovarian-cancer patients face low 5-year survival rates despite chemotherapy. A variety of guideline-recommended second-line therapies are available, but they frequently result in trial-and-error treatment. Alterations and adjustments are common in the treatment of recurrent ovarian cancer. The drug response of 30 lesions obtained from 22 relapsed ovarian cancer patients to different chemotherapeutic and molecular agents was analyzed with the patient-derived ovarian-cancer spheroid model. The profile of druggable biomarkers was immunohistochemically assessed. The second-line combination therapy of carboplatin with gemcitabine was significantly superior to the combination of carboplatin with PEGylated liposomal doxorubicin (p < 0.0001) or paclitaxel (p = 0.0007). Except for treosulfan, all nonplatinum treatments tested showed a lesser effect on tumor spheroids compared to that of platinum-based therapies. Treosulfan showed the highest efficacy of all nonplatinum agents, with significant advantage over vinorelbine (p < 0.0001) and topotecan (p < 0.0001), the next best agents. The comparative testing of a variety of treatment options in the ovarian-cancer spheroid model resulted in the identification of more effective regimens for 30% of patients compared to guideline-recommended therapies. Recurrent cancers obtained from different patients revealed profound interpatient heterogeneity in the expression pattern of druggable protein biomarkers. In contrast, different lesions obtained from the same patient revealed a similar drug response and biomarker expression profile. Biological heterogeneity observed in recurrent ovarian cancers might explain the strong differences in the clinical drug response of these patients. Preclinical drug testing and biomarker profiling in the ovarian-cancer spheroid model might help in optimizing treatment management for individual patients.

Single-cell RNA-seq recognized the initiator of epithelial ovarian cancer recurrence

Epithelial ovarian cancers (EOCs) are sensitive to chemotherapy but will ultimately relapse and develop drug resistance. The origin of EOC recurrence has been elusive due to intra-tumor heterogeneity. Here we performed single-cell RNA sequencing (scRNA-seq) in 13,369 cells from primary, untreated peritoneal metastasis, and relapse tumors. We used time-resolved analysis to chart the developmental sequence of cells from the metastatic tumors, then traced the earliest replanting cells back to the primary tumors. We discovered seven distinct subpopulations in primary tumors where the CYR61+ "stress" subpopulation was identified as the relapse-initiators. Furthermore, a subpopulation of RGS5+ cancer-associated fibroblasts (CAFs) was found to strongly support tumor metastasis. The combined CYR61/RGS5 expression scores significantly correlated with the relapse-free-survival of EOC patients and can be used as predictors of EOC recurrence. Our study provides insights into the mechanism of EOC recurrence and presents CYR61+ relapse-initiating cells as potential therapeutic targets to prevent EOC relapse.

Integration of Genomic Profiling and Organoid Development in Precision Oncology

Precision oncology involves an innovative personalized treatment strategy for each cancer patient that provides strategies and options for cancer treatment. Currently, personalized cancer medicine is primarily based on molecular matching. Next-generation sequencing and related technologies, such as single-cell whole-transcriptome sequencing, enable the accurate elucidation of the genetic landscape in individual cancer patients and consequently provide clinical benefits. Furthermore, advances in cancer organoid models that represent genetic variations and mutations in individual cancer patients have direct and important clinical implications in precision oncology. This review aimed to discuss recent advances, clinical potential, and limitations of genomic profiling and the use of organoids in breast and ovarian cancer. We also discuss the integration of genomic profiling and organoid models for applications in cancer precision medicine.

Integrated Multi-Tumor Radio-Genomic Marker of Outcomes in Patients with High Serous Ovarian Carcinoma

Purpose: Develop an integrated intra-site and inter-site radiomics-clinical-genomic marker of high grade serous ovarian cancer (HGSOC) outcomes and explore the biological basis of radiomics with respect to molecular signaling pathways and the tumor microenvironment (TME). Method: Seventy-five stage III-IV HGSOC patients from internal (N = 40) and external factors via the Cancer Imaging Archive (TCGA) (N = 35) with pre-operative contrast enhanced CT, attempted primary cytoreduction, at least two disease sites, and molecular analysis performed within TCGA were retrospectively analyzed. An intra-site and inter-site radiomics (cluDiss) measure was combined with clinical-genomic variables (iRCG) and compared against conventional (volume and number of sites) and average radiomics (N = 75) for prognosticating progression-free survival (PFS) and platinum resistance. Correlation with molecular signaling and TME derived using a single sample gene set enrichment that was measured. Results: The iRCG model had the best platinum resistance classification accuracy (AUROC of 0.78 [95% CI 0.77 to 0.80]). CluDiss was associated with PFS (HR 1.03 [95% CI: 1.01 to 1.05], p = 0.002), negatively correlated with Wnt signaling, and positively to immune TME. Conclusions: CluDiss and the iRCG prognosticated HGSOC outcomes better than conventional and average radiomic measures and could better stratify patient outcomes if validated on larger multi-center trials.

Insight updating of the molecular hallmarks in ovarian carcinoma

Background and purpose

Ovarian cancer (OC) is the deadliest gynaecologic cancer characterised by a high heterogeneity not only at the clinical point of view but also at the molecular level. This review focuses on the new insights about the OC molecular classification.

Materials and methods

We performed a bibliographic search for different indexed articles focused on the new molecular classification of OC. All of them have been published in PubMed and included information about the most frequent molecular alterations in OC confirmed by omics approaches. In addition, we have extracted information about the role of liquid biopsy in the OC diagnosis and prognosis.

Results

New molecular insights into OC have allowed novel clinical entities to be defined. Among OC, high-grade serous ovarian carcinoma (HGSOC) which is the most common OC is characterised by omics approaches, mutations in TP53 and in other genes involved in the homologous recombination repair, especially BRCA1/2. Recent studies in HGSOC have allowed a new molecular classification in subgroups according to their mutational, transcriptional, methylation and copy number variation signatures with a real impact in the characterisation of new therapeutic targets for OC to be defined. Furthermore, despite the intrinsic intra-tumour heterogeneity, the advances in next generation sequencing (NGS) analyses of ascetic liquid from OC have opened new ways for its characterisation and treatment.

Conclusions

The advances in genomic approaches have been used for the identification of new molecular profiling techniques which define OC subgroups and has supposed advances in the diagnosis and in the personalised treatment of OC.

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Classification of ovarian cancer regarding to widespread genetic and genomic data.

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Highlighted role of p53 and BRCA1/2 in ovarian cancer for diagnosis and treatment.

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Intra-tumour genetic heterogeneity in ovarian cancer.

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Useful of liquid biopsy study in ovarian cancer diagnosis.

Genome-wide DNA copy number profiling and bioinformatics analysis of ovarian cancer reveals key genes and pathways associated with distinct invasive/migratory capabilities

Ovarian cancer (OC) metastasis presents major hurdles that must be overcome to improve patient outcomes. Recent studies have demonstrated copy number variations (CNVs) frequently contribute to alterations in oncogenic drivers. The present study used a CytoScan HD Array to analyse CNVs and loss of heterozygosity (LOH) in the entire genomes of 6 OC patients and human OC cell lines to determine the genetic target events leading to the distinct invasive/migratory capacities of OC. The results showed that LOH at Xq11.1 and Xp21.1 and gains at 8q21.13 were novel, specific CNVs. Ovarian cancer-related CNVs were then screened by bioinformatics analysis. In addition, transcription factors-target gene interactions were predicted with information from PASTAA analysis. As a result, six genes (i.e., GAB2, AKT1, EGFR, COL6A3, UGT1A1 and UGT1A8) were identified as strong candidates by integrating the above data with gene expression and clinical outcome data. In the transcriptional regulatory network, 4 known cancer-related transcription factors (TFs) interacted with 6 CNV-driven genes. The protein/DNA arrays revealed 3 of these 4 TFs as potential candidate gene-related transcription factors in OC. We then demonstrated that these six genes can serve as potential biomarkers for OC. Further studies are required to elucidate the pathogenesis of OC.

Impact of Tumor and Immunological Heterogeneity on the Anti-Cancer Immune Response

Metastatic tumors are the primary cause of cancer-related mortality. In recent years, interest in the immunologic control of malignancy has helped establish escape from immunosurveillance as a critical requirement for incipient metastases. Our improved understanding of the immune system's interactions with cancer cells has led to major therapeutic advances but has also unraveled a previously unsuspected level of complexity. This review will discuss the vast spatial and functional heterogeneity in the tumor-infiltrating immune system, with particular focus on natural killer (NK) cells, as well as the impact of tumor cell-specific factors, such as secretome composition, receptor-ligand repertoire, and neoantigen diversity, which can further drive immunological heterogeneity. We emphasize how tumor and immunological heterogeneity may undermine the efficacy of T-cell directed immunotherapies and explore the potential of NK cells to be harnessed to circumvent these limitations.

Genome-wide bioinformatics analysis reveals CTCFL is upregulated in high-grade epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy that threatens the health of females. Previous studies have demonstrated that the survival outcomes of patients with different EOC grades varied. Therefore, the EOC grade is considered to serve as a distinctive prognostic factor. To date, the evaluation of ovarian cancer grade relies on pathological examination and a quantitative index for diagnosis is lacking. Furthermore, the dysregulation of genes has been demonstrated to exert pivotal functions in the carcinogenesis of EOCs. Therefore, the identification of effective biomarkers associated with EOC grade is of importance for the development of therapeutic regimens, and also contributes to the prediction of EOC prognosis. Microarrays have been increasingly applied for the identification of potential molecular biomarkers for numerous diseases including EOC. In the present study, four public microarray datasets (GSE26193, GSE63885, GSE30161 and GSE9891) were analyzed. A total of 6,103 upregulated probes corresponding to 5,766 genes, and 4,004 downregulated probes corresponding to 3,707 genes were identified in the GSE26193, GSE63885 and GSE30161 datasets. ALK and LTK ligand 2 was the most downregulated gene associated with the tumor grade, while CCCTC-binding factor like (CTCFL), EGF like domain multiple 6, radical S-adenosyl methionine domain containing 2 and SAM and HD domain containing deoxynucleoside triphosphate triphosphohydrolase 1 were the most upregulated genes associated with EOC grade. The GSE9891 dataset was added for further analysis. Only one probe (1552368_at) encoding for CTCFL was identified to be consistently upregulated in the four examined datasets. Immunohistochemical analysis was used to detect the expression of CTCFL between low- and high-grade EOC tissues and revealed that the EOC grade was closely associated with CTCFL level. This was corroborated via the reverse transcription-quantitative polymerase chain reaction. Taken together, the results of the present study suggested that CTCFL is upregulated in high-grade epithelial ovarian cancer.

LPAR1 regulates the development of intratumoral heterogeneity in ovarian serous cystadenocarcinoma by activating the PI3K/AKT signaling pathway

Background

To explore the role of lysophosphatidic acid receptor 1 (LPAR1) and its correlation with the PI3K/AKT pathway in the development of intratumoral heterogeneity (ITH) in human ovarian serous cystadenocarcinoma (OSC).

Methods

Immunohistochemical staining was performed to detect LPAR1 expression in matched primary and recurrent lesions from the same patients. Cell models of ITH were established using the limiting dilution methodology and Transwell invasion/migration assays. LPAR1 expression in the ITH cell models was silenced or upregulated with lentiviral particles, and the biological characteristics were evaluated using various in vitro and in vivo assessments of cell function. The levels of phosphorylated PI3K/AKT (p-PI3K/p-AKT) in LPAR1 knockdown and LPAR1-overexpressing cells were detected.

Results

The H-scores for LPAR1 staining in the lymphatic metastatic and recurrent lesions were noticeably higher than in the primary tumor lesions from the same patients (P = 0.024/0.031). High LPAR1 expression was associated with worse progression-free survival and overall survival (P = 0.017/0.039). Biological functions in vitro, including invasion, migration, and proliferation, and tumor formation in vivo were decreased in the LPAR1-silenced cells (all P < 0.05). These cellular functions were significantly increased in the LPAR1-overexpressing cells in vitro and in vivo (all P < 0.05). The levels of p-PI3K and p-AKT were significantly decreased in the LPAR1 knockdown cells and significantly increased in the LPAR1-overexpressing cells (all P < 0.05).

Conclusions

Higher levels of the LPAR1 protein were associated with a poor prognosis. LPAR1 plays essential roles in the invasion, migration, and proliferation of heterogeneous subsets of OSC cell lines and the development of ITH of OSC, possibly by modulating the activity of the PI3K/AKT signaling pathway.

Intratumor heterogeneity in prostate cancer

Prostate cancer (PCa) has long been thought of as a disease with a heterogeneous phenotype. It can manifest in men as benign growths that can be safely watched or as more aggressive malignancies that can prove fatal. Recent investigations at the genomic, histopathological and molecular levels have identified tumor heterogeneity, the phenomenon of individual tumor cells presenting distinct genomic and phenotypic characteristics, as one of the most confounding and complex factors underlying PCa diagnosis, prognosis, and treatment. Despite tremendous progress made over the course of the last decade we still have an incomplete understanding of the extent and effect of intra- and inter-tumoral heterogeneity in the course of PCa progression. For example, a primary tumor can be classified into one of several molecular subgroups depending on whether the cancer has a particular gene fusion or a mutation which in turn might yield some patient-specific therapeutic regimen, but this same type of heterogeneous growth can be spatially or temporally restricted proving it difficult to detect during biopsy. We therefore present here a comprehensive review of the various studies addressing intra-tumor heterogeneity in PCa and in the context of that seen in other solid tumors. We discuss the impact of heterogeneity on clinical decision-making in treating both primary and metastatic lesions and how our understanding of this heterogeneity might help in developing better diagnostic tools and biomarkers and in guiding the selection of better therapeutic strategies.

Genome-wide DNA copy number analysis in clonally expanded human ovarian cancer cells with distinct invasive/migratory capacities

Ovarian cancer has the worst prognosis of any gynecological malignancy, and generally presents with metastasis at advanced stages. Copy number variation (CNV) frequently contributes to the alteration of oncogenic drivers. In this study, we sought to identify genetic targets in heterogeneous clones from human ovarian cancers cells. We used array-based technology to systematically assess all the genes with CNVs in cell models clonally expanded from A2780 and SKOV3 ovarian cancer cell lines with distinct highly and minimally invasive/migratory capacities. We found that copy number alterations differed between matched highly and minimally invasive/migratory subclones, differentially affecting specific functional processes including immune response processes, DNA damage repair, cell cycle and cell proliferation. We also identified seven genes as strong candidates, including DDB1, ERCC1, ERCC2, PRPF19, BCAT1, CDKN1B and MARK4, by integrating the above data with gene expression and clinical outcome data. Thus, by determining the molecular signatures of heterogeneous invasive/migratory ovarian cancer cells, we identified genes that could be specifically targeted for the treatment and prognosis of advanced ovarian cancers.

A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome

PURPOSE

To evaluate the associations between clinical outcomes and radiomics-derived inter-site spatial heterogeneity metrics across multiple metastatic lesions on CT in patients with high-grade serous ovarian cancer (HGSOC).

METHODS

IRB-approved retrospective study of 38 HGSOC patients. All sites of suspected HGSOC involvement on preoperative CT were manually segmented. Gray-level correlation matrix-based textures were computed from each tumour site, and grouped into five clusters using a Gaussian Mixture Model. Pairwise inter-site similarities were computed, generating an inter-site similarity matrix (ISM). Inter-site texture heterogeneity metrics were computed from the ISM and compared to clinical outcomes.

RESULTS

Of the 12 inter-site texture heterogeneity metrics evaluated, those capturing the differences in texture similarities across sites were associated with shorter overall survival (inter-site similarity entropy, similarity level cluster shade, and inter-site similarity level cluster prominence; p ≤ 0.05) and incomplete surgical resection (similarity level cluster shade, inter-site similarity level cluster prominence and inter-site cluster variance; p ≤ 0.05). Neither the total number of disease sites per patient nor the overall tumour volume per patient was associated with overall survival. Amplification of 19q12 involving cyclin E1 gene (CCNE1) predominantly occurred in patients with more heterogeneous inter-site textures.

CONCLUSION

Quantitative metrics non-invasively capturing spatial inter-site heterogeneity may predict outcomes in patients with HGSOC.

KEY POINTS

• Calculating inter-site texture-based heterogeneity metrics was feasible • Metrics capturing texture similarities across HGSOC sites were associated with overall survival • Heterogeneity metrics were also associated with incomplete surgical resection of HGSOC.

Radiogenomics of High-Grade Serous Ovarian Cancer: Multireader Multi-Institutional Study from the Cancer Genome Atlas Ovarian Cancer Imaging Research Group

Purpose To evaluate interradiologist agreement on assessments of computed tomography (CT) imaging features of high-grade serous ovarian cancer (HGSOC), to assess their associations with time-to-disease progression (TTP) and HGSOC transcriptomic profiles (Classification of Ovarian Cancer [CLOVAR]), and to develop an imaging-based risk score system to predict TTP and CLOVAR profiles. Materials and Methods This study was a multireader, multi-institutional, institutional review board-approved, HIPAA-compliant retrospective analysis of 92 patients with HGSOC (median age, 61 years) with abdominopelvic CT before primary cytoreductive surgery available through the Cancer Imaging Archive. Eight radiologists from the Cancer Genome Atlas Ovarian Cancer Imaging Research Group developed and independently recorded the following CT features: characteristics of primary ovarian mass(es), presence of definable mesenteric implants and infiltration, presence of other implants, presence and distribution of peritoneal spread, presence and size of pleural effusions and ascites, lymphadenopathy, and distant metastases. Interobserver agreement for CT features was assessed, as were univariate and multivariate associations with TTP and CLOVAR mesenchymal profile (worst prognosis). Results Interobserver agreement for some features was strong (eg, α = .78 for pleural effusion and ascites) but was lower for others (eg, α = .08 for intraparenchymal splenic metastases). Presence of peritoneal disease in the right upper quadrant (P = .0003), supradiaphragmatic lymphadenopathy (P = .0004), more peritoneal disease sites (P = .0006), and nonvisualization of a discrete ovarian mass (P = .0037) were associated with shorter TTP. More peritoneal disease sites (P = .0025) and presence of pouch of Douglas implants (P = .0045) were associated with CLOVAR mesenchymal profile. Combinations of imaging features contained predictive signal for TTP (concordance index = 0.658; P = .0006) and CLOVAR profile (mean squared deviation = 1.776; P = .0043). Conclusion These results provide some evidence of the clinical and biologic validity of these image features. Interobserver agreement is strong for some features, but could be improved for others. ^© RSNA, 2017 Online supplemental material is available for this article.

Genetic analysis of uterine aspirates improves the diagnostic value and captures the intra-tumor heterogeneity of endometrial cancers

Endometrial cancer is the most common cancer of the female genital tract in developed countries. Although the majority of endometrial cancers are diagnosed at early stages and the 5-year overall survival is around 80%, early detection of these tumors is crucial to improve the survival of patients given that the advanced tumors are associated with a poor outcome. Furthermore, correct assessment of the pre-clinical diagnosis is decisive to guide the surgical treatment and management of the patient. In this sense, the potential of targeted genetic sequencing of uterine aspirates has been assessed as a pre-operative tool to obtain reliable information regarding the mutational profile of a given tumor, even in samples that are not histologically classifiable. A total of 83 paired samples were sequenced (uterine aspirates and hysterectomy specimens), including 62 endometrioid and non-endometrioid tumors, 10 cases of atypical hyperplasia and 11 non-cancerous endometrial disorders. Even though diagnosing endometrial cancer based exclusively on genetic alterations is currently unfeasible, mutations were mainly found in uterine aspirates from malignant disorders, suggesting its potential in the near future for supporting the standard histologic diagnosis. Moreover, this approach provides the first evidence of the high intra-tumor genetic heterogeneity associated with endometrial cancer, evident when multiple regions of tumors are analyzed from an individual hysterectomy. Notably, the genetic analysis of uterine aspirates captures this heterogeneity, solving the potential problem of incomplete genetic characterization when a single tumor biopsy is analyzed.

Inheritance of deleterious mutations at both BRCA1 and BRCA2 in an international sample of 32,295 women

BACKGROUND

Most BRCA1 or BRCA2 mutation carriers have inherited a single (heterozygous) mutation. Transheterozygotes (TH) who have inherited deleterious mutations in both BRCA1 and BRCA2 are rare, and the consequences of transheterozygosity are poorly understood.

METHODS

From 32,295 female BRCA1/2 mutation carriers, we identified 93 TH (0.3 %). "Cases" were defined as TH, and "controls" were single mutations at BRCA1 (SH1) or BRCA2 (SH2). Matched SH1 "controls" carried a BRCA1 mutation found in the TH "case". Matched SH2 "controls" carried a BRCA2 mutation found in the TH "case". After matching the TH carriers with SH1 or SH2, 91 TH were matched to 9316 SH1, and 89 TH were matched to 3370 SH2.

RESULTS

The majority of TH (45.2 %) involved the three common Jewish mutations. TH were more likely than SH1 and SH2 women to have been ever diagnosed with breast cancer (BC; p = 0.002). TH were more likely to be diagnosed with ovarian cancer (OC) than SH2 (p = 0.017), but not SH1. Age at BC diagnosis was the same in TH vs. SH1 (p = 0.231), but was on average 4.5 years younger in TH than in SH2 (p < 0.001). BC in TH was more likely to be estrogen receptor (ER) positive (p = 0.010) or progesterone receptor (PR) positive (p = 0.013) than in SH1, but less likely to be ER positive (p < 0.001) or PR positive (p = 0.012) than SH2. Among 15 tumors from TH patients, there was no clear pattern of loss of heterozygosity (LOH) for BRCA1 or BRCA2 in either BC or OC.

CONCLUSIONS

Our observations suggest that clinical TH phenotypes resemble SH1. However, TH breast tumor marker characteristics are phenotypically intermediate to SH1 and SH2.

Ascites modulates cancer cell behavior, contributing to tumor heterogeneity in ovarian cancer

Malignant ascites constitute a unique tumor microenvironment providing a physical structure for the accumulation of cellular and acellular components. Ascites is initiated and maintained by physical and biological factors resulting from underlying disease and forms an ecosystem that contributes to disease progression. It has been demonstrated that the cellular contents and the molecular signatures of ascites change continuously during the course of a disease. Over the past decade, increasing attention has been given to the characterization of components of ascites and their role in the progression of ovarian cancer, the most malignant gynecologic cancer in women. This review will discuss the role of ascites in disease progression, in terms of modulating cancer cell behavior and contributing to tumor heterogeneity.

The PI3K/AKT/mTOR pathway is a potential predictor of distinct invasive and migratory capacities in human ovarian cancer cell lines

Objectives

To explore the genetic and molecular events that control subclones exhibiting distinct invasive/migratory capacities derived from human epithelial ovarian cancer (EOC) cell line A2780 and SKOV3.

Methods

Single-cell subclones were isolated and established that were derived from the SKOV3 and A2780 cell lines through limiting dilution methodology. Transwell insert assays and MTT assays were performed to screen and identify the subclones exhibiting the highest and the lowest invasive/migratory capacities, and the selected subclones were renamed as A-H (A2780 high), A-L (A2780 low), S-H (SKOV3 high), and S-L (SKOV3 low). Their biological characteristics were evaluated. RNA-Seq was conducted on the targeted subclones.

Results

Compared with their corresponding counterparts, A-H/S-H cells exhibited significantly higher invasive/migratory capacities (P < 0.001 and = 0.001, respectively). A-H/S-H cells displayed a clear reduction in doubling time (P = 0.004 and 0.001, respectively), and a significant increase in the percentage of cells in S phase (P = 0.004 and 0.022, respectively). Additionally, the apoptotic rates of A-H/S-H cells were significantly lower than those of A-L/S-L cells (P = 0.002 and 0.026, respectively). At both mRNA and protein levels, caspase-3 and caspase-7 expression were reduced but Bcl-2 expression was increased in A-H/S-H cells. The TrkB (anoikis-related) and Beclin1 (autophagy-related) levels were consistently high and low, respectively, in both A-H/S-H cells. Resistance to chemotherapy in vitro and higher capacities on tumor formation in vivo was presented in both A-H/S-H cells. PI3K/AKT/mTOR pathway components, PIK3CA, PIK3CD, AKT3, ECM1, GPCR, mTOR and PRKCB were increased but that the Nur77 and PTEN were decreased in A-H/S-H cells, identified by RNA-Seq and consistently confirmed by RT-PCR and Western blot analyses.

Conclusions

Heterogeneous cell subpopulations exhibiting distinct invasive and migratory capacities co-exist within the SKOV3 and A2780 cell lines. PI3K/AKT/mTOR pathway activation is associated with higher invasive and migratory capacities in subpopulations of human ovarian cancer cell lines. Inhibiting this pathway may be useful for the chemoprevention or treatment of EOC.

Advanced Ovarian Cancer Displays Functional Intratumor Heterogeneity That Correlates to Ex Vivo Drug Sensitivity

Introduction

Epithelial ovarian cancer is recognized to be heterogeneous but is currently treated with a single treatment strategy. Successful patient stratification of emerging chemotherapy agents is dependent upon the availability of reliable biomarkers indicative of the entire tumor.

Aim

The aim of this study was to evaluate intertumor and intratumor heterogeneity within a series of epithelial ovarian cancer using homologous recombination (HR) DNA repair status.

Methods

Primary cultures generated from ascites and solid tumor from multiple intra-abdominal sites were characterized by their morphology and expression of protein markers. Results were compared with Formalin fixed paraffin embedded tissue pathology.

Homologous recombination function was determined by quantification of nuclear Rad51 foci. Growth inhibition (sulforhodamine B) assays were used to calculate the GI50 for cisplatin and rucaparib.

Results

Ascites with matched solid tumor were cultured from 25 patients.

Concordance in functional HR status between ascites and solid tumor subcultures was seen in only 13 (52%) of 25 patients. Heterogeneity in HR status was seen even in patients with homogeneous histological subtype. Homologous recombination defective cultures were significantly more sensitive to cisplatin and rucaparib.

Additionally, intertumor and intratumor heterogeneity was seen between the expression of epithelial and ovarian markers (EpCAM, cytokeratin, CA125, MOC-31, and vimentin). There was no relationship between heterogeneity of HR functional status and antigen expression.

Conclusions

Intertumor and intratumor functional HR heterogeneity exists that cannot be detected using histological classification. This has implications for biomarker-directed treatment.

Prediction of Optimal Cytoreductive Surgery of Serous Ovarian Cancer With Gene Expression Data

OBJECTIVES

Cytoreductive surgery is the cornerstone of ovarian cancer (OVCA) treatment. Detractors of initial maximal surgical effort argue that aggressive tumor biology will dictate survival, not the surgical effort. We investigated the role of biology in achieving optimal cytoreduction in serous OVCA using microarray gene expression analysis.

METHODS

For the initial model, we used a gene expression signature from a microarray expression analysis of 124 women with serous OVCA, defining optimal cytoreduction as removal of all disease greater than 1 cm (with 64 women having optimal and 60 suboptimal cytoreduction). We then applied this model to 2 independent data sets: the Australian Ovarian Cancer Study (AOCS; 190 samples) and The Cancer Genome Atlas (TCGA; 468 samples). We performed a second analysis, defining optimal cytoreduction as removal of all disease to microscopic residual, using data from AOCS to create the gene signature and validating results in TCGA data set.

RESULTS

Of the 12,718 genes included in the initial analysis, 58 predicted accuracy of cytoreductive surgery 69% of the time (P = 0.005). The performance of this classifier, measured by the area under the receiver operating characteristic curve, was 73%. When applied to TCGA and AOCS, accuracy was 56% (P = 0.16) and 62% (P = 0.01), respectively, with performance at 57% and 65%, respectively. In the second analysis, 220 genes predicted accuracy of cytoreductive surgery in the AOCS set 74% of the time, with performance of 73%. When these results were validated in TCGA set, accuracy was 57% (P = 0.31) and performance was at 62%.

CONCLUSION

Gene expression data, used as a proxy of tumor biology, do not predict accurately nor consistently the ability to perform optimal cytoreductive surgery. Other factors, including surgical effort, may also explain part of the model. Additional studies integrating more biological and clinical data may improve the prediction model.

Tumour Cell Heterogeneity

The population of cells that make up a cancer are manifestly heterogeneous at the genetic, epigenetic, and phenotypic levels. In this mini-review, we summarise the extent of intra-tumour heterogeneity (ITH) across human malignancies, review the mechanisms that are responsible for generating and maintaining ITH, and discuss the ramifications and opportunities that ITH presents for cancer prognostication and treatment.

Micro-dissected tumor tissues on chip: an ex vivo method for drug testing and personalized therapy

In cancer research and personalized medicine, new tissue culture models are needed to better predict the response of patients to therapies. With a concern for the small volume of tissue typically obtained through a biopsy, we describe a method to reproducibly section live tumor tissue to submillimeter sizes. These micro-dissected tissues (MDTs) share with spheroids the advantages of being easily manipulated on-chip and kept alive for periods extending over one week, while being biologically relevant for numerous assays. At dimensions below ~420 μm in diameter, as suggested by a simple metabolite transport model and confirmed experimentally, continuous perfusion is not required to keep samples alive, considerably simplifying the technical challenges. For the long-term culture of MDTs, we describe a simple microfluidic platform that can reliably trap samples in a low shear stress environment. We report the analysis of MDT viability for eight different types of tissues (four mouse xenografts derived from human cancer cell lines, three from ovarian and prostate cancer patients, and one from a patient with benign prostatic hyperplasia) analyzed by both confocal microscopy and flow cytometry over an 8-day incubation period. Finally, we provide a proof of principle for chemosensitivity testing of human tissue from a cancer patient performed using the described MDT chip method. This technology has the potential to improve treatment success rates by identifying potential responders earlier during the course of treatment and providing opportunities for direct drug testing on patient tissues in early drug development stages.

Intra-tumor heterogeneity in TP53 null High Grade Serous Ovarian Carcinoma progression

Background

High grade serous ovarian cancer is characterised by high initial response to chemotherapy but poor outcome in the long term due to acquired resistance. One of the main genetic features of this disease is TP53 mutation. The majority of TP53 mutated tumors harbor missense mutations in this gene, correlated with p53 accumulation. TP53 null tumors constitute a specific subgroup characterised by nonsense, frameshift or splice-site mutations associated to complete absence of p53 expression. Different studies show that this kind of tumors may have a worse prognosis than other TP53 mutated HGSC.

Methods

In this study, we sought to characterise the intra-tumor heterogeneity of a TP53 null HGSC consisting of six primary tumor samples, two intra-pelvic and four extra-pelvic recurrences using exome sequencing and comparative genome hybridisation.

Results

Significant heterogeneity was found among the different tumor samples, both at the mutational and copy number levels. Exome sequencing identified 102 variants, of which only 42 were common to all three samples; whereas 7 of the 18 copy number changes found by CGH analysis were presented in all samples. Sanger validation of 20 variants found by exome sequencing in additional regions of the primary tumor and the recurrence allowed us to establish a sequence of the tumor clonal evolution, identifying those populations that most likely gave rise to recurrences and genes potentially involved in this process, like GPNMB and TFDP1. Using functional annotation and network analysis, we identified those biological functions most significantly altered in this tumor. Remarkably, unexpected functions such as microtubule-based movement and lipid metabolism emerged as important for tumor development and progression, suggesting its potential interest as therapeutic targets.

Conclusions

Altogether, our results shed light on the clonal evolution of the distinct tumor regions identifying the most aggressive subpopulations and at least some of the genes that may be implicated in its progression and recurrence, and highlights the importance of considering intra-tumor heterogeneity when carrying out genetic and genomic studies, especially when these are aimed to diagnostic procedures or to uncover possible therapeutic strategies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1952-z) contains supplementary material, which is available to authorized users.

Retreatment with anti-EGFR based therapies in metastatic colorectal cancer: impact of intervening time interval and prior anti-EGFR response

BACKGROUND

This retrospective study aims to investigate the activity of retreatment with anti-EGFR-based therapies in order to explore the concept of clonal evolution by evaluating the impact of prior activity and intervening time interval.

METHODS

Eighty-nine KRAS exon 2-wild-type metastatic colorectal patients were retreated on phase I/II clinical trials containing anti-EGFR therapies after progressing on prior cetuximab or panitumumab. Response on prior anti-EGFR therapy was defined retrospectively per physician-records as response or stable disease ≥6 months. Multivariable statistical methods included a multiple logistic regression model for response, and Cox proportional hazards model for progression-free survival.

RESULTS

Retreatment anti-EGFR agents were cetuximab (n = 76) or cetuximab plus erlotinib (n = 13). The median interval time between prior and retreatment regimens was 4.57 months (range: 0.46-58.7). Patients who responded to the prior cetuximab or panitumumab were more likely to obtain clinical benefit to the retreatment compared to the non-responders in both univariate (p = 0.007) and multivariate analyses (OR: 3.38, 95 % CI: 1.27, 9.31, p = 0.019). The clinical benefit rate on retreatment also showed a marginally significant association with interval time between the two anti-EGFR based therapies (p = 0.053). Median progression-free survival on retreatment was increased in prior responders (4.9 months, 95 % CI: 3.6, 6.2) compared to prior non-responders (2.5 months, 95 % CI, 1.58, 3.42) in univariate (p = 0.064) and multivariate analysis (HR: 0.70, 95 % CI: 0.43-1.15, p = 0.156).

CONCLUSION

Our data lends support to the concept of clonal evolution, though the clinical impact appears less robust than previously reported. Further work to determine which patients benefit from retreatment post progression is needed.

Intratumor heterogeneity and transcriptional profiling in glioblastoma: translational opportunities

The study of phenotypic and genetic intratumor heterogeneity in glioblastoma is attracting a lot of attention. Recent studies have demonstrated that transcriptional profiling analysis can help interpret the complexity of this disease. Previously proposed molecular classifiers have been recently challenged due to the unexpected degree of intratumor heterogeneity that has been described spatially and at single-cell level. Different computational methods have been employed to analyze this huge amount of data, but new experimental designs including multisampling from individual patients and single-cell experiments require new specific approaches. In light of these results, there is hope that integration of genetic, phenotypic and transcriptional data coupled with functional experiments might help define new therapeutic strategies and classify patients according to key pathways and molecular targets that can be further investigated to develop personalized and combinatorial treatment strategies.

Harnessing Pandemonium: The Clinical Implications of Tumor Heterogeneity in Ovarian Cancer

Heterogeneity has emerged as a key feature of ovarian cancer between different ovarian cancer subtypes; within single ovarian cancer subtypes; and within individual patient tumors. At the genomic level, with the advent of ultra-deep sequencing technologies alongside RNA-Seq, epigenomics, and proteomics, the complexity surrounding heterogeneity has deepened. Here, we summarize the emerging understanding of heterogeneity in cancer as a whole and the key discoveries in this area relating to ovarian cancer. We explore the therapeutic limitations and possibilities posed by heterogeneity and how these will influence the future of ovarian cancer treatment and research.

Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic analysis

BACKGROUND

The major clinical challenge in the treatment of high-grade serous ovarian cancer (HGSOC) is the development of progressive resistance to platinum-based chemotherapy. The objective of this study was to determine whether intra-tumour genetic heterogeneity resulting from clonal evolution and the emergence of subclonal tumour populations in HGSOC was associated with the development of resistant disease.

METHODS AND FINDINGS

Evolutionary inference and phylogenetic quantification of heterogeneity was performed using the MEDICC algorithm on high-resolution whole genome copy number profiles and selected genome-wide sequencing of 135 spatially and temporally separated samples from 14 patients with HGSOC who received platinum-based chemotherapy. Samples were obtained from the clinical CTCR-OV03/04 studies, and patients were enrolled between 20 July 2007 and 22 October 2009. Median follow-up of the cohort was 31 mo (interquartile range 22-46 mo), censored after 26 October 2013. Outcome measures were overall survival (OS) and progression-free survival (PFS). There were marked differences in the degree of clonal expansion (CE) between patients (median 0.74, interquartile range 0.66-1.15), and dichotimization by median CE showed worse survival in CE-high cases (PFS 12.7 versus 10.1 mo, p = 0.009; OS 42.6 versus 23.5 mo, p = 0.003). Bootstrap analysis with resampling showed that the 95% confidence intervals for the hazard ratios for PFS and OS in the CE-high group were greater than 1.0. These data support a relationship between heterogeneity and survival but do not precisely determine its effect size. Relapsed tissue was available for two patients in the CE-high group, and phylogenetic analysis showed that the prevalent clonal population at clinical recurrence arose from early divergence events. A subclonal population marked by a NF1 deletion showed a progressive increase in tumour allele fraction during chemotherapy.

CONCLUSIONS

This study demonstrates that quantitative measures of intra-tumour heterogeneity may have predictive value for survival after chemotherapy treatment in HGSOC. Subclonal tumour populations are present in pre-treatment biopsies in HGSOC and can undergo expansion during chemotherapy, causing clinical relapse.

Association between morphologic CT imaging traits and prognostically relevant gene signatures in women with high-grade serous ovarian cancer: a hypothesis-generating study

PURPOSE

To investigate associations among imaging traits observed on computed tomographic (CT) images, Classification of Ovarian Cancer (CLOVAR) gene signatures, and survival in women with high-grade serous ovarian cancer (HGSOC).

MATERIALS AND METHODS

The institutional review board approved this HIPAA-compliant retrospective study of CT images obtained before cytoreductive surgery in 46 women with HGSOC, whose tumors were subjected to molecular analysis performed by the Cancer Genome Atlas Research Network. Two readers independently evaluated the CT features of the primary ovarian mass and sites of metastatic spread if present, including size, outline, and texture. Fisher exact test was used to examine the relationship between imaging traits and CLOVAR subtypes (CLOVAR differentiated, immunoreactive, mesenchymal, and proliferative). Kaplan-Meier and Cox proportional hazards regression survival analyses were performed.

RESULTS

The presence of mesenteric infiltration and diffuse peritoneal involvement by tumor at CT were significantly associated with CLOVAR subtype (P = .002-.004 for reader 1 and P = .005-.012 for reader 2). Mesenteric infiltration at CT was associated with CLOVAR mesenchymal subtype. Patients with mesenteric infiltration had shorter median progression-free survival than patients without mesenteric involvement (14.7 months vs 25.6 months according to both readers; P = .019 for reader 1 and .015 for reader 2) and overall survival (49.0 vs 58.2 months; P = .014 [reader 1] and 50.0 vs 59.1 months; P = .015 [reader 2]). No other imaging features were significantly associated with CLOVAR subtype or survival.

CONCLUSION

Specific CT imaging traits were associated with the CLOVAR subtypes and survival in patients with HGSOC.

NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics Signatures

The National Cancer Institute (NCI) Cancer Imaging Program organized two related workshops on June 26–27, 2013, entitled “Correlating Imaging Phenotypes with Genomics Signatures Research” and “Scalable Computational Resources as Required for Imaging-Genomics Decision Support Systems.” The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently advanced to correlate with imaging phenotypes that underpin genomics and clinical outcomes, and exploring new scientific methods to extract phenotypic features from medical images and relate them to genomics analyses. The second workshop focused on computational methods that explore informatics and computational requirements to extract phenotypic features from medical images and relate them to genomics analyses and improve the accessibility and speed of dissemination of existing NIH resources. These workshops linked clinical and scientific requirements of currently known phenotypic and genotypic cancer biology characteristics with imaging phenotypes that underpin genomics and clinical outcomes. The group generated a set of recommendations to NCI leadership and the research community that encourage and support development of the emerging radiogenomics research field to address short-and longer-term goals in cancer research.

Tumor heterogeneity in the recurrence of epithelial ovarian cancer demonstrated by polycomb group proteins

PURPOSE

To investigate tumor heterogeneity in the recurrence of epithelial ovarian cancer demonstrated by polycomb group (PcG) proteins.

METHODS

Tissue microarrays containing matched primary and recurrent ovarian tumors from the same patients were constructed for detection of PcG protein expression. Survival analyses of clinicopathological parameters and expression of PcG proteins were performed on progression-free survival (PFS) and overall survival (OS) of patients. Genetic and epigenetic heterogeneity was explored in aspects of gene copy number and microRNA (miRNA) profiling.

RESULTS

PcG proteins were heterogeneously expressed in primary versus recurrent tumors (P<0.05). In univariate survival analysis of the ovarian carcinoma cohorts, a significant association of intensive expression of BMI1 and EZH2 in first-onset lymph node metastases with shortened PFS was demonstrated (P=0.010, P=0.019); and a significant association of intensive expression of BMI1 and EZH2 in recurrent tumors with shortened OS was demonstrated (P=0.042, P=0.047). Importantly, BMI1 and EZH2 expression provided significant independent prognostic parameters in multivariate analyses (P<0.05). Gene amplification did not always coincide with PcG protein expression. Eight miRNAs were found to be downregulated in recurrent tumors, among which miR-298 might indirectly regulate the expression of EZH2 through transcription factor ILF3.

CONCLUSION

Tumor heterogeneity exists in the recurrence of epithelial ovarian cancer, manifested by PcG protein expression and underlying genetic and epigenetic alterations. Intensive expression of BMI1 and EZH2 are predictors of earlier relapse and shorter OS, independent of grade and chemotherapy sensitivity. EZH2 and miR-298 have great potential to be new targets for treatment of recurrent ovarian cancer.

Evolution of pre-existing versus acquired resistance to platinum drugs and PARP inhibitors in BRCA-associated cancers

Platinum drugs and PARP inhibitors (“PARPis”) are considered to be effective in BRCA-associated cancers with impaired DNA repair. These agents cause stalled and collapsed replication forks and create double-strand breaks effectively in the absence of repair mechanisms, resulting in arrest of the cell cycle and induction of cell death. However, recent studies have shown failure of these chemotherapeutic agents due to emerging drug resistance. In this study, we developed a stochastic model of BRCA-associated cancer progression in which there are four cancer populations: those with (i) functional BRCA, (ii) dysfunctional BRCA, (iii) functional BRCA and a growth advantage, and (iv) dysfunctional BRCA and a growth advantage. These four cancer populations expand from one cancer cell with normal repair function until the total cell number reaches a detectable amount. We derived formulas for the probability and expected numbers of each population at the time of detection. Furthermore, we extended the model to consider the tumor dynamics during treatment. Results from the model were validated and showed good agreement with clinical and experimental evidence in BRCA-associated cancers. Based on the model, we investigated conditions in which drug resistance during the treatment course originated from either a pre-existing drug-resistant population or a de novo population, due to secondary mutations. Finally, we found that platinum drugs and PARPis were effective if (i) BRCA inactivation is present, (ii) the cancer was diagnosed early, and (iii) tumor growth is rapid. Our results indicate that different types of cancers have a preferential way of acquiring resistance to platinum drugs and PARPis according to their growth and mutational characteristics.

Vascular measurements correlate with estrogen receptor status

Background

Breast carcinoma can be classified as either Estrogen Receptor (ER) positive or negative by immunohistochemical phenotyping, although ER expression may vary from 1 to 100% of malignant cells within an ER + tumor. This is similar to genetic variability observed in other tumor types and is generally viewed as a consequence of intratumoral evolution driven by random genetic mutations. Here we view cellular evolution within tumors as a classical Darwinian system in which variations in molecular properties represent predictable adaptations to spatially heterogeneous environmental selection forces. We hypothesize that ER expression is a successful adaptive strategy only if estrogen is present in the microenvironment. Since the dominant source of estrogen is blood flow, we hypothesized that, in general, intratumoral regions with higher blood flow would contain larger numbers of ER + cells when compared to areas of low blood flow and in turn necrosis.

Methods

This study used digital pathology whole slide image acquisition and advanced image analysis algorithms. We examined the spatial distribution of ER + and ER- cells, vascular density, vessel area, and tissue necrosis within histological sections of 24 breast cancer specimens. These data were correlated with the patients ER status and molecular pathology report findings.

Results

ANOVA analyses revealed a strong correlation between vascular area and ER expression and between high fractional necrosis and absent ER expression (R² = 39%; p < 0.003 and R² = 46%; p < 0.001), respectively). ER expression did not correlate with tumor grade or size.

Conclusion

We conclude that ER expression can be understood as a Darwinian process and linked to variations in estrogen delivery by temporal and spatial heterogeneity in blood flow. This correlation suggests strategies to promote intratumoral blood flow or a cyclic introduction of estrogen in the treatment schedule could be explored as a counter-intuitive approach to increase the efficacy of anti-estrogen drugs.

Phylogenetic quantification of intra-tumour heterogeneity

Intra-tumour genetic heterogeneity is the result of ongoing evolutionary change within each cancer. The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance, and if so, would have prognostic and predictive utility. However, methods for objectively quantifying tumour heterogeneity have been missing and are particularly difficult to establish in cancers where predominant copy number variation prevents accurate phylogenetic reconstruction owing to horizontal dependencies caused by long and cascading genomic rearrangements. To address these challenges, we present MEDICC, a method for phylogenetic reconstruction and heterogeneity quantification based on a Minimum Event Distance for Intra-tumour Copy-number Comparisons. Using a transducer-based pairwise comparison function, we determine optimal phasing of major and minor alleles, as well as evolutionary distances between samples, and are able to reconstruct ancestral genomes. Rigorous simulations and an extensive clinical study show the power of our method, which outperforms state-of-the-art competitors in reconstruction accuracy, and additionally allows unbiased numerical quantification of tumour heterogeneity. Accurate quantification and evolutionary inference are essential to understand the functional consequences of tumour heterogeneity. The MEDICC algorithms are independent of the experimental techniques used and are applicable to both next-generation sequencing and array CGH data.

The use of ovarian cancer cells from patients undergoing surgery to generate primary cultures capable of undergoing functional analysis

The use of cell lines or animal models has significant disadvantages when dealing with a set of heterogeneous diseases such as epithelial ovarian cancer. This has clinical relevance in that biomarkers developed using cell line or animal models are often not transferable to the clinical setting. In this study, we describe the development of a robust protocol for developing primary cultures of ovarian cancer which will overcome some of these difficulties. Women undergoing surgery for ovarian cancer were recruited and samples of ascites and solid tumour deposits were used to develop primary cultures. Cells were characterised using a panel of immunofluorescent antibodies prior to use in a variety of assays including functional assessment of DNA repair pathways. During the four year study period, viable cultures, confirmed to be epithelial in origin were generated from 156 of 172 (91%) cases recruited. Characterisation was carried out using a panel of antibodies including pancytokeratin, CA125, EpCAM, MOC-31, D2-40 and vimentin. Senescence occurred between the 2^nd and 8^th passages in all cultures except one in which spontaneous immortalization occurred. Cells could be successfully cultured even after a period of storage at 4°C and cultured cells were capable of being used for a variety of applications including functional assays. Upon functional assessment there was minimal intra-tumour heterogeneity. It is therefore possible to derive viable ovarian cancer cell cultures in the majority of patients undergoing surgery. Cells cultured directly from patient cancers provide an accurate and highly diverse model.

Association between IHC and MSI testing to identify mismatch repair-deficient patients with ovarian cancer

OBJECTIVE

In epithelial ovarian cancer, concordance between results of microsatellite instability (MSI) and immunohistochemical (IHC) testing has not been demonstrated. This study evaluated the association of MSI-high (MSI-H) status with loss of expression (LoE) of mismatch repair (MMR) proteins on IHC and assessed for potential factors affecting the strength of the association.

METHODS

Tumor specimens from three population-based studies of epithelial ovarian cancer were stained for MMR proteins through manual or automated methods, and results were interpreted by one of two pathologists. Tumor and germline DNA was extracted and MSI testing performed. Multivariable logistic regression models were fitted to predict loss of IHC expression based on MSI status after adjusting for staining method and reading pathologist.

RESULTS

Of 834 cases, 564 (67.6%) were concordant; 41 were classified as MSI-H with LoE and 523 as microsatellite stable (MSS) with no LoE. Of the 270 discordant cases, 83 were MSI-H with no LoE and 187 were MSS with LoE. Both IHC staining method and reading pathologist were strongly associated with discordant results.

CONCLUSIONS

Lack of concordance in the current study may be related to inconsistencies in IHC testing methods and interpretation. Results support the need for validation studies before routine screening of ovarian tumors is implemented in clinical practice for the purpose of identifying Lynch syndrome.

Genomic and transcriptomic plasticity in treatment-naive ovarian cancer

Intra-tumor heterogeneity is a hallmark of many cancers and may lead to therapy resistance or interfere with personalized treatment strategies. Here, we combined topographic mapping of somatic breakpoints and transcriptional profiling to probe intra-tumor heterogeneity of treatment-naïve stage IIIC/IV epithelial ovarian cancer. We observed that most substantial differences in genomic rearrangement landscapes occurred between metastases in the omentum and peritoneum versus tumor sites in the ovaries. Several cancer genes such as NF1, CDKN2A, and FANCD2 were affected by lesion-specific breakpoints. Furthermore, the intra-tumor variability involved different mutational hallmarks including lesion-specific kataegis (local mutation shower coinciding with genomic breakpoints), rearrangement classes, and coding mutations. In one extreme case, we identified two independent TP53 mutations in ovary tumors and omentum/peritoneum metastases, respectively. Examination of gene expression dynamics revealed up-regulation of key cancer pathways including WNT, integrin, chemokine, and Hedgehog signaling in only subsets of tumor samples from the same patient. Finally, we took advantage of the multilevel tumor analysis to understand the effects of genomic breakpoints on qualitative and quantitative gene expression changes. We show that intra-tumor gene expression differences are caused by site-specific genomic alterations, including formation of in-frame fusion genes. These data highlight the plasticity of ovarian cancer genomes, which may contribute to their strong capacity to adapt to changing environmental conditions and give rise to the high rate of recurrent disease following standard treatment regimes.

Implications of intratumour heterogeneity for treatment stratification

Despite advances in the diagnosis and treatment of cancer, the majority of advanced metastatic solid tumours remain incurable. Differential gene expression, somatic mutational status, tumour-specific genetic signatures and micro-environmental selection pressures within individual tumours have implications for the success of predictive assays to guide therapeutic intervention. In this review we discuss the evidence for genetic and phenotypic heterogeneity and its potential implications for clinical decision making. We highlight areas of research that could be improved in order to better stratify patient treatment. We also discuss the predictive potential of patient-derived models of tumour response, including xenograft and cell line-based systems within the context of intratumour heterogeneity.

Ovarian cancer evolution through stochastic genome alterations: defining the genomic role in ovarian cancer

Ovarian cancer is the fifth leading cause of death among women worldwide. Characterized by complex etiology and multi-level heterogeneity, its origins are not well understood. Intense research efforts over the last decade have furthered our knowledge by identifying multiple risk factors that are associated with the disease. However, it is still unclear how genetic heterogeneity contributes to tumor formation, and more specifically, how genome-level heterogeneity acts as the key driving force of cancer evolution. Most current genomic approaches are based on 'average molecular profiling.' While effective for data generation, they often fail to effectively address the issue of high level heterogeneity because they mask variation that exists in a cell population. In this synthesis, we hypothesize that genome-mediated cancer evolution can effectively explain diverse factors that contribute to ovarian cancer. In particular, the key contribution of genome replacement can be observed during major transitions of ovarian cancer evolution including cellular immortalization, transformation, and malignancy. First, we briefly review major updates in the literature, and illustrate how current gene-mediated research will offer limited insight into cellular heterogeneity and ovarian cancer evolution. We next explain a holistic framework for genome-based ovarian cancer evolution and apply it to understand the genomic dynamics of a syngeneic ovarian cancer mouse model. Finally, we employ single cell assays to further test our hypothesis, discuss some predictions, and report some recent findings.

Distinct evolutionary trajectories of primary high-grade serous ovarian cancers revealed through spatial mutational profiling

High-grade serous ovarian cancer (HGSC) is characterized by poor outcome, often attributed to the emergence of treatment-resistant subclones. We sought to measure the degree of genomic diversity within primary, untreated HGSCs to examine the natural state of tumour evolution prior to therapy. We performed exome sequencing, copy number analysis, targeted amplicon deep sequencing and gene expression profiling on 31 spatially and temporally separated HGSC tumour specimens (six patients), including ovarian masses, distant metastases and fallopian tube lesions. We found widespread intratumoural variation in mutation, copy number and gene expression profiles, with key driver alterations in genes present in only a subset of samples (eg PIK3CA, CTNNB1, NF1). On average, only 51.5% of mutations were present in every sample of a given case (range 10.2-91.4%), with TP53 as the only somatic mutation consistently present in all samples. Complex segmental aneuploidies, such as whole-genome doubling, were present in a subset of samples from the same individual, with divergent copy number changes segregating independently of point mutation acquisition. Reconstruction of evolutionary histories showed one patient with mixed HGSC and endometrioid histology, with common aetiologic origin in the fallopian tube and subsequent selection of different driver mutations in the histologically distinct samples. In this patient, we observed mixed cell populations in the early fallopian tube lesion, indicating that diversity arises at early stages of tumourigenesis. Our results revealed that HGSCs exhibit highly individual evolutionary trajectories and diverse genomic tapestries prior to therapy, exposing an essential biological characteristic to inform future design of personalized therapeutic solutions and investigation of drug-resistance mechanisms.

Network analysis identifies an HSP90-central hub susceptible in ovarian cancer

PURPOSE

Epithelial ovarian cancer (EOC) is usually detected at an advanced stage and is frequently lethal. Although many patients respond to initial surgery and standard chemotherapy consisting of a platinum-based agent and a taxane, most experience recurrence and eventually treatment-resistant disease. Although there have been numerous efforts to apply protein-targeted agents in EOC, these studies have so far documented little efficacy. Our goal was to identify broadly susceptible signaling proteins or pathways in EOC.

EXPERIMENTAL DESIGN

As a new approach, we conducted data-mining meta-analyses integrating results from multiple siRNA screens to identify gene targets that showed significant inhibition of cell growth. On the basis of this meta-analysis, we established that many genes with such activity were clients of the protein chaperone HSP90. We therefore assessed ganetespib, a clinically promising second-generation small-molecule HSP90 inhibitor, for activity against EOC, both as a single agent and in combination with cytotoxic and targeted therapeutic agents.

RESULTS

Ganetespib significantly reduced cell growth, induced cell-cycle arrest and apoptosis in vitro, inhibited growth of orthotopic xenografts and spontaneous ovarian tumors in transgenic mice in vivo, and inhibited expression and activation of numerous proteins linked to EOC progression. Importantly, paclitaxel significantly potentiated ganetespib activity in cultured cells and tumors. Moreover, combined treatment of cells with ganetespib and siRNAs or small molecules inhibiting genes identified in the meta-analysis in several cases resulted in enhanced activity.

CONCLUSION

These results strongly support investigation of ganetespib, a single-targeted agent with effects on numerous proteins and pathways, in augmenting standard EOC therapies.

HER2 amplification and clinicopathological characteristics in a large Asian cohort of rare mucinous ovarian cancer

Mucinous epithelial ovarian cancer has a poor prognosis in the advanced stages and responds poorly to conventional chemotherapy. We aim to elucidate the clinicopathological factors and incidence of HER2 expression of this cancer in a large Asian retrospective cohort from Singapore. Of a total of 133 cases, the median age at diagnosis was 48.3 years (range, 15.8–89.0 years), comparatively younger than western cohorts. Most were Chinese (71%), followed by Malays (16%), others (9.0%), and Indians (5%). 24% were noted to have a significant family history of malignancy of which breast and gastrointestinal cancers the most prominent. Majority of the patients (80%) had stage I disease at diagnosis. Information on HER2 status was available in 113 cases (85%). Of these, 31 cases (27.4%) were HER2+, higher than 18.8% reported in western population. HER2 positivity appeared to be lower among Chinese and higher among Malays patients (p = 0.052). With the current standard of care, there was no discernible impact of HER2 status on overall survival. (HR = 1.79; 95% CI, 0.66–4.85; p = 0.249). On the other hand, positive family history of cancer, presence of lymphovascular invasion, and ovarian surface involvements were significantly associated with inferior overall survival on univariate and continued to be statistically significant after adjustment for stage. While these clinical factors identify high risk patients, it is promising that the finding of a high incidence of HER2 in our Asian population may allow development of a HER2 targeted therapy to improve the management of mucinous ovarian cancers.

Empirical chemosensitivity testing in a spheroid model of ovarian cancer using a microfluidics-based multiplex platform

The use of biomarkers to infer drug response in patients is being actively pursued, yet significant challenges with this approach, including the complicated interconnection of pathways, have limited its application. Direct empirical testing of tumor sensitivity would arguably provide a more reliable predictive value, although it has garnered little attention largely due to the technical difficulties associated with this approach. We hypothesize that the application of recently developed microtechnologies, coupled to more complex 3-dimensional cell cultures, could provide a model to address some of these issues. As a proof of concept, we developed a microfluidic device where spheroids of the serous epithelial ovarian cancer cell line TOV112D are entrapped and assayed for their chemoresponse to carboplatin and paclitaxel, two therapeutic agents routinely used for the treatment of ovarian cancer. In order to index the chemoresponse, we analyzed the spatiotemporal evolution of the mortality fraction, as judged by vital dyes and confocal microscopy, within spheroids subjected to different drug concentrations and treatment durations inside the microfluidic device. To reflect microenvironment effects, we tested the effect of exogenous extracellular matrix and serum supplementation during spheroid formation on their chemotherapeutic response. Spheroids displayed augmented chemoresistance in comparison to monolayer culturing. This resistance was further increased by the simultaneous presence of both extracellular matrix and high serum concentration during spheroid formation. Following exposure to chemotherapeutics, cell death profiles were not uniform throughout the spheroid. The highest cell death fraction was found at the center of the spheroid and the lowest at the periphery. Collectively, the results demonstrate the validity of the approach, and provide the basis for further investigation of chemotherapeutic responses in ovarian cancer using microfluidics technology. In the future, such microdevices could provide the framework to assay drug sensitivity in a timeframe suitable for clinical decision making.

Cancer heterogeneity and "the struggle for existence": diagnostic and analytical challenges

The notions of inter- and intra-tumour heterogeneity (ITH) have been recognised for many years but recent advances in sequencing technology are allowing the true extent of both forms of heterogeneity to be revealed in detail for the first time. In this review we examine the current evidence for ITH, the possibility of cancers following a branched rather than linear evolutionary path and the potential implications both of these may have for the mechanisms of drug resistance acquisition. We also note that although clearly present in many cases, heterogeneity and branched evolution are not universal, with cases of tumour homogeneity and linear evolution still detected relatively frequently. The complexity induced by cases of ITH presents a considerable challenge for bioinformatics analyses and we illustrate this by describing the specific case of point mutation detection and a number of approaches which have been taken to combat these issues. Equally, the sequencing procedures which generate these data are rendered much more difficult in the face of ITH and we present a discussion of these problems in addition to describing some of the alternate paradigms being considered to overcome them.