Single-cell tumor-immune microenvironment of BRCA1/2 mutated high-grade serous ovarian cancer

Predicting BRCA mutation and stratifying targeted therapy response using multimodal learning: a multicenter study

BACKGROUND

The status of BRCA1/2 genes plays a crucial role in the treatment decision-making process for multiple cancer types. However, due to high costs and limited resources, a demand for BRCA1/2 genetic testing among patients is currently unmet. Notably, not all patients with BRCA1/2 mutations achieve favorable outcomes with poly (ADP-ribose) polymerase inhibitors (PARPi), indicating the necessity for risk stratification. In this study, we aimed to develop and validate a multimodal model for predicting BRCA1/2 gene status and prognosis with PARPi treatment.

METHODS

We included 1695 slides from 1417 patients with ovarian, breast, prostate, and pancreatic cancers across three independent cohorts. Using a self-attention mechanism, we constructed a multi-instance attention model (MIAM) to detect BRCA1/2 gene status from hematoxylin and eosin (H&E) pathological images. We further combined tissue features from the MIAM model, cell features, and clinical factors (the MIAM-C model) to predict BRCA1/2 mutations and progression-free survival (PFS) with PARPi therapy. Model performance was evaluated using area under the curve (AUC) and Kaplan-Meier analysis. Morphological features contributing to MIAM-C were analyzed for interpretability.

RESULTS

Across the four cancer types, MIAM-C outperformed the deep learning-based MIAM in identifying the BRCA1/2 genotype. Interpretability analysis revealed that high-attention regions included high-grade tumors and lymphocytic infiltration, which correlated with BRCA1/2 mutations. Notably, high lymphocyte ratios appeared characteristic of BRCA1/2 mutations. Furthermore, MIAM-C predicted PARPi therapy response (log-rank p < 0.05) and served as an independent prognostic factor for patients with BRCA1/2-mutant ovarian cancer (p < 0.05, hazard ratio:0.4, 95% confidence interval: 0.16-0.99).

CONCLUSIONS

The MIAM-C model accurately detected BRCA1/2 gene status and effectively stratified prognosis for patients with BRCA1/2 mutations.

Neoadjuvant PARPi or chemotherapy in ovarian cancer informs targeting effector Treg cells for homologous-recombination-deficient tumors

Homologous recombination deficiency (HRD) is prevalent in cancer, sensitizing tumor cells to poly (ADP-ribose) polymerase (PARP) inhibition. However, the impact of HRD and related therapies on the tumor microenvironment (TME) remains elusive. Our study generates single-cell gene expression and T cell receptor profiles, along with validatory multimodal datasets from >100 high-grade serous ovarian cancer (HGSOC) samples, primarily from a phase II clinical trial (NCT04507841). Neoadjuvant monotherapy with the PARP inhibitor (PARPi) niraparib achieves impressive 62.5% and 73.6% response rates per RECIST v.1.1 and GCIG CA125, respectively. We identify effector regulatory T cells (eTregs) as key responders to HRD and neoadjuvant therapies, co-occurring with other tumor-reactive T cells, particularly terminally exhausted CD8+ T cells (Tex). TME-wide interferon signaling correlates with cancer cells upregulating MHC class II and co-inhibitory ligands, potentially driving Treg and Tex fates. Depleting eTregs in HRD mouse models, with or without PARP inhibition, significantly suppresses tumor growth without observable toxicities, underscoring the potential of eTreg-focused therapeutics for HGSOC and other HRD-related tumors.

Immunotherapy for ovarian cancer: towards a tailored immunophenotype-based approach

Despite documented evidence that ovarian cancer cells express immune-checkpoint molecules, such as PD-1 and PD-L1, and of a positive correlation between the presence of tumour-infiltrating lymphocytes and favourable overall survival outcomes in patients with this tumour type, the results of trials testing immune-checkpoint inhibitors (ICIs) in these patients thus far have been disappointing. The lack of response to ICIs can be attributed to tumour heterogeneity as well as inherent or acquired resistance associated with the tumour microenvironment (TME). Understanding tumour immunobiology, discovering biomarkers for patient selection and establishing optimal treatment combinations remains the hope but also a key challenge for the future application of immunotherapy in ovarian cancer. In this Review, we summarize results from trials testing ICIs in patients with ovarian cancer. We propose the implementation of a systematic CD8+ T cell-based immunophenotypic classification of this malignancy, followed by discussions of the preclinical data providing the basis to treat such immunophenotypes with combination immunotherapies. We posit that the integration of an accurate TME immunophenotype characterization with genetic data can enable the design of tailored therapeutic approaches and improve patient recruitment in clinical trials. Lastly, we propose a roadmap incorporating tissue-based profiling to guide future trials testing adoptive cell therapy approaches and assess novel immunotherapy combinations while promoting collaborative research.

NSGO-OV-UMB1/ENGOT-OV30: A phase II study of durvalumab in combination with the anti-CD73 monoclonal antibody Oleclumab in patients with relapsed ovarian cancer

OBJECTIVES

In patients with epithelial ovarian cancer (EOC), the clinical efficacy of monotherapy with immune checkpoint inhibitors (ICIs) against PD-1/PD-L1 is modest. To enhance response rates to these immunotherapeutic agents and broaden the indications for their use, new approaches involving combinational therapy are needed. The immune regulator CD73 is a potential target, as it promotes tumor escape by producing immunosuppressive extracellular adenosine in the tumor microenvironment. Here, we present the results from the NSGO-OV-UMB1/ENGOT-OV-30 trial evaluating the activity of combining the anti-CD73 antibody oleclumab with the anti-PD-L1 checkpoint inhibitor durvalumab in patients with recurrent EOC.

METHODS

In this phase II open-label non-randomized study, patients with CD73-positive relapsed EOC were intravenously administered oleclumab (3000 mg, Q2W) and durvalumab (1500 mg, Q4W). The primary endpoint was disease control rate (DCR) at 16 weeks. The expression of PD-L1 and CD8 was assessed by immunohistochemistry of archival tumors.

RESULTS

This trial included 25 patients with a median age of 66 years (47-77 years). Twenty-two patients were evaluable for treatment activity analysis. The DCR was 27%, the median progression-free survival was 2.7 months (95% CI: 2.2-4.2) and the median overall survival was 8.4 months (95% CI: 5.0-13.4). Infiltration of CD8+ cells and PD-L1 expression on tumor cells were observed in partially overlapping sets of 74% of the tumor samples. Neither CD8- nor PD-L1-positivity were significantly associated with better DCR.

CONCLUSIONS

Combined treatment with oleclumab and durvalumab was safe and demonstrated limited anti-tumor activity in patients with recurrent EOC.

Homologous recombination deficiency (HRD) is associated with better prognosis and possibly causes a non-inflamed tumour microenvironment in nasopharyngeal carcinoma

Homologous recombination deficiency (HRD) score is a reliable indicator of genomic instability. The significance of HRD in nasopharyngeal carcinoma (NPC), particularly its influence on prognosis and the immune microenvironment, has yet to be adequately explored. Understanding HRD status comprehensively can offer valuable insights for guiding precision treatment. We utilised three cohorts to investigate HRD status in NPC: the Zhujiang cohort from local collection and the Hong Kong (SRA288429) and Singapore (SRP035573) cohorts from public datasets. The GATK (genome analysis toolkit) best practice process was employed to investigate germline and somatic BRCA1/2 mutations and various bioinformatics tools and algorithms to examine the association between HRD status and clinical molecular characteristics. We found that individuals with a negative HRD status (no-HRD) exhibited a higher risk of recurrence [hazard ratio (HR), 1.43; 95% confidence interval (CI), 2.03-333.76; p = 0.012] in the Zhujiang cohort, whereas, in the Singapore cohort, they experienced a higher risk of mortality (HR, 26.04; 95% CI, 1.43-34.21; p = 0.016) compared with those in the HRD group. In vitro experiments demonstrated that NPC cells with BRCA1 knockdown exhibit heightened sensitivity to chemoradiotherapy. Furthermore, the HRD group showed significantly higher tumour mutational burden and tumour neoantigen burden levels than the no-HRD group. Immune infiltration analysis indicated that HRD tissues tend to have a non-inflamed tumour microenvironment. In conclusion, patients with HRD exhibit a comparatively favourable prognosis in NPC, possibly associated with a non-inflammatory immune microenvironment. These findings have positive implications for treatment stratification, enabling the selection of more precise and effective therapeutic approaches and aiding in the prediction of treatment response and prognosis to a certain extent.

Tumor-Intrinsic Activity of Chromobox 2 Remodels the Tumor Microenvironment in High-grade Serous Carcinoma

Chromobox 2 (CBX2), an epigenetic reader and component of polycomb repressor complex 1, is highly expressed in >75% of high-grade serous carcinoma. Increased CBX2 expression is associated with poorer survival, whereas CBX2 knockdown leads to improved chemotherapy sensitivity. In a high-grade serous carcinoma immune-competent murine model, knockdown of CBX2 decreased tumor progression. We sought to explore the impact of modulation of CBX2 on the tumor immune microenvironment (TIME), understanding that the TIME plays a critical role in disease progression and development of therapy resistance. Exploration of existing datasets demonstrated that elevated CBX2 expression significantly correlated with specific immune cell types in the TIME. RNA sequencing and pathway analysis of differentially expressed genes demonstrated immune signature enrichment. Confocal microscopy and co-culture experiments found that modulation of CBX2 leads to increased recruitment and infiltration of macrophages. Flow cytometry of macrophages cultured with CBX2-overexpressing cells showed increased M2-like macrophages and decreased phagocytosis activity. Cbx2 knockdown in the Trp53-null, Brca2-null ID8 syngeneic murine model (ID8 Trp53-/-Brca2-/-) led to decreased tumor progression compared with the control. NanoString immuno-oncology panel analysis suggested that knockdown in Cbx2 shifts immune cell composition, with an increase in macrophages. Multispectral immunohistochemistry (mIHC) further confirmed an increase in macrophage infiltration. Increased CBX2 expression leads to recruitment and polarization of protumor macrophages, and targeting CBX2 may serve to modulate the TIME to enhance the efficacy of immune therapies.

SIGNIFICANCE

CBX2 expression correlates with the TIME. CBX2 modulation shifts the macrophage population, potentially leading to an immunosuppressive microenvironment, highlighting CBX2 as a target to improve efficacy of immunotherapy.

Spatial tumor immune microenvironment phenotypes in ovarian cancer

Immunotherapy has largely failed in ovarian carcinoma (OC), likely due to that the vast tumor heterogeneity and variation in immune response have hampered clinical trial outcomes. Tumor-immune microenvironment (TIME) profiling may aid in stratification of OC tumors for guiding treatment selection. Here, we used Digital Spatial Profiling combined with image analysis to characterize regions of spatially distinct TIME phenotypes in OC to assess whether immune infiltration pattern can predict presence of immuno-oncology targets. Tumors with diffuse immune infiltration and increased tumor-immune spatial interactions had higher presence of IDO1, PD-L1, PD-1 and Tim-3, while focal immune niches had more CD163 macrophages and a preliminary worse outcome. Immune exclusion was associated with presence of Tregs and Fibronectin. High-grade serous OC showed an overall stronger immune response and presence of multiple targetable checkpoints. Low-grade serous OC was associated with diffuse infiltration and a high expression of STING, while endometrioid OC had higher presence of CTLA-4. Mucinous and clear cell OC were dominated by focal immune clusters and immune-excluded regions, with mucinous tumors displaying T-cell rich immune niches.

The endothelin-1-driven tumor-stroma feed-forward loops in high-grade serous ovarian cancer

The high-grade serous ovarian cancer (HG-SOC) tumor microenvironment (TME) is constellated by cellular elements and a network of soluble constituents that contribute to tumor progression. In the multitude of the secreted molecules, the endothelin-1 (ET-1) has emerged to be implicated in the tumor/TME interplay; however, the molecular mechanisms induced by the ET-1-driven feed-forward loops (FFL) and associated with the HG-SOC metastatic potential need to be further investigated. The tracking of the patient-derived (PD) HG-SOC cell transcriptome by RNA-seq identified the vascular endothelial growth factor (VEGF) gene and its associated signature among those mostly up-regulated by ET-1 and down-modulated by the dual ET-1R antagonist macitentan. Within the ligand-receptor pairs concurrently expressed in PD-HG-SOC cells, endothelial cells and activated fibroblasts, we discovered two intertwined FFL, the ET-1/ET-1R and VEGF/VEGF receptors, concurrently activated by ET-1 and shutting-down by macitentan, or by the anti-VEGF antibody bevacizumab. In parallel, we observed that ET-1 fine-tuned the tumoral and stromal secretome toward a pro-invasive pattern. Into the fray of the HG-SOC/TME double and triple co-cultures, the secretion of ET-1 and VEGF, that share a common co-regulation, was inhibited upon the administration of macitentan. Functionally, macitentan, mimicking the effect of bevacizumab, interfered with the HG-SOC/TME FFL-driven communication that fuels the HG-SOC invasive behavior. The identification of ET-1 and VEGF FFL as tumor and TME actionable vulnerabilities, reveals how ET-1R blockade, targeting the HG-SOC cells and the TME simultaneously, may represent an effective therapeutic option for HG-SOC patients.

Unique immune characteristics and differential anti-PD-1-mediated reinvigoration potential of CD8+ TILs based on BRCA1/2 mutation status in epithelial ovarian cancers

BACKGROUND

We aimed to investigate the distinct immunological characteristics of the tumor immune microenvironment in epithelial ovarian cancer (EOC) according to BRCA1/2 mutations status and differential PD-1 expression levels.

METHODS

Tumor-infiltrating lymphocytes (TILs) were collected from patients with newly diagnosed advanced-stage EOC (YUHS cohort, n=117). This YUHS cohort was compared with The Cancer Genome Atlas (TCGA) data for ovarian serous cystadenocarcinoma (n=482), in terms of survival outcomes and immune-related gene profiles according to BRCA1/2 status. We used multicolor flow cytometry to characterize the immune phenotypes and heterogeneity of TILs with or without BRCA1/2 mutations. In vitro functional assays were conducted to evaluate the reinvigorating ability of CD8+ TILs on anti-PD-1 treatment.

RESULTS

We found that EOC patients with BRCA1/2 mutations (BRCA1/2mt) exhibited better survival outcomes and significantly higher tumor mutation burden (TMB), compared with BRCA1/2 non-mutated (BRCA1/2wt) patients. Furthermore, CD8+ TILs within BRCA1/2mt tumors displayed characteristics indicating more severe T-cell exhaustion than their BRCA1/2wt counterparts. Notably, the capacity for anti-PD-1-mediated reinvigoration of CD8+ TILs was significantly greater in BRCA1/2wt tumors compared with BRCA1/2mt tumors. Additionally, within the BRCA1/2wt group, the frequency of PD-1highCD8+ TILs was positively correlated with the reinvigoration capacity of CD8+ TILs after anti-PD-1 treatment.

CONCLUSION

Our results highlight unique immune features of CD8+ TILs in EOC and a differential response to anti-PD-1 treatment, contingent on BRCA1/2 mutation status. These findings suggest that immune checkpoint blockade may be a promising frontline therapeutic option for selected BRCA1/2wt EOC patients.

Spatial Profiling of Ovarian Carcinoma and Tumor Microenvironment Evolution under Neoadjuvant Chemotherapy

PURPOSE

This study investigates changes in CD8+ cells, CD8+/Foxp3 ratio, HLA I expression, and immune coregulator density at diagnosis and upon neoadjuvant chemotherapy (NACT), correlating changes with clinical outcomes.

EXPERIMENTAL DESIGN

Multiplexed immune profiling and cell clustering analysis were performed on paired matched ovarian cancer samples to characterize the immune tumor microenvironment (iTME) at diagnosis and under NACT in patients enrolled in the CHIVA trial (NCT01583322).

RESULTS

Several immune cell (IC) subsets and immune coregulators were quantified pre/post-NACT. At diagnosis, patients with higher CD8+ T cells and HLA I+-enriched tumors were associated with a better outcome. The CD8+/Foxp3+ ratio increased significantly post-NACT in favor of increased immune surveillance, and the influx of CD8+ T cells predicted better outcomes. Clustering analysis stratified pre-NACT tumors into four subsets: high Binf, enriched in B clusters; high Tinf and low Tinf, according to their CD8+ density; and desert clusters. At baseline, these clusters were not correlated with patient outcomes. Under NACT, tumors were segregated into three clusters: high BinfTinf, low Tinf, and desert. The high BinfTinf, more diverse in IC composition encompassing T, B, and NK cells, correlated with improved survival. PDL1 was rarely expressed, whereas TIM3, LAG3, and IDO1 were more prevalent.

CONCLUSIONS

Several iTMEs exist during tumor evolution, and the NACT impact on iTME is heterogeneous. Clustering analysis of patients unravels several IC subsets within ovarian cancer and can guide future personalized approaches. Targeting different checkpoints such as TIM3, LAG3, and IDO1, more prevalent than PDL1, could more effectively harness antitumor immunity in this anti-PDL1-resistant malignancy.

Deciphering the tumor immune microenvironment from a multidimensional omics perspective: insight into next-generation CAR-T cell immunotherapy and beyond

Tumor immune microenvironment (TIME) consists of intra-tumor immunological components and plays a significant role in tumor initiation, progression, metastasis, and response to therapy. Chimeric antigen receptor (CAR)-T cell immunotherapy has revolutionized the cancer treatment paradigm. Although CAR-T cell immunotherapy has emerged as a successful treatment for hematologic malignancies, it remains a conundrum for solid tumors. The heterogeneity of TIME is responsible for poor outcomes in CAR-T cell immunotherapy against solid tumors. The advancement of highly sophisticated technology enhances our exploration in TIME from a multi-omics perspective. In the era of machine learning, multi-omics studies could reveal the characteristics of TIME and its immune resistance mechanism. Therefore, the clinical efficacy of CAR-T cell immunotherapy in solid tumors could be further improved with strategies that target unfavorable conditions in TIME. Herein, this review seeks to investigate the factors influencing TIME formation and propose strategies for improving the effectiveness of CAR-T cell immunotherapy through a multi-omics perspective, with the ultimate goal of developing personalized therapeutic approaches.

Exploratory biomarker analysis in the phase III L-MOCA study of olaparib maintenance therapy in patients with platinum-sensitive relapsed ovarian cancer

BACKGROUND

The prospective phase III multi-centre L-MOCA trial (NCT03534453) has demonstrated the encouraging efficacy and manageable safety profile of olaparib maintenance therapy in the Asian (mainly Chinese) patients with platinum-sensitive relapsed ovarian cancer (PSROC). In this study, we report the preplanned exploratory biomarker analysis of the L-MOCA trial, which investigated the effects of homologous recombination deficiency (HRD) and programmed cell death ligand 1 (PD-L1) expression on olaparib efficacy.

METHODS

HRD status was determined using the ACTHRD assay, an enrichment-based targeted next-generation sequencing assay. PD-L1 expression was assessed by SP263 immunohistochemistry assay. PD-L1 expression positivity was defined by the PD-L1 expression on ≥ 1% of immune cells. Kaplan-Meier method was utilised to analyse progression-free survival (PFS).

RESULTS

This exploratory biomarker analysis included 225 patients and tested HRD status [N = 190; positive, N = 125 (65.8%)], PD-L1 expression [N = 196; positive, N = 56 (28.6%)], and BRCA1/2 mutation status (N = 219). The HRD-positive patients displayed greater median PFS than the HRD-negative patients [17.9 months (95% CI: 14.5-22.1) versus 9.2 months (95% CI: 7.5-13.8)]. PD-L1 was predominantly expressed on immune cells. Positive PD-L1 expression on immune cells was associated with shortened median PFS in the patients with germline BRCA1/2 mutations [14.5 months (95% CI: 7.4-18.2) versus 22.2 months (95% CI: 18.3-NA)]. Conversely, positive PD-L1 expression on immune cells was associated with prolonged median PFS in the patients with wild-type BRCA1/2 [20.9 months (95% CI: 13.9-NA) versus 8.3 months (95% CI: 6.7-13.8)].

CONCLUSIONS

HRD remained an effective biomarker for enhanced olaparib efficacy in the Asian patients with PSROC. Positive PD-L1 expression was associated with decreased olaparib efficacy in the patients with germline BRCA1/2 mutations but associated with improved olaparib efficacy in the patients with wild-type BRCA1/2.

TRIAL REGISTRATION

NCT03534453. Registered at May 23, 2018.

A temporal perspective for tumor-associated macrophage identities and functions

Cancer is a progressive disease that can develop and evolve over decades, with inflammation playing a central role at each of its stages, from tumor initiation to metastasis. In this context, macrophages represent well-established bridges reciprocally linking inflammation and cancer via an array of diverse functions that have spurred efforts to classify them into subtypes. Here, we discuss the intertwines between macrophages, inflammation, and cancer with an emphasis on temporal dynamics of macrophage diversity and functions in pre-malignancy and cancer. By instilling temporal dynamism into the more static classic view of tumor-associated macrophage biology, we propose a new framework to better contextualize their significance in the inflammatory processes that precede and result from the onset of cancer and shape its evolution.

Spatiotemporal architecture of immune cells and cancer-associated fibroblasts in high-grade serous ovarian carcinoma

High-grade serous ovarian carcinoma (HGSOC), the deadliest form of ovarian cancer, is typically diagnosed after it has metastasized and often relapses after standard-of-care platinum-based chemotherapy, likely due to advanced tumor stage, heterogeneity, and immune evasion and tumor-promoting signaling from the tumor microenvironment. To understand how spatial heterogeneity contributes to HGSOC progression and early relapse, we profiled an HGSOC tissue microarray of patient-matched longitudinal samples from 42 patients. We found spatial patterns associated with early relapse, including changes in T cell localization, malformed tertiary lymphoid structure (TLS)-like aggregates, and increased podoplanin-positive cancer-associated fibroblasts (CAFs). Using spatial features to compartmentalize the tissue, we found that plasma cells distribute in two different compartments associated with TLS-like aggregates and CAFs, and these distinct microenvironments may account for the conflicting reports about the role of plasma cells in HGSOC prognosis.

Quality Control for Single Cell Analysis of High-plex Tissue Profiles using CyLinter

Tumors are complex assemblies of cellular and acellular structures patterned on spatial scales from microns to centimeters. Study of these assemblies has advanced dramatically with the introduction of high-plex spatial profiling. Image-based profiling methods reveal the intensities and spatial distributions of 20-100 proteins at subcellular resolution in 103-107 cells per specimen. Despite extensive work on methods for extracting single-cell data from these images, all tissue images contain artefacts such as folds, debris, antibody aggregates, optical aberrations and image processing errors that arise from imperfections in specimen preparation, data acquisition, image assembly, and feature extraction. We show that these artefacts dramatically impact single-cell data analysis, obscuring meaningful biological interpretation. We describe an interactive quality control software tool, CyLinter, that identifies and removes data associated with imaging artefacts. CyLinter greatly improves single-cell analysis, especially for archival specimens sectioned many years prior to data collection, such as those from clinical trials.

Chemotherapy induces myeloid-driven spatial T-cell exhaustion in ovarian cancer

To uncover the intricate, chemotherapy-induced spatiotemporal remodeling of the tumor microenvironment, we conducted integrative spatial and molecular characterization of 97 high-grade serous ovarian cancer (HGSC) samples collected before and after chemotherapy. Using single-cell and spatial analyses, we identify increasingly versatile immune cell states, which form spatiotemporally dynamic microcommunities at the tumor-stroma interface. We demonstrate that chemotherapy triggers spatial redistribution and exhaustion of CD8+ T cells due to prolonged antigen presentation by macrophages, both within interconnected myeloid networks termed "Myelonets" and at the tumor stroma interface. Single-cell and spatial transcriptomics identifies prominent TIGIT-NECTIN2 ligand-receptor interactions induced by chemotherapy. Using a functional patient-derived immuno-oncology platform, we show that CD8+T-cell activity can be boosted by combining immune checkpoint blockade with chemotherapy. Our discovery of chemotherapy-induced myeloid-driven spatial T-cell exhaustion paves the way for novel immunotherapeutic strategies to unleash CD8+ T-cell-mediated anti-tumor immunity in HGSC.

Mechanotransduction and epigenetic modulations of chromatin: Role of mechanical signals in gene regulation

Mechanical forces may be generated within a cell due to tissue stiffness, cytoskeletal reorganization, and the changes (even subtle) in the cell's physical surroundings. These changes of forces impose a mechanical tension within the intracellular protein network (both cytosolic and nuclear). Mechanical tension could be released by a series of protein-protein interactions often facilitated by membrane lipids, lectins and sugar molecules and thus generate a type of signal to drive cellular processes, including cell differentiation, polarity, growth, adhesion, movement, and survival. Recent experimental data have accentuated the molecular mechanism of this mechanical signal transduction pathway, dubbed mechanotransduction. Mechanosensitive proteins in the cell's plasma membrane discern the physical forces and channel the information to the cell interior. Cells respond to the message by altering their cytoskeletal arrangement and directly transmitting the signal to the nucleus through the connection of the cytoskeleton and nucleoskeleton before the information despatched to the nucleus by biochemical signaling pathways. Nuclear transmission of the force leads to the activation of chromatin modifiers and modulation of the epigenetic landscape, inducing chromatin reorganization and gene expression regulation; by the time chemical messengers (transcription factors) arrive into the nucleus. While significant research has been done on the role of mechanotransduction in tumor development and cancer progression/metastasis, the mechanistic basis of force-activated carcinogenesis is still enigmatic. Here, in this review, we have discussed the various cues and molecular connections to better comprehend the cellular mechanotransduction pathway, and we also explored the detailed role of some of the multiple players (proteins and macromolecular complexes) involved in mechanotransduction. Thus, we have described an avenue: how mechanical stress directs the epigenetic modifiers to modulate the epigenome of the cells and how aberrant stress leads to the cancer phenotype.

Advances in the role of GPX3 in ovarian cancer (Review)

Ovarian cancer (OC) is the 5th most common malignancy in women, and the leading cause of death from gynecologic malignancies. Owing to tumor heterogeneity, lack of reliable early diagnostic methods and high incidence of chemotherapy resistance, the 5‑year survival rate of patients with advanced OC remains low despite considerable advances in detection and therapeutic approaches. Therefore, identifying novel therapeutic targets to improve the prognosis of patients with OC is crucial. The expression of glutathione peroxidase 3 (GPX3) plays a crucial role in the growth, proliferation and differentiation of various malignant tumors. In OC, GPX3 is the only antioxidant enzyme the high expression of which is negatively correlated with the overall survival of patients. GPX3 may affect lipid metabolism in tumor stem cells by influencing redox homeostasis in the tumor microenvironment. The maintenance of stemness in OC stem cells (OCSCs) is strongly associated with poor prognosis and recurrence in patients. The aim of the present study was to review the role of GPX3 in OC and investigate the potential factors and effects of GPX3 on OCSCs. The findings of the current study offer novel potential targets for drug therapy in OC, enhance the theoretical foundation of OC drug therapy and provide valuable references for clinical treatment.

Tracing back primed resistance in cancer via sister cells

Exploring non-genetic evolution of cell states during cancer treatments has become attainable by recent advances in lineage-tracing methods. However, transcriptional changes that drive cells into resistant fates may be subtle, necessitating high resolution analysis. Here, we present ReSisTrace that uses shared transcriptomic features of sister cells to predict the states priming treatment resistance. Applying ReSisTrace in ovarian cancer cells perturbed with olaparib, carboplatin or natural killer (NK) cells reveals pre-resistant phenotypes defined by proteostatic and mRNA surveillance features, reflecting traits enriched in the upcoming subclonal selection. Furthermore, we show that DNA repair deficiency renders cells susceptible to both DNA damaging agents and NK killing in a context-dependent manner. Finally, we leverage the obtained pre-resistance profiles to predict and validate small molecules driving cells to sensitive states prior to treatment. In summary, ReSisTrace resolves pre-existing transcriptional features of treatment vulnerability, facilitating both molecular patient stratification and discovery of synergistic pre-sensitizing therapies.

The spatial structure of the tumor immune microenvironment can explain and predict patient response in high-grade serous carcinoma

Despite ovarian cancer being the deadliest gynecological malignancy, there has been little change to therapeutic options and mortality rates over the last three decades. Recent studies indicate that the composition of the tumor immune microenvironment (TIME) influences patient outcomes but are limited by a lack of spatial understanding. We performed multiplexed ion beam imaging (MIBI) on 83 human high-grade serous carcinoma tumors - one of the largest protein-based, spatially-intact, single-cell resolution tumor datasets assembled - and used statistical and machine learning approaches to connect features of the TIME spatial organization to patient outcomes. Along with traditional clinical/immunohistochemical attributes and indicators of TIME composition, we found that several features of TIME spatial organization had significant univariate correlations and/or high relative importance in high-dimensional predictive models. The top performing predictive model for patient progression-free survival (PFS) used a combination of TIME composition and spatial features. Results demonstrate the importance of spatial structure in understanding how the TIME contributes to treatment outcomes. Furthermore, the present study provides a generalizable roadmap for spatial analyses of the TIME in ovarian cancer research.

Targeting the immune microenvironment for ovarian cancer therapy

Ovarian cancer (OC) is an aggressive malignancy characterized by a complex immunosuppressive tumor microenvironment (TME). Immune checkpoint inhibitors have emerged as a breakthrough in cancer therapy by reactivating the antitumor immune response suppressed by tumor cells. However, in the case of OC, these inhibitors have failed to demonstrate significant improvements in patient outcomes, and existing biomarkers have not yet identified promising subgroups. Consequently, there remains a pressing need to understand the interplay between OC tumor cells and their surrounding microenvironment to develop effective immunotherapeutic approaches. This review aims to provide an overview of the OC TME and explore its potential as a therapeutic strategy. Tumor-infiltrating lymphocytes (TILs) are major actors in OC TME. Evidence has been accumulating regarding the spontaneous TILS response against OC antigens. Activated T-helpers secrete a wide range of inflammatory cytokines with a supportive action on cytotoxic T-cells. Simultaneously, mature B-cells are recruited and play a significant antitumor role through opsonization of target antigens and T-cell recruitment. Macrophages also form an important subset of innate immunity (M1-macrophages) while participating in the immune-stimulation context. Finally, OC has shown to engage a significant natural-killer-cells immune response, exerting direct cytotoxicity without prior sensitization. Despite this initial cytotoxicity, OC cells develop various strategies to induce an immune-tolerant state. To this end, multiple immunosuppressive molecules are secreted to impair cytotoxic cells, recruit regulatory cells, alter antigen presentation, and effectively evade immune response. Consequently, OC TME is predominantly infiltrated by immunosuppressive cells such as FOXP3+ regulatory T-cells, M2-polarized macrophages and myeloid-derived suppressor cells. Despite this strong immunosuppressive state, PD-1/PD-L1 inhibitors have failed to improve outcomes. Beyond PD-1/PD-L1, OC expresses multiple other immune checkpoints that contribute to immune evasion, and each representing potential immune targets. Novel immunotherapies are attempting to overcome the immunosuppressive state and induce specific immune responses using antibodies adoptive cell therapy or vaccines. Overall, the OC TME presents both opportunities and obstacles. Immunotherapeutic approaches continue to show promise, and next-generation inhibitors offer exciting opportunities. However, tailoring therapies to individual immune characteristics will be critical for the success of these treatments.

Mesenchymal ovarian cancer cells promote CD8+ T cell exhaustion through the LGALS3-LAG3 axis

Cancer cells often metastasize by undergoing an epithelial-mesenchymal transition (EMT). Although abundance of CD8+ T-cells in the tumor microenvironment correlates with improved survival, mesenchymal cancer cells acquire greater resistance to antitumor immunity in some cancers. We hypothesized the EMT modulates the immune response to ovarian cancer. Here we show that cancer cells from infiltrated/inflamed tumors possess more mesenchymal cells, than excluded and desert tumors. We also noted high expression of LGALS3 is associated with EMT in vivo, a finding validated with in vitro EMT models. Dissecting the cellular communications among populations in the tumor revealed that mesenchymal cancer cells in infiltrated tumors communicate through LGALS3 to LAG3 receptor expressed by CD8+ T cells. We found CD8+ T cells express high levels of LAG3, a marker of T cell exhaustion. The results indicate that EMT in ovarian cancer cells promotes interactions between cancer cells and T cells through the LGALS3 - LAG3 axis, which could increase T cell exhaustion in infiltrated tumors, dampening antitumor immunity.

Metabolic and senescence characteristics associated with the immune microenvironment in ovarian cancer

Ovarian cancer is a highly malignant gynecological cancer influenced by the immune microenvironment, metabolic reprogramming, and cellular senescence. This review provides a comprehensive overview of these characteristics. Metabolic reprogramming affects immune cell function and tumor growth signals. Cellular senescence in immune and tumor cells impacts anti-tumor responses and therapy resistance. Targeting immune cell metabolism and inducing tumor cell senescence offer potential therapeutic strategies. However, challenges remain in identifying specific targets and biomarkers. Understanding the interplay of these characteristics can lead to innovative therapeutic approaches. Further research is needed to elucidate mechanisms, validate strategies, and improve patient outcomes in ovarian cancer.

The prognostic value of tumor-stroma ratio and a newly developed computer-aided quantitative analysis of routine H&amp;E slides in high-grade serous ovarian cancer

INTRODUCTION

Tumor-stroma ratio (TSR) is prognostic in multiple cancers, while its role in high-grade serous ovarian cancer (HGSOC) remains unclear. Despite the prognostic insight gained from genetic profiles and tumor-infiltrating lymphocytes (TILs), the prognostic use of histology slides remains limited, while it enables the identification of tumor characteristics via computational pathology reducing scoring time and costs. To address this, this study aimed to assess TSR's prognostic role in HGSOC and its association with TILs. We additionally developed an algorithm, Ovarian-TSR (OTSR), using deep learning for TSR scoring, comparing it to manual scoring. Methods : 340 patients with advanced-stage who underwent primary debulking surgery (PDS) or neo-adjuvant chemotherapy (NACT) with interval debulking (IDS). TSR was assessed in both the most invasive (MI) and whole tumor (WT) regions through manual scoring by pathologists and quantification using OTSR. Patients were categorized as stroma-rich (≥ 50% stroma) or stroma-poor (< 50%). TILs were evaluated via immunohistochemical staining. Result s: In PDS, stroma-rich tumors were significantly associated with a more frequent papillary growth pattern (60% vs 34%), while In NACT stroma-rich tumors had a lower Tumor Regression Grading (TRG 4&5, 21% vs 57%) and increased pleural metastasis (25% vs 16%). Stroma-rich patients had significantly shorter overall and progression-free survival compared to stroma-poor (31 versus 45 months; P < 0.0001, and 15 versus 17 months; P = 0.0008, respectively). Combining stromal percentage and TILs led to three distinct survival groups with good (stroma-poor, high TIL), medium (stroma-rich, high TIL, or; stroma-poor, Low TIL), and poor(stroma-rich, low TIL) survival. These survival groups remained significant in CD8 and CD103 in multivariable analysis (Hazard ratio (HR) = 1.42, 95% Confidence-interval (CI) = 1.02-1.99; HR = 1.49, 95% CI = 1.01-2.18, and HR = 1.48, 95% CI = 1.05-2.08; HR = 2.24, 95% CI = 1.55-3.23, respectively). OTSR was able to recapitulate these results and demonstrated high concordance with expert pathologists (correlation = 0.83). Conclusions : TSR is an independent prognostic factor for survival assessment in HGSOC. Stroma-rich tumors have a worse prognosis and, in the case of NACT, a higher likelihood of pleural metastasis. OTSR provides a cost and time-efficient way of determining TSR with high reproducibility and reduced inter-observer variability.

Multi-scale characterisation of homologous recombination deficiency in breast cancer

BACKGROUND

Homologous recombination is a robust, broadly error-free mechanism of double-strand break repair, and deficiencies lead to PARP inhibitor sensitivity. Patients displaying homologous recombination deficiency can be identified using 'mutational signatures'. However, these patterns are difficult to reliably infer from exome sequencing. Additionally, as mutational signatures are a historical record of mutagenic processes, this limits their utility in describing the current status of a tumour.

METHODS

We apply two methods for characterising homologous recombination deficiency in breast cancer to explore the features and heterogeneity associated with this phenotype. We develop a likelihood-based method which leverages small insertions and deletions for high-confidence classification of homologous recombination deficiency for exome-sequenced breast cancers. We then use multinomial elastic net regression modelling to develop a transcriptional signature of heterogeneous homologous recombination deficiency. This signature is then applied to single-cell RNA-sequenced breast cancer cohorts enabling analysis of homologous recombination deficiency heterogeneity and differential patterns of tumour microenvironment interactivity.

RESULTS

We demonstrate that the inclusion of indel events, even at low levels, improves homologous recombination deficiency classification. Whilst BRCA-positive homologous recombination deficient samples display strong similarities to those harbouring BRCA1/2 defects, they appear to deviate in microenvironmental features such as hypoxic signalling. We then present a 228-gene transcriptional signature which simultaneously characterises homologous recombination deficiency and BRCA1/2-defect status, and is associated with PARP inhibitor response. Finally, we show that this signature is applicable to single-cell transcriptomics data and predict that these cells present a distinct milieu of interactions with their microenvironment compared to their homologous recombination proficient counterparts, typified by a decreased cancer cell response to TNFα signalling.

CONCLUSIONS

We apply multi-scale approaches to characterise homologous recombination deficiency in breast cancer through the development of mutational and transcriptional signatures. We demonstrate how indels can improve homologous recombination deficiency classification in exome-sequenced breast cancers. Additionally, we demonstrate the heterogeneity of homologous recombination deficiency, especially in relation to BRCA1/2-defect status, and show that indications of this feature can be captured at a single-cell level, enabling further investigations into interactions between DNA repair deficient cells and their tumour microenvironment.

TMSB4X: A novel prognostic marker for non-small cell lung cancer

Non-small cell lung cancer (NSCLC), as the main type of lung cancer, has a long history of high incidence and mortality. Despite the continuous updates to the American Joint Committee on Cancer (AJCC) staging system, which adapt to evolving treatment modalities and diagnostic advancements, it is evident that patients at the same stage exhibit varying prognoses. The heterogeneity of tumors underscores the need for molecular diagnostics to assume a pivotal role in tumor staging and patient stratification. In our investigation, we meticulously analyzed the data of the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, incorporating clinical patients and scrutinizing pathological specimens. Through this comprehensive approach, we established a correlation between the expression of the Thymosin beta 4 X-linked (TMSB4X) gene and poorer disease-free survival (DFS) and overall survival (OS) post-surgery. Compared to the TMSB4X positive expression group, patients in the negative expression group had a better prognosis, with longer DFS (median disease-free survival (median DFS): 16.2 months vs. 11.3 months, P = 0.032) and OS (median overall survival (mOS): 29.8 months vs. 18.5 months, P = 0.033). Furthermore, our findings suggest that TMSB4X may facilitate immune evasion in non-small cell lung cancer cells by influencing the activation of infiltrating dendritic cells (DCs) in tumor infiltrating immune cells (TIICs) (R = 0.27, P = 4.8E+08). In summary, TMSB4X emerges as an unfavorable prognostic factor for NSCLC, potentially modulating the tumor immune microenvironment through its regulatory impact on dendritic cell function, thus facilitating tumor immune escape.

The DNA Damage Response and Inflammation in Cancer

Genomic stability in normal cells is crucial to avoid oncogenesis. Accordingly, multiple components of the DNA damage response (DDR) operate as bona fide tumor suppressor proteins by preserving genomic stability, eliciting the demise of cells with unrepairable DNA lesions, and engaging cell-extrinsic oncosuppression via immunosurveillance. That said, DDR sig-naling can also favor tumor progression and resistance to therapy. Indeed, DDR signaling in cancer cells has been consistently linked to the inhibition of tumor-targeting immune responses. Here, we discuss the complex interactions between the DDR and inflammation in the context of oncogenesis, tumor progression, and response to therapy.

SIGNIFICANCE

Accumulating preclinical and clinical evidence indicates that DDR is intimately connected to the emission of immunomodulatory signals by normal and malignant cells, as part of a cell-extrinsic program to preserve organismal homeostasis. DDR-driven inflammation, however, can have diametrically opposed effects on tumor-targeting immunity. Understanding the links between the DDR and inflammation in normal and malignant cells may unlock novel immunotherapeutic paradigms to treat cancer.

Exploring the tumor immune microenvironment in ovarian cancer: a way-out to the therapeutic roadmap

INTRODUCTION

Despite cancer treatment strides, mortality due to ovarian cancer remains high globally. While immunotherapy has proven effective in treating cancers with low cure rates, it has limitations. Growing evidence suggests that both tumoral and non-tumoral components of the tumor immune microenvironment (TIME) play a significant role in cancer growth. Therefore, developing novel and focused therapy for ovarian cancer is critical. Studies indicate that TIME is involved in developing ovarian cancer, particularly genome-, transcriptome-, and proteome-wide studies. As a result, TIME may present a prospective therapeutic target for ovarian cancer patients.

AREAS COVERED

We examined several TIME-targeting medicines and the connection between TIME and ovarian cancer. The key protagonists and events in the TIME and therapeutic strategies that explicitly target these events in ovarian cancer are discussed.

EXPERT OPINION

We highlighted various targeted therapies against TIME in ovarian cancer, including anti-angiogenesis therapies and immune checkpoint inhibitors. While these therapies are in their infancy, they have shown promise in controlling ovarian cancer progression. The use of 'omics' technology is helping in better understanding of TIME in ovarian cancer and potentially identifying new therapeutic targets. TIME-targeted strategies could account for an additional treatment strategy when treating ovarian cancer.

Single-cell profiling of low-stage endometrial cancers identifies low epithelial vimentin expression as a marker of recurrent disease

BACKGROUND

Identification of aggressive low-stage endometrial cancers is challenging. So far, studies have failed to pinpoint robust features or biomarkers associated with risk of recurrence for these patients.

METHODS

Imaging mass cytometry was used to examine single-cell expression of 23 proteins in 36 primary FIGO IB endometrial cancers, of which 17 recurred. Single-cell information was extracted for each tumor and unsupervised clustering was used to identify cellular phenotypes. Distinct phenotypes and cellular neighborhoods were compared in relation to recurrence. Cellular differences were validated in a separate gene expression dataset and the TCGA EC dataset. Vimentin protein expression was evaluated by IHC in pre-operative samples from 518 patients to validate its robustness as a prognostic marker.

FINDINGS

The abundance of epithelial, immune or stromal cell types did not associate with recurrence. Clustering of patients based on tumor single cell marker expression revealed distinct patient clusters associated with outcome. A cell population neighboring CD8+ T cells, defined by vimentin, ER, and PR expressing epithelial cells, was more prevalent in non-recurrent tumors. Importantly, lower epithelial vimentin expression and lower gene expression of VIM associated with worse recurrence-free survival. Loss and low expression of vimentin was validated by IHC as a robust marker for recurrence in FIGO I stage disease and predicted poor prognosis also when including all patients and in endometrioid patients only.

INTERPRETATION

This study reveals distinct characteristics in low-stage tumors and points to vimentin as a clinically relevant marker that may aid in identifying a here to unidentified subgroup of high-risk patients.

FUNDING

A full list of funding that contributed to this study can be found in the Acknowledgements section.

Pan-cancer analysis revealed H3K4me1 at bivalent promoters premarks DNA hypermethylation during tumor development and identified the regulatory role of DNA methylation in relation to histone modifications

BACKGROUND

DNA hypermethylation at promoter CpG islands (CGIs) is a hallmark of cancers and could lead to dysregulation of gene expression in the development of cancers, however, its dynamics and regulatory mechanisms remain elusive. Bivalent genes, that direct development and differentiation of stem cells, are found to be frequent targets of hypermethylation in cancers.

RESULTS

Here we performed comprehensive analysis across multiple cancer types and identified that the decrease in H3K4me1 levels coincides with DNA hypermethylation at the bivalent promoter CGIs during tumorigenesis. Removal of DNA hypermethylation leads to increment of H3K4me1 at promoter CGIs with preference for bivalent genes. Nevertheless, the alteration of H3K4me1 by overexpressing or knockout LSD1, the demethylase of H3K4, doesn't change the level or pattern of DNA methylation. Moreover, LSD1 was found to regulate the expression of a bivalent gene OVOL2 to promote tumorigenesis. Knockdown of OVOL2 in LSD1 knockout HCT116 cells restored the cancer cell phenotype.

CONCLUSION

In summary, our work identified a universal indicator that can pre-mark DNA hypermethylation in cancer cells, and dissected the interplay between H3K4me1 and DNA hypermethylation in detail. Current study also reveals a novel mechanism underlying the oncogenic role of LSD1, providing clues for cancer therapies.

Spatial Transcriptomics Depict Ligand-Receptor Cross-talk Heterogeneity at the Tumor-Stroma Interface in Long-Term Ovarian Cancer Survivors

Advanced high-grade serous ovarian cancer (HGSC) is an aggressive disease that accounts for 70% of all ovarian cancer deaths. Nevertheless, 15% of patients diagnosed with advanced HGSC survive more than 10 years. The elucidation of predictive markers of these long-term survivors (LTS) could help identify therapeutic targets for the disease, and thus improve patient survival rates. To investigate the stromal heterogeneity of the tumor microenvironment (TME) in ovarian cancer, we used spatial transcriptomics to generate spatially resolved transcript profiles in treatment-naïve advanced HGSC from LTS and short-term survivors (STS) and determined the association between cancer-associated fibroblasts (CAF) heterogeneity and survival in patients with advanced HGSC. Spatial transcriptomics and single-cell RNA-sequencing data were integrated to distinguish tumor and stroma regions, and a computational method was developed to investigate spatially resolved ligand-receptor interactions between various tumor and CAF subtypes in the TME. A specific subtype of CAFs and its spatial location relative to a particular ovarian cancer cell subtype in the TME correlated with long-term survival in patients with advanced HGSC. Also, increased APOE-LRP5 cross-talk occurred at the stroma-tumor interface in tumor tissues from STS compared with LTS. These findings were validated using multiplex IHC. Overall, this spatial transcriptomics analysis revealed spatially resolved CAF-tumor cross-talk signaling networks in the ovarian TME that are associated with long-term survival of patients with HGSC. Further studies to confirm whether such cross-talk plays a role in modulating the malignant phenotype of HGSC and could serve as a predictive biomarker of patient survival are warranted.

SIGNIFICANCE

Generation of spatially resolved gene expression patterns in tumors from patients with ovarian cancer surviving more than 10 years allows the identification of novel predictive biomarkers and therapeutic targets for better patient management. See related commentary by Kelliher and Lengyel, p. 1383.

RAD54L promotes progression of hepatocellular carcinoma via the homologous recombination repair pathway

Hepatocellular carcinoma (HCC) is a malignant tumor with high incidence worldwide. The underlying mechanisms remain poorly understood. The DNA metabolic process of homologous recombination repair (HRR) has been linked to a high probability of tumorigenesis and drug resistance. This study aimed to determine the role of HRR in HCC and identify critical HRR-related genes that affect tumorigenesis and prognosis. A total of 613 tumor and 252 para-carcinoma tissue samples were collected from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) to obtain differentially expressed genes (DEGs). HRR-related genes were assessed using gene enrichment and pathway analyses. Survival analysis was performed using the Kaplan-Meier method in the Gene Expression Profiling Interactive Analysis portal. The levels of RAD54L in the HRR pathway were detected by RT-qPCR and western blotting in para-carcinoma and HCC tissues and in L02 normal human liver cells and Huh7 HCC cells. Immunohistochemistry (IHC) was performed on the clinical specimens to determine the connection between gene expression and clinical features. Bioinformatics analysis revealed that the HRR pathway was enriched in HCC tissues. Upregulation of HRR pathway DEGs in HCC tissues was positively correlated with tumor pathological staging and negatively associated with patient overall survival. RAD54B, RAD54L, and EME1 genes in the HRR pathway were screened as markers for predicting HCC prognosis. RT-qPCR identified RAD54L as the most significantly expressed of the three genes. Western blotting and IHC quantitative analyses further demonstrated that RAD54L protein levels were higher in HCC tissues. IHC analysis of 39 pairs of HCC and para-carcinoma tissue samples also revealed an association between RAD54L and Edmondson-Steiner grade and the proliferation-related gene Ki67. The collective findings positively correlate RAD54L in the HRR signaling pathway with HCC staging and implicate RAD54L as a marker to predict HCC progression.

Machine learning-based integration develops an immune-related risk model for predicting prognosis of high-grade serous ovarian cancer and providing therapeutic strategies

Background

High-grade serous ovarian cancer (HGSOC) is a highly lethal gynecological cancer that requires accurate prognostic models and personalized treatment strategies. The tumor microenvironment (TME) is crucial for disease progression and treatment. Machine learning-based integration is a powerful tool for identifying predictive biomarkers and developing prognostic models. Hence, an immune-related risk model developed using machine learning-based integration could improve prognostic prediction and guide personalized treatment for HGSOC.

Methods

During the bioinformatic study in HGSOC, we performed (i) consensus clustering to identify immune subtypes based on signatures of immune and stromal cells, (ii) differentially expressed genes and univariate Cox regression analysis to derive TME- and prognosis-related genes, (iii) machine learning-based procedures constructed by ten independent machine learning algorithms to screen and construct a TME-related risk score (TMErisk), and (iv) evaluation of the effect of TMErisk on the deconstruction of TME, indication of genomic instability, and guidance of immunotherapy and chemotherapy.

Results

We identified two different immune microenvironment phenotypes and a robust and clinically practicable prognostic scoring system. TMErisk demonstrated superior performance over most clinical features and other published signatures in predicting HGSOC prognosis across cohorts. The low TMErisk group with a notably favorable prognosis was characterized by BRCA1 mutation, activation of immunity, and a better immune response. Conversely, the high TMErisk group was significantly associated with C-X-C motif chemokine ligands deletion and carcinogenic activation pathways. Additionally, low TMErisk group patients were more responsive to eleven candidate agents.

Conclusion

Our study developed a novel immune-related risk model that predicts the prognosis of ovarian cancer patients using machine learning-based integration. Additionally, the study not only depicts the diversity of cell components in the TME of HGSOC but also guides the development of potential therapeutic techniques for addressing tumor immunosuppression and enhancing the response to cancer therapy.

Multiparameter single-cell proteomic technologies give new insights into the biology of ovarian tumors

High-grade serous ovarian cancer (HGSOC) is the most lethal gynecological malignancy. Its diagnosis at advanced stage compounded with its excessive genomic and cellular heterogeneity make curative treatment challenging. Two critical therapeutic challenges to overcome are carboplatin resistance and lack of response to immunotherapy. Carboplatin resistance results from diverse cell autonomous mechanisms which operate in different combinations within and across tumors. The lack of response to immunotherapy is highly likely to be related to an immunosuppressive HGSOC tumor microenvironment which overrides any clinical benefit. Results from a number of studies, mainly using transcriptomics, indicate that the immune tumor microenvironment (iTME) plays a role in carboplatin response. However, in patients receiving treatment, the exact mechanistic details are unclear. During the past decade, multiplex single-cell proteomic technologies have come to the forefront of biomedical research. Mass cytometry or cytometry by time-of-flight, measures up to 60 parameters in single cells that are in suspension. Multiplex cellular imaging technologies allow simultaneous measurement of up to 60 proteins in single cells with spatial resolution and interrogation of cell-cell interactions. This review suggests that functional interplay between cell autonomous responses to carboplatin and the HGSOC immune tumor microenvironment could be clarified through the application of multiplex single-cell proteomic technologies. We conclude that for better clinical care, multiplex single-cell proteomic technologies could be an integral component of multimodal biomarker development that also includes genomics and radiomics. Collection of matched samples from patients before and on treatment will be critical to the success of these efforts.

Unraveling the Transcriptomic Signatures of Homologous Recombination Deficiency in Ovarian Cancers

Homologous recombination deficiency (HRD) is a crucial driver of tumorigenesis by inducing impaired repair of double-stranded DNA breaks. Although HRD possibly triggers the production of numerous tumor neoantigens that sufficiently stimulate and activate various tumor-immune responses, a comprehensive understanding of the HRD-associated tumor microenvironment is elusive. To investigate the effect of HRD on the selective enrichment of transcriptomic signatures, 294 cases from The Cancer Genome Atlas-Ovarian Cancer project with both RNA-sequencing and SNP array data are analyzed. Differentially expressed gene analysis and network analysis are performed to identify HRD-specific signatures. Gene-sets associated with mitochondrial activation, including enhanced oxidative phosphorylation (OxPhos), are significantly enriched in the HRD-high group. Furthermore, a wide range of immune cell activation signatures is enriched in HRD-high cases of high-grade serous ovarian cancer (HGSOC). On further cell-type-specific analysis, M1-like macrophage genes are significantly enriched in HRD-high HGSOC cases, whereas M2-macrophage-related genes are not. The immune-response-associated genomic features, including tumor mutation rate, neoantigens, and tumor mutation burdens, correlated with HRD scores. In conclusion, the results of this study highlight the biological properties of HRD, including enhanced energy metabolism, increased tumor neoantigens and tumor mutation burdens, and consequent exacerbation of immune responses, particularly the enrichment of M1-like macrophages in HGSOC cases.

Integration of local and systemic immunity in ovarian cancer: Implications for immunotherapy

Cancer is a disease that induces many local and systemic changes in immunity. The difficult nature of ovarian cancer stems from the lack of characteristic symptoms that contributes to a delayed diagnosis and treatment. Despite the enormous progress in immunotherapy, its efficacy remains limited. The heterogeneity of tumors, lack of diagnostic biomarkers, and complex immune landscape are the main challenges in the treatment of ovarian cancer. Integrative approaches that combine the tumor microenvironment - local immunity - together with periphery - systemic immunity - are urgently needed to improve the understanding of the disease and the efficacy of treatment. In fact, multiparametric analyses are poised to improve our understanding of ovarian tumor immunology. We outline an integrative approach including local and systemic immunity in ovarian cancer. Understanding the nature of both localized and systemic immune responses will be crucial to boosting the efficacy of immunotherapies in ovarian cancer patients.

Antibody therapeutics for epithelial ovarian cancer

INTRODUCTION

High-grade serous ovarian carcinoma (HGSC) is an aggressive subtype of epithelial ovarian carcinoma (EOC) and remains the most lethal gynecologic cancer. A lack of effective and tolerable therapeutic options and nonspecific symptoms at presentation with advanced stage of disease are among the challenges in the management of the disease.

AREAS COVERED

An overview of ovarian cancer, followed by a discussion of the current therapeutic regimes and challenges that arise during and after the treatment of EOC. We discuss different formats of antibody therapeutics and their usage in targeting validated targets implicated in ovarian cancer, as well as three emerging novel proteins as examples recently implicated in their contribution to adaptive resistance in ovarian cancer.

EXPERT OPINION

Antibody therapeutics allow for a unique and effective way to target proteins implicated in cancer and other diseases, and have the potential to radically change the outcomes of patients suffering from ovarian cancer. The vast array of targets that have been implicated in ovarian cancer and yet the lack of effective therapeutic options for patients further stresses the importance of discovering novel proteins that can be targeted, as well as predictive biomarkers that can inform the stratification of patients into treatment-specific populations.

Liquid Biopsy and the Translational Bridge from the TIME to the Clinic

Research and advancing understanding of the tumor immune microenvironment (TIME) is vital to optimize and direct more effective cancer immune therapy. Pre-clinical bench research is vital to better understand the genomic interplay of the TIME and immune therapy responsiveness. However, a vital key to effective translational cancer research is having a bridge of translation to bring that understanding from the bench to the bedside. Without that bridge, research into the TIME will lack an efficient and effective translation into the clinic and cancer treatment decision making. As a clinical oncologist, the purpose of this commentary is to emphasize the importance of researching and improving clinical utility of the bridge, as well as the TIME research itself.

Stitching and registering highly multiplexed whole-slide images of tissues and tumors using ASHLAR

MOTIVATION

Stitching microscope images into a mosaic is an essential step in the analysis and visualization of large biological specimens, particularly human and animal tissues. Recent approaches to highly multiplexed imaging generate high-plex data from sequential rounds of lower-plex imaging. These multiplexed imaging methods promise to yield precise molecular single-cell data and information on cellular neighborhoods and tissue architecture. However, attaining mosaic images with single-cell accuracy requires robust image stitching and image registration capabilities that are not met by existing methods.

RESULTS

We describe the development and testing of ASHLAR, a Python tool for coordinated stitching and registration of 103 or more individual multiplexed images to generate accurate whole-slide mosaics. ASHLAR reads image formats from most commercial microscopes and slide scanners, and we show that it performs better than existing open-source and commercial software. ASHLAR outputs standard OME-TIFF images that are ready for analysis by other open-source tools and recently developed image analysis pipelines.

AVAILABILITY AND IMPLEMENTATION

ASHLAR is written in Python and is available under the MIT license at https://github.com/labsyspharm/ashlar. The newly published data underlying this article are available in Sage Synapse at https://dx.doi.org/10.7303/syn25826362; the availability of other previously published data re-analyzed in this article is described in Supplementary Table S4. An informational website with user guides and test data is available at https://labsyspharm.github.io/ashlar/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.