Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer

Predictors of residual disease after debulking surgery in advanced stage ovarian cancer

Objective

Optimal debulking with no macroscopic residual disease strongly predicts ovarian cancer survival. The ability to predict likelihood of optimal debulking, which may be partially dependent on tumor biology, could inform clinical decision-making regarding use of neoadjuvant chemotherapy. Thus, we developed a prediction model including epidemiological factors and tumor markers of residual disease after primary debulking surgery.

Methods

Univariate analyses examined associations of 11 pre-diagnosis epidemiologic factors (n=593) and 24 tumor markers (n=204) with debulking status among incident, high-stage, epithelial ovarian cancer cases from the Nurses' Health Studies and New England Case Control study. We used Bayesian model averaging (BMA) to develop prediction models of optimal debulking with 5x5-fold cross-validation and calculated the area under the curve (AUC).

Results

Current aspirin use was associated with lower odds of optimal debulking compared to never use (OR=0.52, 95%CI=0.31-0.86) and two tissue markers, ADRB2 (OR=2.21, 95%CI=1.23-4.41) and FAP (OR=1.91, 95%CI=1.24-3.05) were associated with increased odds of optimal debulking. The BMA selected aspirin, parity, and menopausal status as the epidemiologic/clinical predictors with the posterior effect probability ≥20%. While the prediction model with epidemiologic/clinical predictors had low performance (average AUC=0.49), the model adding tissue biomarkers showed improved, but weak, performance (average AUC=0.62).

Conclusions

Addition of ovarian tumor tissue markers to our multivariable prediction models based on epidemiologic/clinical data slightly improved the model performance, suggesting debulking status may be in part driven by tumor characteristics. Larger studies are warranted to identify those at high risk of poor surgical outcomes informing personalized treatment.

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.

Metabolic rearrangements and intratumoral heterogeneity for immune response in hepatocellular carcinoma

Liver cancer is one of the most common malignant tumors globally. Not only is it difficult to diagnose, but treatments are scarce and the prognosis is generally poor. Hepatocellular carcinoma (HCC) is the most common type of liver cancer. Aggressive cancer cells, such as those found in HCC, undergo extensive metabolic rewiring as tumorigenesis, the unique feature, ultimately causes adaptation to the neoplastic microenvironment. Intratumoral heterogeneity (ITH) is defined as the presence of distinct genetic features and different phenotypes in the same tumoral region. ITH, a property unique to malignant cancers, results in differences in many different features of tumors, including, but not limited to, tumor growth and resistance to chemotherapy, which in turn is partly responsible for metabolic reprogramming. Moreover, the different metabolic phenotypes might also activate the immune response to varying degrees and help tumor cells escape detection by the immune system. In this review, we summarize the reprogramming of glucose metabolism and tumoral heterogeneity and their associations that occur in HCC, to obtain a better understanding of the mechanisms of HCC oncogenesis.

Targeted therapy and immunotherapy: Diamonds in the rough in the treatment of epithelial ovarian cancer

Currently, for ovarian cancer, which has the highest mortality rate among all gynecological cancers, the standard treatment protocol is initial tumor cytoreductive surgery followed by platinum-based combination chemotherapy. Although the survival rate after standard treatment has improved, the therapeutic effect of traditional chemotherapy is very limited due to problems such as resistance to platinum-based drugs and recurrence. With the advent of the precision medicine era, molecular targeted therapy has gradually entered clinicians' view, and individualized precision therapy has been realized, surpassing the limitations of traditional therapy. The detection of genetic mutations affecting treatment, especially breast cancer susceptibility gene (BRCA) mutations and mutations of other homologous recombination repair defect (HRD) genes, can guide the targeted drug treatment of patients, effectively improve the treatment effect and achieve a better patient prognosis. This article reviews different sites and pathways of targeted therapy, including angiogenesis, cell cycle and DNA repair, and immune and metabolic pathways, and the latest research progress from preclinical and clinical trials related to ovarian cancer therapy.

Necroptosis-Related Modification Patterns Depict the Tumor Microenvironment, Redox Stress Landscape, and Prognosis of Ovarian Cancer

Necroptosis is one of programmed cell death discovered recently, which involves in tumorigenesis, cancer metastasis, and immune reaction. We studied the necroptosis-related genes (NRGs) in ovarian cancer (OV) tissues using data from public databases, which separated into two NRGclusters. Patients in cluster A would have severe clinical characteristics, poor prognosis, and worse tumor microenvironment infiltration characteristics. The NRG score was achieved through the Cox analysis, along with a construction of a prognostic model. People with lower risk score would have better prognosis, lower expression of redox related genes, higher immunogenicity, and better effect on immunotherapy. In addition, the NRG score was closely related to cancer stem cell index, copy number variations, tumor mutation load, and chemosensitivity. We built a nomogram to enhance clinical application of the signature. These outcomes can help use know the function of NRGs in OV and provide new ideas for evaluating clinical outcome and developing more effective treatment protocols.

Immune-related pan-cancer gene expression signatures of patient survival revealed by NanoString-based analyses

The immune system plays a central role in the onset and progression of cancer. A better understanding of transcriptional changes in immune cell-related genes associated with cancer progression, and their significance in disease prognosis, is therefore needed. NanoString-based targeted gene expression profiling has advantages for deployment in a clinical setting over RNA-seq technologies. We analysed NanoString PanCancer Immune Profiling panel gene expression data encompassing 770 genes, and overall survival data, from multiple previous studies covering 10 different cancer types, including solid and blood malignancies, across 515 patients. This analysis revealed an immune gene signature comprising 39 genes that were upregulated in those patients with shorter overall survival; of these 39 genes, three (MAGEC2, SSX1 and ULBP2) were common to both solid and blood malignancies. Most of the genes identified have previously been reported as relevant in one or more cancer types. Using Cibersort, we investigated immune cell levels within individual cancer types and across groups of cancers, as well as in shorter and longer overall survival groups. Patients with shorter survival had a higher proportion of M2 macrophages and γδ T cells. Patients with longer overall survival had a higher proportion of CD8+ T cells, CD4+ T memory cells, NK cells and, unexpectedly, T regulatory cells. Using a transcriptomics platform with certain advantages for deployment in a clinical setting, our multi-cancer meta-analysis of immune gene expression and overall survival data has identified a specific transcriptional profile associated with poor overall survival.

Spatial heterogeneity of infiltrating T cells in high-grade serous ovarian cancer revealed by multi-omics analysis

Tumor-infiltrating lymphocytes (TILs), especially CD8⁺ TILs, represent a favorable prognostic factor in high-grade serous ovarian cancer (HGSOC) and other tumor lineages. Here, we analyze the spatial heterogeneity of different TIL subtypes in HGSOC. We integrated RNA sequencing, whole-genome sequencing, bulk T cell receptor (TCR) sequencing, as well as single-cell RNA/TCR sequencing to investigate the characteristics and differential composition of TILs across different HGSOC sites. Two immune "cold" patterns in ovarian cancer are identified: (1) ovarian lesions with low infiltration of mainly dysfunctional T cells and immunosuppressive Treg cells and (2) omental lesions infiltrated with non-tumor-specific bystander cells. Exhausted CD8 T cells that are preferentially enriched in ovarian tumors exhibit evidence for expansion and cytotoxic activity. Inherent tumor immune microenvironment characteristics appear to be the main contributor to the spatial differences in TIL status. The landscape of spatial heterogeneity of TILs may inform potential strategies for therapeutic manipulation in HGSOC.

Therapy sculpts the complex interplay between cancer and the immune system during tumour evolution

Cancer development is an evolutionary process. A key selection pressure is exerted by therapy, one of the few players in cancer evolution that can be controlled. As such, an understanding of how treatment acts to sculpt the tumour and its microenvironment and how this influences a tumour's subsequent evolutionary trajectory is critical. In this review, we examine cancer evolution and intra-tumour heterogeneity in the context of therapy. We focus on how radiotherapy, chemotherapy and immunotherapy shape both tumour development and the environment in which tumours evolve and how resistance can develop or be selected for during treatment.

Immunogenomic intertumor heterogeneity across primary and metastatic sites in a patient with lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer death, partially owing to its extensive heterogeneity. The analysis of intertumor heterogeneity has been limited by an inability to concurrently obtain tissue from synchronous metastases unaltered by multiple prior lines of therapy.

Methods

In order to study the relationship between genomic, epigenomic and T cell repertoire heterogeneity in a rare autopsy case from a 32-year-old female never-smoker with left lung primary late-stage lung adenocarcinoma (LUAD), we did whole-exome sequencing (WES), DNA methylation and T cell receptor (TCR) sequencing to characterize the immunogenomic landscape of one primary and 19 synchronous metastatic tumors.

Results

We observed heterogeneous mutation, methylation, and T cell patterns across distinct metastases. Only TP53 mutation was detected in all tumors suggesting an early event while other cancer gene mutations were later events which may have followed subclonal diversification. A set of prevalent T cell clonotypes were completely excluded from left-side thoracic tumors indicating distinct T cell repertoire profiles between left-side and non left-side thoracic tumors. Though a limited number of predicted neoantigens were shared, these were associated with homology of the T cell repertoire across metastases. Lastly, ratio of methylated neoantigen coding mutations was negatively associated with T-cell density, richness and clonality, suggesting neoantigen methylation may partially drive immunosuppression.

Conclusions

Our study demonstrates heterogeneous genomic and T cell profiles across synchronous metastases and how restriction of unique T cell clonotypes within an individual may differentially shape the genomic and epigenomic landscapes of synchronous lung metastases.

Ovarian cancer mutational processes drive site-specific immune evasion

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability1-4 patterned by distinct mutational processes5,6, tumour heterogeneity7-9 and intraperitoneal spread7,8,10. Immunotherapies have had limited efficacy in HGSOC11-13, highlighting an unmet need to assess how mutational processes and the anatomical sites of tumour foci determine the immunological states of the tumour microenvironment. Here we carried out an integrative analysis of whole-genome sequencing, single-cell RNA sequencing, digital histopathology and multiplexed immunofluorescence of 160 tumour sites from 42 treatment-naive patients with HGSOC. Homologous recombination-deficient HRD-Dup (BRCA1 mutant-like) and HRD-Del (BRCA2 mutant-like) tumours harboured inflammatory signalling and ongoing immunoediting, reflected in loss of HLA diversity and tumour infiltration with highly differentiated dysfunctional CD8+ T cells. By contrast, foldback-inversion-bearing tumours exhibited elevated immunosuppressive TGFβ signalling and immune exclusion, with predominantly naive/stem-like and memory T cells. Phenotypic state associations were specific to anatomical sites, highlighting compositional, topological and functional differences between adnexal tumours and distal peritoneal foci. Our findings implicate anatomical sites and mutational processes as determinants of evolutionary phenotypic divergence and immune resistance mechanisms in HGSOC. Our study provides a multi-omic cellular phenotype data substrate from which to develop and interpret future personalized immunotherapeutic approaches and early detection research.

Space in cancer biology: its role and implications

Tumor cells present complex behaviors in their interactions with other cells. This intricate behavior is driving the need to develop new tools to understand these ecosystems. The surge of spatial technologies allows evaluation of the complexity of relationships between cells present in a tumor, giving insights about tumor heterogeneity and the tumor microenvironment while providing clinically relevant metrics for tumor classification. In this review, we describe key results obtained using spatial techniques, present recent advances in methods to uncover spatially relevant biological significance, and summarize their main characteristics. We expect spatial technologies to significantly broaden our understanding of tumor biology and to generate clinically relevant tools that will ultimately impact personalized medicine.

Single-cell genomic variation induced by mutational processes in cancer

How cell-to-cell copy number alterations that underpin genomic instability1 in human cancers drive genomic and phenotypic variation, and consequently the evolution of cancer2, remains understudied. Here, by applying scaled single-cell whole-genome sequencing3 to wild-type, TP53-deficient and TP53-deficient;BRCA1-deficient or TP53-deficient;BRCA2-deficient mammary epithelial cells (13,818 genomes), and to primary triple-negative breast cancer (TNBC) and high-grade serous ovarian cancer (HGSC) cells (22,057 genomes), we identify three distinct 'foreground' mutational patterns that are defined by cell-to-cell structural variation. Cell- and clone-specific high-level amplifications, parallel haplotype-specific copy number alterations and copy number segment length variation (serrate structural variations) had measurable phenotypic and evolutionary consequences. In TNBC and HGSC, clone-specific high-level amplifications in known oncogenes were highly prevalent in tumours bearing fold-back inversions, relative to tumours with homologous recombination deficiency, and were associated with increased clone-to-clone phenotypic variation. Parallel haplotype-specific alterations were also commonly observed, leading to phylogenetic evolutionary diversity and clone-specific mono-allelic expression. Serrate variants were increased in tumours with fold-back inversions and were highly correlated with increased genomic diversity of cellular populations. Together, our findings show that cell-to-cell structural variation contributes to the origins of phenotypic and evolutionary diversity in TNBC and HGSC, and provide insight into the genomic and mutational states of individual cancer cells.

Adoptive tumor infiltrating lymphocytes cell therapy for cervical cancer

Cervical cancer is one of the most common malignancies among females. As a virus-related cancer, cervical cancer has attracted a lot of attention to develop virus-targeted immune therapy, including vaccine and adoptive immune cell therapy (ACT). Adoptive tumor infiltrating lymphocytes (TILs) cell therapy has been found to be able to control advanced disease progression in some cervical cancer patients who have received several lines of treatment in a pilot clinical trial. In addition, sustainable therapeutic effect has been identified in some cases. The safety risks of TIL therapy for patients are minimal or at least manageable. In this review, we focused on the versatility of TILs and tried to summarize potential strategies to improve the therapeutic effect of TILs and discuss related perspectives.

Establishment of an ovarian cancer omentum metastasis-related prognostic model by integrated analysis of scRNA-seq and bulk RNA-seq

OBJECTIVE

Ovarian cancer has the highest mortality rate among gynecological malignant tumors, and it preferentially metastasizes to omental tissue, leading to intestinal obstruction and death. scRNA-seq is a powerful technique to reveal tumor heterogeneity. Analyzing omentum metastasis of ovarian cancer at the single-cell level may be more conducive to exploring and understanding omentum metastasis and prognosis of ovarian cancer at the cellular function and genetic levels.

METHODS

The omentum metastasis site scRNA-seq data of GSE147082 were acquired from the GEO (Gene Expression Omnibus) database, and single cells were clustered by the Seruat package and annotated by the SingleR package. Cell differentiation trajectories were reconstructed through the monocle package. The ovarian cancer microarray data of GSE132342 were downloaded from GEO and were clustered by using the ConsensusClusterPlus package into omentum metastasis-associated clusters according to the marker genes gained from single-cell differentiation trajectory analysis. The tumor microenvironment (TME) and immune infiltration differences between clusters were analyzed by the estimate and CIBERSORT packages. The expression matrix of genes used to cluster GSE132342 patients was extracted from bulk RNA-seq data of TCGA-OV (The Cancer Genome Atlas ovarian cancer), and least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were performed to establish an omentum metastasis-associated gene (OMAG) signature. The signature was then tested by GSE132342 data. Finally, the clinicopathological characteristics of TCGA-OV were screened by univariate and multivariate Cox regression analysis to draw the nomogram.

RESULTS

A total of 9885 cells from 6 patients were clustered into 18 cell clusters and annotated into 14 cell types. Reconstruction of differentiation trajectories divided the cells into 5 branches, and a total of 781 cell trajectory-related characteristic genes were obtained. A total of 3769 patients in GSE132342 were subtyped into 3 clusters by 74 cell trajectory-related characteristic genes. Kaplan-Meier (K-M) survival analysis showed that the prognosis of cluster 2 was the worst, P < 0.001. The TME analysis showed that the ESTIMATE score and stromal score in cluster 2 were significantly higher than those in the other two clusters, P < 0.001. The immune infiltration analysis showed differences in the fraction of 8 immune cells among the 3 clusters, P < 0.05. The expression data of 74 genes used for GEO clustering were extracted from 379 patients in TCGA-OV, and combined with survival information, 10 candidates for OMAGs were filtered by LASSO. By using multivariate Cox regression, the 6-OMAGs signature was established as RiskScore = 0.307*TIMP3 + 3.516*FBN1-0.109*IGKC + 0.209*RPL21 + 0.870*UCHL1 + 0.365*RARRES1. Taking TCGA-OV as the training set and GSE132342 as the test set, receiver operating characteristic (ROC) curves were drawn to verify the prognostic value of 6-OMAGs. Screened by univariate and multivariate Cox regression analysis, 3 (age, cancer status, primary therapy outcome) of 5 clinicopathological characteristics were used to construct the nomogram combined with risk score.

CONCLUSION

We constructed an ovarian cancer prognostic model related to omentum metastasis composed of 6-OMAGs and 3 clinicopathological features and analyzed the potential mechanism of these 6-OMAGs in ovarian cancer omental metastasis.

Very large hidden genetic diversity in one single tumor: evidence for tumors-in-tumor

Despite the concern of within-tumor genetic diversity, this diversity is in fact limited by the kinship among cells in the tumor. Indeed, genomic studies have amply supported the 'Nowell dogma' whereby cells of the same tumor descend from a single progenitor cell. In parallel, genomic data also suggest that the diversity could be >10-fold larger if tumor cells are of multiple origins. We develop an evolutionary hypothesis that a single tumor may often harbor multiple cell clones of independent origins, but only one would be large enough to be detected. To test the hypothesis, we search for independent tumors within a larger one (or tumors-in-tumor). Very high density sampling was done on two cases of colon tumors. Case 1 indeed has 13 independent clones of disparate sizes, many having heavy mutation burdens and potentially highly tumorigenic. In Case 2, despite a very intensive search, only two small independent clones could be found. The two cases show very similar movements and metastasis of the dominant clone. Cells initially move actively in the expanding tumor but become nearly immobile in late stages. In conclusion, tumors-in-tumor are plausible but could be very demanding to find. Despite their small sizes, they can enhance the within-tumor diversity by orders of magnitude. Such increases may contribute to the missing genetic diversity associated with the resistance to cancer therapy.

Immunobiology of high-grade serous ovarian cancer: lessons for clinical translation

Treatment of high-grade serous ovarian cancer (HGSOC) remains challenging. Although HGSOC can potentially be responsive to immunotherapy owing to endogenous immunity at the molecular or T cell level, immunotherapy for this disease has fallen short of expectations to date. This Review proposes a working classification for HGSOC based on the presence or absence of intraepithelial T cells, and elaborates the putative mechanisms that give rise to such immunophenotypes. These differences might explain the failures of existing immunotherapies, and suggest that rational therapeutic approaches tailored to each immunophenotype might meet with improved success. In T cell-inflamed tumours, treatment could focus on mobilizing pre-existing immunity and strengthening the activation of T cells embedded in intraepithelial tumour myeloid niches. Conversely, in immune-excluded and immune-desert tumours, treatment could focus on restoring inflammation by reprogramming myeloid cells, stromal cells and vascular epithelial cells. Poly(ADP-ribose) polymerase (PARP) inhibitors, low-dose radiotherapy, epigenetic drugs and anti-angiogenesis therapy are among the tools available to restore T cell infiltration in HGSOC tumours and could be implemented in combination with vaccines and redirected T cells.

Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer

Chromosomal instability is a major challenge to patient stratification and targeted drug development for high-grade serous ovarian carcinoma (HGSOC). Here we show that somatic copy number alterations (SCNAs) in frequently amplified HGSOC cancer genes significantly correlate with gene expression and methylation status. We identify five prevalent clonal driver SCNAs (chromosomal amplifications encompassing MYC, PIK3CA, CCNE1, KRAS and TERT) from multi-regional HGSOC data and reason that their strong selection should prioritise them as key biomarkers for targeted therapies. We use primary HGSOC spheroid models to test interactions between in vitro targeted therapy and SCNAs. MYC chromosomal copy number is associated with in-vitro and clinical response to paclitaxel and in-vitro response to mTORC1/2 inhibition. Activation of the mTOR survival pathway in the context of MYC-amplified HGSOC is statistically associated with increased prevalence of SCNAs in genes from the PI3K pathway. Co-occurrence of amplifications in MYC and genes from the PI3K pathway is independently observed in squamous lung cancer and triple negative breast cancer. In this work, we show that identifying co-occurrence of clonal driver SCNA genes could be used to tailor therapeutics for precision medicine.

Enhancing therapeutic anti-cancer responses by combining immune checkpoint and tyrosine kinase inhibition

Over the past decade, immune checkpoint inhibitor (ICI) therapy has been established as the standard of care for many types of cancer, but the strategies employed have continued to evolve. Recently, much clinical focus has been on combining targeted therapies with ICI for the purpose of manipulating the immune setpoint. The latter concept describes the equilibrium between factors that promote and those that suppress anti-cancer immunity. Besides tumor mutational load and other cancer cell-intrinsic determinants, the immune setpoint is also governed by the cells of the tumor microenvironment and how they are coerced by cancer cells to support the survival and growth of the tumor. These regulatory mechanisms provide therapeutic opportunities to intervene and reduce immune suppression via application of small molecule inhibitors and antibody-based therapies against (receptor) tyrosine kinases and thereby improve the response to ICIs. This article reviews how tyrosine kinase signaling in the tumor microenvironment can promote immune suppression and highlights how therapeutic strategies directed against specific tyrosine kinases can be used to lower the immune setpoint and elicit more effective anti-tumor immunity.

Research progress of neoantigens in gynecologic cancers

The incidence and mortality of gynecological cancers have increased over the past decade. In the absence of effective treatment strategies, many advanced patients develop resistance to conventional therapies and have poor prognosis. Neoantigens have emerged as a novel tumor-specific antigen (TSA) that arises from genomic mutations in tumor cells. With higher immunogenicity than tumor-associated antigens (TAA), they have no risk of developing autoimmune response, leading them an attractive candidate for tumor therapeutic vaccines. With the development of next-generation sequencing (NGS) technology, the identification of neoantigens has been gradually improved, and the scope of application of neoantigen vaccines has continued to expand. Combined with other therapies such as immune-checkpoint inhibitors (ICIs) or adoptive cell therapy (ACT), the application of neoantigen in gynecological cancers has extended to clinical practice. Here, we reviewed the preclinical and clinical studies of neoantigens in gynecological cancers.

Paving the Way to Solid Tumors: Challenges and Strategies for Adoptively Transferred Transgenic T Cells in the Tumor Microenvironment

T cells are important players in the antitumor immune response. Over the past few years, the adoptive transfer of genetically modified, autologous T cells-specifically redirected toward the tumor by expressing either a T cell receptor (TCR) or a chimeric antigen receptor (CAR)-has been adopted for use in the clinic. At the moment, the therapeutic application of CD19- and, increasingly, BCMA-targeting-engineered CAR-T cells have been approved and have yielded partly impressive results in hematologic malignancies. However, employing transgenic T cells for the treatment of solid tumors remains more troublesome, and numerous hurdles within the highly immunosuppressive tumor microenvironment (TME) need to be overcome to achieve tumor control. In this review, we focused on the challenges that these therapies must face on three different levels: infiltrating the tumor, exerting efficient antitumor activity, and overcoming T cell exhaustion and dysfunction. We aimed to discuss different options to pave the way for potent transgenic T cell-mediated tumor rejection by engineering either the TME or the transgenic T cell itself, which responds to the environment.

HPV-Positive and -Negative Cervical Cancers Are Immunologically Distinct

Although infection with human papillomavirus (HPV) is associated with nearly all cervical cancers (CC), a small proportion are HPV-negative. Recently, it has become clear that HPV-negative CC represent a distinct disease phenotype compared to HPV-positive disease and exhibit increased mortality. In addition, variations between different HPV types associated with CC have been linked to altered molecular pathology and prognosis. We compared the immune microenvironments of CC caused by HPV α9 species (HPV16-like), HPV α7 species (HPV18-like) and HPV-negative disease. HPV-negative CC appeared distinct from other subtypes, with greatly reduced levels of lymphocyte infiltration compared to either HPV α9 or α7 CC. Besides reduced levels of markers indicative of B, T, and NK lymphocytes, the expression of T-cell effector molecules, activation/exhaustion markers, and T-cell receptor diversity were also significantly lower in HPV-negative CC. Interestingly, HPV-negative CC expressed much higher levels of potential neoantigens than HPV-positive CC. These results identify profound differences between the immune landscape of HPV-positive and HPV-negative CC as well as modest differences between HPV α9 and α7 CC. These differences may contribute to altered patient outcomes between HPV-negative and HPV-positive CC and potentially between CC associated with different HPV types.

The impact of neoadjuvant chemotherapy on the tumor microenvironment in advanced high-grade serous carcinoma

High-grade serous ovarian, fallopian tube or peritoneal carcinoma is an aggressive subtype of ovarian cancer that frequently develops resistance to chemotherapy. It remains contested whether the resistance is caused by the acquisition of novel molecular aberrations or alternatively through the selection of rare pre-existing tumor clones. To address this question, we applied single-cell RNA sequencing to depict the tumor landscape of 6 samples from a single case of advanced high-grade serous fallopian tube carcinoma during neoadjuvant chemotherapy (NACT). We analyzed a total of 32,079 single cells, with 17,249 cells derived from the pre-NACT multisite tumor tissue samples and 14,830 cells derived from the post-NACT multisite tumor tissue samples. We identified the diverse properties of the tumor, immune and stromal cell types between the pre-NACT and post-NACT tumors. The malignant epithelial cells displayed a high degree of intratumor heterogeneity in response to NACT. We showed that the primary resistant clone (clone 63) epithelial genotype was already present in the pre-NACT tumors, and was adaptively enriched after NACT. This clone 63 was correlated with a poor clinical prognosis. Furthermore, single-cell analysis of CD4⁺ T cells demonstrated that IL2RAhi-CCL22+-Tregs were selectively enriched in post-NACT tumors. Interestingly, this Treg subtype could recruit and enrich themselves through secreting the CCL22-CCR1 combination in pre-NACT and post-NACT tumors, and further express CD274 to suppress other CD4 and CD8 T cells through a CD274-PDCD1 axis in the post-NACT tumors, and this predicted an immunosuppressive state after NACT. Overall, our results provide important evidence for the adaptive resistance theory of HGSC, and for the potential development of therapeutic strategies to treat HGSC and improve the survival of patients with HGSC.

"Fateful" encounter: Lineage tracing meets phylogeny to unravel mysteries of cancer progression

In a recent issue of Cell, Yang et al. utilize evolvable cellular barcodes to investigate the evolutionary trajectories of murine lung adenocarcinoma. Reconstructing the life histories of these tumors based on cellular barcodes reveals stringent selection and phenotypic differences across subclonal lineages.

Chromosome instability and aneuploidy as context-dependent activators or inhibitors of antitumor immunity

Chromosome instability (CIN) and its major consequence, aneuploidy, are hallmarks of human cancers. In addition to imposing fitness costs on tumor cells through several cell-intrinsic mechanisms, CIN/aneuploidy also provokes an antitumor immune response. However, as the major contributor to genomic instability, intratumor heterogeneity generated by CIN/aneuploidy helps tumor cells to evolve methods to overcome the antitumor role of the immune system or even convert the immune system to be tumor-promoting. Although the interplay between CIN/aneuploidy and the immune system is complex and context-dependent, understanding this interplay is essential for the success of immunotherapy in tumors exhibiting CIN/aneuploidy, regardless of whether the efficacy of immunotherapy is increased by combination with strategies to promote CIN/aneuploidy or by designing immunotherapies to target CIN/aneuploidy directly.

Intratumor Heterogeneity and Antitumor Immunity Shape One Another Bidirectionally

Over the last decade, it has become clear that the genomic landscapes of tumors profoundly impact their immunogenicity and how tumor cells interact with immune cells. Whereas past discoveries mainly focused on the interplay between tumor immunogenicity and tumor mutational burden (TMB), under the assumption that a higher mutation load would give rise to a better patient response to immune checkpoint blockade therapies, we and others have underlined intratumor heterogeneity (ITH) as an important determinant of the magnitude of the antitumor response and the nature of the tumor microenvironment. In this review, we define TMB versus ITH and how the two factors are being inferred from data, examine key findings in the cancer immunogenomics literature deciphering the complex cross-talk between TMB, ITH, and antitumor immunity in human cancers and in vivo models, and discuss the mutual influence of ITH and immunity-how the antitumor response can give rise to tumors with higher ITH, and how higher ITH can put shackles on the antitumor response.

Macrophage-derived CCL23 upregulates expression of T-cell exhaustion markers in ovarian cancer

BACKGROUND

Macrophages are an important component of the tumour immune microenvironment (TME) and can promote tumour growth and metastasis. Macrophage-secreted chemokine-ligand-23 (CCL23) induces ovarian cancer cell migration via chemokine-receptor 1 (CCR1). However, the effect of CCL23 on other immune cells in the TME is unknown.

METHODS

CCL23 levels were measured by ELISA. The expression of surface markers in exhaustion assays was quantified by flow cytometry. Signalling pathways were identified by phosphokinase array and validated by western blot.

RESULTS

Ascites from patients with high-grade serous ovarian cancer (HGSC) contain high levels of CCL23. Similarly, significantly higher CCL23 levels were found in plasma from HGSC patients compared to healthy individuals. RNA-seq analysis of ovarian cancer tissues from TCGA showed that expression of CCL23 correlated with the presence of macrophages. In tissues with high levels of CCL23 and macrophage content, the fraction of CD8 + T cells expressing exhaustion markers CTLA-4 and PD-1 were significantly higher compared to low-level CCL23 tissues. In vitro, CCL23 induced upregulation of immune checkpoint proteins on CD8 + T cells, including CTLA-4, TIGIT, TIM-3 and LAG-3 via phosphorylation of GSK3β in CD8 + T cells.

CONCLUSIONS

Our data suggest that CCL23 produced by macrophages contributes to the immune-suppressive TME in ovarian cancer by inducing an exhausted T-cell phenotype.

Predictive biomarker for surgical outcome in patients with advanced primary high-grade serous ovarian cancer. Are we there yet? An analysis of the prospective biobank for ovarian cancer

BACKGROUND

High-grade serous ovarian cancer (HGSOC) is the most common subtype of ovarian cancer and is associated with high mortality rates. Surgical outcome is one of the most important prognostic factors. There are no valid biomarkers to identify which patients may benefit from a primary debulking approach.

OBJECTIVE

Our study aimed to discover and validate a predictive panel for surgical outcome of residual tumor mass after first-line debulking surgery.

STUDY DESIGN

Firstly, "In silico" analysis of publicly available datasets identified 200 genes as predictors for surgical outcome. The top selected genes were then validated using the novel Nanostring method, which was applied for the first time for this particular research objective. 225 primary ovarian cancer patients with well annotated clinical data and a complete debulking rate of 60% were compiled for a clinical cohort. The 14 best rated genes were then validated through the cohort, using immunohistochemistry testing. Lastly, we used our biomarker expression data to predict the presence of miliary carcinomatosis patterns.

RESULTS

The Nanostring analysis identified 37 genes differentially expressed between optimal and suboptimal debulked patients (p < 0.05). The immunohistochemistry validated the top 14 genes, reaching an AUC Ø0.650. The analysis for the prediction of miliary carcinomatosis patterns reached an AUC of Ø0.797.

CONCLUSION

The tissue-based biomarkers in our analysis could not reliably predict post-operative residual tumor. Patient and non-patient-associated co-factors, surgical skills, and center experience remain the main determining factors when considering the surgical outcome at primary debulking in high-grade serous ovarian cancer patients.

Glioma progression is shaped by genetic evolution and microenvironment interactions

The factors driving therapy resistance in diffuse glioma remain poorly understood. To identify treatment-associated cellular and genetic changes, we analyzed RNA and/or DNA sequencing data from the temporally separated tumor pairs of 304 adult patients with isocitrate dehydrogenase (IDH)-wild-type and IDH-mutant glioma. Tumors recurred in distinct manners that were dependent on IDH mutation status and attributable to changes in histological feature composition, somatic alterations, and microenvironment interactions. Hypermutation and acquired CDKN2A deletions were associated with an increase in proliferating neoplastic cells at recurrence in both glioma subtypes, reflecting active tumor growth. IDH-wild-type tumors were more invasive at recurrence, and their neoplastic cells exhibited increased expression of neuronal signaling programs that reflected a possible role for neuronal interactions in promoting glioma progression. Mesenchymal transition was associated with the presence of a myeloid cell state defined by specific ligand-receptor interactions with neoplastic cells. Collectively, these recurrence-associated phenotypes represent potential targets to alter disease progression.

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.

Chromosomal instability as a source of genomic plasticity

Chromosomal instability (CIN) is a hallmark of the most aggressive malignancies. Features of these tumors include complex genomic rearrangements, the presence of mis-segregated chromosomes in micronuclei, and extrachromosomal DNA (ecDNA) formation. Here, we review the development of CIN, and examine CIN in the context of cancer evolution, tumor genomic evolution, and therapeutic resistance. We also discuss the role of whole-genome duplications, breakage-fusion-bridge cycles, ecDNA or double minutes in gene amplification promoting tumor evolution.

Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer

Patients with high-grade serous ovarian cancer suffer poor prognosis and variable response to treatment. Known prognostic factors for this disease include homologous recombination deficiency status, age, pathological stage and residual disease status after debulking surgery. Recent work has highlighted important prognostic information captured in computed tomography and histopathological specimens, which can be exploited through machine learning. However, little is known about the capacity of combining features from these disparate sources to improve prediction of treatment response. Here, we assembled a multimodal dataset of 444 patients with primarily late-stage high-grade serous ovarian cancer and discovered quantitative features, such as tumor nuclear size on staining with hematoxylin and eosin and omental texture on contrast-enhanced computed tomography, associated with prognosis. We found that these features contributed complementary prognostic information relative to one another and clinicogenomic features. By fusing histopathological, radiologic and clinicogenomic machine-learning models, we demonstrate a promising path toward improved risk stratification of patients with cancer through multimodal data integration.

Therapy resistance: opportunities created by adaptive responses to targeted therapies in cancer

Normal cells explore multiple states to survive stresses encountered during development and self-renewal as well as environmental stresses such as starvation, DNA damage, toxins or infection. Cancer cells co-opt normal stress mitigation pathways to survive stresses that accompany tumour initiation, progression, metastasis and immune evasion. Cancer therapies accentuate cancer cell stresses and invoke rapid non-genomic stress mitigation processes that maintain cell viability and thus represent key targetable resistance mechanisms. In this Review, we describe mechanisms by which tumour ecosystems, including cancer cells, immune cells and stroma, adapt to therapeutic stresses and describe three different approaches to exploit stress mitigation processes: (1) interdict stress mitigation to induce cell death; (2) increase stress to induce cellular catastrophe; and (3) exploit emergent vulnerabilities in cancer cells and cells of the tumour microenvironment. We review challenges associated with tumour heterogeneity, prioritizing actionable adaptive responses for optimal therapeutic outcomes, and development of an integrative framework to identify and target vulnerabilities that arise from adaptive responses and engagement of stress mitigation pathways. Finally, we discuss the need to monitor adaptive responses across multiple scales and translation of combination therapies designed to take advantage of adaptive responses and stress mitigation pathways to the clinic.

Immune Mechanisms of Resistance to Cediranib in Ovarian Cancer

This article investigates mechanisms of resistance to the VEGF receptor inhibitor cediranib in high-grade serous ovarian cancer (HGSOC), and defines rational combination therapies. We used three different syngeneic orthotopic mouse HGSOC models that replicated the human tumor microenvironment (TME). After 4 to 5 weeks treatment of established tumors, cediranib had antitumor activity with increased tumor T-cell infiltrates and alterations in myeloid cells. However, continued cediranib treatment did not change overall survival or the immune microenvironment in two of the three models. Moreover, treated mice developed additional peritoneal metastases not seen in controls. Cediranib-resistant tumors had intrinsically high levels of IL6 and JAK/STAT signaling and treatment increased endothelial STAT3 activation. Combination of cediranib with a murine anti-IL6 antibody was superior to monotherapy, increasing mouse survival, reducing blood vessel density, and pSTAT3, with increased T-cell infiltrates in both models. In a third HGSOC model, that had lower inherent IL6 JAK/STAT3 signaling in the TME but high programmed cell death protein 1 (PD-1) signaling, long-term cediranib treatment significantly increased overall survival. When the mice eventually relapsed, pSTAT3 was still reduced in the tumors but there were high levels of immune cell PD-1 and Programmed death-ligand 1. Combining cediranib with an anti-PD-1 antibody was superior to monotherapy in this model, increasing T cells and decreasing blood vessel densities. Bioinformatics analysis of two human HGSOC transcriptional datasets revealed distinct clusters of tumors with IL6 and PD-1 pathway expression patterns that replicated the mouse tumors. Combination of anti-IL6 or anti-PD-1 in these patients may increase activity of VEGFR inhibitors and prolong disease-free survival.

Neoantigen quality predicts immunoediting in survivors of pancreatic cancer

Cancer immunoediting¹ is a hallmark of cancer² that predicts that lymphocytes kill more immunogenic cancer cells to cause less immunogenic clones to dominate a population. Although proven in mice^1,3, whether immunoediting occurs naturally in human cancers remains unclear. Here, to address this, we investigate how 70 human pancreatic cancers evolved over 10 years. We find that, despite having more time to accumulate mutations, rare long-term survivors of pancreatic cancer who have stronger T cell activity in primary tumours develop genetically less heterogeneous recurrent tumours with fewer immunogenic mutations (neoantigens). To quantify whether immunoediting underlies these observations, we infer that a neoantigen is immunogenic (high-quality) by two features—‘non-selfness’  based on neoantigen similarity to known antigens^4,5, and ‘selfness’  based on the antigenic distance required for a neoantigen to differentially bind to the MHC or activate a T cell compared with its wild-type peptide. Using these features, we estimate cancer clone fitness as the aggregate cost of T cells recognizing high-quality neoantigens offset by gains from oncogenic mutations. With this model, we predict the clonal evolution of tumours to reveal that long-term survivors of pancreatic cancer develop recurrent tumours with fewer high-quality neoantigens. Thus, we submit evidence that that the human immune system naturally edits neoantigens. Furthermore, we present a model to predict how immune pressure induces cancer cell populations to evolve over time. More broadly, our results argue that the immune system fundamentally surveils host genetic changes to suppress cancer.

The human immune system naturally edits cancers of high-quality neoantigens.

Human liver single nucleus and single cell RNA sequencing identify a hepatocellular carcinoma-associated cell-type affecting survival

BACKGROUND

Hepatocellular carcinoma (HCC) is a common primary liver cancer with poor overall survival. We hypothesized that there are HCC-associated cell-types that impact patient survival.

METHODS

We combined liver single nucleus (snRNA-seq), single cell (scRNA-seq), and bulk RNA-sequencing (RNA-seq) data to search for cell-type differences in HCC. To first identify cell-types in HCC, adjacent non-tumor tissue, and normal liver, we integrated single-cell level data from a healthy liver cohort (n = 9 non-HCC samples) collected in the Strasbourg University Hospital; an HCC cohort (n = 1 non-HCC, n = 14 HCC-tumor, and n = 14 adjacent non-tumor samples) collected in the Singapore General Hospital and National University; and another HCC cohort (n = 3 HCC-tumor and n = 3 adjacent non-tumor samples) collected in the Dumont-UCLA Liver Cancer Center. We then leveraged these single cell level data to decompose the cell-types in liver bulk RNA-seq data from HCC patients' tumor (n = 361) and adjacent non-tumor tissue (n = 49) from the Cancer Genome Atlas (TCGA) multi-center cohort. For replication, we decomposed 221 HCC and 209 adjacent non-tumor liver microarray samples from the Liver Cancer Institute (LCI) cohort collected by the Liver Cancer Institute and Zhongshan Hospital of Fudan University.

RESULTS

We discovered a tumor-associated proliferative cell-type, Prol (80.4% tumor cells), enriched for cell cycle and mitosis genes. In the liver bulk tissue from the TCGA cohort, the proportion of the Prol cell-type is significantly increased in HCC and associates with a worse overall survival. Independently from our decomposition analysis, we reciprocally show that Prol nuclei/cells significantly over-express both tumor-elevated and survival-decreasing genes obtained from the bulk tissue. Our replication analysis in the LCI cohort confirmed that an increased estimated proportion of the Prol cell-type in HCC is a significant marker for a shorter overall survival. Finally, we show that somatic mutations in the tumor suppressor genes TP53 and RB1 are linked to an increase of the Prol cell-type in HCC.

CONCLUSIONS

By integrating liver single cell, single nucleus, and bulk expression data from multiple cohorts we identified a proliferating cell-type (Prol) enriched in HCC tumors, associated with a decreased overall survival, and linked to TP53 and RB1 somatic mutations.

Single-cell sequencing: a promising approach for uncovering the mechanisms of tumor metastasis

Single-cell sequencing (SCS) is an emerging high-throughput technology that can be used to study the genomics, transcriptomics, and epigenetics at a single cell level. SCS is widely used in the diagnosis and treatment of various diseases, including cancer. Over the years, SCS has gradually become an effective clinical tool for the exploration of tumor metastasis mechanisms and the development of treatment strategies. Currently, SCS can be used not only to analyze metastasis-related malignant biological characteristics, such as tumor heterogeneity, drug resistance, and microenvironment, but also to construct metastasis-related cell maps for predicting and monitoring the dynamics of metastasis. SCS is also used to identify therapeutic targets related to metastasis as it provides insights into the distribution of tumor cell subsets and gene expression differences between primary and metastatic tumors. Additionally, SCS techniques in combination with artificial intelligence (AI) are used in liquid biopsy to identify circulating tumor cells (CTCs), thereby providing a novel strategy for treating tumor metastasis. In this review, we summarize the potential applications of SCS in the field of tumor metastasis and discuss the prospects and limitations of SCS to provide a theoretical basis for finding therapeutic targets and mechanisms of metastasis.

Tumour immunotherapy: lessons from predator-prey theory

With the burgeoning use of immune-based treatments for cancer, never has there been a greater need to understand the tumour microenvironment within which immune cells function and how it can be perturbed to inhibit tumour growth. Yet, current challenges in identifying optimal combinations of immunotherapies and engineering new cell-based therapies highlight the limitations of conventional paradigms for the study of the tumour microenvironment. Ecology has a rich history of studying predator-prey dynamics to discern factors that drive prey to extinction. Here, we describe the basic tenets of predator-prey theory as applied to 'predation' by immune cells and the 'extinction' of cancer cells. Our synthesis reveals fundamental mechanisms by which antitumour immunity might fail in sometimes counterintuitive ways and provides a fresh yet evidence-based framework to better understand and therapeutically target the immune-cancer interface.

Paired primary and metastatic lesions of patients with ipilimumab-treated melanoma: high variation in lymphocyte infiltration and HLA-ABC expression whereas tumor mutational load is similar and correlates with clinical outcome

BACKGROUND

Immune checkpoint inhibitors (ICI) can lead to long-term responses in patients with metastatic melanoma. Still many patients with melanoma are intrinsically resistant or acquire secondary resistance. Previous studies have used primary or metastatic tumor tissue for biomarker assessment. Especially in melanoma, metastatic lesions are often present at different anatomical sites such as skin, lymph nodes, and visceral organs. The anatomical site may directly affect the tumor microenvironment (TME). To evaluate the impact of tumor evolution on the TME and on ICI treatment outcome, we directly compared paired primary and metastatic melanoma lesions for tumor mutational burden (TMB), HLA-ABC status, and tumor infiltrating lymphocytes (TILs) of patients that received ipilimumab.

METHODS

TMB was analyzed by sequencing primary and metastatic melanoma lesions using the TruSight Oncology 500 assay. Tumor tissues were subjected to multiplex immunohistochemistry to assess HLA-ABC status and for the detection of TIL subsets (B cells, cytotoxic T cells, helper T cells, and regulatory T cells), by using a machine-learning algorithm.

RESULTS

While we observed a very good agreement between TMB of matched primary and metastatic melanoma lesions (intraclass coefficient=0.921), such association was absent for HLA-ABC status, TIL density, and subsets thereof. Interestingly, analyses of different metastatic melanoma lesions within a single patient revealed that TIL density and composition agreed remarkably well, rejecting the hypothesis that the TME of different anatomical sites affects TIL infiltration. Similarly, the HLA-ABC status between different metastatic lesions within patients was also comparable. Furthermore, high TMB, of either primary or metastatic melanoma tissue, directly correlated with response to ipilimumab, whereas lymphocyte density or composition did not. Loss of HLA-ABC in the metastatic lesion correlated to a shorter progression-free survival on ipilimumab.

CONCLUSIONS

We confirm the link between TMB and HLA-ABC status and the response to ipilimumab-based immunotherapy in melanoma, but no correlation was found for TIL density, neither in primary nor metastatic lesions. Our finding that TMB between paired primary and metastatic melanoma lesions is highly stable, demonstrates its independency of the time point and location of acquisition. TIL and HLA-ABC status in metastatic lesions of different anatomical sites are highly similar within an individual patient.

Heterogeneity of the tumor immune microenvironment and its clinical relevance

During the course of tumorigenesis and subsequent metastasis, malignant cells gradually diversify and become more heterogeneous. Consequently, the tumor mass might be infiltrated by diverse immune-related components, including the cytokine/chemokine environment, cytotoxic activity, or immunosuppressive elements. This immunological heterogeneity is universally presented spatially or varies temporally along with tumor evolution or therapeutic intervention across almost all solid tumors. The heterogeneity of anti-tumor immunity shows a profound association with the progression of disease and responsiveness to treatment, particularly in the realm of immunotherapy. Therefore, an accurate understanding of tumor immunological heterogeneity is essential for the development of effective therapies. Facilitated by multi-regional and -omics sequencing, single cell sequencing, and longitudinal liquid biopsy approaches, recent studies have demonstrated the potential to investigate the complexity of immunological heterogeneity of the tumors and its clinical relevance in immunotherapy. Here, we aimed to review the mechanism underlying the heterogeneity of the immune microenvironment. We also explored how clinical assessments of tumor heterogeneity might facilitate the development of more effective personalized therapies.

The STING pathway: Therapeutic vulnerabilities in ovarian cancer

Ovarian cancer is the leading cause of mortality due to gynecologic malignancy. The majority of women diagnosed with the most common subtype, high-grade serous ovarian carcinoma (HGSC), develop resistance to conventional therapies despite initial response to treatment. HGSC tumors displaying DNA damage repair (DDR) gene deficiency and high chromosomal instability mainly associate with higher cytotoxic immune cell infiltration and expression of genes associated with these immune pathways. Despite the high level of immune infiltration observed, the majority of patients with HGSC have not benefited from immunomodulatory treatments as the mechanistic basis of this infiltration is unclear. This lack of response can be primarily attributed to heterogeneity at the levels of both cancer cell genetic alterations and the tumour immune microenvironment. Strategies to enhance anti-tumour immunity have been investigated in ovarian cancer, of which interferon activating therapies present as an attractive option. Of the several type I interferon (IFN-1) stimulating therapies, exogenously activating the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway is emerging as a promising avenue. Herein, we highlight our current understanding of how constitutive and induced cGAS-STING pathway activation influences the ovarian tumour microenvironment. We further elaborate on the links between the genomic alterations prevalent in ovarian tumours and how the resultant immune phenotypes can make them more susceptible to exogenous STING pathway activation and potentiate immune-mediated killing of cancer cells. The therapeutic potential of cGAS-STING pathway activation in ovarian cancer and factors implicating treatment outcomes are discussed, providing a rationale for future combinatorial treatment approaches on the backbone of chemotherapy.

Identification of Neoantigens in Cancer Cells as Targets for Immunotherapy

The clinical benefits of immune checkpoint blockage (ICB) therapy have been widely reported. In patients with cancer, researchers have demonstrated the clinical potential of antitumor cytotoxic T cells that can be reinvigorated or enhanced by ICB. Compared to self-antigens, neoantigens derived from tumor somatic mutations are believed to be ideal immune targets in tumors. Candidate tumor neoantigens can be identified through immunogenomic or immunopeptidomic approaches. Identification of neoantigens has revealed several points of the clinical relevance. For instance, tumor mutation burden (TMB) may be an indicator of immunotherapy. In various cancers, mutation rates accompanying neoantigen loads may be indicative of immunotherapy. Furthermore, mismatch repair-deficient tumors can be eradicated by T cells in ICB treatment. Hence, immunotherapies using vaccines or adoptive T-cell transfer targeting neoantigens are potential innovative strategies. However, significant efforts are required to identify the optimal epitopes. In this review, we summarize the recent progress in the identification of neoantigens and discussed preclinical and clinical studies based on neoantigens. We also discuss the issues remaining to be addressed before clinical applications of these new therapeutic strategies can be materialized.

Natural Killer Cells: the Missing Link in Effective Treatment for High-Grade Serous Ovarian Carcinoma

OPINION STATEMENT

Ovarian cancer (OC), especially high-grade serous cancer (HGSC), is a highly heterogeneous malignancy with limited options for curative treatment and a high frequency of relapse. Interactions between OC and the immune system may permit immunoediting and immune escape, and current standard of care therapies can influence immune cell infiltration and function within the tumor microenvironment. Natural killer (NK) cells are involved in cancer immunosurveillance and immunoediting and can be activated by therapy, but deliberate approaches to maximize NK cell reactivity for treatment of HGSC are in their infancy. NK cells may be the ideal target for immunotherapy of HGSC. The diverse functions of NK cells, and their established roles in immunosurveillance, make them attractive candidates for more precise and effective HGSC treatment. NK cells' functional capabilities differ because of variation in receptor expression and genetics, with meaningful impacts on their anticancer activity. Studying HGSC:NK cell interactions will define the features that predict the best outcomes for patients with the disease, but the highly diverse nature of HGSC will likely require combination therapies or approaches to simultaneously target multiple, co-existing features of the tumor to avoid tumor escape and relapse. We expect that the ideal therapy will enable NK cell infiltration and activity, reverse immunosuppression within the tumor microenvironment, and enable effector functions against the diverse subpopulations that comprise HGSC.

Eradicating tumor in a recurrent cervical cancer patient with autologous tumor-infiltrating lymphocytes and a modified lymphodepleting regimen

Tumor-infiltrating lymphocyte (TIL) therapy has shown promising results against several cancers. However, traditional lymphodepleting regimens are severe and represent a major limitation for a more widespread use of TIL. The modified pretreatment strategies may alleviate side effects and demonstrate the persistence of tumor-reactive T cells in the blood. Here, we report a case who was diagnosed recurrent cervical cancer with bladder metastasis. Omitting high dose of IL-2, she received intravenous dose of cyclophosphamide (20 mg/kg) for 3 days, approximately 48 hours before receiving the intravenous infusion of TILs. Half dosage (100 mg) of PD1 antibody was administered with purpose of neutralizing PD1 expressed on T cells surface. She achieved complete response 10 weeks after one-time TILs infusion. Adverse reactions were negligible and safely manageable in a general ward without the need for intervention from intensive care units. Time-course peripheral blood counts and TCR repertoire sequencing demonstrated a robust expansion and long-term persistence of the infused TILs. These results illustrated the potential value of modified lymphodepletion, followed by TILs for the treatment of patients with cervical cancer with local recurrence. Trial registration number, NCT04766320.

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

The majority of high-grade serous ovarian cancers (HGSCs) are deficient in homologous recombination (HR) DNA repair, most commonly due to mutations or hypermethylation of the BRCA1/2 genes. We aimed to discover how BRCA1/2 mutations shape the cellular phenotypes and spatial interactions of the tumor microenvironment. Using a highly multiplex immunofluorescence and image analysis we generate spatial proteomic data for 21 markers in 124,623 single cells from 112 tumor cores originating from 31 tumors with BRCA1/2 mutation (BRCA1/2mut), and from 13 tumors without alterations in HR genes. We identify a phenotypically distinct tumor microenvironment in the BRCA1/2mut tumors with evidence of increased immunosurveillance. Importantly, we report a prognostic role of a proliferative tumor-cell subpopulation, which associates with enhanced spatial tumor-immune interactions by CD8+ and CD4 + T-cells in the BRCA1/2mut tumors. The single-cell spatial landscapes indicate distinct patterns of spatial immunosurveillance with the potential to improve immunotherapeutic strategies and patient stratification in HGSC.

PTEN Loss and BRCA1 Promoter Hypermethylation Negatively Predict for Immunogenicity in BRCA-Deficient Ovarian Cancer

PURPOSE

Ovarian cancers can exhibit a prominent immune infiltrate, but clinical trials have not demonstrated substantive response rates to immune checkpoint blockade monotherapy. We aimed to understand genomic features associated with immunogenicity in BRCA1/2 mutation-associated cancers.

MATERIALS AND METHODS

Using the Cancer Genome Atlas whole-exome sequencing, methylation, and expression data, we analyzed 66 ovarian cancers with either germline or somatic loss of BRCA1/2 and whole-exome sequencing, immunohistochemistry, and CyTOF in 20 ovarian cancers with germline BRCA1/2 pathogenic variants from Penn.

RESULTS

We found two groups of BRCA1/2 ovarian cancers differing in their immunogenicity: (1) 37 tumors significantly enriched for PTEN loss (11, 30%) and BRCA1 promoter-hypermethylated (10, 27%; P = .0016) and (2) PTEN wild-type (28 of 29 tumors) cancers, with the latter group having longer overall survival (OS; P = .0186, median OS not reached v median OS = 66.1 months). BRCA1/2-mutant PTEN loss and BRCA1 promoter-hypermethylated cancers were characterized by the decreased composition of lymphocytes estimated by gene expression (P = .0030), cytolytic index (P = .034), and cytokine expression but higher homologous recombination deficiency scores (P = .00013). Large-scale state transitions were the primary discriminating feature (P = .001); neither mutational burden nor neoantigen burden could explain differences in immunogenicity. In Penn tumors, PTEN loss and high homologous recombination deficiency cancers exhibited fewer CD3+ (P = .05), CD8+ (P = .012), and FOXP3+ (P = .0087) T cells; decreased PRF1 expression (P = .041); and lower immune costimulatory and inhibitory molecule expression.

CONCLUSION

Our study suggests that within ovarian cancers with genetic loss of BRCA1/2 are two subsets exhibiting differential immunogenicity, with lower levels associated with PTEN loss and BRCA hypermethylation. These genomic features of BRCA1/2-associated ovarian cancers may inform considerations around how to optimally deploy immune checkpoint inhibitors in the clinic.

Trabectedin plus durvalumab in patients with advanced pretreated soft tissue sarcoma and ovarian carcinoma (TRAMUNE): an open-label, multicenter phase Ib study

PURPOSE

Trabectedin has shown pre-clinical synergy with immune-checkpoint inhibitors in pre-clinical models.

EXPERIMENTAL DESIGN

TRAMUNE is a phase Ib study investigating trabectedin combined with durvalumab trough a dose-escalation phase and two expansion cohorts (soft tissue sarcoma and ovarian carcinoma). Trabectedin was given at three dose levels (1 mg/m2, 1.2 mg/m2 and 1.5 mg/m2) on day 1, in combination with durvalumab, 1120 mg on day 2, every 3 weeks. The primary endpoints were the recommended phase II dose (RP2D) of trabectedin combined with durvalumab and the objective response rate (ORR) as per RECIST 1.1. The secondary endpoints included safety, 6-month progression-free rate (PFR), progression-free survival (PFS), overall survival, and biomarker analyses.

RESULTS

40 patients were included (dose escalation: n=9; STS cohort: n=16; ovarian cohort: n=15, 80% platinum resistant/refractory). The most frequent toxicities were grade 1-2 fatigue, nausea, neutropenia, and alanine/aspartate aminotransferase increase. One patient experienced a dose-limiting toxicity at dose level 2. Trabectedin at 1.2 mg/m2 was selected as the RP2D. In the STS cohort, 43% of patients experienced tumor shrinkage, the ORR was 7% (95% CI 0.2 - 33.9) and the 6-month PFR 28.6% (95% CI 8.4-58.1). In the ovarian carcinoma cohort, 43% of patients experienced tumor shrinkage, the ORR was 21.4% (95% CI 4.7 - 50.8) and the 6-month PFR 42.9% (95% CI 17.7 - 71.1). Baseline levels of PD-L1 expression and CD8-positive T-cell infiltrates were associated with PFS in ovarian carcinoma patients.

CONCLUSIONS

Combining trabectedin and durvalumab is manageable. Promising activity is observed in platinum-refractory ovarian carcinoma patients.

Quantitative single-cell analysis of immunofluorescence protein multiplex images illustrates biomarker spatial heterogeneity within breast cancer subtypes

BACKGROUND

The extent of cellular heterogeneity in breast cancer could have potential impact on diagnosis and long-term outcome. However, pathology evaluation is limited to biomarker immunohistochemical staining and morphology of the bulk cancer. Inter-cellular heterogeneity of biomarkers is not usually assessed. As an initial evaluation of the extent of breast cancer cellular heterogeneity, we conducted quantitative and spatial imaging of Estrogen Receptor (ER), Progesterone Receptor (PR), Epidermal Growth Factor Receptor-2 (HER2), Ki67, TP53, CDKN1A (P21/WAF1), CDKN2A (P16INK4A), CD8 and CD20 of a tissue microarray (TMA) representing subtypes defined by St. Gallen surrogate classification.

METHODS

Quantitative, single cell-based imaging was conducted using an Immunofluorescence protein multiplexing platform (MxIF) to study protein co-expression signatures and their spatial localization patterns. The range of MxIF intensity values of each protein marker was compared to the respective IHC score for the TMA core. Extent of heterogeneity in spatial neighborhoods was analyzed using co-occurrence matrix and Diversity Index measures.

RESULTS

On the 101 cores from 59 cases studied, diverse expression levels and distributions were observed in MxIF measures of ER and PR among the hormonal receptor-positive tumor cores. As expected, Luminal A-like cancers exhibit higher proportions of cell groups that co-express ER and PR, while Luminal B-like (HER2-negative) cancers were composed of ER+, PR- groups. Proliferating cells defined by Ki67 positivity were mainly found in groups with PR-negative cells. Triple-Negative Breast Cancer (TNBC) exhibited the highest proliferative fraction and incidence of abnormal P53 and P16 expression. Among the tumors exhibiting P53 overexpression by immunohistochemistry, a group of TNBC was found with much higher MxIF-measured P53 signal intensity compared to HER2+, Luminal B-like and other TNBC cases. Densities of CD8 and CD20 cells were highest in HER2+ cancers. Spatial analysis demonstrated variability in heterogeneity in cellular neighborhoods in the cancer and the tumor microenvironment.

CONCLUSIONS

Protein marker multiplexing and quantitative image analysis demonstrated marked heterogeneity in protein co-expression signatures and cellular arrangement within each breast cancer subtype. These refined descriptors of biomarker expressions and spatial patterns could be valuable in the development of more informative tools to guide diagnosis and treatment.

Signature of arylacetamide deacetylase expression is associated with prognosis and immune infiltration in ovarian cancer

Objective

The role of the protein-coding gene arylacetamide deacetylase (AADAC) in the prognostication of ovarian cancer remains uncertain. We aimed to identify and validate its prognostic value using integrated bioinformatics analyses.

Methods

Gene expression profiles of RNA-sequencing and microarray data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus. Univariate and multivariate Cox regression models were used to evaluate the prognostic value of gene expression. The predictive accuracy of the gene signature model was evaluated using a time-dependent receiver operating characteristic (ROC) curve. In addition, the correlation between immune infiltration and AADAC was identified. A nomogram of the gene signature with clinical parameters was constructed to estimate the clinical application of the signature for survival prediction in patients with ovarian cancer.

Results

Univariate and multivariate Cox regression analyses in the training and validation cohorts indicated that a high AADAC expression signature was significantly and independently correlated with better survival outcomes in ovarian cancer. AADAC upregulation positively correlated with the infiltration of CD4+ memory T cells. Immunological signature gene sets were significantly enriched in CD4+ T cell regulation pathways. The area under the curve of the time-dependent ROC for overall survival indicated that the constructed nomogram had a moderate predictive ability for prognostic prediction in ovarian cancer.

Conclusion

AADAC expression signature significantly and independently correlated with the survival outcome and CD4+ memory T cell infiltration in ovarian cancer, indicating its potential applicability in the prediction of prognosis and immunotherapy efficacy.

Rejuvenating dysfunctional T cells in ovarian cancer: CD28 is the license to kill

High-grade serous ovarian cancers (HGSOCs) exhibit limited response to immune checkpoint blockade. In a new study in Cancer Cell, Duraiswamy et al. highlight intratumoral CD28 co-stimulation by myeloid-antigen-presenting cells as a key mechanism required for activation of programmed cell death receptor 1 (PD-1)⁺ tumor-infiltrating T lymphocytes during PD-1 blockade in HGSOC.