Heterogeneous Tumor-Immune Microenvironments among Differentially Growing Metastases in an Ovarian Cancer Patient

RNA vaccines for cancer: Principles to practice

Vaccines are the most impactful medicines to improve health. Though potent against pathogens, vaccines for cancer remain an unfulfilled promise. However, recent advances in RNA technology coupled with scientific and clinical breakthroughs have spurred rapid discovery and potent delivery of tumor antigens at speed and scale, transforming cancer vaccines into a tantalizing prospect. Yet, despite being at a pivotal juncture, with several randomized clinical trials maturing in upcoming years, several critical questions remain: which antigens, tumors, platforms, and hosts can trigger potent immunity with clinical impact? Here, we address these questions with a principled framework of cancer vaccination from antigen detection to delivery. With this framework, we outline features of emergent RNA technology that enable rapid, robust, real-time vaccination with somatic mutation-derived neoantigens-an emerging "ideal" antigen class-and highlight latent features that have sparked the belief that RNA could realize the enduring vision for vaccines against cancer.

Poor efficacy of immune checkpoint inhibitor treatment in advanced thymic carcinoma patients with liver metastases

Background

Although immune checkpoint inhibitor treatment for advanced thymic carcinoma exhibits promising efficacy, factors that affect the efficacy and prognosis, including metastases sites, remain uncertain.

Objectives

Our study aimed to investigate the determinants of survival among patients with advanced thymic carcinoma who underwent immunotherapy in real-world settings, with implications for clinical practice.

Designs

Different therapy regimens of immunotherapy were produced to analyze the influence of liver metastases on survival and prognosis for advanced thymic carcinoma patients.

Methods

Data for advanced thymic carcinoma patients receiving immunotherapy and their metastases sites were collected for analysis from seven different hospitals between January 2015 and January 2023. Progression-free survival (PFS) and overall survival (OS) analyses were performed using the Kaplan-Meier method. Cox analysis was used to evaluate factors influencing survival.

Results

The present study analyzed 136 advanced thymic carcinoma patients from seven different hospitals.The PFS for all patients receiving immunotherapy was 6.4 months, while the OS was 24.0 months. The objective response rate was different for patients with liver and non-liver metastases (11.9% versus 37.2%, p = 0.003). The disease control rate values were also different between the two groups (47.6% versus 80.9%, p = 0.037). The PFS for patients with liver metastases demonstrated poor immunotherapy efficacy compared to patients with non-liver metastases (3.0 versus 8.0 months, p < 0.0001). The OS was also significantly different between these two patient groups (16.1 versus 29.1 months, p = 0.009).

Conclusion

Immunotherapy had poor efficacy in advanced thymic carcinoma patients with liver metastases.

Modeling of Intracellular Taurine Levels Associated with Ovarian Cancer Reveals Activation of p53, ERK, mTOR and DNA-damage-sensing-dependent Cell Protection

Taurine, a non-proteogenic amino acid, and commonly used nutritional supplement can protect various tissues from degeneration associated with the action of the DNA-damaging chemotherapeutic agent cisplatin. Whether and how taurine protects human ovarian cancer (OC) cells from DNA damage caused by cisplatin is not well understood. We have found that OC ascites-derived cells contained significantly more intracellular taurine than cell cultures modeling OC. In culture, elevation of intracellular taurine concentration to OC ascites-cells-associated levels suppressed proliferation of various OC cell lines and patient-derived organoids, reduced glycolysis, and induced cell protection from cisplatin. Taurine cell protection was associated with decreased DNA damage in response to cisplatin. A combination of RNA sequencing, reverse phase protein arrays, live-cell microscopy, flow cytometry, and biochemical validation experiments provided evidence for taurine-mediated induction of mutant- or wild-type p53 binding to DNA, and activation of p53 effectors involved in negative regulation of the cell cycle (p21), and glycolysis (TIGAR). Paradoxically, taurine's suppression of cell proliferation was associated with activation of pro-mitogenic signal transduction including ERK, mTOR, and increased mRNA expression of major DNA damage sensing molecules such as DNAPK, ATM and ATR. While inhibition of ERK or p53 did not interfere with taurine's ability to protect cells from cisplatin, suppression of mTOR with Torin2, a clinically relevant inhibitor that also targets DNAPK and ATM/ATR, broke taurine's cell protection. Our studies implicate that elevation of intracellular taurine could suppress cell growth, metabolism, and activate cell protective mechanisms involving mTOR and DNA damage sensing signal transduction.

MRI-based radiomics model to preoperatively predict mesenchymal transition subtype in high-grade serous ovarian cancer

AIM

To develop a magnetic resonance imaging (MRI)-based radiomics model for the preoperative identification of mesenchymal transition (MT) subtype in high-grade serous ovarian cancer (HGSOC).

MATERIALS AND METHODS

One hundred and eighty-nine patients with histopathologically confirmed HGSOC were enrolled retrospectively. Among the included patients, 55 patients were determined as the MT subtype and the remaining 134 were non-MT subtype. After extracting a total of 204 features from T2-weighted imaging (T2WI) and contrast-enhanced (CE)-T1WI images, the Mann-Whitney U-test, Spearman correlation test, and Boruta algorithm were adopted to select the optimal feature set. Three classifiers, including logistic regression (LR), support vector machine (SVM), and random forest (RF), were trained to develop radiomics models. The performance of established models was evaluated from three aspects: discrimination, calibration, and clinical utility.

RESULTS

Seven radiomics features relevant to MT subtypes were selected to build the radiomics models. The model based on the RF algorithm showed the best performance in predicting MT subtype, with areas under the curves (AUCs) of 0.866 (95 % confidence interval [CI]: 0.797-0.936) and 0.852 (95 % CI: 0.736-0.967) in the training and testing cohorts, respectively. The calibration curves, supported with Brier scores, indicated very good consistency between observation and prediction. Decision curve analysis (DCA) showed that the RF-based model could provide more net benefit, which suggested favorable utility in clinical application.

CONCLUSION

The RF-based radiomics model provided accurate identification of MT from the non-MT subtype and may help facilitate personalised management of HGSOC.

Heterogeneity of primary and metastatic CAFs: From differential treatment outcomes to treatment opportunities (Review)

Compared with primary tumor sites, metastatic sites appear more resistant to treatments and respond differently to the treatment regimen. It may be due to the heterogeneity in the microenvironment between metastatic sites and primary tumors. Cancer‑associated fibroblasts (CAFs) are widely present in the tumor stroma as key components of the tumor microenvironment. Primary tumor CAFs (pCAFs) and metastatic CAFs (mCAFs) are heterogeneous in terms of source, activation mode, markers and functional phenotypes. They can shape the tumor microenvironment according to organ, showing heterogeneity between primary tumors and metastases, which may affect the sensitivity of these sites to treatment. It was hypothesized that understanding the heterogeneity between pCAFs and mCAFs can provide a glimpse into the difference in treatment outcomes, providing new ideas for improving the rate of metastasis control in various cancers.

Cell-intrinsic and microenvironmental determinants of metastatic colonization

Cancer metastasis is a biologically complex process that remains a major challenge in the oncology clinic, accounting for nearly all of the mortality associated with malignant neoplasms. To establish metastatic growths, carcinoma cells must disseminate from the primary tumour, survive in unfamiliar tissue microenvironments, re-activate programs of proliferation, and escape innate and adaptive immunosurveillance. The entire process is extremely inefficient and can occur over protracted timescales, yielding only a vanishingly small number of carcinoma cells that are able to complete all of the required steps. Here we review both the cancer-cell-intrinsic mechanisms and microenvironmental interactions that enable metastatic colonization. In particular, we highlight recent work on the behaviour of already-disseminated tumour cells, since meaningful progress in treating metastatic disease will clearly require a better understanding of the cells that spawn metastases, which generally have disseminated by the time of initial diagnosis.

Radiomic analysis of patient and inter-organ heterogeneity in response to immunotherapies and BRAF targeted therapy in metastatic melanoma

Background

Variability in treatment response may be attributable to organ-level heterogeneity in tumor lesions. Radiomic analysis of medical images can elucidate non-invasive biomarkers of clinical outcome. Organ-specific radiomic comparison across immunotherapies and targeted therapies has not been previously reported.

Methods

We queried UPMC Hillman Cancer Center registry for patients with metastatic melanoma (MEL) treated with immune checkpoint inhibitors (ICI) (anti-PD1/CTLA4 [ipilimumab+nivolumab; I+N] or anti-PD1 monotherapy) or BRAF targeted therapy. Best overall response was measured using RECIST v1.1. Lesions were segmented into discrete volume-of-interest with 400 radiomics features extracted. Overall and organ-specific machine-learning models were constructed to predict disease control (DC) versus progressive disease (PD) using XGBoost.

Results

291 MEL patients were identified, including 242 ICI (91 I+N, 151 PD1) and 49 BRAF. 667 metastases were analyzed, including 541 ICI (236 I+N, 305 PD1) and 126 BRAF. Across cohorts, baseline demographics included 39-47% female, 24-29% M1C, 24-46% M1D, and 61-80% with elevated LDH. Among patients experiencing DC, the organs with the greatest reduction were liver (-88%±12%, I+N; mean±S.E.M.) and lung (-72%±8%, I+N). For patients with multiple same-organ target lesions, the highest inter-lesion heterogeneity was observed in brain among patients who received ICI while no intra-organ heterogeneity was observed in BRAF. 267 patients were kept for radiomic modeling, including 221 ICI (86 I+N, 135 PD1) and 46 BRAF. Models consisting of optimized radiomic signatures classified DC/PD across I+N (AUC=0.85) and PD1 (0.71) and within individual organ sites (AUC=0.72∼0.94). Integration of clinical variables improved the models' performance. Comparison of models between treatments and across organ sites suggested mostly non-overlapping DC or PD features. Skewness, kurtosis, and informational measure of correlation (IMC) were among the radiomic features shared between overall response models. Kurtosis and IMC were also utilized by multiple organ-site models.

Conclusions

Differential organ-specific response was observed across BRAF and ICI with within organ heterogeneity observed for ICI but not for BRAF. Radiomic features of organ-specific response demonstrated little overlap. Integrating clinical factors with radiomics improves the prediction of disease course outcome and prediction of tumor heterogeneity.

Multimodal immune phenotyping reveals microbial-T cell interactions that shape pancreatic cancer

Microbes are an integral component of the tumor microenvironment. However, determinants of microbial presence remain ill-defined. Here, using spatial-profiling technologies, we show that bacterial and immune cell heterogeneity are spatially coupled. Mouse models of pancreatic cancer recapitulate the immune-microbial spatial coupling seen in humans. Distinct intra-tumoral niches are defined by T cells, with T cell-enriched and T cell-poor regions displaying unique bacterial communities that are associated with immunologically active and quiescent phenotypes, respectively, but are independent of the gut microbiome. Depletion of intra-tumoral bacteria slows tumor growth in T cell-poor tumors and alters the phenotype and presence of myeloid and B cells in T cell-enriched tumors but does not affect T cell infiltration. In contrast, T cell depletion disrupts the immunological state of tumors and reduces intra-tumoral bacteria. Our results establish a coupling between microbes and T cells in cancer wherein spatially defined immune-microbial communities differentially influence tumor biology.

Clinical and molecular features of acquired resistance to immunotherapy in non-small cell lung cancer

Although immunotherapy with PD-(L)1 blockade is routine for lung cancer, little is known about acquired resistance. Among 1,201 patients with non-small cell lung cancer (NSCLC) treated with PD-(L)1 blockade, acquired resistance is common, occurring in >60% of initial responders. Acquired resistance shows differential expression of inflammation and interferon (IFN) signaling. Relapsed tumors can be separated by upregulated or stable expression of IFNγ response genes. Upregulation of IFNγ response genes is associated with putative routes of resistance characterized by signatures of persistent IFN signaling, immune dysfunction, and mutations in antigen presentation genes which can be recapitulated in multiple murine models of acquired resistance to PD-(L)1 blockade after in vitro IFNγ treatment. Acquired resistance to PD-(L)1 blockade in NSCLC is associated with an ongoing, but altered IFN response. The persistently inflamed, rather than excluded or deserted, tumor microenvironment of acquired resistance may inform therapeutic strategies to effectively reprogram and reverse acquired resistance.

Adoptive cell therapy for high grade gliomas using simultaneous temozolomide and intracranial mgmt-modified γδ t cells following standard post-resection chemotherapy and radiotherapy: current strategy and future directions

Cellular therapies, including chimeric antigen receptor T cell therapies (CAR-T), while generally successful in hematologic malignancies, face substantial challenges against solid tumors such as glioblastoma (GBM) due to rapid growth, antigen heterogeneity, and inadequate depth of response to cytoreductive and immune therapies, We have previously shown that GBM constitutively express stress associated NKG2D ligands (NKG2DL) recognized by gamma delta (γδ) T cells, a minor lymphocyte subset that innately recognize target molecules via the γδ T cell receptor (TCR), NKG2D, and multiple other mechanisms. Given that NKG2DL expression is often insufficient on GBM cells to elicit a meaningful response to γδ T cell immunotherapy, we then demonstrated that NKG2DL expression can be transiently upregulated by activation of the DNA damage response (DDR) pathway using alkylating agents such as Temozolomide (TMZ). TMZ, however, is also toxic to γδ T cells. Using a p140K/MGMT lentivector, which confers resistance to TMZ by expression of O(6)-methylguanine-DNA-methyltransferase (MGMT), we genetically engineered γδ T cells that maintain full effector function in the presence of therapeutic doses of TMZ. We then validated a therapeutic system that we termed Drug Resistance Immunotherapy (DRI) that combines a standard regimen of TMZ concomitantly with simultaneous intracranial infusion of TMZ-resistant γδ T cells in a first-in-human Phase I clinical trial (NCT04165941). This manuscript will discuss DRI as a rational therapeutic approach to newly diagnosed GBM and the importance of repeated administration of DRI in combination with the standard-of-care Stupp regimen in patients with stable minimal residual disease.

Aneuploid serves as a prognostic marker and favors immunosuppressive microenvironment in ovarian cancer

Ovarian cancer is the most lethal gynecologic neoplasm, and most patients experience recurrence and chemoresistance. Even the promising immunotherapy showed limited efficacy in ovarian cancer, probably due to the immunosuppressive microenvironment. However, the behind mechanisms of the immune exclusion or cold phenotype in ovarian cancer still remain to be explored. As a cancer dominated by copy number variations instead of mutations, ovarian cancer contains a high fraction of aneuploid, which might correlate with immune inhibition. Nevertheless, whether or how aneuploid affects ovarian cancer is still unclear. For exploring the role of aneuploid cancer cells and the potential ploidy-immune relationship, herein, the ploidy information was first comprehensively analyzed combining the karyotype data and copy number variation data obtained from Mitelman and cBioPortal databases, respectively. Ovarian cancer showed strong ploidy heterogeneity, with high fraction of aneuploid and recurrent arm-level and whole chromosome changes. Furthermore, clinical parameters were compared between the highly-aneuploid and the near-diploid ovarian cancers. Aneuploid indicated high grade, poor overall survival and poor disease-free survival in ovarian cancer. To understand the biofunction affected by aneuploid, the differentially expressed genes between the highly-aneuploid and the near-diploid groups were analyzed. Transcription data suggested that aneuploid cancer correlated with deregulated MHC expression, abnormal antigen presentation, and less infiltration of macrophages and activated T cells and higher level of T cell exclusion. Furthermore, the ploidy-MHC association was verified using the Human Protein Atlas database. All these data supported that aneuploid might be promising for cancer management and immune surveillance in ovarian cancer.

Forces at play: exploring factors affecting the cancer metastasis

Metastatic disease, a leading and lethal indication of deaths associated with tumors, results from the dissemination of metastatic tumor cells from the site of primary origin to a distant organ. Dispersion of metastatic cells during the development of tumors at distant organs leads to failure to comply with conventional treatments, ultimately instigating abrupt tissue homeostasis and organ failure. Increasing evidence indicates that the tumor microenvironment (TME) is a crucial factor in cancer progression and the process of metastatic tumor development at secondary sites. TME comprises several factors contributing to the initiation and progression of the metastatic cascade. Among these, various cell types in TME, such as mesenchymal stem cells (MSCs), lymphatic endothelial cells (LECs), cancer-associated fibroblasts (CAFs), myeloid-derived suppressor cells (MDSCs), T cells, and tumor-associated macrophages (TAMs), are significant players participating in cancer metastasis. Besides, various other factors, such as extracellular matrix (ECM), gut microbiota, circadian rhythm, and hypoxia, also shape the TME and impact the metastatic cascade. A thorough understanding of the functions of TME components in tumor progression and metastasis is necessary to discover new therapeutic strategies targeting the metastatic tumor cells and TME. Therefore, we reviewed these pivotal TME components and highlighted the background knowledge on how these cell types and disrupted components of TME influence the metastatic cascade and establish the premetastatic niche. This review will help researchers identify these altered components' molecular patterns and design an optimized, targeted therapy to treat solid tumors and restrict metastatic cascade.

Limitations and potential of immunotherapy in ovarian cancer

Ovarian cancer (OC) is the third most common gynecological cancer and alone has an emergence rate of approximately 308,069 cases worldwide (2020) with dire survival rates. To put it into perspective, the mortality rate of OC is three times higher than that of breast cancer and it is predicted to only increase significantly by 2040. The primary reasons for such a high rate are that the physical symptoms of OC are detectable only during the advanced phase of the disease when resistance to chemotherapies is high and around 80% of the patients that do indeed respond to chemotherapy initially, show a poor prognosis subsequently. This highlights a pressing need to develop new and effective therapies to tackle advanced OC to improve prognosis and patient survival. A major advance in this direction is the emergence of combination immunotherapeutic methods to boost CD8+ T cell function to tackle OC. In this perspective, we discuss our view of the current state of some of the combination immunotherapies in the treatment of advanced OC, their limitations, and potential approaches toward a safer and more effective response.

Shift in Tissue-Specific Immune Niches and CD137 Expression in Tuberculoma of Pembrolizumab-Treated Nasopharyngeal Carcinoma Patients

The use of immune checkpoint inhibitors (ICIs) in cancer treatment has shown promise but can also have unintended consequences, such as reactivating latent tuberculosis (TB). To develop treatments that address ICIs-related adverse events, it is essential to understand cellular heterogeneity across healthy and pathological tissues. We performed cross-tissue multiplexed staining analysis on samples from two patients with TB reactivation during pembrolizumab treatment for metastatic nasopharyngeal carcinoma. CD8+ T cells, rather than CD4+ T cells, accumulated preferentially in the tuberculoma and were associated with increased production of IFNγ and expression of CD137. Additionally, CD137 enrichment played a role in the spatial organization of the tuberculoma, with specific interaction limited to spatial proximal cells between IFNγ+ CD137+ CD8+ T cells and IL12+ CD137+ type-1 macrophages. This unique feature was not observed in non-tumoral or tumoral tissues. Our analysis of public transcriptomic datasets supported the notion that this cellular interaction was more prominent in patients with durable ICI responses compared to those with non-ICI-related TB. We suggest that shifts towards CD137-rich immune niches are correlated with both off-target immune-related adverse events and anti-tumor efficacy. Targeting the tumor microenvironment through conditional activation of anti-CD137 signaling in combination with ICIs can modulate the reactivity of T cells and macrophages for localized tumor killing without the potential off-target immune-related risks associated with ICIs alone.

Integrated multi-omics profiling to dissect the spatiotemporal evolution of metastatic hepatocellular carcinoma

Comprehensive molecular analyses of metastatic hepatocellular carcinoma (HCC) are lacking. Here, we generate multi-omic profiling of 257 primary and 176 metastatic regions from 182 HCC patients. Primary tumors rich in hypoxia signatures facilitated polyclonal dissemination. Genomic divergence between primary and metastatic HCC is high, and early dissemination is prevalent. The remarkable neoantigen intratumor heterogeneity observed in metastases is associated with decreased T cell reactivity, resulting from disruptions to neoantigen presentation. We identify somatic copy number alterations as highly selected events driving metastasis. Subclones without Wnt mutations show a stronger selective advantage for metastasis than those with Wnt mutations and are characterized by a microenvironment rich in activated fibroblasts favoring a pro-metastatic phenotype. Finally, metastases without Wnt mutations exhibit higher enrichment of immunosuppressive B cells that mediate terminal exhaustion of CD8+ T cells via HLA-E:CD94-NKG2A checkpoint axis. Collectively, our results provide a multi-dimensional dissection of the complex evolutionary process of metastasis.

The sorafenib resistance-related gene signature predicts prognosis and indicates immune activity in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related death worldwide. Most patients with advanced HCC acquire sorafenib resistance. Drug resistance reflects the heterogeneity of tumors and is the main cause of tumor recurrence and death.We identified and validated sorafenib resistance related-genes (SRGs) as prognostic biomarkers for HCC. We obtained SRGs from the Gene Expression Omnibus and selected four key SRGs using the least absolute shrinkage and selection operator, random forest, and Support Vector Machine-Recursive feature elimination machine learning algorithms. Samples from the The Cancer Genome Atlas (TCGA)-HCC were segregated into two groups by consensus clustering. Following difference analysis, 19 SRGs were obtained through univariate Cox regression analysis, and a sorafenib resistance model was constructed for risk stratification and prognosis prediction. In multivariate Cox regression analysis, the risk score was an independent predictor of overall survival (OS). Patients classified as high-risk were more sensitive to other chemotherapy drugs and showed a higher expression of the common immune checkpoints. Additionally, the expression of drug-resistance genes was verified in the International Cancer Genome Consortium cohort. A nomogram model with a risk score was established, and its prediction performance was verified by calibration chart analysis of the TCGA-HCC cohort. We conclude that there is a significant correlation between sorafenib resistance and the tumor immune microenvironment in HCC. The risk score could be used to identify a reliable prognostic biomarker to optimize the therapeutic benefits of chemotherapy and immunotherapy, which can be helpful in the clinical decision-making for HCC patients.

A Microfluidics Approach for Ovarian Cancer Immune Monitoring in an Outpatient Setting

Among cancer diagnoses in women, ovarian cancer has the fifth-highest mortality rate. Current treatments are unsatisfactory, and new therapies are highly needed. Immunotherapies show great promise but have not reached their full potential in ovarian cancer patients. Implementation of an immune readout could offer better guidance and development of immunotherapies. However, immune profiling is often performed using a flow cytometer, which is bulky, complex, and expensive. This equipment is centralized and operated by highly trained personnel, making it cumbersome and time-consuming. We aim to develop a disposable microfluidic chip capable of performing an immune readout with the sensitivity needed to guide diagnostic decision making as close as possible to the patient. As a proof of concept of the fluidics module of this concept, acquisition of a limited immune panel based on CD45, CD8, programmed cell death protein 1 (PD1), and a live/dead marker was compared to a conventional flow cytometer (BD FACSymphony). Based on a dataset of peripheral blood mononuclear cells of 15 patients with ovarian cancer across different stages of treatment, we obtained a 99% correlation coefficient for the detection of CD8+PD1+ T cells relative to the total amount of CD45+ white blood cells. Upon further system development comprising further miniaturization of optics, this microfluidics chip could enable immune monitoring in an outpatient setting, facilitating rapid acquisition of data without the need for highly trained staff.

FLT3L-dependent dendritic cells control tumor immunity by modulating Treg and NK cell homeostasis

FLT3-L-dependent classical dendritic cells (cDCs) recruit anti-tumor and tumor-protecting lymphocytes. We evaluate cancer growth in mice with low, normal, or high levels of cDCs. Paradoxically, both low or high numbers of cDCs improve survival in mice with melanoma. In low cDC context, tumors are restrained by the adaptive immune system through influx of effector T cells and depletion of Tregs and NK cells. High cDC numbers favor the innate anti-tumor response, with massive recruitment of activated NK cells, despite high Treg infiltration. Anti CTLA-4 but not anti PD-1 therapy synergizes with FLT3-L therapy in the cDCHi but not in the cDCLo context. A combination of cDC boost and Treg depletion dramatically improves survival of tumor-bearing mice. Transcriptomic data confirm the paradoxical effect of cDC levels on survival in several human tumor types. cDCHi-TregLo state in such patients predicts best survival. Modulating cDC numbers via FLT3 signaling may have therapeutic potential in human cancer.

Prognostic role of long non-coding RNA USP30-AS1 in ovarian cancer: insights into immune cell infiltration in the tumor microenvironment

Ovarian cancer represents a formidable gynecologic malignancy bearing a dismal prognosis owing to the dearth of reliable early detection approaches and a high recurrence rate. Long non-coding RNAs (lncRNAs) have garnered immense attention as key orchestrators involved in diverse biological processes and take part in cancer initiation and progression. The present study investigated the potential significance of lncRNA USP30-AS1 in ovarian cancer prognosis, as well as its putative association with immune cell infiltration in tumor immune microenvironment (TIME). By analyzing publicly available datasets, we identified six lncRNAs with prognostic prediction ability, including USP30-AS1. The results revealed a significant positive correlation of USP30-AS1 expression with the infiltration of immune cells such as Th1 cells, TFH, CD8 T cells, B cells, antigen-presenting dendritic cells (aDC), and plasmacytoid dendritic cells (pDC) in ovarian cancer specimens. These findings provide compelling evidence of the potential involvement of lncRNA in the regulation of the TME in ovarian carcinoma. The outcomes from this study underscore the potential of USP30-AS1 as a promising prognostic biomarker for ovarian cancer. Additionally, the findings offer significant insights into the plausible role of lncRNAs in modulating immune activities, thus adding to our understanding of the disease biology. Additional investigations are necessary to unravel the molecular mechanisms underpinning these connections and validate the results seen in independent cohorts and experimental models.

Evaluation of combined pathological responses in primary tumor and lymph nodes following neoadjuvant chemoimmunotherapy in non-small cell lung cancer

BACKGROUND

Inconsistent pathological responses of tumor and lymph nodes (LNs) were frequently observed in non-small cell lung cancer (NSCLC) receiving neoadjuvant chemoimmunotherapy. However, there is a lack of studies to report the prognostic significance and the relevant clinicopathological factors of tumor-nodal inconsistent responses after neoadjuvant immunotherapy or chemoimmunotherapy. Therefore, this study aimed to depict the inconsistent pathological combined tumor-nodal responses in NSCLC patients after neoadjuvant chemoimmunotherapy as well as the underlying clinical significance.

METHODS

A total of 81 node-positive NSCLC patients who underwent neoadjuvant chemoimmunotherapy were eligible for inclusion. Demographic, radiologic, and pathological features of patients were recorded. Patients with pathological complete response of both tumor (ypT(pCR)) and LNs (ypN0) were classified into the combined good responder group and the relevant clinicopathological features were evaluated. The event-free survival (EFS) outcome was analyzed using Kaplan-Meier analysis.

RESULTS

The ypN0 and ypT(pCR) rates were 74.1 % and 42.0 %, respectively. A significant correlation was observed between ypT(pCR) and ypN0 (P = 0.003), but inconsistent responses remained. The combined responses of the primary tumor and LNs demonstrated a significant association with the prognosis outcome (P = 0.005). Notably,patients who received at least twice of their infusions of immune checkpoint inhibitors after 15:30 had a worse prognosis (P = 0.015).

CONCLUSION

A significant but not absolute correlation was observed between good tumor response and good nodal response in NSCLC patients after neoadjuvant chemoimmunotherapy, but inconsistent responses were also found. The combination of tumor and nodal responses is significantly associated with prognosis and combined good responder can be used as a reliable prognosis predictor.

Immunochemotherapy alone or immunochemotherapy plus subsequent locoregional radiotherapy in de novo metastatic nasopharyngeal carcinoma

BACKGROUND

To demonstrate whether the benefit of locoregional radiotherapy in de novo metastatic nasopharyngeal carcinoma remains in the immunotherapy era and which patients can benefit from radiotherapy.

MATERIALS AND METHODS

A total of 273 histopathology-confirmed de novo metastatic nasopharyngeal carcinoma was enrolled between May 2017 and October 2021 if receiving immunochemotherapy with or without subsequent intensity-modulated radiotherapy to the nasopharynx and neck. We compared the progression-free survival, overall survival, and safety between the two groups. Additionally, subgroup analysis was conducted and a scoring model was developed to identify suitable patients for radiation.

RESULTS

There were 95 (34.8 %) patients with immunochemotherapy alone, and 178 (65.2 %) with immunochemotherapy plus subsequent locoregional radiotherapy. With a median follow-up time of 18 months, patients with immunochemotherapy plus subsequent radiotherapy had higher 1-year progression-free survival (80.6 % vs. 65.1 %, P < 0.001) and overall survival (98.3 % vs. 89.5 %, P = 0.001) than those with immunochemotherapy alone. The benefit was retained in multivariate analysis and propensity score-matched analysis. Mainly, it was more significant in patients with oligometastases, EBV DNA below 20,200 copies/mL, and complete or partial relapse after immunochemotherapy. The combined treatment added grade 3 or 4 anemia and radiotherapy-related toxicities.

CONCLUSION

Immunochemotherapy plus subsequent locoregional radiotherapy prolonged the survival of de novo metastatic nasopharyngeal carcinoma with tolerable toxicities. A scoring model based on oligometastases, EBV DNA level, and response after immunochemotherapy could facilitate individualized management.

Genomic profiling of subcutaneous patient-derived xenografts reveals immune constraints on tumor evolution in childhood solid cancer

Subcutaneous patient-derived xenografts (PDXs) are an important tool for childhood cancer research. Here, we describe a resource of 68 early passage PDXs established from 65 pediatric solid tumor patients. Through genomic profiling of paired PDXs and patient tumors (PTs), we observe low mutational similarity in about 30% of the PT/PDX pairs. Clonal analysis in these pairs show an aggressive PT minor subclone seeds the major clone in the PDX. We show evidence that this subclone is more immunogenic and is likely suppressed by immune responses in the PT. These results suggest interplay between intratumoral heterogeneity and antitumor immunity may underlie the genetic disparity between PTs and PDXs. We further show that PDXs generally recapitulate PTs in copy number and transcriptomic profiles. Finally, we report a gene fusion LRPAP1-PDGFRA. In summary, we report a childhood cancer PDX resource and our study highlights the role of immune constraints on tumor evolution.

Unveiling the novel immune and molecular signatures of ovarian cancer: insights and innovations from single-cell sequencing

Ovarian cancer is a highly heterogeneous and lethal malignancy with limited treatment options. Over the past decade, single-cell sequencing has emerged as an advanced biological technology capable of decoding the landscape of ovarian cancer at the single-cell resolution. It operates at the level of genes, transcriptomes, proteins, epigenomes, and metabolisms, providing detailed information that is distinct from bulk sequencing methods, which only offer average data for specific lesions. Single-cell sequencing technology provides detailed insights into the immune and molecular mechanisms underlying tumor occurrence, development, drug resistance, and immune escape. These insights can guide the development of innovative diagnostic markers, therapeutic strategies, and prognostic indicators. Overall, this review provides a comprehensive summary of the diverse applications of single-cell sequencing in ovarian cancer. It encompasses the identification and characterization of novel cell subpopulations, the elucidation of tumor heterogeneity, the investigation of the tumor microenvironment, the analysis of mechanisms underlying metastasis, and the integration of innovative approaches such as organoid models and multi-omics analysis.

Total-body Dynamic Imaging and Kinetic Modeling of 18F-AraG in Healthy Individuals and a Non-Small Cell Lung Cancer Patient Undergoing Anti-PD-1 Immunotherapy

Immunotherapies, especially the checkpoint inhibitors such as anti-PD-1 antibodies, have transformed cancer treatment by enhancing immune system's capability to target and kill cancer cells. However, predicting immunotherapy response remains challenging. 18F-AraG is a molecular imaging tracer targeting activated T cells, which may facilitate therapy response assessment by non-invasive quantification of immune cell activity within tumor microenvironment and elsewhere in the body. The aim of this study was to obtain preliminary data on total-body pharmacokinetics of 18F-AraG, as a potential quantitative biomarker for immune response evaluation.

Methods

The study consisted of 90-min total-body dynamic scans of four healthy subjects and one non-small cell lung cancer (NSCLC) patient, scanned before and after anti-PD-1 immunotherapy. Compartmental modeling with Akaike information criterion model selection were employed to analyze tracer kinetics in various organs. Additionally, seven sub-regions of the primary lung tumor and four mediastinal lymph nodes were analyzed. Practical identifiability analysis was performed to assess reliability of kinetic parameter estimation. Correlations of SUVmean, SUVR (tissue-to-blood ratio), and Logan plot slope K L o g a n with total volume-of-distribution V T were calculated to identify potential surrogates for kinetic modeling.

Results

Strong correlations were observed between K L o g a n and SUVR values with V T , suggesting that they can be used as promising surrogates for V T , especially in organs with low blood-volume fraction. Moreover, the practical identifiability analysis suggests that the dynamic 18F-AraG PET scans could potentially be shortened to 60 minutes, while maintaining quantification accuracy for all organs-of-interest. The study suggests that although 18F-AraG SUV images can provide insights on immune cell distribution, kinetic modeling or graphical analysis methods may be required for accurate quantification of immune response post-therapy. While SUVmean showed variable changes in different sub-regions of the tumor post-therapy, the SUVR, K L o g a n , and V T showed consistent increasing trends in all analyzed sub-regions of the tumor with high practical identifiability.

Conclusion

Our findings highlight the promise of 18F-AraG dynamic imaging as a non-invasive biomarker for quantifying the immune response to immunotherapy in cancer patients. The promising total-body kinetic modeling results also suggest potentially wider applications of the tracer in investigating the role of T cells in the immunopathogenesis of diseases.

A phase 1 trial of adoptive transfer of vaccine-primed autologous circulating T cells in ovarian cancer

We have previously shown that vaccination with tumor-pulsed dendritic cells amplifies neoantigen recognition in ovarian cancer. Here, in a phase 1 clinical study ( NCT01312376 /UPCC26810) including 19 patients, we show that such responses are further reinvigorated by subsequent adoptive transfer of vaccine-primed, ex vivo-expanded autologous peripheral blood T cells. The treatment is safe, and epitope spreading with novel neopeptide reactivities was observed after cell infusion in patients who experienced clinical benefit, suggesting reinvigoration of tumor-sculpting immunity.

Ovarian cancer beyond imaging: integration of AI and multiomics biomarkers

High-grade serous ovarian cancer is the most lethal gynaecological malignancy. Detailed molecular studies have revealed marked intra-patient heterogeneity at the tumour microenvironment level, likely contributing to poor prognosis. Despite large quantities of clinical, molecular and imaging data on ovarian cancer being accumulated worldwide and the rise of high-throughput computing, data frequently remain siloed and are thus inaccessible for integrated analyses. Only a minority of studies on ovarian cancer have set out to harness artificial intelligence (AI) for the integration of multiomics data and for developing powerful algorithms that capture the characteristics of ovarian cancer at multiple scales and levels. Clinical data, serum markers, and imaging data were most frequently used, followed by genomics and transcriptomics. The current literature proves that integrative multiomics approaches outperform models based on single data types and indicates that imaging can be used for the longitudinal tracking of tumour heterogeneity in space and potentially over time. This review presents an overview of studies that integrated two or more data types to develop AI-based classifiers or prediction models.Relevance statement Integrative multiomics models for ovarian cancer outperform models using single data types for classification, prognostication, and predictive tasks.Key points• This review presents studies using multiomics and artificial intelligence in ovarian cancer.• Current literature proves that integrative multiomics outperform models using single data types.• Around 60% of studies used a combination of imaging with clinical data.• The combination of genomics and transcriptomics with imaging data was infrequently used.

Computational Quantification of Cancer Immunoediting

The remarkable success of cancer immunotherapy has revolutionized cancer treatment, emphasizing the importance of tumor-immune interactions in cancer evolution and treatment. Cancer immunoediting describes the dual effect of tumor-immune interactions: inhibiting tumor growth by destroying tumor cells and facilitating tumor escape by shaping tumor immunogenicity. To better understand tumor-immune interactions, it is critical to develop computational methods to measure the extent of cancer immunoediting. In this review, we provide a comprehensive overview of the computational methods for quantifying cancer immunoediting. We focus on describing the basic ideas, computational processes, advantages, limitations, and influential factors. We also summarize recent advances in quantifying cancer immunoediting studies and highlight future research directions. As the methods for quantifying cancer immunoediting are continuously improved, future research will further help define the role of immunity in tumorigenesis and hopefully provide a basis for the design of new personalized cancer immunotherapy strategies.

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.

Immune suppressive microenvironment in liver metastases contributes to organ-specific response of immunotherapy in advanced non-small cell lung cancer

BACKGROUND

The liver is a frequent site of metastases and liver metastases (LM) correlate with diminished immunotherapy efficacy in non-small cell lung cancer (NSCLC). This study aimed to analyze whether tumor response to immunotherapy differs between pulmonary lesions (PL) and LM in NSCLC and to explore potential mechanisms through multiomics analysis.

METHODS

This observational longitudinal clinical cohort study included patients with NSCLC with LM receiving immunotherapy was conducted to evaluate organ-specific tumor response of PL and LM. We collected paired PL and LM tumor samples to analyze the organ-specific difference using whole-exome sequencing, RNA sequencing, and multiplex immunohistochemistry.

RESULTS

A total of 52 patients with NSCLC with LM were enrolled to evaluate the organ-specific response of immunotherapy. The objective response rate (21.1% vs 32.7%) and disease control rate of LM were lower than that of PL (67.3% vs 86.5%). One-third of patients showed mixed response, among whom 88.2% (15/17) presented with LM increasing, but PL decreasing, while the others had the opposite pattern (p=0.002). In another independent cohort, 27 pairs of matched PL and LM tumor samples from the same individuals, including six simultaneously collected pairs, were included in the translational part. Genomic landscapes profiling revealed similar somatic mutations, tumor mutational burden, and neoantigen number between PL and LM. Bulk-RNA sequencing showed immune activation-related genes including CD8A, LCK, and ICOS were downregulated in LM. The antigen processing and presentation, natural killer (NK) cell-mediated cytotoxicity and T-cell receptor signaling pathway were enriched in PL compared with LM. Multiplex immunohistochemistry detected significantly lower fractions of CD8⁺ cells (p=0.036) and CD56^dim+ cells (p=0.016) in LM compared with PL. Single-cell RNA sequencing also characterized lower effector CD8⁺ T cells activation and NK cells cytotoxicity in LM.

CONCLUSIONS

Compared with PL, LM presents an inferior organ-specific tumor response to immunotherapy. PL and LM showed limited heterogeneity in the genomic landscape, while the LM tumor microenvironment displayed lower levels of immune activation and infiltration than PL, which might contribute to developing precise immunotherapy strategies for patients with NSCLC with LM.

Mechanisms and clinical implications in renal carcinoma resistance: narrative review of immune checkpoint inhibitors

Clear cell renal cell carcinoma (ccRCC) is the most common histological subtype of renal cell carcinoma. The prognosis for patients with ccRCC has improved over recent years with the use of combination therapies with an anti-programmed death-1 (PD-1) backbone. This has enhanced the quality of life and life expectancy of patients with this disease. Unfortunately, not all patients benefit; eventually, most patients will develop resistance to therapy and progress. Recent molecular, biochemical, and immunological research has extensively researched anti-angiogenic and immune-based treatment resistance mechanisms. This analysis offers an overview of the principles underpinning the resistance pathways related to immune checkpoint inhibitors (ICIs). Additionally, novel approaches to overcome resistance that may be considered for the trial context are discussed.

Heterogeneity in functional genetic screens: friend or foe?

Functional genetic screens to uncover tumor-intrinsic nodes of immune resistance have uncovered numerous mechanisms by which tumors evade our immune system. However, due to technical limitations, tumor heterogeneity is imperfectly captured with many of these analyses. Here, we provide an overview of the nature and sources of heterogeneity that are relevant for tumor-immune interactions. We argue that this heterogeneity may actually contribute to the discovery of novel mechanisms of immune evasion, given a sufficiently large and heterogeneous set of input data. Taking advantage of tumor cell heterogeneity, we provide proof-of-concept analyses of mechanisms of TNF resistance. Thus, consideration of tumor heterogeneity is imperative to increase our understanding of immune resistance mechanisms.

Spatial and temporal intra-tumoral heterogeneity in advanced HGSOC: Implications for surgical and clinical outcomes

Limited evidence exists on the impact of spatial and temporal heterogeneity of high-grade serous ovarian cancer (HGSOC) on tumor evolution, clinical outcomes, and surgical operability. We perform systematic multi-site tumor mapping at presentation and matched relapse from 49 high-tumor-burden patients, operated up front. From SNP array-derived copy-number data, we categorize dendrograms representing tumor clonal evolution as sympodial or dichotomous, noting most chemo-resistant patients favor simpler sympodial evolution. Three distinct tumor evolutionary patterns from primary to relapse are identified, demonstrating recurrent disease may emerge from pre-existing or newly detected clones. Crucially, we identify spatial heterogeneity for clinically actionable homologous recombination deficiency scores and for poor prognosis biomarkers CCNE1 and MYC. Copy-number signature, phenotypic, proteomic, and proliferative-index heterogeneity further highlight HGSOC complexity. This study explores HGSOC evolution and dissemination across space and time, its impact on optimal surgical cytoreductive effort and clinical outcomes, and its consequences for clinical decision-making.

NIR-II Imaging and Sandwiched Plasmonic Biosensor for Ultrasensitive Intraoperative Definition of Tumor-Invaded Lymph Nodes

Radical lymphadenectomy remains the cornerstone of preventing tumor metastasis through the lymphatic system. Current surgical resection of lymph nodes (LNs) based on fluorescence-guided surgery (FGS) suffers from low sensitivity/selectivity with only qualitative information, hampering accurate intraoperative decision-making. Herein, we develop a modularized theranostic system including NIR-II FGS and a sandwiched plasmonic chip (SPC). Intraoperative NIR-II FGS and detection of tumor-positive lymph nodes were performed on the gastric tumor to determine the feasibility of the modularized theranostic system in defining LN metastasis. Under the NIR-II imaging window, the orthotopic tumor and sentinel lymph nodes (SLNs) were successfully excised without ambient light interference in the operating room. Importantly, the SPC biosensor achieved 100% sensitivity and 100% specificity for tumor markers and realized rapid and high-throughput intraoperative SLN detection. We propose the synergetic design of combining the NIR-II FGS and suitable biosensor will substantially improve the efficiency of cancer diagnosis and therapy follow-up.

Implications of the Organ-Specific Immune Environment for Immune Priming Effect of Radiotherapy in Metastatic Setting

With the development of immune checkpoint inhibitors (ICIs), the tumour immune microenvironment (TIME) has been increasingly considered to improve cancer management. The TIME of metastatic lesions is strongly influenced by the underlying immune contexture of the organ in which they are located. The metastatic location itself appears to be an important prognostic factor in predicting outcomes after ICI treatment in cancer patients. Patients with liver metastases are less likely to respond to ICIs than patients with metastases in other organs, likely due to variations in the metastatic TIME. Combining additional treatment modalities is an option to overcome this resistance. Radiotherapy (RT) and ICIs have been investigated together as an option to treat various metastatic cancers. RT can induce a local and systemic immune reaction, which can promote the patient's response to ICIs. Here, we review the differential impact of the TIME according to metastatic location. We also explore how RT-induced TIME modifications could be modulated to improve outcomes of RT-ICI combinations.

Weakly supervised deep learning to predict recurrence in low-grade endometrial cancer from multiplexed immunofluorescence images

Predicting recurrence in low-grade, early-stage endometrial cancer (EC) is both challenging and clinically relevant. We present a weakly-supervised deep learning framework, NaroNet, that can learn, without manual expert annotation, the complex tumor-immune interrelations at three levels: local phenotypes, cellular neighborhoods, and tissue areas. It uses multiplexed immunofluorescence for the simultaneous visualization and quantification of CD68 + macrophages, CD8 + T cells, FOXP3 + regulatory T cells, PD-L1/PD-1 protein expression, and tumor cells. We used 489 tumor cores from 250 patients to train a multilevel deep-learning model to predict tumor recurrence. Using a tenfold cross-validation strategy, our model achieved an area under the curve of 0.90 with a 95% confidence interval of 0.83-0.95. Our model predictions resulted in concordance for 96,8% of cases (κ = 0.88). This method could accurately assess the risk of recurrence in EC, outperforming current prognostic factors, including molecular subtyping.

An EMT-based gene signature enhances the clinical understanding and prognostic prediction of patients with ovarian cancers

BACKGROUND

Ovarian cancer (OC) is one of the most common gynecological cancers with malignant metastasis and poor prognosis. Current evidence substantiates that epithelial-mesenchymal transition (EMT) is a critical mechanism that drives OC progression. In this study, we aspire to identify pivotal EMT-related genes (EMTG) in OC development, and establish an EMT gene-based model for prognosis prediction.

METHODS

We constructed the risk score model by screening EMT genes via univariate/LASSO/step multivariate Cox regressions in the OC cohort from TCGA database. The efficacy of the EMTG model was tested in external GEO cohort, and quantified by the nomogram. Moreover, the immune infiltration and chemotherapy sensitivity were analyzed in different risk score groups.

RESULTS

We established a 11-EMTGs risk score model to predict the prognosis of OC patients. Based on the model, OC patients were split into high- and low- risk score groups, and the high-risk score group had an inevitably poor survival. The predictive power of the model was verified by external OC cohort. The nomogram showed that the model was an independent factor for prognosis prediction. Moreover, immune infiltration analysis revealed the immunosuppressive microenvironment in the high-risk score group. Finally, the EMTG model can be used to predict the sensitivity to chemotherapy drugs.

CONCLUSIONS

This study demonstrated that EMTG model was a powerful tool for prognostic prediction of OC patients. Our work not only provide a novel insight into the etiology of OC tumorigenesis, but also can be used in the clinical decisions on OC treatment.

Radiomics and Radiogenomics of Ovarian Cancer

Ovarian cancer, one of the deadliest gynecologic malignancies, is characterized by high intra- and inter-site genomic and phenotypic heterogeneity. The traditional information provided by the conventional interpretation of diagnostic imaging studies cannot adequately represent this heterogeneity. Radiomics analyses can capture the complex patterns related to the microstructure of the tissues and provide quantitative information about them. This review outlines how radiomics and its integration with other quantitative biological information, like genomics and proteomics, can impact the clinical management of ovarian cancer.

Optimizing the tumor shrinkage threshold for evaluating immunotherapy efficacy for advanced non-small-cell lung cancer

PURPOSE

The rise of immune checkpoint inhibitors (ICIs) in recent years has coincided with unusual clinical response patterns. Modification of the sum of longest diameters (SLD)-based threshold that reflecting dynamic change of the tumor burden and predicting response to ICIs, may markedly improve current treatment regimens.

METHODS

The baseline and post-treatment SLD of target lesion was recorded and the maximum percent change of the SLD from baseline was designated as SLD-change score. The optimal cut-off value was obtained using the X-tile program. The relationship between SLD-change score and survival outcome (PFS, OS) was evaluated.

RESULTS

10% cut-off value of SLD-change score was found to be most distinctive for PFS. Responders defined according to this cut-off value showed a significant improvement for PFS and OS. Bone metastasis and brain metastasis were also two independent prognostic factors of PFS and OS, respectively.

CONCLUSIONS

10% SLD change score could discriminate for ICIs treatment response, which holds great promise in promoting the development of precise immunotherapeutic strategy.

Potential links between the microbiota and T cell immunity determine the tumor cell fate

The central role of the microbiota as a pivotal factor regulating anti-tumor immune responses has recently been appreciated. Increasing evidence has put a spotlight on the connection of microbiota to T cells, by showing impaired effector and/or memory responses in germ-free (GF) mice or in the presence of dysbiotic communities, and association with tumor growth and overall survival (OS). These observations also have significant implications for anti-tumor therapy and vaccination, suggesting that the communication between T cells and the microbiota involves soluble mediators (microbiota-derived metabolites) that influence various functions of T cells. In addition, there is growing appreciation of the role of bacterial translocation into the peritumoral milieu from the intestinal tract, as well as of locally developed tumor microbial communities, spatially separated from the gut microbiota, in shaping the tumor microbiome. Collectively, these findings have added new support to the idea that tonic inputs mirroring the existence of tumor microbiome could regulate the function of tumor-infiltrating T cells and tissue-resident memory T (TRM) cells. In this review, we focus on recent advances and aspects of these active areas of investigation and provide a comprehensive overview of the unique mechanisms that play a pivotal role in the regulation of anti-tumor immunity by the microbiota, some of which could be of particular relevance for addressing problems caused by tumor heterogeneity. It is our hope that this review will provide a theoretical foundation for future investigations in this area.

Development and Validation of a Prognostic Risk Model Based on Nature Killer Cells for Serous Ovarian Cancer

Nature killer (NK) cells are increasingly considered important in tumor microenvironment, but their role in predicting the prognosis of ovarian cancer has not been revealed. This study aimed to develop a prognostic risk model for ovarian cancer based on NK cells. Firstly, differentially expressed genes (DEGs) of NK cells were found by single-cell RNA-sequencing dataset analysis. Based on six NK-cell DEGs identified by univariable, Lasso and multivariable Cox regression analyses, a prognostic risk model for serous ovarian cancer was developed in the TCGA cohort. This model was then validated in three external cohorts, and evaluated as an independent prognostic factor by multivariable Cox regression analysis together with clinical characteristics. With the investigation of the underlying mechanism, a relation between a higher risk score of this model and more immune activities in tumor microenvironment was revealed. Furthermore, a detailed inspection of infiltrated immunocytes indicated that not only quantity, but also the functional state of these immunocytes might affect prognostic risk. Additionally, the potential of this model to predict immunotherapeutic response was exhibited by evaluating the functional state of cytotoxic T lymphocytes. To conclude, this study introduced a novel prognostic risk model based on NK-cell DEGs, which might provide assistance for the personalized management of serous ovarian cancer patients.

Locally sourced: site-specific immune barriers to metastasis

Tumour cells migrate very early from primary sites to distant sites, and yet metastases often take years to manifest themselves clinically or never even surface within a patient's lifetime. This pause in cancer progression emphasizes the existence of barriers that constrain the growth of disseminated tumour cells (DTCs) at distant sites. Although the nature of these barriers to metastasis might include DTC-intrinsic traits, recent studies have established that the local microenvironment also controls the formation of metastases. In this Perspective, I discuss how site-specific differences of the immune system might be a major selective growth restraint on DTCs, and argue that harnessing tissue immunity will be essential for the next stage in immunotherapy development that reliably prevents the establishment of metastases.

The ratio of adaptive to innate immune cells differs between genders and associates with improved prognosis and response to immunotherapy

Immunotherapy has revolutionised cancer treatment. However, not all cancer patients benefit, and current stratification strategies based primarily on PD1 status and mutation burden are far from perfect. We hypothesised that high activation of an innate response relative to the adaptive response may prevent proper tumour neoantigen identification and decrease the specific anticancer response, both in the presence and absence of immunotherapy. To investigate this, we obtained transcriptomic data from three large publicly available cancer datasets, the Cancer Genome Atlas (TCGA), the Hartwig Medical Foundation (HMF), and a recently published cohort of metastatic bladder cancer patients treated with immunotherapy. To analyse immune infiltration into bulk tumours, we developed an RNAseq-based model based on previously published definitions to estimate the overall level of infiltrating innate and adaptive immune cells from bulk tumour RNAseq data. From these, the adaptive-to-innate immune ratio (A/I ratio) was defined. A meta-analysis of 32 cancer types from TCGA overall showed improved overall survival in patients with an A/I ratio above median (Hazard ratio (HR) females 0.73, HR males 0.86, P < 0.05). Of particular interest, we found that the association was different for males and females for eight cancer types, demonstrating a gender bias in the relative balance of the infiltration of innate and adaptive immune cells. For patients with metastatic disease, we found that responders to immunotherapy had a significantly higher A/I ratio than non-responders in HMF (P = 0.036) and a significantly higher ratio in complete responders in a separate metastatic bladder cancer dataset (P = 0.022). Overall, the adaptive-to-innate immune ratio seems to define separate states of immune activation, likely linked to fundamental immunological reactions to cancer. This ratio was associated with improved prognosis and improved response to immunotherapy, demonstrating potential relevance to patient stratification. Furthermore, by demonstrating a significant difference between males and females that associates with response, we highlight an important gender bias which likely has direct clinical relevance.

Wnt/β-Catenin Signaling and Resistance to Immune Checkpoint Inhibitors: From Non-Small-Cell Lung Cancer to Other Cancers

Lung cancer is the leading cause of cancer-related deaths worldwide. The standard of care for advanced non-small-cell lung cancer (NSCLC) without driver-gene mutations is a combination of an anti-PD-1/PD-L1 antibody and chemotherapy, or an anti-PD-1/PD-L1 antibody and an anti-CTLA-4 antibody with or without chemotherapy. Although there were fewer cases of disease progression in the early stages of combination treatment than with anti-PD-1/PD-L1 antibodies alone, only approximately half of the patients had a long-term response. Therefore, it is necessary to elucidate the mechanisms of resistance to immune checkpoint inhibitors. Recent reports of such mechanisms include reduced cancer-cell immunogenicity, loss of major histocompatibility complex, dysfunctional tumor-intrinsic interferon-γ signaling, and oncogenic signaling leading to immunoediting. Among these, the Wnt/β-catenin pathway is a notable potential mechanism of immune escape and resistance to immune checkpoint inhibitors. In this review, we will summarize findings on these resistance mechanisms in NSCLC and other cancers, focusing on Wnt/β-catenin signaling. First, we will review the molecular biology of Wnt/β-catenin signaling, then discuss how it can induce immunoediting and resistance to immune checkpoint inhibitors. We will also describe other various mechanisms of immune-checkpoint-inhibitor resistance. Finally, we will propose therapeutic approaches to overcome these mechanisms.

The other immuno-PET: Metabolic tracers in evaluation of immune responses to immune checkpoint inhibitor therapy for solid tumors

Unique patterns of response to immune checkpoint inhibitor therapy, discernable in the earliest clinical trials, demanded a reconsideration of the standard methods of radiological treatment assessment. Immunomonitoring, that characterizes immune responses, offers several significant advantages over the tumor-centric approach currently used in the clinical practice: 1) better understanding of the drugs' mechanism of action and treatment resistance, 2) earlier assessment of response to therapy, 3) patient/therapy selection, 4) evaluation of toxicity and 5) more accurate end-point in clinical trials. PET imaging in combination with the right agent offers non-invasive tracking of immune processes on a whole-body level and thus represents a method uniquely well-suited for immunomonitoring. Small molecule metabolic tracers, largely neglected in the immuno-PET discourse, offer a way to monitor immune responses by assessing cellular metabolism known to be intricately linked with immune cell function. In this review, we highlight the use of small molecule metabolic tracers in imaging immune responses, provide a view of their value in the clinic and discuss the importance of image analysis in the context of tracking a moving target.

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.

Computational studies reveal co-occurrence of two mutations in IL7R gene of high-grade serous carcinoma patients

Major cause of mortality in ovarian cancer can be attributed to a lack of specific and sensitive biomarkers for diagnosis and prognosis of the disease. Uncovering the mutations in genes involved in crucial oncogenic pathways is a key step in discovery and development of novel biomarkers. Whole exome sequencing (WES) is a powerful method for the detection of cancer driver mutations. The present work focuses on identifying functionally damaging mutations in patients with high-grade serous ovarian carcinoma (HGSC) through computational analysis of WES. In this study, WES data of HGSC patients was retrieved from the genomic literature available in sequence read archive, the variants were identified and comprehensive structural and functional analysis was performed. Interestingly, I66T and V138I mutations were found to be co-occurring in the IL7R gene in four out of five HGSC patient samples investigated in this study. The V138I mutation was located in the fibronectin type-3 domain and computationally assessed to be causing disruptive effects on the structure and dynamics of IL7R protein. This mutation was found to be co-occurring with the neutral I66T mutation in the same domain which compensated the disruptive effects of V138I variant. These comprehensive studies point to a hitherto unexplored significant role of the IL7R gene in ovarian carcinoma. It is envisaged that the work will lay the foundation for the development of a novel biomarker with potential application in molecular profiling and in estimation of the disease prognosis.Communicated by Ramaswamy H. Sarma.

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.

The genomic and immune landscape of long-term survivors of high-grade serous ovarian cancer

Fewer than half of all patients with advanced-stage high-grade serous ovarian cancers (HGSCs) survive more than five years after diagnosis, but those who have an exceptionally long survival could provide insights into tumor biology and therapeutic approaches. We analyzed 60 patients with advanced-stage HGSC who survived more than 10 years after diagnosis using whole-genome sequencing, transcriptome and methylome profiling of their primary tumor samples, comparing this data to 66 short- or moderate-term survivors. Tumors of long-term survivors were more likely to have multiple alterations in genes associated with DNA repair and more frequent somatic variants resulting in an increased predicted neoantigen load. Patients clustered into survival groups based on genomic and immune cell signatures, including three subsets of patients with BRCA1 alterations with distinctly different outcomes. Specific combinations of germline and somatic gene alterations, tumor cell phenotypes and differential immune responses appear to contribute to long-term survival in HGSC.

Modulating the tumor immune microenvironment with nanoparticles: A sword for improving the efficiency of ovarian cancer immunotherapy

With encouraging antitumor effects, immunotherapy represented by immune checkpoint blockade has developed into a mainstream cancer therapeutic modality. However, only a minority of ovarian cancer (OC) patients could benefit from immunotherapy. The main reason is that most OC harbor a suppressive tumor immune microenvironment (TIME). Emerging studies suggest that M2 tumor-associated macrophages (TAMs), T regulatory cells (Tregs), myeloid-derived suppressor cells (MDSCs), and cancer-associated fibroblasts (CAFs) are enriched in OC. Thus, reversing the suppressive TIME is considered an ideal candidate for improving the efficiency of immunotherapy. Nanoparticles encapsulating immunoregulatory agents can regulate immunocytes and improve the TIME to boost the antitumor immune response. In addition, some nanoparticle-mediated photodynamic and photothermal therapy can directly kill tumor cells and induce tumor immunogenic cell death to activate antigen-presenting cells and promote T cell infiltration. These advantages make nanoparticles promising candidates for modulating the TIME and improving OC immunotherapy. In this review, we analyzed the composition and function of the TIME in OC and summarized the current clinical progress of OC immunotherapy. Then, we expounded on the promising advances in nanomaterial-mediated immunotherapy for modulating the TIME in OC. Finally, we discussed the obstacles and challenges in the clinical translation of this novel combination treatment regimen. We believe this resourceful strategy will open the door to effective immunotherapy of OC and benefit numerous patients.