In situ Metabolic Profiling of Ovarian Cancer Tumor Xenografts: A Digital Pathology Approach

MRRM: Advanced Biomarker Alignment in Multi-Staining Pathology Images via Multi-Scale Ring Rotation-Invariant Matching

Pathology image matching is crucial for assisting pathologists in the comprehensive diagnosis of cancerous areas. However, variations in image rotation and staining caused by inherent slide imaging techniques increase the burden on pathologists, complicating the examination of cancer across different pathology slides. To address this challenge, we introduce multi-scale ring rotation-invariant matching (MRRM), which improves image matching efficiency using ring topology, assisting pathologists in robustly aligning biomarker information across various pathology images. Specifically, by employing multi-scale rings as convolution kernels, we accurately locate keypoints from the differencing of the ring pyramid, which not only enhances the likelihood of successful pathology image matching but also supports our feature descriptor in achieving advantageous performance in rotation-invariance. Experiments show that with manually annotated golden landmarks as the standard in 81 cases, exhibiting significantly superior matching accuracy (130.93 $\,\mu \mathrm{m}$) and a success rate of 93.83% compared to other methods, particularly in cases with rotated pathology images. This meets the routine diagnostic requirements of pathologists for cancer diagnosis.

Pathogenic mitochondrial DNA variants are associated with response to anti-VEGF therapy in ovarian cancer PDX models

BACKGROUND

Mitochondrial DNA (mtDNA) pathogenic variants have been reported in several solid tumors including ovarian cancer (OC), the most lethal gynecologic malignancy, and raised interest as they potentially induce mitochondrial dysfunction and rewiring of cellular metabolism. Despite advances in recent years, functional characterization of mtDNA variants in cancer and their possible modulation of drug response remain largely uncharted.

METHODS

Here, we characterized mtDNA variants in OC patient derived xenografts (PDX) and investigated their impact on cancer cells at multiple levels.

RESULTS

Genetic analysis revealed that mtDNA variants predicted as pathogenic, mainly involving complex I and IV genes, were present in all but one PDX (n = 20) at different levels of heteroplasmy, including 7 PDXs with homoplasmic variants. Functional analyses demonstrated that pathogenic mtDNA variants impacted on respiratory complexes activity and subunits abundance as well as on mitochondrial morphology. Moreover, PDX cells bearing homoplasmic mtDNA variants behaved as glucose-addicted and could barely survive glucose starvation in vitro. RNA-seq analysis indicated that mtDNA mutated (heteroplasmy > 50%) PDXs were endowed with upregulated glycolysis and other pathways connected with cancer metabolism. These findings led us to investigate whether pathogenic mtDNA variants correlated with response to anti-VEGF therapy, since the latter was shown to reduce glucose availability in tumors. Strikingly, PDXs bearing homoplasmic pathogenic mtDNA variants associated with improved survival upon anti-VEGF treatment in mice, compared with mtDNA wild type or low heteroplasmy PDXs.

CONCLUSIONS

These results hint at mtDNA variants as potential biomarkers of response to antiangiogenic drugs.

Impact of metabolism-related markers on outcomes in ovarian cancer patients: Findings of the MITO16A/MaNGO-OV2 trial

INTRODUCTION

In ovarian cancer, expression of metabolism-related markers has been investigated in several studies focusing on individual markers; however, a parallel quantitative evaluation of markers mapping to distinct metabolic processes and their prognostic value in large patient cohorts is still lacking.

METHODS

Here, by using immunohistochemistry followed by digital pathology, we investigated the expression of several markers related to glycolysis including monocarboxylate transporter 1 and 4 (MCT1, MCT4), glutamine metabolism (glutaminase, GLS) and hypoxia/acidosis (carbonic anhydrase 9, CA IX) in tissue microarrays of > 300 patients recruited in the MITO16A clinical trial, which involved treatment of ovarian cancer patients with carboplatin/taxol plus bevacizumab.

RESULTS

Regarding the prognostic impact of these markers, results indicate that GLS expression correlated with progression-free survival, but this effect disappeared when data were corrected for multiple testing. All other markers showed no correlation with clinical outcome.

CONCLUSION

These results indicate marked heterogeneity of expression of metabolism-associated markers in ovarian cancer; however, there was a lack of association with clinical benefit after chemotherapy/anti-vascular endothelial growth factor treatment. Notwithstanding the lack of prognostic value, knowledge of the pattern of expression of these biomarkers in tumors can be useful for patient stratification purposes when new drugs targeting these metabolic pathways will be tested.

Scientific and clinical relevance of non-cellular tumor microenvironment components in ovarian cancer chemotherapy resistance

The tumor microenvironment (TME) components play a crucial role in cancer cells' resistance to chemotherapeutic agents. This phenomenon is exceptionally fundamental in patients with ovarian cancer (OvCa), whose outcome depends mainly on their response to chemotherapy. Until now, most reports have focused on the role of cellular components of the TME, while less attention has been paid to the stroma and other non-cellular elements of the TME, which may play an essential role in the therapy resistance. Inhibiting these components could help define new therapeutic targets and potentially restore chemosensitivity. The aim of the present article is both to summarize the knowledge about non-cellular components of the TME in the development of OvCa chemoresistance and to suggest targeting of non-cellular elements of the TME as a valuable strategy to overcome chemoresistance and to develop new therapeutic strategies in OvCA patients.

Anti-VEGF therapy selects for clones resistant to glucose starvation in ovarian cancer xenografts

BACKGROUND

Genetic and metabolic heterogeneity are well-known features of cancer and tumors can be viewed as an evolving mix of subclonal populations, subjected to selection driven by microenvironmental pressures or drug treatment. In previous studies, anti-VEGF therapy was found to elicit rewiring of tumor metabolism, causing marked alterations in glucose, lactate ad ATP levels in tumors. The aim of this study was to evaluate whether differences in the sensitivity to glucose starvation existed at the clonal level in ovarian cancer cells and to investigate the effects induced by anti-VEGF therapy on this phenotype by multi-omics analysis.

METHODS

Clonal populations, obtained from both ovarian cancer cell lines (IGROV-1 and SKOV3) and tumor xenografts upon glucose deprivation, were defined as glucose deprivation resistant (GDR) or glucose deprivation sensitive (GDS) clones based on their in vitro behaviour. GDR and GDS clones were characterized using a multi-omics approach, including genetic, transcriptomic and metabolic analysis, and tested for their tumorigenic potential and reaction to anti-angiogenic therapy.

RESULTS

Two clonal populations, GDR and GDS, with strikingly different viability following in vitro glucose starvation, were identified in ovarian cancer cell lines. GDR clones survived and overcame glucose starvation-induced stress by enhancing mitochondrial oxidative phosphorylation (OXPHOS) and both pyruvate and lipids uptake, whereas GDS clones were less able to adapt and died. Treatment of ovarian cancer xenografts with the anti-VEGF drug bevacizumab positively selected for GDR clones that disclosed increased tumorigenic properties in NOD/SCID mice. Remarkably, GDR clones were more sensitive than GDS clones to the mitochondrial respiratory chain complex I inhibitor metformin, thus suggesting a potential therapeutic strategy to target the OXPHOS-metabolic dependency of this subpopulation.

CONCLUSION

A glucose-deprivation resistant population of ovarian cancer cells showing druggable OXPHOS-dependent metabolic traits is enriched in experimental tumors treated by anti-VEGF therapy.

Metabolic classification of non-small cell lung cancer patient-derived xenografts by a digital pathology approach: A pilot study

Introduction

Genetically characterized patient-derived tumor xenografts (PDX) are a valuable resource to understand the biological complexity of cancer and to investigate new therapeutic approaches. Previous studies, however, lack information about metabolic features of PDXs, which may limit testing of metabolism targeting drugs.

Methods

In this pilot study, we investigated by immunohistochemistry (IHC) expression of five essential metabolism-associated markers in a set of lung adenocarcinoma PDX samples previously established and characterized. We exploited digital pathology to quantify expression of the markers and correlated results with tumor cell proliferation, angiogenesis and time of PDX growth in mice.

Results

Our results indicate that the majority of the analyzed PDX models rely on oxidative phosphorylation (OXPHOS) metabolism, either alone or in combination with glucose metabolism. Double IHC enabled us to describe spatial expression of the glycolysis-associated monocarboxylate transporter 4 (MCT4) marker and the OXPHOS-associated glutaminase (GLS) marker. GLS expression was associated with cell proliferation and with expression of liver-kinase B1 (LKB1), a tumor suppressor involved in the regulation of multiple metabolic pathways. Acetyl CoA carboxylase (ACC) was associated with the kinetics of PDX growth.

Conclusion

Albeit limited by the small number of samples and markers analyzed, metabolic classification of existing collections of PDX by this mini panel will be useful to inform pre-clinical testing of metabolism-targeting drugs.

Energy Substrate Transporters in High-Grade Ovarian Cancer: Gene Expression and Clinical Implications

Ovarian cancer is a non-homogenous malignancy. High-grade serous carcinoma (HGSC) is the most common subtype, and its drug resistance mechanisms remain unclear. Despite the advantages of modern pharmacotherapy, high-grade ovarian cancer is associated with a poor prognosis and research into targeted therapies is in progress. The aim of the study was to assess the dominant energy substrate transport mechanism in ovarian cancer cells and to verify whether genomic aberrations could predict clinical outcomes using the Cancer Genome Atlas (TCGA) dataset. Total RNA was extracted from HGSC frozen tissues, and the expression of selected genes was compared to respective controls. GLUT1, FABPpm, MCT4 and SNAT1 genes were significantly overexpressed in carcinomas compared with controls, while expression of CD36/SR-B2, FATP1, FABP4, GLUT4, ASCT2 and LPL was decreased. No differences were found in FATP4, LAT1, MCT1 and FASN. The transcript content of mitochondrial genes such as PGC-1α, TFAM and COX4/1 was similar between groups, while the β-HAD level declined in ovarian cancer. Additionally, the MCT4 level was reduced and PGC-1α was elevated in cancer tissue from patients with ‘small’ primary tumor and omental invasion accompanied by ascites as compared to patients that exhibited greater tendencies to metastasize to lymph nodes with clear omentum. Based on TCGA, higher FABP4 and LPL and lower TFAM expression indicated poorer overall survival in patients with ovarian cancer. In conclusion, the presented data show that there is no exclusive energy substrate in HGSC. However, this study indicates the advantage of glucose and lactate transport over fatty acids, thereby suggesting potential therapeutic intervention targets to impede ovarian cancer growth.

PGK1 Is a Key Target for Anti-Glycolytic Therapy of Ovarian Cancer: Based on the Comprehensive Analysis of Glycolysis-Related Genes

Reprogramming of energy metabolism is a key hallmark of cancer, which provides a new research perspective for exploring the development of cancer. However, the most critical target of anti-glycolytic therapy for ovarian cancer remains unclear. Therefore, in the present study, Oncomine, GEPIA, and HPA databases, combined with clinical specimens of different histological types of ovarian cancer were used to comprehensively evaluate the expression levels of glycolysis-related metabolite transporters and enzymes in ovarian cancer. We selected phosphoglycerate kinase 1 (PGK1), which showed the greatest prognostic value in the Kaplan-Meier Plotter database, for subsequent validation. Immunochemistry assays confirmed that PGK1 was highly expressed in ovarian cancer. The PGK1 expression level was an independent risk factor for the survival and prognosis of patients with ovarian cancer. Functional analysis showed that the PGK1 expression level was positively correlated with the infiltration of neutrophils. Cell experiments confirmed that inhibiting PGK1 expression in ovarian cancer cells could reduce the epithelial-mesenchymal transition (EMT) process, resulting in loss of cell migration and invasion ability. The small molecule NG52 dose-dependently inhibited the proliferation of ovarian cancer cells. In addition, NG52 reduced the EMT process and reversed the Warburg effect by inhibiting PGK1 activity. Therefore, PGK1 is an attractive molecular target for anti-glycolytic therapy of ovarian cancer.

Expression and prognostic value of TRPM7 in canine mammary tumours

Canine mammary gland tumour (CMTs) are one of the most commonly found tumours in intact female dogs. A previous study on canine mammary glands demonstrated the presence of the transient receptor potential melastatin 7 (TRPM7) ion channels in healthy canine mammary tissues. However, the significance of TRPM7 in CMT is not yet known. TRPM7 is a Ca²⁺ and Mg²⁺ permeable cation channel that contains a protein kinase domain. The aim of this study was to determine TRPM7 expression in 57 benign and malignant CMT tissues of dogs using immunohistochemistry (IHC) and evaluate its correlation with clinicopathological features and explore the potential prognostic value of TRPM7 in a prospective survival study. IHC analysis shows that TRPM7 was expressed in the cytoplasm of neoplastic epithelial cells. Moreover, TRPM7 expression was significantly associated with tumour malignancy (P = .027), Ki-67 index (P < .0001) and metastasis (P < .0001). Survival curve analysis indicates that high TRPM7 expression was significantly associated with poor disease-free (P = .035) and overall survival (P = .011) in malignant CMTs. Our results demonstrate that TRPM7 is expressed in CMTs and that its expression is positively correlated with clinicopathological parameters. Thus, TRPM7 was assumed to be a potential prognostic factor for CMTs.

Genetic Perturbation of Pyruvate Dehydrogenase Kinase 1 Modulates Growth, Angiogenesis and Metabolic Pathways in Ovarian Cancer Xenografts

Pyruvate dehydrogenase kinase 1 (PDK1) blockade triggers are well characterized in vitro metabolic alterations in cancer cells, including reduced glycolysis and increased glucose oxidation. Here, by gene expression profiling and digital pathology-mediated quantification of in situ markers in tumors, we investigated effects of PDK1 silencing on growth, angiogenesis and metabolic features of tumor xenografts formed by highly glycolytic OC316 and OVCAR3 ovarian cancer cells. Notably, at variance with the moderate antiproliferative effects observed in vitro, we found a dramatic negative impact of PDK1 silencing on tumor growth. These findings were associated with reduced angiogenesis and increased necrosis in the OC316 and OVCAR3 tumor models, respectively. Analysis of viable tumor areas uncovered increased proliferation as well as increased apoptosis in PDK1-silenced OVCAR3 tumors. Moreover, RNA profiling disclosed increased glucose catabolic pathways-comprising both oxidative phosphorylation and glycolysis-in PDK1-silenced OVCAR3 tumors, in line with the high mitotic activity detected in the viable rim of these tumors. Altogether, our findings add new evidence in support of a link between tumor metabolism and angiogenesis and remark on the importance of investigating net effects of modulations of metabolic pathways in the context of the tumor microenvironment.