The genes controlling normal function of citrate and spermine secretion are lost in aggressive prostate cancer and prostate model systems

Metabolic readouts of tumor instructed normal tissues (TINT) identify aggressive prostate cancer subgroups for tailored therapy

Introduction

Prostate cancer (PC) diagnosis relies on histopathological examination of prostate biopsies, which is restricted by insufficient sampling of all tumors present. Including samples from non-PC but tumor instructed normal tissues (TINT) may increase the diagnostic power by displaying the adaptive responses in benign tissues near tumors.

Methods

Here, we applied high-resolution magic angle spinning nuclear magnetic resonance (HR MAS NMR) to identify metabolomic biomarkers of possible diagnostic value in benign prostate tissues near low/high-grade tumors.

Results

Benign samples near high-grade tumors (B ISUP 3 + 4) exhibited altered metabolic profiles compared to those close to low-grade tumors (B ISUP 1 + 2). The levels of six metabolites differentiated between the two groups; myo-inositol, lysine, serine and combined signal of lysine/leucine/arginine were increased in benign samples near high-grade tumors (B ISUP 3 + 4) compared to near low-grade tumors (B ISUP 1 + 2), while levels of ethanolamine and lactate were decreased. Additionally, we revealed metabolic differences in non-cancer tissues as a function of their distance to the nearest tumor. Eight metabolites (glutathione, glutamate, combined signal of glutamate/glutamine - glx, glycerol, inosine, ethanolamine, serine and arginine) differentiated between benign tissue located close to the tumor (d ≤ 5 mm) compared to those far away (d ≥ 1 cm).

Conclusion

Our HR MAS NMR-based approach identified metabolic signatures in prostate biopsies that reflect the response of benign tissues to the presence of nearby located tumors in the same prostate and confirmed the power of the TINT concept for improved PC diagnostics and understanding of tumor-tissue interactions.

Spatial integration of multi-omics data from serial sections using the novel Multi-Omics Imaging Integration Toolset

BACKGROUND

Truly understanding the cancer biology of heterogeneous tumors in precision medicine requires capturing the complexities of multiple omics levels and the spatial heterogeneity of cancer tissue. Techniques like mass spectrometry imaging (MSI) and spatial transcriptomics (ST) achieve this by spatially detecting metabolites and RNA but are often applied to serial sections. To fully leverage the advantage of such multi-omics data, the individual measurements need to be integrated into 1 dataset.

RESULTS

We present the Multi-Omics Imaging Integration Toolset (MIIT), a Python framework for integrating spatially resolved multi-omics data. A key component of MIIT's integration is the registration of serial sections for which we developed a nonrigid registration algorithm, GreedyFHist. We validated GreedyFHist on 244 images from fresh-frozen serial sections, achieving state-of-the-art performance. As a proof of concept, we used MIIT to integrate ST and MSI data from prostate tissue samples and assessed the correlation of a gene signature for citrate-spermine secretion derived from ST with metabolic measurements from MSI.

CONCLUSION

MIIT is a highly accurate, customizable, open-source framework for integrating spatial omics technologies performed on different serial sections.

PSA, an outdated biomarker for prostate cancer: In search of a more specific biomarker, citrate takes the spotlight

The prevailing biomarker employed for prostate cancer (PCa) screening and diagnosis is the prostate-specific antigen (PSA). Despite excellent sensitivity, PSA lacks specificity, leading to false positives, unnecessary biopsies and overdiagnosis. Consequently, PSA is increasingly less used by clinicians, thus underscoring the imperative for the identification of new biomarkers. An emerging biomarker in this context is citrate, a molecule secreted by the normal prostate, which has been shown to be inversely correlated with PCa. Here, we discuss about PSA and its usage for PCa diagnosis, its lack of specificity, and the various conditions that can affect its levels. We then provide our vision about what we think would be a valuable addition to our PCa diagnosis toolkit, citrate. We describe the unique citrate metabolic program in the prostate and how this profile is reprogrammed during carcinogenesis. Finally, we summarize the evidence that supports the usage of citrate as a biomarker for PCa diagnosis, as it can be measured in various patient samples and be analyzed by several methods. The unique relationship between citrate and PCa, combined with the stability of citrate levels in other prostate-related conditions and the simplicity of its detection, further accentuates its potential as a biomarker.

Metabolic Adaptation and Cellular Stress Response As Targets for Cancer Therapy

Cancer cells, which divide indefinitely and without control, are frequently exposed to various stress factors but manage to adapt and survive. The mechanisms by which cancer cells maintain cellular homeostasis and exploit stress conditions are not yet clear. Here, we elucidate the roles of diverse cellular metabolism and its regulatory mechanisms, highlighting the essential role of metabolism in cellular composition and signal transduction. Cells respond to various stresses, including DNA damage, energy stress, and oxidative stress, thereby causing metabolic alteration. We provide profound insight into the adaptive mechanisms employed by cancer cells to ensure their survival among internal and external stressors through a comprehensive analysis of the correlation between metabolic alterations and cellular stress. Furthermore, this research establishes a robust framework for the development of innovative therapeutic strategies that specifically target the cellular adaptations of cancer cells.

Mechanisms of Prostate Cancer Cells Survival and Their Therapeutic Targeting

Prostate cancer (PCa) is today the second most common cancer in the world, with almost 400,000 deaths annually. Multiple factors are involved in the etiology of PCa, such as older age, genetic mutations, ethnicity, diet, or inflammation. Modern treatment of PCa involves radical surgical treatment or radiation therapy in the stages when the tumor is limited to the prostate. When metastases develop, the standard procedure is androgen deprivation therapy, which aims to reduce the level of circulating testosterone, which is achieved by surgical or medical castration. However, when the level of testosterone decreases to the castration level, the tumor cells adapt to the new conditions through different mechanisms, which enable their unhindered growth and survival, despite the therapy. New knowledge about the biology of the so-called of castration-resistant PCa and the way it adapts to therapy will enable the development of new drugs, whose goal is to prolong the survival of patients with this stage of the disease, which will be discussed in this review.