Combined impact of lipidomic and genetic aberrations on clinical outcomes in metastatic castration-resistant prostate cancer

Targeting PI3K/AKT/mTOR signaling to overcome drug resistance in cancer

This review comprehensively explores the challenge of drug resistance in cancer by focusing on the pivotal PI3K/AKT/mTOR pathway, elucidating its role in oncogenesis and resistance mechanisms across various cancer types. It meticulously examines the diverse mechanisms underlying resistance, including genetic mutations, feedback loops, and microenvironmental factors, while also discussing the associated resistance patterns. Evaluating current therapeutic strategies targeting this pathway, the article highlights the hurdles encountered in drug development and clinical trials. Innovative approaches to overcome resistance, such as combination therapies and precision medicine, are critically analyzed, alongside discussions on emerging therapies like immunotherapy and molecularly targeted agents. Overall, this comprehensive review not only sheds light on the complexities of resistance in cancer but also provides a roadmap for advancing cancer treatment.

Untargeted lipidomics reveal association of elevated plasma C18 ceramide levels with reduced survival in metastatic castration-resistant prostate cancer patients

Emerging evidence highlights the potential prognostic relevance of circulating lipids in metastatic castration-resistant prostate cancer (mCRPC), with a proposed 3-lipid signature. This study aims to analyze the lipidomic profiles of individuals with mCRPC to identify lipid species that could serve as predictive indicators of prognosis and therapeutic response. Plasma samples were collected from mCRPC patients initiating first-line treatment (1 L) (n = 29) and those previously treated with at least two lines of therapy (> 2 L) (n = 19), including an androgen-receptor signaling inhibitor and a taxane. Employing an untargeted lipidomic approach, lipids were extracted from the plasma samples and subjected to analysis. A comprehensive identification and quantification of 789 plasma lipids was achieved. Notably, 75 species displayed significant dysregulation in > 2 L patients in comparison to the 1 L group. Among these, 63 species exhibited elevated levels, while 12 were reduced. Patients included in > 2 L cohort showed elevated levels of acylcarnitines (CAR), diacylglycerols (DG), phosphatidylethanolamines (PE), triacylglycerols (TG), and ceramides (Cer). Notably, some upregulated lipids, including CAR 14:0, CAR 24:1, Cer d18:1/16:0, Cer d18:1/18:0 (C18 Cer), Cer d18:2/18:0, Cer d18:1/24:1, and Cer d20:1/24:1, showed significant associations with overall survival (OS) in univariate models. Specifically, increased levels of C18 Cer remained significantly associated with poorer OS in the multivariate model, even after adjusting for treatment line and PSA levels (Hazard Ratio: 3.59 [95% Confidence Interval 1.51-8.52], p = 0.004). Employing quantitative mass spectrometry, our findings underscore the independent prognostic significance of C18 Cer in individuals with mCRPC. This discovery opens avenues for further studies within this field.

Multi-Omic Integration of Blood-Based Tumor-Associated Genomic and Lipidomic Profiles Using Machine Learning Models in Metastatic Prostate Cancer

PURPOSE

To determine prognostic and predictive clinical outcomes in metastatic hormone-sensitive prostate cancer (mHSPC) and metastatic castrate-resistant prostate cancer (mCRPC) on the basis of a combination of plasma-derived genomic alterations and lipid features in a longitudinal cohort of patients with advanced prostate cancer.

METHODS

A multifeature classifier was constructed to predict clinical outcomes using plasma-based genomic alterations detected in 120 genes and 772 lipidomic species as informative features in a cohort of 71 patients with mHSPC and 144 patients with mCRPC. Outcomes of interest were collected over 11 years of follow-up. These included in mHSPC state early failure of androgen-deprivation therapy (ADT) and exceptional responders to ADT; early death (poor prognosis) and long-term survivors in mCRPC state. The approach was to build binary classification models that identified discriminative candidates with optimal weights to predict outcomes. To achieve this, we built multi-omic feature-based classifiers using traditional machine learning (ML) methods, including logistic regression with sparse regularization, multi-kernel Gaussian process regression, and support vector machines.

RESULTS

The levels of specific ceramides (d18:1/14:0 and d18:1/17:0), and the presence of CHEK2 mutations, AR amplification, and RB1 deletion were identified as the most crucial factors associated with clinical outcomes. Using ML models, the optimal multi-omics feature combination determined resulted in AUC scores of 0.751 for predicting mHSPC survival and 0.638 for predicting ADT failure; and in mCRPC state, 0.687 for prognostication and 0.727 for exceptional survival. The models were observed to be superior than using a limited candidate number of features for developing multi-omic prognostic and predictive signatures.

CONCLUSION

Using a ML approach that incorporates multiple omic features improves the prediction accuracy for metastatic prostate cancer outcomes significantly. Validation of these models will be needed in independent data sets in future.

Phase II proof-of-concept study of atorvastatin in castration-resistant prostate cancer

OBJECTIVES

To test for evidence of statin-mediated effects in patients with castration-resistant prostate cancer (CRPC) as post-diagnosis use of statins in patients with prostate cancer is associated with favourable survival outcome.

PATIENTS AND METHODS

The SPECTRE trial was a 6-weeks-long proof-of-concept single-arm Phase II treatment trial, combining atorvastatin and androgen deprivation therapy in patients with CRPC (regardless of metastatic status), designed to test for evidence of statin-mediated effects in patients with CRPC. The primary study endpoint was the proportion of patients achieving a ≥50% drop from baseline in prostate-specific antigen (PSA) levels at any time over the 6-week period of atorvastatin medication (PSA response). Exploratory endpoints include PSA velocity and serum metabolites identified by mass spectrometry .

RESULTS

At the scheduled interim analysis, one of 12 patients experienced a ≥50% drop in PSA levels (primary endpoint), with ≥2 patients satisfying the primary endpoint required for further recruitment. All 12 patients experienced substantial falls in serum cholesterol levels following statin treatment. While all patients had comparable pre-study PSA velocities, six of 12 patients showed decreased PSA velocities after statin treatment, suggestive of disease stabilization. Unbiased metabolomics analysis on serial weekly blood samples identified tryptophan to be the dominant metabolite associated with patient response to statin.

CONCLUSIONS

Data from the SPECTRE study provide the first evidence of statin-mediated effects on CRPC and early sign of disease stabilization. Our data also highlight the possibility of altered tryptophan metabolism being associated with tumour response.

Targeting lipid metabolism in metastatic prostate cancer

Despite key advances in the treatment of prostate cancer (PCa), a proportion of men have de novo resistance, and all will develop resistance to current therapeutics over time. Aberrant lipid metabolism has long been associated with prostate carcinogenesis and progression, but more recently there has been an explosion of preclinical and clinical data which is informing new clinical trials. This review explores the epidemiological links between obesity and metabolic syndrome and PCa, the evidence for altered circulating lipids in PCa and their potential role as biomarkers, as well as novel therapeutic strategies for targeting lipids in men with PCa, including therapies widely used in cardiovascular disease such as statins, metformin and lifestyle modification, as well as novel targeted agents such as sphingosine kinase inhibitors, DES1 inhibitors and agents targeting FASN and beta oxidation.

Addressing the Reciprocal Crosstalk between the AR and the PI3K/AKT/mTOR Signaling Pathways for Prostate Cancer Treatment

The reduction in androgen synthesis and the blockade of the androgen receptor (AR) function by chemical castration and AR signaling inhibitors represent the main treatment lines for the initial stages of prostate cancer. Unfortunately, resistance mechanisms ultimately develop due to alterations in the AR pathway, such as gene amplification or mutations, and also the emergence of alternative pathways that render the tumor less or, more rarely, completely independent of androgen activation. An essential oncogenic axis activated in prostate cancer is the phosphatidylinositol-3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway, as evidenced by the frequent alterations of the negative regulator phosphatase and tensin homolog (PTEN) and by the activating mutations in PI3K subunits. Additionally, crosstalk and reciprocal feedback loops between androgen signaling and the PI3K/AKT/mTOR signaling cascade that activate pro-survival signals and play an essential role in disease recurrence and progression have been evidenced. Inhibitors addressing different players of the PI3K/AKT/mTOR pathway have been evaluated in the clinic. Only a limited benefit has been reported in prostate cancer up to now due to the associated side effects, so novel combination approaches and biomarkers predictive of patient response are urgently needed. Here, we reviewed recent data on the crosstalk between AR signaling and the PI3K/AKT/mTOR pathway, the selective inhibitors identified, and the most advanced clinical studies, with a focus on combination treatments. A deeper understanding of the complex molecular mechanisms involved in disease progression and treatment resistance is essential to further guide therapeutic approaches with improved outcomes.

Modulation of Plasma Lipidomic Profiles in Metastatic Castration-Resistant Prostate Cancer by Simvastatin

Elevated circulating sphingolipids are associated with shorter overall survival and therapeutic resistance in metastatic castration-resistant prostate cancer (mCRPC), suggesting that perturbations in sphingolipid metabolism promotes prostate cancer growth. This study assessed whether addition of simvastatin to standard treatment for mCRPC can modify a poor prognostic circulating lipidomic profile represented by a validated 3-lipid signature (3LS). Men with mCRPC (n = 27) who were not on a lipid-lowering agent, were given simvastatin for 12 weeks (40 mg orally, once daily) with commencement of standard treatment. Lipidomic profiling was performed on their plasma sampled at baseline and after 12 weeks of treatment. Only 11 men had the poor prognostic 3LS at baseline, of whom five (45%) did not retain the 3LS after simvastatin treatment (expected conversion rate with standard treatment = 19%). At baseline, the plasma profiles of men with the 3LS displayed higher levels (p < 0.05) of sphingolipids (ceramides, hexosylceramides and sphingomyelins) than those of men without the 3LS. These plasma sphingolipids were reduced after statin treatment in men who lost the 3LS (mean decrease: 23−52%, p < 0.05), but not in men with persistent 3LS, and were independent of changes to plasma cholesterol, LDL-C or triacylglycerol. In conclusion, simvastatin in addition to standard treatment can modify the poor prognostic circulating lipidomic profile in mCRPC into a more favourable profile at twice the expected conversion rate.