Tumor DNA circulates in the plasma of cancer patients admixed with DNA from noncancerous cells. The genomic landscape of plasma DNA has been characterized in metastatic castration-resistant prostate cancer (mCRPC) but the plasma methylome has not been extensively explored. Here, we performed next-generation sequencing (NGS) on plasma DNA with and without bisulfite treatment from mCRPC patients receiving either abiraterone or enzalutamide in the pre- or post-chemotherapy setting. Principal component analysis on the mCRPC plasma methylome indicated that the main contributor to methylation variance (principal component one, or PC1) was strongly correlated with genomically determined tumor fraction (r = –0.96; P < 10^–8) and characterized by hypermethylation of targets of the polycomb repressor complex 2 components. Further deconvolution of the PC1 top-correlated segments revealed that these segments are comprised of methylation patterns specific to either prostate cancer or prostate normal epithelium. To extract information specific to an individual’s cancer, we then focused on an orthogonal methylation signature, which revealed enrichment for androgen receptor binding sequences and hypomethylation of these segments associated with AR copy number gain. Individuals harboring this methylation pattern had a more aggressive clinical course. Plasma methylome analysis can accurately quantitate tumor fraction and identify distinct biologically relevant mCRPC phenotypes.

Multiple myeloma (MM) is an incurable malignancy characterized by altered expression of coding and noncoding genes promoting tumor growth and drug resistance. Although the crucial role of long noncoding RNAs (lncRNAs) in MM is clearly established, the function of the noncoding RNAome, which might allow the design of novel therapeutics, is largely unknown. We performed an unbiased CRISPR-Cas9 loss-of-function screen of 671 lncRNAs in MM cells and their bortezomib (BZB)–resistant derivative. To rank functionally and clinically relevant candidates, we designed and used a bioinformatic prioritization pipeline combining functional data from cellular screens with prognostic and transcriptional data from patients with MM. With this approach, we unveiled and prioritized 8 onco-lncRNAs essential for MM cell fitness, associated with high expression and poor prognosis in patients with MM. The previously uncharacterized RP11-350G8.5 emerged as the most promising target, irrespective of BZB resistance. We (1) demonstrated the anti-tumoral effect obtained by RP11-350G8.5 inhibition in vitro and in vivo; (2) highlighted a modulation of the unfolded protein response and the induction of immunogenic cell death triggered by the RP11-350G8.5 knockout, via RNA sequencing and molecular studies; (3) characterized its cytoplasmic homing through RNA fluorescence in situ hybridization; and (4) predicted its 2-dimensional structure and identified 2 G-quadruplex and 3 hairpin-forming regions by biophysical assays, including thioflavin T, 1H nuclear magnetic resonance, and circular dichroism, to pave the way to the development of novel targeted therapeutics. Overall, we provided innovative insights about unexplored lncRNAs in MM and identified RP11-350G8.5 as an oncogenic target for treatment-naïve and BZB-resistant patients with MM.

Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient evolutionary relationships of metastases that evade treatment, we perform genome-wide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 167 metastatic regions from 11 organs harvested post-mortem from 10 men who died from prostate cancer. We identify diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number changes, we confirm a common clone of origin across metastases and diagnostic biopsies, and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. These autosome-defined clusters are characterized by cluster-specific AR gene architectures, and in two index cases are topologically more congruent than by chance (p-values 3.07 × 10⁻⁸ and 6.4 × 10⁻⁴). Integration with anatomical sites suggests patterns of spread and points of genomic divergence. Here, we show that copy number boundaries identify treatment-selected clones with putatively distinct lethal trajectories.

In the past few years, the role of long noncoding RNAs (lncRNAs) in tumor development and progression has been disclosed although their mechanisms of action remain to be elucidated. An important contribution to the comprehension of lncRNAs biology in cancer could be obtained through the integrated analysis of multiple expression datasets. However, the growing availability of public datasets requires new data mining techniques to integrate and describe relationship among data. In this perspective, we explored the powerness of the Association Rule Mining (ARM) approach in gene expression data analysis. By the ARM method, we performed a meta-analysis of cancer-related microarray data which allowed us to identify and characterize a set of ten lncRNAs simultaneously altered in different brain tumor datasets. The expression profiles of the ten lncRNAs appeared to be sufficient to distinguish between cancer and normal tissues. A further characterization of this lncRNAs signature through a comodulation expression analysis suggested that biological processes specific of the nervous system could be compromised.

Purpose: Taxanes are life-prolonging treatments for patients with advanced prostate cancer. However, treatment resistance and lethal disease invariably develop. Here we used liquid biopsies to identify and characterize resistance to cabazitaxel. Experimental Design: We analyzed serial plasma from patients with metastatic castration-resistant prostate cancer treated with cabazitaxel in a prospective biomarker study (NCT03381326, N = 97). ctDNA was studied using a bespoke, targeted genomic test (PCF_SELECT). Clinical and molecular variables were evaluated for associations with overall survival (OS) and radiographic progression-free survival (rPFS). Results: Patients categorized by median ctDNA fraction had progressively worse survival for ctDNA-negative versus -low versus -high patients (median OS: 26.8, 12.4, and 8.2 months; median rPFS: 8.0, 5.3, and 3.1 months). A ctDNA fraction increase at cycle 3 compared with patients who remained ctDNA negative associated with shorter OS [median, 7.5 vs. 29.9 months; HR, 4.60 (95% confidence interval, 2.06–10.28), P < 0.0001] and rPFS [median, 2.6 vs. 8.2 months; HR, 3.73 (95% confidence interval, 1.75–7.93), P < 0.0001]. Plasma DNA collected at progression on an androgen receptor pathway inhibitor was enriched for alterations in the androgen receptor gene, whereas after a taxane (docetaxel before cabazitaxel or after cabazitaxel), there was enrichment of copy-number gains of genes sited on chromosome 3 (ATR, PIK3CB, MLH1, and FANCD2) or involved in cell cycle regulation, including mutually exclusive alterations in CCND1 and CDKN1B. Conclusions: Sequential liquid biopsy identifies ctDNA features associated with treatment benefit in patients with metastatic castration-resistant prostate cancer treated with cabazitaxel. There was overlap of gene alterations selected for at progression on docetaxel or cabazitaxel, in part explaining cross-resistance.

Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient relationships of metastases that evade treatment, we performed genome-wide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 142 metastatic regions from 10 organs harvested post-mortem from nine men who died from prostate cancer. We identified diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number change, we confirmed a common clone of origin across metastases and diagnostic biopsies; and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations and cluster-specific AR gene architectures. Copy number boundaries identified treatment-selected clones with distinct lethal trajectories.