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Background and objectiveWe characterized tumor prostate-specific membrane antigen (PSMA) levels as a reflection of cancer biology and treatment sensitivities for treatment-naïve prostate cancer.MethodsWe first correlated PSMA positron emission tomography (PET) maximum standardized uptake values (SUVmax) in primary prostate cancer with tumor FOLH1 (PSMA RNA abundance) to establish RNA as a proxy (n = 55). We then discovered and validated molecular pathways associated with PSMA RNA levels in two large primary tumor cohorts. We validated those associations in independent cohorts (18 total; 5684 tumor samples) to characterize the pathways and treatment responses associated with PSMA.Key findings and limitationsPSMA RNA abundance correlates moderately with SUVmax (ρ = 0.41). In independent cohorts, androgen receptor signaling is more active in tumors with high PSMA. Accordingly, patients with high PSMA tumors experienced longer cancer-specific survival when managed with androgen deprivation therapy for biochemical recurrence (adjusted hazard ratio [AHR] 0.54 [0.34-0.87]; n = 174). PSMA low tumors possess molecular markers of resistance to radiotherapy. Consistent with this, patients with high PSMA tumors experience longer time to recurrence following primary radiotherapy (AHR 0.50 [0.28-0.90]; n = 248). In the SAKK09/10 trial (n = 224), patients with high PSMA tumors who were managed with salvage radiotherapy experienced longer time to progression in the 64-Gy arm (restricted mean survival time [RMST] +7.60 [0.05-15.16]), but this effect was mitigated in the 70-Gy arm (RMST 3.52 [-3.30 to 10.33]). Limitations include using PSMA RNA as a surrogate for PET SUVmax.Conclusions and clinical implicationsPSMA levels in treatment-naïve prostate cancer differentiate tumor biology and treatment susceptibilities. These results warrant validation using PET metrics to substantiate management decisions based on imaging.

313 Background: Advanced molecular PET/CT (mPET) studies are increasingly being utilized in conjunction with multiparametric MRI (mpMRI) to evaluate the burden of radiorecurrent disease in men who develop a biochemical recurrence following definitive radiotherapy (RT) for prostate cancer (PCa). However, radiographic concordance with pathologic confirmation of radiorecurrent disease in this setting is poorly described. We sought to conduct a patient-level analysis comparing concordance of radiographic and pathologic findings between mpMRI and mPET. Methods: Men who had previously undergone definitive RT for PCa and subsequently experienced treatment failure defined by the Phoenix definition were enrolled in a prospective registry study wherein radiographically identified local PCa recurrences were biopsied using mpMRI or mPET fusion (Artemis) with real-time ultrasound. Prior to biopsy, men underwent diagnostic imaging with mpMRI, advanced mPET (68Ga-PSMA-11 or 18F-FACBC), or both in order to identify a biopsy target. At least one imaging modality had to reveal a recurrent lesion based on PIRADS or PROMISE imaging classifications in order to prompt biopsy. Radiographic and pathologic findings were classified as either “treatment effect” or “recurrent disease”. Using biopsy as the reference standard, positive predictive value (PPV) was evaluated for mpMRI and mPET modalities separately. Results: Of 28 patients with radiographic recurrence on mpMRI or mPET, 10/28 (35.7%) exhibited treatment effect without evidence of active cancer on biopsy confirmation. Prostate adenocarcinoma was identified in 17/28 patient biopsies, whereas small cell prostate cancer was present in 1 patient. All 28 men underwent mpMRI prior to biopsy and 23/28 (82.1%) additionally underwent mPET; 19/23 (82.6%) underwent 68Ga-PSMA-11 and 4/23 (17.4%) were imaged with 18F-FACBC. Concordance in the assessment of recurrent disease between mpMRI and mPET was achieved in 12/23 (52.2%) men who underwent both imaging modalities. Among the 28 men who underwent mpMRI, PPV was 0.84, whereas PPV for the 23 men who underwent mPET was 0.70. Conclusions: In patients for whom clinical suspicion of radiorecurrence was high enough to warrant a biopsy, pre-biopsy mpMRI outperforms mPET in terms of PPV for detecting pathologically confirmed locally radiorecurrent PCa. Used in tandem, mpMRI and mPET might better select appropriate candidates for biopsy than either radiographic modality alone. While advanced mPET remains promising for detecting distant recurrences at the time of RT failure, biopsy confirmation following radiographic detection of local radiorecurrence remains essential for evaluating the true burden of local recurrence.

Single-cell RNA sequencing studies have suggested that total mRNA content correlates with tumor phenotypes. Technical and analytical challenges, however, have so far impeded at-scale pan-cancer examination of total mRNA content. Here we present a method to quantify tumor-specific total mRNA expression (TmS) from bulk sequencing data, taking into account tumor transcript proportion, purity and ploidy, which are estimated through transcriptomic/genomic deconvolution. We estimate and validate TmS in 6,590 patient tumors across 15 cancer types, identifying significant inter-tumor variability. Across cancers, high TmS is associated with increased risk of disease progression and death. TmS is influenced by cancer-specific patterns of gene alteration and intra-tumor genetic heterogeneity as well as by pan-cancer trends in metabolic dysregulation. Taken together, our results indicate that measuring cell-type-specific total mRNA expression in tumor cells predicts tumor phenotypes and clinical outcomes.

Although cancer genomes are replete with noncoding mutations, the effects of these mutations remain poorly characterized. Here we perform an integrative analysis of 930 tumor whole genomes and matched transcriptomes, identifying a network of 193 noncoding loci in which mutations disrupt target gene expression. These 'somatic eQTLs' (expression quantitative trait loci) are frequently mutated in specific cancer tissues, and the majority can be validated in an independent cohort of 3,382 tumors. Among these, we find that the effects of noncoding mutations on DAAM1, MTG2 and HYI transcription are recapitulated in multiple cancer cell lines and that increasing DAAM1 expression leads to invasive cell migration. Collectively, the noncoding loci converge on a set of core pathways, permitting a classification of tumors into pathway-based subtypes. The somatic eQTL network is disrupted in 88% of tumors, suggesting widespread impact of noncoding mutations in cancer.

Many recent efforts to analyze cancer genomes involve aggregation of mutations within reference maps of molecular pathways and protein networks. Here, we find these pathway studies are impeded by molecular interactions that are functionally irrelevant to cancer or the patient's tumor type, as these interactions diminish the contrast of driver pathways relative to individual frequently mutated genes. This problem can be addressed by creating stringent tumor-specific networks of biophysical protein interactions, identified by signatures of epistatic selection during tumor evolution. Using such an evolutionarily selected pathway (ESP) map, we analyze the major cancer genome atlases to derive a hierarchical classification of tumor subtypes linked to characteristic mutated pathways. These pathways are clinically prognostic and predictive, including the TP53-AXIN-ARHGEF17 combination in liver and CYLC2-STK11-STK11IP in lung cancer, which we validate in independent cohorts. This ESP framework substantially improves the definition of cancer pathways and subtypes from tumor genome data.

We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbations coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with dual guide RNAs in three cell lines, comprising 141,912 tests of interaction. Numerous therapeutically relevant interactions were identified, and these patterns replicated with combinatorial drugs at 75% precision. From these results, we anticipate that cellular context will be critical to synthetic-lethal therapies.

Head and neck squamous cell carcinoma (HNSCC) is characterized by aggressive behavior with a propensity for metastasis and recurrence. Here we report a comprehensive analysis of the molecular and clinical features of HNSCC that govern patient survival. We find that TP53 mutation is frequently accompanied by loss of chromosome 3p and that the combination of these events is associated with a surprising decrease in survival time (1.9 years versus >5 years for TP53 mutation alone). The TP53-3p interaction is specific to chromosome 3p and validates in HNSCC and pan-cancer cohorts. In human papillomavirus (HPV)-positive tumors, in which HPV inactivates TP53, 3p deletion is also common and is associated with poor outcomes. The TP53-3p event is modified by mir-548k expression, which decreases survival further, and is mutually exclusive with mutations affecting RAS signaling. Together, the identified markers underscore the molecular heterogeneity of HNSCC and enable a new multi-tiered classification of this disease.

Many forms of cancer have multiple subtypes with different causes and clinical outcomes. Somatic tumor genome sequences provide a rich new source of data for uncovering these subtypes but have proven difficult to compare, as two tumors rarely share the same mutations. Here we introduce network-based stratification (NBS), a method to integrate somatic tumor genomes with gene networks. This approach allows for stratification of cancer into informative subtypes by clustering together patients with mutations in similar network regions. We demonstrate NBS in ovarian, uterine and lung cancer cohorts from The Cancer Genome Atlas. For each tissue, NBS identifies subtypes that are predictive of clinical outcomes such as patient survival, response to therapy or tumor histology. We identify network regions characteristic of each subtype and show how mutation-derived subtypes can be used to train an mRNA expression signature, which provides similar information in the absence of DNA sequence.

As the aging and cancer populations in the world continue to increase, the need for complements to traditional geriatric assessments and the logical incorporation of fast and reliable telehealth tools have become interlinked. In the United States, studies examining the use of telehealth for chronic disease management have shown promising results in small groups. The implementation of health technology on a broader scale requires older adults to both accept and adapt such innovation into routine medical care. Though the commercial and recreational use of new technology has increased in older individuals, the transition into creating a smart and connected home that can interface with both patients and healthcare professionals is in its early phases. Current limitations include an inherent digital divide, as well as concerns regarding privacy, data volume, rapid change, cost and reimbursement. The emergence of low-cost, high-fidelity wearable sensors with a spectrum of clinical utility may be the key to increased use and adaptation by older adults. An opportunity to utilize wearable sensors for objective and real-time assessment of older patients with cancer for baseline functional status and treatment toxicity may be on the horizon. [ABSTRACT FROM AUTHOR]