Quantification and molecular correlates of tertiary lymphoid structures in primary prostate cancer.

OBJECTIVE: To morphologically describe tertiary lymphoid structures (TLS) in prostatectomy specimens and correlate them with clinical and transcriptomic features. METHODOLOGY: A total of 72 consecutive cases of entirely submitted radical prostatectomy (RP) patients tested with the Decipher Genomic Classifier were included in the study. Images were manually annotated using QuPath tools to denote tumor regions and each cluster of TLS. Clusters of lymphocytes that were surrounded on all four sides by tumor were defined as intra-tumor TLS (IT-TLS). Clusters of lymphocytes at the leading edge of carcinoma with either the prostatic pseudocapsule or benign parenchyma at one end were defined as peri-tumor TLS (PT-TLS). A classification algorithm to distinguish lymphocytes from non-lymphocytic cells using a supervised machine learning model was used. The associations between TLS formation and 265 gene expression-based signatures were examined. RESULTS: The magnitude of total TLS correlations with primary tumor gene expression signatures was moderate (~0.35-0.5) with several HLA, T-cell and B-cell Cluster signatures, showing positive correlation with various metrics for quantification of TLS. On the other hand, immune suppressive signatures (Treg, MDSC) were negatively correlated. While signatures for macrophages, NK cells and other immune cell types were uncorrelated for the most part. PT-TLS was associated with MHC signatures while IT TLS correlated with MHC and T-cell signatures. CONCLUSIONS: Clusters of inflammatory cells in the RP specimen can be divided spatially into PT TLS and IT-TLS, each with its unique molecular correlates of tumor immune microenvironment. The presence of TLS is positively correlated with MHC signatures, T- cell and B-cell cluster signatures but, negatively correlated with immune suppressive signatures. A subset of prostate cancer demonstrate a robust inflammatory response, and warrant further characterization in larger cohorts.

Pathological Effects of Apalutamide in Lower-risk Prostate Cancer: Results From a Phase II Clinical Trial.

PURPOSE: Active surveillance is a safe and effective strategy for men with lower-risk prostate cancer who want to avoid local therapy; however, many patients on active surveillance progress to active treatment (eg, prostatectomy or radiation). We hypothesized that apalutamide would decrease active surveillance attrition rates through downstaging low-grade tumors. MATERIALS AND METHODS: This was an open-label, single-arm, phase II study testing 90 days of oral apalutamide 240 mg daily in men with low- to intermediate-risk prostate cancer on active surveillance. The primary objective was to determine the percentage of patients with a negative biopsy immediately following treatment. Secondary objectives were to assess long-term clinical outcomes, quality of life, safety, and biomarkers of response/resistance. RESULTS: Twenty-three patients enrolled and 22 completed 90 days of apalutamide with post-treatment biopsy. Fifteen (65%) had Grade Group 1 disease, and all others had Grade Group 2 disease. Seven (30%) had favorable- to intermediate-risk disease. Of 22 evaluable patients, 13 (59%) had no residual cancer on post-treatment biopsy. The median time to first positive biopsy was 364 days (95% CI: 91-742 days). The impact of apalutamide on quality of life was minimal and transient. Decipher risk classifier revealed a greater number of negative post-treatment biopsies in those with higher baseline genomic risk score (P = .01). CONCLUSIONS: The negative repeat biopsy rate following 90 days of apalutamide was high in men with prostate cancer followed on active surveillance. Apalutamide was safe, well tolerated, and had minimal impact on quality of life. Randomized studies evaluating the effects of apalutamide in men enrolled on active surveillance are warranted.

In vitro Inhibition of respiratory pathogens by lactobacillus and alpha haemolytic streptococci from Aboriginal and Torres Strait Islander children.

AIMS: To explore the in vitro ability of alpha haemolytic streptococcus (AHS) and lactobacilli (LBs), from Indigenous Australian children, to inhibit the growth of respiratory pathogens (Streptococcus pneumoniae, Haemophilus influenzae and Moraxella catarrhalis), also from Indigenous Australian children. METHODS AND RESULTS: The bacterial interference of 91 isolates, from Indigenous Australian children both with and without otitis media (OM) or rhinorrhoea, was investigated using agar overlay and cell-free supernatant. Promising isolates underwent whole genome sequencing to investigate upper respiratory tract tropism, antibiotic resistance and virulence. Antibiotic susceptibility was examined for ampicillin, amoxicillin +clavulanic acid and azithromycin. Differences in the strength of bacterial inferences in relation to OM was examined using a case series of three healthy and three children with OM. LBs readily inhibited the growth of pathogens. AHS were less effective, although several isolates inhibited S. pneumoniae. One L. rhamnosus had genes coding for pili to adhere to epithelial cells. We detected antibiotic resistance genes coding for antibiotic efflux pump and ribosomal protection protein. LBs were susceptible to antimicrobials in vitro. Screening for virulence detected genes encoding for two putative capsule proteins. Healthy children had AHS and LB that were more potent inhibitors of respiratory pathogens in vitro than children with OM. CONCLUSIONS: L. rhamnosus from remote Indigenous Australian children are potent inhibitors of respiratory pathogens in vitro. SIGNIFICANCE AND IMPACT OF STUDY: Respiratory/ear disease are endemic in Indigenous Australians. There is an urgent call for more effective treatment/prevention; beneficial microbes have not been explored. L. rhamnosus investigated in this study are potent inhibitors of respiratory pathogens in vitro and require further investigation.

Development of a Longitudinal Prostate Cancer Transcriptomic and Clinical Data Linkage.

Importance: Although tissue-based gene expression testing has become widely used for prostate cancer risk stratification, its prognostic performance in the setting of clinical care is not well understood. Objective: To develop a linkage between a prostate genomic classifier (GC) and clinical data across payers and sites of care in the US. Design, Setting, and Participants: In this cohort study, clinical and transcriptomic data from clinical use of a prostate GC between 2016 and 2022 were linked with data aggregated from insurance claims, pharmacy records, and electronic health record (EHR) data. Participants were anonymously linked between datasets by deterministic methods through a deidentification engine using encrypted tokens. Algorithms were developed and refined for identifying prostate cancer diagnoses, treatment timing, and clinical outcomes using diagnosis codes, Common Procedural Terminology codes, pharmacy codes, Systematized Medical Nomenclature for Medicine clinical terms, and unstructured text in the EHR. Data analysis was performed from January 2023 to January 2024. Exposure: Diagnosis of prostate cancer. Main Outcomes and Measures: The primary outcomes were biochemical recurrence and development of prostate cancer metastases after diagnosis or radical prostatectomy (RP). The sensitivity of the linkage and identification algorithms for clinical and administrative data were calculated relative to clinical and pathological information obtained during the GC testing process as the reference standard. Results: A total of 92 976 of 95 578 (97.2%) participants who underwent prostate GC testing were successfully linked to administrative and clinical data, including 53 871 who underwent biopsy testing and 39 105 who underwent RP testing. The median (IQR) age at GC testing was 66.4 (61.0-71.0) years. The sensitivity of the EHR linkage data for prostate cancer diagnoses was 85.0% (95% CI, 84.7%-85.2%), including 80.8% (95% CI, 80.4%-81.1%) for biopsy-tested participants and 90.8% (95% CI, 90.5%-91.0%) for RP-tested participants. Year of treatment was concordant in 97.9% (95% CI, 97.7%-98.1%) of those undergoing GC testing at RP, and 86.0% (95% CI, 85.6%-86.4%) among participants undergoing biopsy testing. The sensitivity of the linkage was 48.6% (95% CI, 48.1%-49.1%) for identifying RP and 50.1% (95% CI, 49.7%-50.5%) for identifying prostate biopsy. Conclusions and Relevance: This study established a national-scale linkage of transcriptomic and longitudinal clinical data yielding high accuracy for identifying key clinical junctures, including diagnosis, treatment, and early cancer outcome. This resource can be leveraged to enhance understandings of disease biology, patterns of care, and treatment effectiveness.

Psychological Treatment Targeting Acceptance and Compassion in Patients With Chronic Pain: A Randomized Controlled, Internet-delivered, Treatment Trial.

OBJECTIVES: Chronic pain is often associated with lower function. Self-criticism is associated with depressive symptoms. The purpose of this study was to explore if fusing Acceptance and Commitment Therapy and compassion-focused therapy could improve psychological well-being and disability in individuals with chronic pain with high levels of self-criticism in comparison to a wait-list control group. METHODS: Individuals with chronic pain (n=71) were randomly assigned to an 8-week internet-based intervention focused on acceptance and compassion or a wait-list condition. Primary treatment outcomes were the Chronic Pain Acceptance Questionnaire, Self-Compassion Scale, and Pain Disability Index. Secondary outcomes were the Montgomery Åsberg Depression Rating Scale, Anxiety Sensitivity Index, Quality of Life Inventory, Multidimensional Pain Inventory, and Perseverative Thinking Questionnaire. RESULTS: Missing data at postintervention were 22.5%. Intention-to-treat analyses were conducted using linear mixed models. The results revealed greater levels of acceptance and self-compassion for the treatment group, which were primary outcomes, with effect sizes ranging from small to large, and these results were maintained at 6-month follow-up. The rates of clinically significant improvements were also greater for the treatment group in comparison to the wait-list control group on acceptance and compassion. The treatment group also improved in the third primary outcome, pain disability. Significant differences were found in several of the secondary outcomes, in favor of the treatment group. DISCUSSION: Internet-based Acceptance and Commitment Therapy with compassion-focused therapy components shows promise as a viable treatment option in the management of chronic pain.

Transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate-risk clear cell kidney cancer.

BACKGROUND: Risk stratification of kidney cancer patients after nephrectomy may tailor surveillance intensity and selection for adjuvant therapy. Transcriptomic approaches are effective in predicting recurrence, but whether they add value to clinicopathologic models remains unclear. METHODS: Data from patients with clear cell renal cell carcinoma (ccRCC) was downloaded from The Cancer Genome Atlas. Clinicopathologic variables were used to calculate SSIGN (stage, size, grade, and necrosis) scores. The 16 gene recurrence score (RS) signature was generated using RNA-seq data. Transcriptomic risk groups were calculated using the original thresholds. SSIGN groups were divided into low, intermediate, and high risk. Disease-free status was the primary endpoint assessed. RESULTS: SSIGN and RS were calculated for 428 patients with non-metastatic ccRCC. SSIGN low-, intermediate-, and high-risk groups demonstrated 2.7%, 15.2%, and 27.5%, 3-year recurrence risk, respectively. On multivariable analysis, the RS was associated with disease-free status (sub-distribution hazard ratio (sHR) 1.43 per 25 RS [95% CI (1.00-1.43)], p = 0.05). By risk groups, RS further risk stratified the SSIGN intermediate-risk group (sHR 2.22 [95% CI 1.10-4.50], p = 0.03). SSIGN intermediate-risk patients with low and high RS had a 3-year recurrence rate of 8.0% and 25.2%, respectively. Within this risk group, the area under the curve (AUC) at 3 years was 0.69 for SSIGN, 0.74 for RS, and 0.78 for their combination. CONCLUSIONS: Transcriptomic recurrence scores improve risk prediction even when controlling for clinicopathologic factors. Utility may be best suited for intermediate-risk patients who have heterogeneous outcomes and further refinement for clinical utility is warranted.

Analysing the tumor transcriptome of prostate cancer to predict efficacy of Lu-PSMA therapy.

RATIONALE: 177Lu-PSMA ([177Lu]Lutetium-PSMA-617) therapy is an effective treatment option for patients with prostate specific membrane antigen (PSMA)-positive metastatic castration-resistant prostate cancer, but still shows a non-responder rate of approximately 30%. Combination regimes of programmed death-ligand 1 (PD-L1) inhibition and concomitant 177Lu-PSMA therapy have been proposed to increase the response rate. However, the interplay of immune landscape and 177Lu-PSMA therapy efficacy is poorly understood. METHODS: Between March 2018 and December 2021, a total of 168 patients were referred to 177Lu-PSMA therapy in our department and received a mean total dose of 21.9 GBq (three cycles in mean). All patients received baseline PSMA positron emission tomography to assess the PSMA uptake. The histopathological specimen of the primary prostate tumor was available with sufficient RNA passing quality control steps for genomic analysis in n=23 patients. In this subset of patients, tumor RNA transcriptomic analyses assessed 74 immune-related features in total, out of which n=24 signatures were not co-correlated and investigated further for outcome prognostication. RESULTS: In the subset of patients who received 177Lu-PSMA therapy, PD-L1 was not significantly associated with OS (HR per SD change (95% CI) 0.74 (0.42 to 1.30); SD: 0.18; p=0.29). In contrast, PD-L2 signature was positively associated with longer OS (HR per SD change 0.46 (95% CI 0.29 to 0.74); SD: 0.24; p=0.001; median OS 17.2 vs 5.7 months in higher vs lower PD-L2 patients). In addition, PD-L2 signature correlated with PSA-response (ϱ=-0.46; p=0.04). The PD-L2 signature association with OS was significantly moderated by L-Lactatdehydrogenase (LDH) levels (Cox model interaction p=0.01). CONCLUSION: Higher PD-L2 signature might be associated with a better response to 177Lu-PSMA therapy and warrants further studies investigating additional immunotherapy. In contrast, PD-L1 was not associated with outcome. The protective effect of PD-L2 signature might be present only in men with lower LDH levels.

Tumor immune microenvironment of primary prostate cancer with and without germline mutations in homologous recombination repair genes.

BACKGROUND: Aberrations in homologous recombination repair (HRR) genes are emerging as important biomarkers for personalized treatment in prostate cancer (PCa). HRR deficiency (HRD) could affect the tumor immune microenvironment (TIME), potentially contributing to differential responses to poly ADP-ribose polymerase (PARP) inhibitors and immune checkpoint inhibitors. Spatial distribution of immune cells in a range of cancers identifies novel disease subtypes and is related to prognosis. In this study we aimed to determine the differences in the TIME of PCa with and without germline (g) HRR mutations. METHODS: We performed gene expression analysis, multiplex immunohistochemistry of T and B cells and quantitative spatial analysis of PCa samples from 36 patients with gHRD and 26 patients with sporadic PCa. Samples were archival tumor tissue from radical prostatectomies with the exception of one biopsy. Results were validated in several independent cohorts. RESULTS: Although the composition of the T cell and B cells was similar in the tumor areas of gHRD-mutated and sporadic tumors, the spatial profiles differed between these cohorts. We describe two T-cell spatial profiles across primary PCa, a clustered immune spatial (CIS) profile characterized by dense clusters of CD4+ T cells closely interacting with PD-L1+ cells, and a free immune spatial (FIS) profile of CD8+ cells in close proximity to tumor cells. gHRD tumors had a more T-cell inflamed microenvironment than sporadic tumors. The CIS profile was mainly observed in sporadic tumors, whereas a FIS profile was enriched in gHRD tumors. A FIS profile was associated with lower Gleason scores, smaller tumors and longer time to biochemical recurrence and metastasis. CONCLUSIONS: gHRD-mutated tumors have a distinct immune microenvironment compared with sporadic tumors. Spatial profiling of T-cells provides additional information beyond T-cell density and is associated with time to biochemical recurrence, time to metastasis, tumor size and Gleason scores.