Molecular classification of hormone-sensitive and castration-resistant prostate cancer, using nonnegative matrix factorization molecular subtyping of primary and metastatic specimens.

BACKGROUND: Despite the rapidly evolving therapeutic landscape, immunotherapy has demonstrated limited activity in prostate cancer. A greater understanding of the molecular landscape, particularly the expression of immune-related pathways, will inform future immunotherapeutic strategies. Consensus nonnegative matrix factorization (cNMF) is a novel model of molecular classification analyzing gene expression data, focusing on biological interpretation of metagenes and selecting meaningful clusters. OBJECTIVE: We aimed to identify molecular subtypes of prostate cancer using cNMF and correlate these with existing biomarkers to inform future immunotherapeutic strategies. METHODS: A cohort of archival tumor specimens from hormone-sensitive and castration-resistant disease was studied. Whole transcriptomic profiles were generated using TruSeq RNA Access technology and subjected to cNMF. Comprehensive genomic profiling was performed with the FoundationOne assay. NMF subtypes were characterized by gene expression pathways, genomic alterations and correlated with clinical data, then applied to The Cancer Genome Atlas data set. RESULTS: We studied 164 specimens, including 52 castration-resistant and 13 paired primary/metastatic specimens. cNMF identified four distinct subtypes. NMF1 (19%) is enriched for immune-related and stromal-related pathways with transforming growth factor ß (TGFß) signature. NMF2 (36%) is associated with FOXO-mediated transcription signature and AKT signaling, NMF3 (26%) is enriched for ribosomal RNA processing, while NMF4 (19%) is enriched for cell cycle and DNA-repair pathways. The most common gene alterations included TMPRSS22 (42%), TP53 (23%), and DNA-repair genes (19%), occurring across all subtypes. NMF4 is significantly enriched for MYC and Wnt-signaling gene alterations. TMB, CD8 density, and PD-L1 expression were low overall. NMF1 and NMF4 were NMF2 was associated with superior overall survival. CONCLUSIONS: Using cNMF, we identified four molecularly distinct subtypes which may inform treatment selection. NMF1 demonstrates the most inflammatory signature with asuppressive TGFß signature, suggesting potential benefit with immunotherapy combination strategies targeting TGFß and PD-(L)1. Prospective studies are required to evaluate the use of this novel model to molecularly stratify patients for optimal treatment selection.

COVID-19 infection among patients with cancer in Australia from 2020 to 2022: a national multicentre cohort study.

Background: The global COVID-19 pandemic disproportionately affected certain populations and its management differed between countries. This national study describes characteristics and outcomes of COVID-19 in patients with cancer in Australia. Methods: We performed a multicentre cohort study of patients with cancer and COVID-19 from March 2020 to April 2022. Data were analysed to determine varying characteristics between cancer types and changes in outcomes over time. Multivariable analysis was performed to determine risk factors associated with oxygen requirement. Findings: 620 patients with cancer from 15 hospitals had confirmed COVID-19. There were 314/620 (50.6%) male patients, median age 63.5 years (IQR 50-72) and majority had solid organ tumours (392/620, 63.2%). The rate of COVID-19 vaccination (≥1 dose) was 73.4% (455/620). Time from symptom onset to diagnosis was median 1 day (IQR 0-3), patients with haematological malignancy had a longer duration of test positivity. Over the study period, there was a significant decline in COVID-19 severity. Risk factors associated with oxygen requirement included male sex (OR 2.34, 95% CI 1.30-4.20, p = 0.004), age (OR 1.03, 95% CI 1.01-1.06, p = 0.005); not receiving early outpatient therapy (OR 2.78, 95% CI 1.41-5.50, p = 0.003). Diagnosis during the omicron wave was associated with lower odds of oxygen requirement (OR 0.24, 95% CI 0.13-0.43, p < 0.0001). Interpretation: Outcomes from COVID-19 in patients with cancer in Australia over the pandemic have improved, potentially related to changing viral strain and outpatient therapies. Funding: This study was supported by research funding from MSD.

Enhancing Chemotherapy Capabilities in Rural Hospitals: Implementation of a Telechemotherapy Model (QReCS) in North Queensland, Australia.

INTRODUCTION: The Queensland Remote Chemotherapy Supervision (QReCS) model enables rural nurses to administer chemotherapy in smaller rural towns under supervision by health professionals from larger centers using telehealth. Its implementation began in North Queensland, Australia (population, 650,000), in 2014 between two regional cancer centers (Townsville and Cairns as primary sites) and six rural sites (125 to 1,000 kilometers from primary sites). Our study examined the implementation processes, feasibility, and safety of this model. METHODS: Details of implementation and patients' clinical details for the period of 2014 to 2016 for descriptive analysis were extracted from telechemotherapy project notes and oncology information systems of North Queensland, respectively. RESULTS: After a successful pilot study in Townsville Cancer Centre, statewide rural and cancer networks of Queensland Health, in collaboration with clinicians and managers across the state of Queensland, developed the QReCS model and a guide for operationalizing it. QReCS was implemented at six sites from 2014 to 2016. Main enablers across North Queensland included collaboration among clinicians and managers, availability of common electronic medical records, funding from Queensland Health, and installation of telehealth infrastructure by statewide telehealth services. Main barriers included turnover of senior management and nursing staff at two rural towns. Sixty-two patients received 327 cycles of low- to medium-risk chemotherapy agents. Rates of treatment delays, adverse events, and hospital admissions were similar to those in face-to-face care. CONCLUSION: Implementation of the QReCS model across a large geographic region is feasible with acceptable safety profiles. Leadership by and collaboration among clinicians and managers, adequacy of resources and common governance are key enablers.