JNCI Cancer Spectrum最新文献

Colorectal cancer (CRC) is a major global health challenge. Emerging research highlights the pivotal role of the gut microbiota in influencing CRC risk, progression, and treatment response. Metagenomic approaches, especially high-throughput shotgun sequencing, have provided unprecedented insights into the intricate connections between the gut microbiome and CRC. By enabling comprehensive taxonomic and functional profiling, metagenomics has revealed microbial signatures, activities, and biomarkers associated with colorectal tumorigenesis. Furthermore, metagenomics has shown a potential to guide patient stratification, predict treatment outcomes, and inform microbiome-targeted interventions. Despite remaining challenges in multi-omics data integration, taxonomic gaps, and validation across diverse cohorts, metagenomics has propelled our comprehension of the intricate gut microbiome-CRC interplay. This review underscores the clinical relevance of microbial signatures as potential diagnostic and prognostic tools in CRC. Furthermore, it discusses personalized treatment strategies guided by this omics' approaches.

Background: It is important to understand the relationship between drug efficacy measured in randomized clinical trials (RCTs) and real-world drug effectiveness. We estimate how RCT overall survival (OS) and RCT radiographic progression-free survival (rPFS) benefits predict the association between treatments and real-world OS gains for metastatic castration-resistant prostate cancer (mCRPC) drugs.

Methods: Using the National Cancer Institute list of approved cancer drugs and the National Comprehensive Cancer Network Treatment Guidelines, we identified all pharmaceutical therapies for mCRPC approved between 2010 and 2019. We obtained RCT OS and rPFS hazard ratios from the pivotal trials used for Food and Drug Administration (FDA) approval, and we estimated real-world OS hazard ratios using the Optum Clinformatics Extended DataMart Databases. We modeled real-world OS hazard ratios as a function of both RCT OS and RCT rPFS hazard ratios using Cox proportional hazards regressions, adjusted for year of diagnosis, age, race, and Elixhauser Comorbidity Index.

Results: When we did not account for nonrandom real-world selection of patients into receiving a newly approved therapy (ie, "treatment selection bias"), real-world OS gains were 15% lower than associated RCT OS and RCT rPFS benefits. However, after accounting for treatment selection bias in real-world settings, real-world OS gains were almost 28% greater than RCT OS and RCT rPFS benefits. Association between treatment and OS gains increased the longer a new therapy was on the market.

Conclusions: After adjusting for treatment selection bias, RCT OS and RCT rPFS estimates serve as useful, or even conservative, predictors of RW OS gains.

Background: It is unknown if a period of active surveillance before prostatectomy for prostate cancer (PCa) worsens functional outcomes. The aim of this study was to compare functional outcomes after primary vs delayed robot-assisted radical prostatectomy.

Methods: We included men registered in the National Prostate Cancer Register of Sweden with low and favorable intermediate-risk PCa who underwent robot-assisted prostatectomy in 2018-2020 and had filled a questionnaire on patient-reported outcome measures. Multivariable logistic regression analysis was used to compare the functional outcomes of primary and delayed prostatectomy.

Results: 2571 men underwent primary, and 921 men underwent delayed prostatectomy. Delayed prostatectomy was not associated with reduced overall quality of life (adjusted Odds Ratio [OR] 1.04; 95% confidence interval [CI] 0.71-1.55) or erectile dysfunction (adjusted OR 0.90, 95% CI 0.69-1.22). Urinary incontinence was slightly more common after delayed prostatectomy (15% vs 11%; adjusted OR 1.38, 95% CI 0.91-2.01). There were weak associations between time to prostatectomy and urinary symptoms and bother, with a 3% annual increase in the risk for urinary incontinence (adjusted OR 1.03; 95% CI 0.94-1.13).

Conclusion: These results suggest that a period on active surveillance before robot-assisted radical prostatectomy has little detrimental effect on functional outcomes. Since only around half of men on active surveillance will transit to prostatectomy, these outcomes represent a worst-case scenario for men who start active surveillance. These results support the use of active surveillance for men with low-risk and favorable intermediate-risk PCa.

Background: To determine the performance of a multi-gene copy number variation (MG-CNV) risk score in metastatic tissue and plasma biospecimens from treatment-naïve metastatic castrate-resistant prostate cancer (mCRPC) patients for prediction of clinical outcomes.

Methods: mCRPC tissue and plasma cell-free DNA (cfDNA) biospecimen sequencing results obtained from publicly accessed cohorts in dbGaP, cBioPortal, and an institutional mCRPC cohort were used to develop a MG-CNV risk score derived from gains in AR, MYC, COL22A1, PIK3CA, PIK3CB, NOTCH1 and losses in TMPRSS2, NCOR1, ZBTB16, TP53, NKX3-1 in independent cohorts for determining overall survival (OS), progression free survival (PFS) to first-line Androgen Receptor Pathway Inhibitors (ARPIs). The range of the risk scores for each cohort was dichotomized into "high-risk" group and "low-risk" groups and association with OS/PFS determined. Univariate and multi-variate Cox Proportional Hazard Regressions were applied for survival analyses (P < .05 for statistical significance).

Results: Of 1,137 metastatic tissue-plasma biospecimens across all cohorts, 699/1137 were treatment-naive mCRPC (235/699 metastatic tissue; 464/699 plasma-cfDNA) and 311/1137 were matched tissue-cfDNA pairs. In multivariate analysis the MG-CNV risk score derived from metastatic tissue or in cfDNA was statistically significantly associated with OS with high score associated with short survival, Hazard Ratio (HR) 2.65 (CI: 1.99- 3.51; P = 1.35-11) and shorter PFS to ARPIs (median PFS of 7.8 months) compared to 14 months in patients with low-risk score.

Conclusions: A molecular risk score in treatment-naïve mCRPC state obtained either in metastatic tissue or cfDNA predicts clinical survival outcomes and offers a tumor biology-based tool to design biomarker -based enrichment clinical trials.

This study examined the association of physical activity (PA) with cognitive difficulties (CD) and education, income, poverty, and age among cancer survivors (CS) using data from the 2020 National Health Interview Survey. Causal mediation analysis was tested using the bootstrapping method to examine associations between PA, cognitive difficulties, and other sociodemographic characteristics. Results showed statistically significant disparities in both CD and physical inactivity among CS with low education, low income, high poverty, and certain age categories. Health disparities related to CD based on race/ethnicity, sex, and age were also identified. PA mediated the relationship between CD and education, income, poverty, and age. Future research is needed to gain deeper insight into the mechanisms of PA-induced health benefits and to develop specific PA prescription guidelines in the subgroups at-risk for CD.

Background: Pathological complete response (pCR) has been used as a primary endpoint in neoadjuvant trials in early-stage triple negative breast cancer (TNBC) and the Food and Drug Administration (FDA) accepted pCR as a surrogate endpoint for long-term survival outcomes in high-risk early-stage BC for new drug approval. However, there is insufficient trial-level data to robustly support pCR as a surrogate for long-term survival in TNBC.

Methods: A systematic literature review was performed to identify randomized clinical trials of neoadjuvant systemic therapy for patients with clinical stage I-III TNBC. Data of odds ratios (ORs) for pCR, hazard ratios (HRs) for event-free survival (EFS) and overall survival (OS) were extracted. Disease-free survival was used as an alternative when EFS data were unavailable. A linear regression model on a logarithmic scale, coefficient of difference, and 95% confidential interval (CI) were calculated to assess the trial-level association between OR for pCR and HR for OS and EFS.

Results: Eight trials with a total of 2,342 patients were included. Three trials tested immune checkpoint inhibitors. Coefficient of difference (R2) was 0.2 for HR of EFS (95% CI, 0.17 to 0.22, P = .27), and R2 for HR of OS was 0.19 (95% CI, 0.17 to 0.22, P = .33).

Conclusion: There is no strong evidence to support using pCR as a surrogate marker for EFS or OS in early-stage TNBC at the trial level. Because of the necessity of minimizing drug approval delay with reliable long-term outcome, further studies of surrogate markers in early-stage TNBC are warranted.

Background: Pancreatic ductal adenocarcinoma (PDAC) is a clinically challenging malignancy, largely due to chemoresistance. Bacteria within the PDAC microbiome may mediate chemoresistance, suggesting that alteration of the microbiome with antibiotics could improve chemotherapy response.

Methods: We utilized the SEER-Medicare database to select patients with resected, early-stage PDAC diagnosed between 2007 and 2017. The primary outcome of this study was overall survival (OS). Receipt of antibiotic treatment within one month after adjuvant chemotherapy initiation was determined from Medicare claims data. Propensity scores (PSs) were used to match patients who received antibiotics with patients who did not receive antibiotics. The Kaplan-Meier method was used to calculate 5-year OS rates, and cox regression analysis was used to assess association between receiving antibiotics and OS. All hypotheses were 2-sided.

Results: Of the 712 patients with resected, early-stage PDAC, 629 (88.3%) were treated with adjuvant gemcitabine and 177 (24.9%) received antibiotics in the one month following chemotherapy initiation. The mean (SD) age at diagnosis was 73.7 (5.1) years and patients were mostly women, White, and from metropolitan areas in the northeastern or western US. A total of 143 PS-matched pairs were evaluated. Among patients treated with gemcitabine, antibiotic treatment was associated with a 37% improvement in OS and a 30% improvement in cancer-specific survival.

Conclusions: Antibiotic treatment in the one month following adjuvant gemcitabine initiation was associated with improved survival. These findings provide additional support for the hypothesis that antibiotic treatment may alter the pancreatic microbiome in a manner that reduces chemoresistance, potentially improving PDAC outcomes.

Background: Adequate patient awareness and understanding of cancer clinical trials is essential for trial recruitment, informed decision-making, and protocol adherence. While Large Language Models (LLMs) have shown promise for patient education, their role in enhancing patient awareness of clinical trials remains unexplored. This study explored the performance and risks of LLMs in generating trial-specific educational content for potential participants.

Methods: GPT4 was prompted to generate short clinical trial summaries and multiple-choice question-answer pairs from informed consent forms (ICFs) from ClinicalTrials.gov. Zero-shot learning was used for summaries, using a direct summarization, sequential extraction, and summarization approach. One-shot learning was used for question-answer pairs development. We evaluated performance through patient surveys of summary effectiveness and crowdsourced annotation of question-answer pair accuracy, using held-out cancer trial ICFs not used in prompt development.

Results: For summaries, both prompting approaches achieved comparable results for readability and core content. Patients found summaries to be understandable, and to improve clinical trial comprehension and interest in learning more about trials. The generated multiple-choice questions achieved high accuracy and agreement with crowdsourced annotators. For both summaries and multiple-choice questions, GPT4 was most likely to include inaccurate information when prompted to provide information that was not adequately described in the ICFs.

Conclusions: LLMs such as GPT4 show promise in generating patient-friendly educational content for clinical trials with minimal trial-specific engineering. The findings serve as a proof-of-concept for the role of LLMs in improving patient education and engagement in clinical trials, as well as the need for ongoing human oversight.

Background: Prostate cancer is a significant health concern in the Middle East and North Africa (MENA), with many cases diagnosed at advanced stages, a high mortality-to-incidence ratio, and low prostate cancer awareness. This study aims to evaluate prostate cancer screening practices in the region to inform effective early detection and management strategies.

Methods: A cross-sectional survey was conducted from July 1, 2023, to November 8, 2024, among physicians from 19 countries in the MENA region. The study utilized a validated questionnaire to assess prostate cancer screening practices, barriers, and educational needs.

Results: The survey had a response rate of 96.8%, with 1,163 participants. Of these, 34.7% routinely performed prostate cancer screenings, with 61.1% using PSA tests. The primary barrier was lack of patient awareness (51.2%). Additionally, 65.3% of participants had no formal training. To improve screening rates, participants suggested better patient education (63.5%), increased training for healthcare providers (41.9%), and improved access to screening equipment (38.9%).

Conclusion: This study reveals that prostate cancer screening was low, with barriers including a lack of patient awareness and formal training among physicians. Addressing these issues through culturally tailored education programs may improve early detection rates and ultimately reduce the burden of prostate cancer in the MENA region.

Background: The causes of bladder cancer are not completely understood. Our objective was to identify blood proteins and modifiable causal risk factors for bladder cancer by combining genome-wide association studies (GWAS) and Mendelian randomization (MR) analyses.

Methods: We first performed a GWAS meta-analysis of 6984 bladder cancer cases and 708 432 controls from three European databases. Next, we conducted two-sample MR and colocalization analyses using data from the present GWAS and published GWAS meta-analyses on plasma proteins and modifiable factors.

Results: GWAS meta-analysis uncovered 17 bladder cancer susceptibility loci, of which 3 loci were novel. Genes were enriched in pathways related to the metabolic and catabolic processes of xenobiotics and cellular detoxification. Proteome-wide MR analysis based on cis-acting genetic variants revealed that higher plasma levels of glutathione S-transferases were strongly associated with a reduced risk of bladder cancer. There is strong evidence of colocalization between GSTM1 and bladder cancer. Finally, multivariable MR analyses of suspected risk factors for bladder cancer revealed independent causal associations between smoking and adiposity, particularly abdominal obesity, and risk of bladder cancer.

Conclusions: Findings from this large-scale GWAS and multivariable MR analyses highlight the key role of detoxification processes, particularly glutathione S-transferase 1, as well as smoking and abdominal obesity in bladder cancer etiology.