JCO precision oncology最新文献

Purpose: Human epidermal growth factor receptor 2 (HER2)-low is a newly defined subgroup of HER2-negative breast cancer. It is unknown whether HER2-low status is associated with brain metastases (BrM) development. We aimed to determine the association between HER2-low status and the time to developing BrM.

Methods: HER2 status was determined in a cohort of 689 women with metastatic breast cancer (MBC) who underwent treatment for BrM at Sunnybrook Odette Cancer Centre from 2008 to 2018. In patients with primary breast cancer (PBC) HER2 subclassification available (subgroup 1), we investigated time from PBC diagnosis to BrM diagnosis (PBC-time to brain metastases [TTBM]). In patients with HER2 subclassification available in any tissue (subgroup 2), we investigated time from MBC diagnosis to BrM diagnosis (MBC-TTBM).

Results: In subgroup 1 (n = 175), patients with HER2-low disease (n = 42) had a shorter PBC-TTBM compared with those with HER2-zero disease (n = 77; hazard ratio, 2.4; P = .0003). When stratified by hormone receptor (HR) status, this observation held true in the HR+/HER2- population, but not in the triple-negative breast cancer (TNBC) population. In subgroup 2 (n = 279), patients with HER2-low disease (n = 53) had a shorter MBC-TTBM compared to those with HER2-zero disease (n = 44) in the HR+/HER2- population (hazard ratio, 1.55; P = .036); however, this did not hold true in the TNBC population. Likelihood ratio test revealed significant interaction between HER2 and HR status in subgroup 2 (P = .016), but not subgroup 1 (P = .21).

Conclusion: Our findings suggest that among patients with HR+ breast cancer, HER2-low status was associated with shorter TTBM compared with HER2-zero status. In a subset of patients for whom HER2 status of the PBC was available, HER2-low status was associated with shorter PBC-TTBM, irrespective of HR status. This study suggests a previously unrecognized association between HER2-low status and timing of BrM development.

Purpose: Circulating tumor DNA (ctDNA) is an emerging tool in the evaluation of GI cancers. Challenges remain in defining its utility and role as a primary end point in therapeutic trials. The National Cancer Institute (NCI) ctDNA GI working group was created to evaluate current data and provide guidance on the inclusion of ctDNA in GI cancer trials.

Methods: The NCI GI steering committee assigned four task force members to serve as co-chairs for the working group. Co-chairs identified experts within each GI disease group to form a panel that convened to review data and provide recommendations. The group focused on ctDNA's role as a potential surrogate for assessing prognosis and guiding treatment decisions that may enhance GI cancer trials. A manuscript was drafted, circulated, revised, and voted on by the panel. The final draft was reviewed by the Cancer Therapy Evaluation Program.

Results: Further data are required to support ctDNA as a primary end point for late-phase therapeutic trials, particularly in studies that could change the standard-of-care. However, the group supports ctDNA as a primary efficacy end point for phase II studies and as a noninvasive evaluation strategy for new drug development. Incorporation of ctDNA as a biomarker in trial design must consider the specific context of disease biology of the GI cancer subtypes. ctDNA should be incorporated as an exploratory end point across a variety of disease settings and indications. Several practical considerations were identified to optimize the incorporation of ctDNA in future trial design.

Conclusion: Prospective trials are required to clarify the role of ctDNA as a valid surrogate end point for progression-free or overall survival in GI cancers.

Purpose: Current precision medicine (CPM) matches patients to therapies using traditional biomarkers, but inevitably resistance develops. Dynamic precision medicine (DPM) is a new evolutionary guided precision medicine (EGPM) approach undergoing translational development. It tracks intratumoral genetic heterogeneity and evolutionary dynamics, adapts as frequently as every 6 weeks, plans proactively for future resistance development, and incorporates multiple therapeutic agents. Simulations indicated DPM can significantly improve long-term survival and cure rates in a cohort of 3 million virtual patients representing a variety of clinical scenarios. Given the cost and invasiveness of monitoring subclones frequently, we sought to determine the value of a short DPM window of only two 6-week adaptations (moves).

Methods: In a new simulation, nearly 3 million virtual patients, differing in DPM input parameters of initial subclone compositions, drug sensitivities, and growth and mutational kinetics, were simulated as previously described. Each virtual patient was treated with CPM, DPM, and DPM for two moves followed by CPM.

Results: The first two DPM moves provide similar average benefit to a 5-year, 40-move sequence in the full virtual population. If the first two moves are identical for DPM and CPM, patients will not benefit from DPM (65% negative predictive value). A patient subset (20%) in which 2-move DPM and 40-move DPM provide closely similar outcomes has extraordinary predicted benefit (hazard ratio of DPM/CPM 0.03).

Conclusion: The first two DPM moves provide most of the clinical benefit of DPM, reducing the duration required for subclone monitoring. This also leads to an evolutionary classifier selecting patients who will benefit: those in whom DPM and CPM recommendations differ early. These advances bring DPM (and potentially other EGPM approaches) closer to potential clinical testing.

Purpose: Combining radiotherapy with androgen deprivation therapy (ADT) is recommended for localized prostate cancer. However, the time required for significant therapeutic benefits is not well quantified. This study aims to determine the time to benefit (TTB) of ADT in these patients.

Methods: We systematically searched PubMed, Scopus, Embase, and Cochrane databases for randomized clinical trials that compared definitive radiotherapy with or without ADT in localized prostate cancer. The primary end point was all-cause mortality. We reconstructed individual patient survival data and calculated TTB using Weibull survival curves, the frequentist method, and the delta method.

Results: Eight trials with 6,839 participants were included, with more than 80% of them being patients with intermediate- or high-risk prostate cancer. For patients adding ADT to radiotherapy, it took 7.46 (95% CI, 2.53 to 22.00), 11.36 (95% CI, 4.61 to 28.03), 19.97 (95% CI, 10.03 to 39.78), and 30.90 months (95% CI, 17.90 to 53.36) to prevent one case of all-cause mortality per 1,000, 500, 200, and 100 patients, respectively. To prevent one case of prostate cancer-specific mortality, local progression, distant metastasis, and biochemical failure per 100 patients, it required 40.58 (95% CI, 30.20 to 54.53), 10.92 (95% CI, 6.03 to 19.79), 11.36 (95% CI, 6.55 to 19.69), and 7.80 months (95% CI, 5.14 to 11.83), respectively.

Conclusion: Adding ADT to radiotherapy provides rapid clinical benefits for patients with intermediate- and high-risk localized prostate cancer. Patients with an expected lifespan over 30 months may benefit from this treatment.

Purpose: It is a clinical challenge to select patients for BRAF-targeted therapy because of the lack of predictive biomarkers besides the BRAF V600E mutation. By analyzing the genome, transcriptome, and proteome, this study investigated the association between baseline molecular alterations and outcomes of BRAF-targeted therapy.

Patients and methods: Fresh tumor tissue from patients enrolled in the Copenhagen Prospective Personalized Oncology study was collected and underwent comprehensive molecular profiling.

Results: TP53 comutations were most frequently detected. Patients with a TP53 wild-type tumor had a significantly longer median progression-free survival than those with TP53 comutations (hazard ratio, 2.8 [95% CI, 1.13 to 7.08]; P = .02). RNAseq revealed a distinct gene expression signature for patients with long-term disease control (LDC), including hallmarks of cell cycle arrest and proliferation in the p53 pathway. The protein analysis demonstrated that ubiquitin-conjugating enzyme EK2 was significantly downregulated in patients with LDC.

Conclusion: Using a multiomic approach, we identified molecular alterations associated with treatment outcomes. The potential of analyzing multiomic data is promising and should be prioritized in translational cancer research to uncover the full potential within precision oncology.

Purpose: Copanlisib, a pan-class phosphatidylinositol 3-kinase (PI3K) inhibitor with activity predominantly against the PI3K-delta and PI3K-alpha isoforms, has shown promising results in preclinical cancer models with PTEN loss. Herein, we report the activity and safety data from the Z1G and Z1H subprotocols, which included patients with PTEN loss, of the National Cancer Institute Molecular Analysis for Therapy Choice trial.

Methods: Patients with complete loss of cytoplasmic and nuclear PTEN as determined by immunohistochemistry regardless of PTEN mutation or deletion status were included in subprotocol Z1G, and patients with a deleterious mutation in the PTEN gene and retained expression of PTEN were included in subprotocol Z1H. Copanlisib was given intravenously over 1 hour at a dose of 60 mg on days 1, 8, and 15 in a 21-day-on and 7-day-off schedule in 28-day cycles. Patients continued treatment until disease progression or unacceptable toxicity.

Results: Overall, 49 patients (20 patients in Z1G and 29 in Z1H) were included in the primary efficacy analyses. The objective response rates in both cohorts were 0% (Z1G; 90% CI, 0 to 13.9) and 3.4% (Z1H; 90% CI, 0.2 to 15.3), respectively. The median progression-free and overall survival durations were 1.8 months (90% CI, 1.4 to 3.9 months) and 13.7 months (90% CI, 6.8 to 18.3 months) for the Z1G cohort and 1.8 months (90% CI, 1.8 to 2.1 months) and 9.0 months (90% CI, 5.4 to 13.3 months) for the Z1H cohort, respectively.

Conclusion: Our results do not support the antitumor activity of single-agent copanlisib in tumors with PTEN loss regardless of mutation or deletion status or PTEN deleterious mutations with PTEN expression.

Purpose: Treatment stratification in ALL includes diverse (cyto)genetic aberrations, requiring diverse tests to yield conclusive data. We optimized the diagnostic workflow to detect all relevant aberrations with a limited number of tests in a clinically relevant time frame.

Methods: In 467 consecutive patients with ALL (0-20 years), we compared RNA sequencing (RNAseq), fluorescence in situ hybridization (FISH), reverse transcriptase polymerase chain reaction (RT-PCR), karyotyping, single-nucleotide polymorphism (SNP) array, and multiplex ligation-dependent probe amplification (MLPA) for technical success, concordance of results, and turnaround time.

Results: To detect stratifying fusions (ETV6::RUNX1, BCR::ABL1, ABL-class, KMT2Ar, TCF3::HLF, IGH::MYC), RNAseq and FISH were conclusive for 97% and 96% of patients, respectively, with 99% concordance. RNAseq performed well in samples with a low leukemic cell percentage or low RNA quality. RT-PCR for six specific fusions was conclusive for >99% but false-negative for six patients with alternatively fused exons. RNAseq also detected gene fusions not yet used for stratification in 14% of B-cell precursor-ALL and 33% of T-ALL. For aneuploidies and intrachromosomal amplification of chromosome 21, SNP array gave a conclusive result in 99%, thereby outperforming karyotyping, which was conclusive for 64%. To identify deletions in eight stratifying genes/regions, SNP array was conclusive in 99% and MLPA in 95% of patients, with 98% concordance. The median turnaround times were 10 days for RNAseq, 9 days for FISH, 10 days for SNP array, and <7 days for MLPA and RT-PCR in this real-world prospective study.

Conclusion: Combining RNAseq and SNP array outperformed current diagnostic tools to detect all stratifying genetic aberrations in ALL. The turnaround time is <15 days matching major treatment decision time points. Moreover, combining RNAseq and SNP array has the advantage of detecting new lesions for studies on prognosis and pathobiology.