JCO precision oncology最新文献

Purpose: To determine whether driver gene alterations in metastatic non-small cell lung carcinoma (NSCLC) spine metastases are associated with local tumor control after radiotherapy (RT).

Methods: Patients with NSCLC who underwent RT for spine metastasis and tumor genetic profiling were ascertained. Associations between driver gene mutations incidence of local failure were analyzed, followed by competing risk analysis for significant associations. The results were validated using in vitro clonal survival assays of CRISPR-engineered NSCLC cell lines.

Results: A total of 181 patients were analyzed, with a median follow-up of 15.2 months (IQR, 8.0-31.9 months). The 3-year risk of local failure was 0.15 (95% CI, 0.10 to 0.20). Patients harboring NF1 or BRAF driver alterations experienced higher 3-year local failure rates (NF1: 0.33 [0.09-0.61] v 0.13 [0.09-0.19]; P = .002); BRAF: 0.31 [0.08-0.57] v 0.13 [0.09-0.19]; P = .04). NF1 loss-of-function mutations conferred radioresistance in one of two NSCLC cell lines tested in vitro. Based on the convergence of NF1 and BRAF signaling, the RAS-mitogen-activated protein kinase (MAPK) pathway was further interrogated. KRAS mutations overall were not associated with local failure. However, comutation of KRAS/TP53 exhibited a trend toward elevated 3-year local failure, 0.31 (0.11-0.55) versus 0.13 (0.08 v 0.19), P = .05. RAS-MAPK pathway driver alterations accounted for 53% of all local failures (P < .0001) and showed an elevated 3-year risk of local failure (0.36 [0.2-0.51] v 0.09 [0.05-0.15]; P < .001), including when treated with stereotactic body RT (0.28 [0.1-0.5] v 0.05 [0.02-0.11]; P = .001).

Conclusion: Driver alterations in the RAS-MAPK signaling pathway confer radioresistance in metastatic NSCLC. These genetic alterations may serve as biomarkers to personalize RT strategies or as targets to enhance radiosensitivity.

Purpose: Diagnostic delays are common for patients with NUT carcinoma (NC), a cancer driven by NUT fusion oncoprotein. Rapid diagnosis is crucial for the best outcomes. We investigated NC's presenting features and associations with diagnostic delays.

Methods: We manually reviewed medical records from US participants in the NC Registry (2007-2024). Baseline features were analyzed descriptively, and multivariable logistic regression was used to examine odds ratios for delays.

Results: We analyzed 132 patients (median age 37 years). At presentation, 55% had metastatic disease and 64% had a thoracic primary. The median interval from symptom onset to diagnosis was 10 weeks (range, 1-165 weeks). The initial histopathologic diagnosis was poorly differentiated/squamous cell cancer in 52%, insufficient malignant cells in 14%, carcinoma in 12%, and NC in 22%. Immunohistochemistry (IHC) testing revealed NUT in 100%; 93% were keratin+, 88% p63+, 89% p40+, and 72% had Ki-67 ≥50%. IHC was used to diagnose NC in 79%. Nonthoracic primaries were associated with a longer time between symptom onset and NC diagnosis (odds ratio, 3.25). Of 32 patients who started treatment before diagnosis, 78% were on agents appropriate for NC. After a diagnosis of NC, 33% participated in clinical trials.

Conclusion: NC almost always presents as squamous/poorly differentiated non-small cell lung or head and neck cancer. Overall, 78% of patients were initially diagnosed as non-NC. Efforts to raise awareness, recognition, and rapid diagnosis of NC by both oncologists and pathologists are critical if we are to improve outcomes.

Purpose: Targeting TIGIT is under investigation in various cancers. We explored the expression and clinical significance of the poliovirus receptor (PVR), the ligand of TIGIT, in the tumor microenvironment (TME) of hepatocellular carcinoma (HCC).

Patients and methods: Two groups of patients with HCC, those with metastatic and early-stage disease, were identified at a single medical center. The expression levels of PVR and PD-L1 in tumor cells (TCs) and tumor-infiltrating immune cells (ICs) were evaluated by immunohistochemistry for membranous staining. Immune gene expression profiling and data from The Cancer Genome Atlas (TCGA) were used for validation.

Results: Among 66 metastatic HCC tissues, 13 (19.7%) and 18 (27.3%) exhibited positive PVR expression and 17 (25.8%) and 36 (54.5%) exhibited positive PD-L1 expression in TCs and ICs, respectively. In both TCs and ICs, the intensities of PVR and PD-L1 expression were negatively correlated. Immune profiling of representative tumor specimens revealed that those with high PVR/low PD-L1 expressions had significantly lower CD8⁺ T-cell scores, cytotoxic cell scores, and CD8⁺/regulatory T-cell score ratios compared with those with high PD-L1/low PVR expressions. In the other group of 90 early-stage hepatectomy HCC tissues, the expression levels of PVR and PD-L1 were lower than those in metastatic HCC tissues. The inverse correlation between PVR and PD-L1 expression, and the association between PVR expression and low infiltration of CD8⁺ T cells or cytotoxic cells were also demonstrated in early-stage HCC tissues and supported by the TCGA data set.

Conclusion: HCC tissues with high PVR expression were more common in metastatic disease and were associated with an immune-cold TME. These findings may have implications for the development of immunotherapies for HCC.

Purpose: Actionable genomic alterations (AGA) are rare in large cell neuroendocrine carcinoma (LCNEC), and outcomes with small molecule inhibitors (SMI) are not well studied. We evaluated SMI response in LCNEC with AGAs, and also assessed molecular testing rates using the nationwide Netherlands Cancer Registry (NCR).

Materials and methods: In this European multicenter cohort, clinical data were collected from patients with LCNEC harboring AGAs (age 18 years and older) who were treated with an SMI. Overall survival (OS) was calculated from first-line systemic treatment to death or last follow-up. Radiologic response was evaluated for each treatment line. Molecular (AGA and retinoblastoma 1 gene [RB1]) and immunohistochemical (protein RB1 [pRb] and Ki-67) data were collected. NCR data were analyzed to determine molecular testing frequency and AGA types in stage IV LCNEC (2016-2022).

Results: In total, 28 patients with LCNEC were identified. The most common AGAs were epidermal growth factor receptor mutations (35.7%) and anaplastic lymphoma kinase fusions (32.1%). Median OS was 14.6 months (95% CI, 11 to 32). Across 38 SMI treatment lines, partial response was observed in 19 (50%). A trend toward longer survival was seen in patients with functional RB1 versus inactivated RB1 (hazard ratio, 0.32 [95% CI, 0.12 to 1.03]; P = .057). Within the NCR, molecular testing was conducted in 498/927 (53.7%) patients with stage IV LCNEC in the Netherlands, with AGAs detected in 111/498 (22.3%).

Conclusion: In our series, patients with LCNEC harboring AGAs who are treated with SMIs achieved a response in 50% of cases, including durable responses. However, only half of the patients with LCNEC are screened for AGAs. These findings highlight the need for standardized testing for AGAs in LCNEC.

Purpose: Gastric cancer (GC) is a significant global health challenge, often diagnosed late, limiting treatment success. Early detection through biomarkers is critical for better outcomes. This study developed a noninvasive, cost-effective tool using circulating cell-free DNA (cfDNA) sequencing and advanced modeling for early GC detection.

Methods: We performed low-coverage whole-genome sequencing on plasma from 404 patients with GC and 428 non-GC participants (healthy donors and patients with colorectal, esophageal, or liver cancer). Participants were divided into a training set (579) and a validation set (253). A deep learning model, GastricAI, was trained on raw cfDNA reads using Mamba, an advanced sequence model enhancing the structured state space model (S4) with adaptive parameters. Performance was evaluated in a second validation set (73 GC patients, 94 controls).

Results: In the first validation set, GastricAI achieved an area under receiver operating characteristic curve (AUROC) of 0.886 (95% CI, 0.842 to 0.930), accuracy of 0.846, sensitivity of 0.789, and specificity of 0.900. Across TNM stages, it recorded sensitivity/specificity of 0.920/0.738 (stage I), 0.846/0.900 (stage II), 0.811/0.900 (stage III), and 1.000/0.623 (stage IV). In the second validation set, it showed an AUROC of 0.850 (95% CI, 0.793 to 0.907), accuracy of 0.772, sensitivity of 0.973, and specificity of 0.617. GastricAI consistently detected intestinal, diffuse, and mixed GC subtypes per Lauren's classification and outperformed conventional biomarkers carbohydrate antigen 724 (P < .001) and carcinoembryonic antigen (P = .037).

Conclusion: GastricAI provides a promising noninvasive method for GC detection via cfDNA sequencing, with high sensitivity and reasonable specificity. It holds potential for early screening to improve prognosis, although further prospective studies are needed to validate and refine its clinical utility across diverse populations.

Purpose: The atlas of immune microenvironment at single-cell level in BRCA1/2-mutated breast cancer is largely unknown and whether an immune signature on the basis of single-cell atlas is associated with response to neoadjuvant chemotherapy remains to be investigated.

Materials and methods: The immune microenvironment between BRCA1/2-mutated and BRCA wild-type breast tumors was explored using single-cell RNA sequencing (scRNA-seq) assay and was validated in an independent cohort of 40 BRCA1/2 carriers and 56 noncarriers via immunohistochemistry assay (IHC). Bulk RNA-seq was performed using RNA extracted from fresh-frozen pretreatment core-needle tumor tissues in 80 BRCA1/2 carriers with operable primary human epidermal growth factor receptor 2-negative tumors who received neoadjuvant chemotherapy, and the associations between immune cell subtypes defined by scRNA-seq and pathologic complete response (pCR) were investigated.

Results: BRCA1/2-mutated tumors exhibited an enriched immune microenvironment compared with the wild-type counterparts at single-cell level, particularly regulatory T cells and exhausted T cells, which were validated in the IHC cohort. Among the neoadjuvant chemotherapy cohort of 80 BRCA1/2 carriers, 36.2% achieved a pCR. We established an immune signature on the basis of the single-cell and bulk RNA-seq data, named BRCA-IM. The BRCA-IM model exhibited an excellent prediction of pCR in the neoadjuvant chemotherapy cohort, with AUC values of 0.81(95% CI, 0.69 to 0.92) in the training set and 0.91(95% CI, 0.79 to 1.00) in the test set, respectively; and the BRCA-IM model remained as an independent predictor for pCR after adjusting for other factors. Moreover, higher BRCA-IM scores were significantly associated with more favorable survival in the neoadjuvant chemotherapy cohort.

Conclusion: BRCA1/2-mutated breast cancer shows an enriched tumor immune microenvironment, and the BRCA-IM model exhibits a good performance in prediction of pCR in BRCA1/2-mutated tumors.

Purpose: We previously developed quality control materials (QCMs) to aid in the development of circulating tumor DNA (ctDNA) assays. In this study, we further characterize the performance of the QCMs relative to clinical samples.

Methods: QCMs were provided by three manufacturers. To functionally characterize the QCMs, we (1) evaluated EGFR L858R and ex19del (range, 0.5%-5.0% variant allele frequency [VAF]) in QCMs compared with clinical samples by droplet digital polymerase chain reaction (ddPCR), targeted-amplicon sequencing (Tag-seq), and hybrid capture next-generation sequencing (NGS); and (2) evaluated the QCMs and clinical samples near the Tag-seq limit of detection. A clinical pilot was also conducted in 11 clinical laboratories spanning four continents.

Results: For functional characterization, part 1, QCM VAFs for hybrid capture were similar to ddPCR for EGFR L858R but lower for ex19del. By contrast, hybrid capture results for EGFR L858R clinical samples showed a positive trend compared with ddPCR. For amplicon NGS, QCMs performed similarly to clinical samples for both variants. For part 2, observed hit rates approximated expected values. In the clinical pilot, median ex19del VAF was higher for Tag-seq than hybrid capture for both 1.0% and 0.5% QCM formulations. Median QCM L858R VAFs were similar for Tag-seq and hybrid capture, with greatest interlaboratory differences observed for Thermo Fisher Scientific QCMs. For non-EGFR variants, we observed assay and QCM-dependent trends, with no particular QCM or assay driving these trends.

Conclusion: This project revealed unexpected differences in performance of both assays and QCMs. These findings highlight the need for further validation across diverse alteration types and merit consideration by laboratories that rely on QCMs to develop and perform ctDNA assays for diagnostic applications.

In clinical trials, the initial step typically involves assessing a new drug's toxicity profile, aiming to identify a tolerable dose level for subsequent studies. In phase I trials, the primary objective is to determine the maximum tolerated dose, defined as the highest dose associated with an acceptable level of toxicity. Numerous methods have been developed to guide dose escalation and de-escalation decisions during trial conduct. Among these approaches, the calibration-free odds (CFO) design has demonstrated superior operating characteristics and has emerged as one of the most effective approaches for dose finding. To facilitate the application of the CFO design in clinical trial practice, an R package and a Shiny app have been released. This study presents CFO decision tables in Excel files to further remove the barrier of applying the CFO design to real trials. Anyone involved in the trial conduct can implement the CFO design with no difficulties. During the trial, dose movement decisions can be made simply by referring to the cumulative data (including numbers of patients treated and observed toxicities) and the pregenerated decision tables, without any additional statistical calculation. This approach significantly enhances the usability of the CFO design and reduces the operational complexity associated with its implementation in clinical trials. The Excel CFO decision tables can be downloaded from CFO Shiny App.

Purpose: We performed spatial transcriptomics of estrogen receptor (ER)-negative, ER-low, and ER-high tumor regions of breast cancers that were intermediate (10%-60%) ER-positive by immunohistochemistry to better understand the intratumor heterogeneity in ER expression and to elucidate whether cells of different molecular subtypes (ie, Luminal A [LumA], Luminal B [LumB], human epidermal growth factor receptor 2-enriched, or Basal-like) can coexist in the same tumor.

Methods: Digital spatial profiling was performed on 10 ER-heterogeneous (10%-60% ER+) and 10 ER-high (>60% ER+) primary breast cancers using the NanoString GeoMx platform with the Human Whole Transcriptome Atlas probe set.

Results: LumA and LumB molecular subtypes were intermixed, but there were no Basal-like populations in these ER-heterogeneous tumors. The ER-negative (ER-) regions were LumB-like and showed lower expression of ESR1 and endocrine therapy sensitivity gene signatures but higher expression of immune-related genes and higher recurrence scores, indicating a more endocrine-resistant but chemotherapy-sensitive phenotype. We also found that ESR1 strongly positive cells enriched after preoperative chemotherapy in clinical trial tissues.

Conclusion: This study demonstrates mixed Lum-A and Lum-B molecular subtypes within ER-intermediate primary breast cancers and reveals that ER- tumor cell populations have molecular features of endocrine resistance but chemotherapy sensitivity. These findings may explain the worse clinical outcomes of patients with ER-heterogeneous breast cancers and suggest benefit from combined endocrine and chemotherapy strategies.