The value of interventional radiology in clinical trial teams: experience from the BATTLE lung cancer trials.

AIM: To report on the multidisciplinary approach, focusing specifically on the role of the interventional radiologist (IR), used to support the Biomarker-integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) and BATTLE-2 trials. MATERIALS AND METHODS: Patients who underwent percutaneous image-guided biopsy for the BATTLE and BATTLE-2 trials were reviewed. A radiology-based, three-point, lesion-scoring system was developed and used by two IRs. Lesions were given a score of 3 (most likely to yield sufficient material for biomarker analysis) if they met the following criteria: size >2 cm, solid mass, demonstrated imaging evidence of viability, and were technically easy to sample. Lesions not meeting all four criteria were scored 2 with the missing criteria noted as negative factors. Lesions considered to have risks that outweighed potential benefits receive a score of 1 and were not biopsied. Univariate and multivariate analyses were performed to evaluate the score's ability to predict successful yield for biomarker adequacy. RESULTS: A total of 555 biopsies were performed. The overall yield for analysis of the required biomarkers was 86.1% (478/555), and 84% (268/319) and 88.9% (210/236) for BATTLE and BATTLE-2, respectively (p=0.09). Lesions receiving a score of 3 were adequate for biomarker analysis in 89% of cases. Lesions receiving a score of 2 with more than two negative factors were adequate for molecular analysis in 69.2% (IR1, p=0.03) and 74% (IR2, p=0.04) of cases. The two IRs scored 78.4% of the lesions the same indicating moderate agreement (kappa=0.55; 95% confidence interval [CI]: 0.48, 0.61). CONCLUSIONS: IRs add value to clinical trial teams by optimising lesions selected for biopsy and biomarker analysis.

Whole-exome sequencing and immune profiling of early-stage lung adenocarcinoma with fully annotated clinical follow-up.

Background: Lung adenocarcinomas (LUADs) lead to the majority of deaths attributable to lung cancer. We performed whole-exome sequencing (WES) and immune profiling analyses of a unique set of clinically annotated early-stage LUADs to better understand the pathogenesis of this disease and identify clinically relevant molecular markers. Methods: We performed WES of 108 paired stage I-III LUADs and normal lung tissues using the Illumina HiSeq 2000 platform. Ten immune markers (PD-L1, PD-1, CD3, CD4, CD8, CD45ro, CD57, CD68, FOXP3 and Granzyme B) were profiled by imaging-based immunohistochemistry (IHC) in a subset of LUADs (n = 92). Associations among mutations, immune markers and clinicopathological variables were analyzed using ANOVA and Fisher's exact test. Cox proportional hazards regression models were used for multivariate analysis of clinical outcome. Results: LUADs in this cohort exhibited an average of 243 coding mutations. We identified 28 genes with significant enrichment for mutation. SETD2-mutated LUADs exhibited relatively poor recurrence- free survival (RFS) and mutations in STK11 and ATM were associated with poor RFS among KRAS-mutant tumors. EGFR, KEAP1 and PIK3CA mutations were predictive of poor response to adjuvant therapy. Immune marker analysis revealed that LUADs in smokers and with relatively high mutation burdens exhibited increased levels of immune markers. Analysis of immunophenotypes revealed that LUADs with STK11 mutations exhibited relatively low levels of infiltrating CD4+/CD8+ T-cells indicative of a muted immune response. Tumoral PD-L1 was significantly elevated in TP53 mutant LUADs whereas PIK3CA mutant LUADs exhibited markedly down-regulated PD-L1 expression. LUADs with TP53 or KEAP1 mutations displayed relatively increased CD57 and Granzyme B levels indicative of augmented natural killer (NK) cell infiltration. Conclusion(s): Our study highlights molecular and immune phenotypes that warrant further analysis for their roles in clinical outcomes and personalized immune-based therapy of LUAD.

Mutation profiles in early-stage lung squamous cell carcinoma with clinical follow-up and correlation with markers of immune function.

Background: Lung squamous cell carcinoma (LUSC) accounts for 20­30% of non-small cell lung cancers (NSCLCs). There are limited treatment strategies for LUSC in part due to our inadequate understanding of the molecular underpinnings of the disease. We performed whole-exome sequencing (WES) and comprehensive immune profiling of a unique set of clinically annotated early-stage LUSCs to increase our understanding of the pathobiology of this malignancy. Methods: Matched pairs of surgically resected stage I-III LUSCs and normal lung tissues (n = 108) were analyzed by WES. Immunohistochemistry and image analysis-based profiling of 10 immune markers were done on a subset of LUSCs (n = 91). Associations among mutations, immune markers and clinicopathological variables were statistically examined using analysis of variance and Fisher's exact test. Cox proportional hazards regression models were used for statistical analysis of clinical outcome. Results: This early-stage LUSC cohort displayed an average of 209 exonic mutations per tumor. Fourteen genes exhibited significant enrichment for somatic mutation: TP53, MLL2, PIK3CA, NFE2L2, CDH8, KEAP1, PTEN, ADCY8, PTPRT, CALCR, GRM8, FBXW7, RB1 and CDKN2A. Among mutated genes associated with poor recurrence-free survival, MLL2 mutations predicted poor prognosis in both TP53 mutant and wild-type LUSCs. We also found that in treated patients, FBXW7 and KEAP1 mutations were associated with poor response to adjuvant therapy, particularly in TP53-mutant tumors. Analysis of mutations with immune markers revealed that ADCY8 and PIK3CA mutations were associated with markedly decreased tumoral PD-L1 expression, LUSCs with PIK3CA mutations exhibited elevated CD45ro levels and CDKN2A-mutant tumors displayed an up-regulated immune response. Conclusion(s): Our findings pinpoint mutated genes that may impact clinical outcome as well as personalized strategies for targeted immunotherapies in early-stage LUSC.

Strong spin-photon coupling in silicon.

Long coherence times of single spins in silicon quantum dots make these systems highly attractive for quantum computation, but how to scale up spin qubit systems remains an open question. As a first step to address this issue, we demonstrate the strong coupling of a single electron spin and a single microwave photon. The electron spin is trapped in a silicon double quantum dot, and the microwave photon is stored in an on-chip high-impedance superconducting resonator. The electric field component of the cavity photon couples directly to the charge dipole of the electron in the double dot, and indirectly to the electron spin, through a strong local magnetic field gradient from a nearby micromagnet. Our results provide a route to realizing large networks of quantum dot-based spin qubit registers.