Lung cancer is a paradigm for a genetically driven tumor. A variety of drugs were developed targeting specific biomarkers requiring testing for tumor genetic alterations in relevant biomarkers. Different next-generation sequencing technologies are available for library generation: 1) anchored multiplex-, 2) amplicon based- and 3) hybrid capture-based-PCR. Anchored multiplex PCR-based sequencing was investigated for routine molecular testing within the national Network Genomic Medicine Lung Cancer (nNGM). Four centers applied the anchored multiplex ArcherDX-Variantplex nNGMv2 panel to re-analyze samples pre-tested during routine diagnostics. Data analyses were performed by each center and compiled centrally according to study design. Pre-defined standards were utilized, and panel sensitivity was determined by dilution experiments. nNGMv2 panel sequencing was successful in 98.9% of the samples (N = 90). With default filter settings, all but two potential MET exon 14 skipping variants were identified at similar allele frequencies. Both MET variants were found with an adapted calling filter. Three additional variants (KEAP1, STK11, TP53) were called that were not identified in pre-testing analyses. Only total DNA amount but not a qPCR-based DNA quality score correlated with average coverage. Analysis was successful with a DNA input as low as 6.25 ng. Anchored multiplex PCR-based sequencing (nNGMv2) and a sophisticated user-friendly Archer-Analysis pipeline is a robust and specific technology to detect tumor genetic mutations for precision medicine of lung cancer patients.

Over the last two decades, the use of Next-Generation Sequencing (NGS) in medical oncology has increased the likelihood of identifying druggable mutations that may be potentially susceptible to targeted treatments. The European Society for Medical Oncology (ESMO) currently does not recommend the use of the NGS test to determine the therapeutic course of patients with metastatic breast cancer (mBC) in daily clinical practice. However, the aim of this work is to evaluate the potential contribution of the NGS test in selecting targeted therapies for patients with mBC. Data were retrospectively collected from 101 patients diagnosed with metastatic breast cancer and treated at the Modena Cancer Center between January 2015 and April 2022. A NGS test was performed on the tumor tissue of each patient at the Laboratory of Molecular Pathology of the University Hospital of Modena. This study analyzed the clinical-pathological characteristics and mutational profile of the population using NGS tests, with a focus on actionable mutations that could be targeted in advanced stages of clinical development. The indicator of this study was to quantify the actionable mutations that resulted in a change of cancer treatment. In total, 101 patients with metastatic breast cancer were analyzed, including 86 with luminal phenotype, 10 who were HER2-positive and 5 who were triple-negative. Median age was 52 years. NGS analysis was conducted on 47 samples of primary breast cancer, 52 on metastatic sites of disease and 2 on liquid biopsies. A total of 85 gene mutations were found. The most common mutations were identified in the PIK3CA (47%), FGFR (19%) and ERBB2 genes (12%), and to a lesser extent in other genes. Of the 61 patients with pathogenic mutations, 46 (75%) had at least one actionable mutation. Of these, nine received treatment with a molecular target drug: eight patients with a mutation of the PIK3CA gene were treated with alpelisib and fulvestrant; one patient with FGFR1/2 amplifications received TAS120. Median PFS for these patients was 3.8 months. The study results show that using the NGS test on cancer tissue of metastatic breast cancer could influence the therapeutic choices, considering the small sample size and limited follow-up. About 9% of the study population had their therapy modified based on the results of NGS. The growing number of detectable mutations and increased accessibility of the test may lead to a greater number of potential therapeutic implications for the NGS assay. Perspectives suggest that NGS analysis can be implemented in daily clinical practice, particularly in contexts where a Molecular Tumor Board (MTB) is active.

Circulating tumor cells (CTCs) are cancer cells that slough off from the tumor and circulate in the peripheral blood and lymphatic system as micro metastases that eventually results in macro metastases. Through a simple blood draw, sensitive CTC detection from clinical samples has proven to be a useful tool for determining the prognosis of cancer. Recent technological developments now make it possible to detect CTCs reliably and repeatedly from a simple and straightforward blood test. Multicenter trials to assess the clinical value of CTCs have demonstrated the prognostic value of these cancer cells. Studies on CTCs have filled huge knowledge gap in understanding the process of metastasis since their identification in the late 19th century. However, these rare cancer cells have not been regularly used to tailor precision medicine and or identify novel druggable targets. In this review, we have attempted to summarize the milestones of CTC-based research from the time of identification to molecular characterization. Additionally, the need for a paradigm shift in dissecting these seeds of metastasis and the possible future avenues to improve CTC-based discoveries are also discussed.

BACKGROUND: Several studies have indicated that intrapleural infusion of bevacizumab is an effective treatment for non-small cell lung cancer (NSCLC) with malignant pleural effusion (MPE). However, the impact of bevacizumab administered through an indwelling pleural catheter (IPC) on the prognosis of these patients is unknown.
METHODS: Consecutive advanced NSCLC patients with symptomatic MPE receiving an IPC alone or bevacizumab through an IPC were identified in a tertiary hospital. The patient characteristics and clinical outcomes were collected.
RESULTS: A total of 149 patients were included, and the median age was 60.3 years. Males and nonsmokers accounted for 48.3% and 65.8%, respectively. A total of 69.8% (104/149) of patients harbored actionable mutations, including 92 EGFR-activating mutations, 11 ALK fusions, and 1 ROS1 fusion. A total of 81.9% (122/149) of patients received IPC alone, and 18.1% (27/149) received bevacizumab through an IPC. The incidence of spontaneous pleurodesis during the first 6 months was greater in the bevacizumab-treated group than in the IPC-treated group in the subgroup with actionable mutations (64.3% vs. 46.9%, P = 0.28). The median overall survival (OS) in patients with actionable mutations treated with bevacizumab through an IPC was 42.2 months, which was significantly longer than the 26.7 months in patients who received an IPC alone (P = 0.045). However, the median OS did not differ between the two arms in the subgroup without actionable mutations (10.8 vs. 41.0 months, P = 0.24). No significant difference between the bevacizumab through an IPC group and the IPC group was detected in the number of participants who had adverse events, either in patients with actionable mutations (14.3% vs. 8.4%; P = 0.42) or in patients without actionable mutations (16.7% vs. 12.8%; P = 1.00).
CONCLUSIONS: Bevacizumab through an IPC resulted in a significantly improved prognosis for NSCLC patients with MPE and actionable mutations. However, patients without actionable mutations do not benefit from bevacizumab through IPC.

BACKGROUND: Recurrent intestinal-type sinonasal adenocarcinoma (ITAC) can occur several years after primary treatment and with different histology. We aimed to clarify if such recurrences could be second primary tumors and to identify actionable mutations as targets for personalized treatment of recurrent ITAC.
METHODS: Twelve pairs of primary and recurrent ITAC were histologically examined and analyzed by next-generation sequencing.
RESULTS: Histological differences between primary and recurrent tumor pairs were observed in five cases. Frequent mutations included TP53, APC, TSC2, ATM, EPHA2, BRCA2, LRP1B, KRAS, and KMT2B. There was 86% concordance of somatic mutations between the tumor pairs, while four cases carried additional mutations in the recurrence.
CONCLUSIONS: We found all cases to be clonal recurrences and not second primary tumors. Moreover, tumor pairs showed a remarkable genomic stability, suggesting that personalized treatment of a recurrence may be based on actionable molecular genetic targets observed in the primary tumor.

BACKGROUND: Accurate prediction of tumor molecular alterations is vital for optimizing cancer treatment. Traditional tissue-based approaches encounter limitations due to invasiveness, heterogeneity, and molecular dynamic changes. We aim to develop and validate a deep learning radiomics framework to obtain imaging features that reflect various molecular changes, aiding first-line treatment decisions for cancer patients.
METHODS: We conducted a retrospective study involving 508 NSCLC patients from three institutions, incorporating CT images and clinicopathologic data. Two radiomic scores and a deep network feature were constructed on three data sources in the 3D tumor region. Using these features, we developed and validated the \'Deep-RadScore,\' a deep learning radiomics model to predict prognostic factors, gene mutations, and immune molecule expression levels.
RESULTS: The Deep-RadScore exhibits strong discrimination for tumor molecular features. In the independent test cohort, it achieved impressive AUCs: 0.889 for lymphovascular invasion, 0.903 for pleural invasion, 0.894 for T staging; 0.884 for EGFR and ALK, 0.896 for KRAS and PIK3CA, 0.889 for TP53, 0.895 for ROS1; and 0.893 for PD-1/PD-L1. Fusing features yielded optimal predictive power, surpassing any single imaging feature. Correlation and interpretability analyses confirmed the effectiveness of customized deep network features in capturing additional imaging phenotypes beyond known radiomic features.
CONCLUSIONS: This proof-of-concept framework demonstrates that new biomarkers across imaging features and molecular phenotypes can be provided by fusing radiomic features and deep network features from multiple data sources. This holds the potential to offer valuable insights for radiological phenotyping in characterizing diverse tumor molecular alterations, thereby advancing the pursuit of non-invasive personalized treatment for NSCLC patients.

BACKGROUND: Selecting therapeutic strategies for cancer patients is typically based on key target-molecule biomarkers that play an important role in cancer onset, progression, and prognosis. Thus, there is a pressing need for novel biomarkers that can be utilized longitudinally to guide treatment selection.
METHODS: Using data from 508 non-small cell lung cancer (NSCLC) patients across three institutions, we developed and validated a comprehensive predictive biomarker that distinguishes six genotypes and infiltrative immune phenotypes. These features were analyzed to establish the association between radiological phenotypes and tumor genotypes/immune phenotypes and to create a radiological interpretation of molecular features. In addition, we assessed the sensitivity of the models by evaluating their performance at five different voxel intervals, resulting in improved generalizability of the proposed approach.
RESULTS: The radiomics model we developed, which integrates clinical factors and multi-regional features, outperformed the conventional model that only uses clinical and intratumoral features. Our combined model showed significant performance for EGFR, KRAS, ALK, TP53, PIK3CA, and ROS1 mutation status with AUCs of 0.866, 0.874, 0.902, 0.850, 0.860, and 0.900, respectively. Additionally, the predictive performance for PD-1/PD-L1 was 0.852. Although the performance of all models decreased to different degrees at five different voxel space resolutions, the performance advantage of the combined model did not change.
CONCLUSIONS: We validated multiscale radiomic signatures across tumor genotypes and immunophenotypes in a multi-institutional cohort. This imaging-based biomarker offers a non-invasive approach to select patients with NSCLC who are sensitive to targeted therapies or immunotherapy, which is promising for developing personalized treatment strategies during therapy.

UNASSIGNED: There have been needs to improve the sensitivity of liquid biopsy. This report aims to report the analytical and clinical validation of a next generation sequencing (NGS)-based circulating tumor DNA (ctDNA) assay.
UNASSIGNED: Analytical validation was conducted in vitro by evaluating the limit of detection (LOD), precision, and specificity for various genomic aberrations. The real-world performance in non-small cell lung cancer (NSCLC) was assessed by comparing the results of AlphaLiquid®100 to the tissue-based results.
UNASSIGNED: The LODs with 30 ng input DNA were 0.11%, 0.11%, 0.06%, 0.21%, and 2.13 copies for detecting SNVs, insertions, deletions, fusions, and copy number alterations (CNA), respectively. Quantitatively, SNV/INDELs, fusions, and CNAs showed a good correlation (R2=0.91, 0.40, and 0.65; y=0.95, 1.06, and 1.19) to the manufacturer\'s values, and per-base specificities for all types of variants were near 100%. In real-world NSCLC (n=122), key actionable mutations in NSCLC were detected in 60.7% (74/122) with the ctDNA assay. Comparative analysis against the NGS-based tissue results for all key mutations showed positive percent agreement (PPA) of 85.3%. For individual genes, the PPA was as high as 95.7% for EGFR mutations and 83.3% for ALK translocations. AlphaLiquid 100 detected drug-sensitive EGFR mutation at a variant allele frequency as low as 0.02% and also identified an EGFR mutation in a case where tissue sample missed. Blood samples collected post-targeted therapies revealed additional acquired mutations.
UNASSIGNED: The AlphaLiquid®100 ctDNA assay demonstrates robust analytical validity, offering clinically important information for NSCLC patients.

UNASSIGNED: Brain metastases derived from non-small cell lung cancer (NSCLC) represent a significant clinical problem. We aim to characterize the genomic landscape of brain metastases derived from NSCLC and assess clinical actionability.
UNASSIGNED: We searched Embase, MEDLINE, Web of Science, and BIOSIS from inception to 18/19 May 2022. We extracted information on patient demographics, smoking status, genomic data, matched primary NSCLC, and programmed cell death ligand 1 expression.
UNASSIGNED: We found 72 included papers and data on 2346 patients. The most frequently mutated genes from our data were EGFR (n = 559), TP53 (n = 331), KRAS (n = 328), CDKN2A (n = 97), and STK11 (n = 72). Common missense mutations included EGFR L858R (n = 80) and KRAS G12C (n = 17). Brain metastases of ever versus never smokers had differing missense mutations in TP53 and EGFR, except for L858R and T790M in EGFR, which were seen in both subgroups. Of the top 10 frequently mutated genes that had primary NSCLC data, we found 37% of the specific mutations assessed to be discordant between the primary NSCLC and brain metastases.
UNASSIGNED: To our knowledge, this is the first systematic review to describe the genomic landscape of brain metastases derived from NSCLC. These results provide a comprehensive outline of frequently mutated genes and missense mutations that could be clinically actionable. These data also provide evidence of differing genomic landscapes between ever versus never smokers and primary NSCLC compared to the BM. This information could have important consequences for the selection and development of targeted drugs for these patients.

Differentiated thyroid cancer (DTC) is a rare disease in the paediatric population (≤ 18 years old. at diagnosis). Increasing incidence is reflected by increases in incidence for papillary thyroid carcinoma (PTC) subtypes. Compared to those of adults, despite aggressive presentation, paediatric DTC has an excellent prognosis. As for adult DTC, European and American guidelines recommend individualised management, based on the differences in clinical presentation and genetic findings. Therefore, we conducted a systematic review to identify the epidemiological landscape of all genetic alterations so far investigated in paediatric populations at diagnosis affected by thyroid tumours and/or DTC that have improved and/or informed preventive and/or curative diagnostic and prognostic clinical conduct globally. Fusions involving the gene RET followed by NTRK, ALK and BRAF, were the most prevalent rearrangements found in paediatric PTC. BRAF V600E was found at lower prevalence in paediatric (especially ≤ 10 years old) than in adults PTC. We identified TERT and RAS mutations at very low prevalence in most countries. DICER1 SNVs, while found at higher prevalence in few countries, they were found in both benign and DTC. Although the precise role of DICER1 is not fully understood, it has been hypothesised that additional genetic alterations, similar to that observed for RAS gene, might be required for the malignant transformation of these nodules. Regarding aggressiveness, fusion oncogenes may have a higher growth impact compared with BRAF V600E. We reported the shortcomings of the systematized research and outlined three key recommendations for global authors to improve and inform precision health approaches, glocally.