The journey of lung cancer patients from symptoms to diagnosis in Greece. A mixed methods approach.

The early diagnosis of lung cancer improves the probability of successful treatment. However, patients and physicians face several difficulties that can considerably delay the diagnostic process. A mixed-methods study that would follow the patient's journey throughout the diagnostic process could alleviate these difficulties. This study aimed to (a) track the patients' journey from the onset of symptoms until diagnosis and, (b) explore the patients' perspective of the journey until diagnosis, on the largest island of Greece. A convergent mixed-methods study was conducted with 94 patients with lung cancer. Patients completed a self-report questionnaire and were interviewed about their symptoms and journey through the healthcare system before their diagnosis. Our findings revealed several problems and delays in the diagnostic process. Both quantitative and qualitative data showed that patients did not recognize their symptoms and sought medical advice in time because they overlooked or attributed their symptoms to 'simpler'/'more common' causes. Furthermore, most patients were diagnosed 1-3 months after their first visit to a physician for their symptoms. Qualitative data analysis revealed three broad categories of problems that delayed diagnosis: (1) physician missteps, (2) administrative problems, and (3) the effect of the Covid-19 pandemic. This study found that major issues and delays prolong the diagnostic process for lung cancer. Therefore, optimization of diagnostic processes at each level of healthcare and interspecialty cooperation programs are needed. Furthermore, population-based interventions and patient education can help lung cancer patients be diagnosed early and improve their quality of life and disease outcomes.

Corrigendum: MicroRNAs regulating tumor immune response in the prediction of the outcome in patients with breast cancer.

[This corrects the article DOI: 10.3389/fmolb.2021.668534.].

Rapid and reliable testing for clinically actionable EGFR mutations in non-small cell lung cancer using the IdyllaTM platform: a real-world two-center experience in Greece.

BACKGROUND: Limited information exists on epidermal growth factor receptor (EGFR) molecular epidemiology in Greece. Next-generation sequencing (NGS) is the recommended method for EGFR genotyping in NSCLC. The Idylla Biocartis platform is a fully automated system for actionable EGFR mutation detection. RESEARCH DESIGN AND METHODS: We describe the prevalence of EGFR mutations in NSCLC patients in two high-volume clinical centers in Greece and compare key methods used for their determination. Eight hundred and fifty-seven FFPE samples from NSCLC patients were tested for EGFR mutations at University of Crete (UoC; n = 324) and at Evangelismos Hospital, Athens (Evangelismos; n = 503). RESULTS: The prevalence of EGFR mutations was 11.1% in the whole cohort (11.5% in non-squamous). The detection rate was 11.0% by NGS, 9.8% by Sanger and 11.3% by Idylla for the whole cohort (12.0% in non-squamous). The agreement between Idylla and Sanger was 93.2%. A targetable EGFR mutation was detected in 10.0% using tissue NGS alone, and in 16.0% using concurrent Idylla ctEGFR testing. CONCLUSION: The frequency of EGFR mutations was as expected for a Caucasian population. The Idylla EGFR test performance is comparable to reference methods and with a shorter TAT. Adding a concurrent plasma Idylla test to tissue NGS testing increases the detection rate of EGFR mutations in NSCLC.

LKB1 Loss Correlates with STING Loss and, in Cooperation with ß-Catenin Membranous Loss, Indicates Poor Prognosis in Patients with Operable Non-Small Cell Lung Cancer.

To investigate the incidence and prognostically significant correlations and cooperations of LKB1 loss of expression in non-small cell lung cancer (NSCLC), surgical specimens from 188 metastatic and 60 non-metastatic operable stage I-IIIA NSCLC patients were analyzed to evaluate their expression of LKB1 and pAMPK proteins in relation to various processes. The investigated factors included antitumor immunity response regulators STING and PD-L1; pro-angiogenic, EMT and cell cycle targets, as well as metastasis-related (VEGFC, PDGFRα, PDGFRß, p53, p16, Cyclin D1, ZEB1, CD24) targets; and cell adhesion (ß-catenin) molecules. The protein expression levels were evaluated via immunohistochemistry; the RNA levels of LKB1 and NEDD9 were evaluated via PCR, while KRAS exon 2 and BRAFV600E mutations were evaluated by Sanger sequencing. Overall, loss of LKB1 protein expression was observed in 21% (51/248) patients and correlated significantly with histotype (p < 0.001), KRAS mutations (p < 0.001), KC status (concomitant KRAS mutation and p16 downregulation) (p < 0.001), STING loss (p < 0.001), and high CD24 expression (p < 0.001). STING loss also correlated significantly with loss of LKB1 expression in the metastatic setting both overall (p = 0.014) and in lung adenocarcinomas (LUACs) (p = 0.005). Additionally, LKB1 loss correlated significantly with a lack of or low ß-catenin membranous expression exclusively in LUACs, both independently of the metastatic status (p = 0.019) and in the metastatic setting (p = 0.007). Patients with tumors yielding LKB1 loss and concomitant nonexistent or low ß-catenin membrane expression experienced significantly inferior median overall survival of 20.50 vs. 52.99 months; p < 0.001 as well as significantly greater risk of death (HR: 3.32, 95% c.i.: 1.71-6.43; p <0.001). Our findings underscore the impact of the synergy of LKB1 with STING and ß-catenin in NSCLC, in prognosis.

Exploring Gut Microbiome Composition and Circulating Microbial DNA Fragments in Patients with Stage II/III Colorectal Cancer: A Comprehensive Analysis.

BACKGROUND: Colorectal cancer (CRC) significantly contributes to cancer-related mortality, necessitating the exploration of prognostic factors beyond TNM staging. This study investigates the composition of the gut microbiome and microbial DNA fragments in stage II/III CRC. METHODS: A cohort of 142 patients with stage II/III CRC and 91 healthy controls underwent comprehensive microbiome analysis. Fecal samples were collected for 16S rRNA sequencing, and blood samples were tested for the presence of microbial DNA fragments. De novo clustering analysis categorized individuals based on their microbial profiles. Alpha and beta diversity metrics were calculated, and taxonomic profiling was conducted. RESULTS: Patients with CRC exhibited distinct microbial composition compared to controls. Beta diversity analysis confirmed CRC-specific microbial profiles. Taxonomic profiling revealed unique taxonomies in the patient cohort. De novo clustering separated individuals into distinct groups, with specific microbial DNA fragment detection associated with certain patient clusters. CONCLUSIONS: The gut microbiota can differentiate patients with CRC from healthy individuals. Detecting microbial DNA fragments in the bloodstream may be linked to CRC prognosis. These findings suggest that the gut microbiome could serve as a prognostic factor in stage II/III CRC. Identifying specific microbial markers associated with CRC prognosis has potential clinical implications, including personalized treatment strategies and reduced healthcare costs. Further research is needed to validate these findings and uncover underlying mechanisms.