Real-world biomarker testing patterns: clinical-pathological portrait of early and late non-small cell lung cancer in hub and spoke North Italian centers
Highlight box
Key findings
• The assessment of most biomarkers is still challenging in advanced non-small cell lung cancer (NSCLC).
• Hub can support spoke centers by providing complementary techniques.
• The co-occurrence of gene alterations highlights a deep molecular assessment.
• Immune and molecular changes are similarly altered in early and advanced NSCLC.
• Clinical/pathological/molecular correlations can improve prognostic/predictive grounds.
What is known and what is new?
• The immune/molecular signature is key in NSCLC patients’ management
• We described the extent and effectiveness of pathologic and clinical characterization in NSCLC in a real-world context, highlighting the importance of hub and spoke cooperation.
What is the implication, and what should change now?
• The complexity of NSCLC immune/molecular profile requires deep and complete understanding.
• Our data foster the collaboration between clinicians and pathologists and support the interaction between hub and spoke centers to achieve the best management of NSCLC patients.
Introduction
Lung cancer is the first cause of cancer-related death worldwide. Most cases are diagnosed in the advanced stage when tumor-related symptoms become evident (1). The revolutionary progresses in lung cancer screening, diagnosis, and treatment will hopefully modify this scenario in the near future. Among these, the use of powerful treatment options relying on the detection of molecular and immune biomarkers has had an important impact on non-small cell lung cancer (NSCLC) patient survival (2). Current guidelines (3-5) strongly recommend testing for actionable targets including epidermal growth factor receptor (EGFR), proto-oncogene B-Raf (BRAF) V600, anaplastic lymphoma kinase (ALK), c-ros oncogene 1 (ROS1), MET exon 14 skipping mutations and amplifications; RET rearrangements, Kirsten Rat Sarcoma viral oncogene (KRAS) G12C, human epidermal growth factor 2 receptor (HER2) mutations, neurotrophin receptor tyrosine kinase (NTRK1–3) and programmed death ligand 1 (PD-L1) in tumor samples from patients with metastatic NSCLC to support treatment decision making. Based on recent evidence (6-8) to select patients for adjuvant treatment, the international guidelines have been updated with the expansion of routine molecular analysis to all early-stage lung adenocarcinomas (3,9). Since 2017, guidelines have also reported next-generation sequencing (NGS) testing, at least using limited gene panel testing, has been recognized as an option for multiplex biomarker testing (10). NGS can detect a broad spectrum of alterations, including not only emerging actionable mutations but also concomitant mutations that may be responsible for targeted therapy resistance (11,12). However, upfront NGS testing of advanced NSCLC compared to sequential panel evaluation is still a matter of debate with a major issue being lab expertise and overall cost of the procedure (13,14).
Veneto was one of the first regions in Italy to share a lung cancer care pathway among hub (3 centers) and spoke hospitals (4 centers). Inspired by the European Cancer Organization essential requirements for quality cancer care (15), it draws the lines to identify precise diagnostic paths between different specialists, strengthening collaboration of hub structures and most of the spoke centers in Veneto (16). The systematic assessment of biomarkers in advanced NSCLC—and, based on new evidence, even in early stages (6-8)—and the weekly multidisciplinary discussions along with the annual updated scientific meetings between the pulmonologist and pathologist unit (PPU), can be considered the milestones of this document. Although several short-term performance indicators are included in our lung cancer care pathway, a systematic analysis of effective adherence to biomarker investigation coming from a large PPU network experience has never been reported. Thus, in the present study we sought to explore the current real-world diagnostic journey mainly focusing on molecular assessment and its performance in all Veneto hub and spoke centers. Correlations between molecular and clinical phenotypes have also been investigated. Furthermore, the study summarizes the experience shared among different PPUs in Veneto during annual meetings held over the last two years. We present this article in accordance with the STROBE reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-107/rc).
Methods
Study design
Using a multicenter retrospective observational study, we examined demographic and clinical characteristics, and biomarker testing patterns of patients diagnosed with NSCLC between January 1, 2021, and December 31, 2022, across 7 hospitals (3 hubs and 4 spokes) in the Northern Italy Veneto region. The study was carried out in accordance with the Declaration of Helsinki (as revised in 2013) and the protocol was approved by the Comitato Etico per la Sperimentazione Clinica della Provincia di Padova (No. 5646/AO/23). All participating hospitals were informed and agreed to the study. Informed consent was obtained from each patient in the study.
Data collection
At least one leading pathologist and one referral pulmonologist were identified in each center and supported the collaboration. The three hubs for cancer care were designated on the base of performance criteria (volumes of specialized cancer surgery). The four spokes were connected to the hub hospital for selected services (e.g., administration of standard chemotherapies, diagnosis/staging by imaging techniques). All patients with NSCLC (early and advanced stages) diagnosed in each center were included in the study. Precise inclusion and exclusion criteria for pathological and clinical data were shared among PPUs (Figure 1). Clinical data included smoking history distinguishing current smoker (if they smoked until the month before diagnosis), former smoker (if they had stopped smoking at least one month before the diagnosis), and never-smoker, professional exposure, major symptoms, Eastern Cooperative Oncology Group (ECOG) performance status, diagnostic procedure, and pulmonary function tests that were available at the time of diagnosis. Pathological data comprised histo-type, type of specimen (surgical resection, biopsy, and cytology), biomarkers, and type of method used. The subgroup with complete clinical data was used to assess potential correlations between clinical and pathological findings (Figure 1).
The PPU of each center was responsible for filling an anonymous electronic case report form-Research Electronic Data Capture (REDCap®).
Data analysis
Data were reported as means and standard deviations for continuous variables and as absolute values and percentages for categorical variables. Different tissue sources were compared using Pearson’s chi-square test; P values were adjusted for multiplicity using the Benjamini-Hochberg correction.
Multivariable logistic regression analyses were employed to estimate the effects of various variables on the presence of mutations in different genes. The results were reported as odds ratios (ORs) with 95% confidence intervals (CIs). Statistical significance was set at P<0.05. Statistical analyses were performed using the R software version 4.3.1 (17).
Results
A total of 1,817 patients met the eligibility criteria for the primary goal of our study. The median age was 69 years (standard deviation ±10), the majority of patients were males (1,072, 59%) and in advanced stages 927 (51%) (further details are provided in Table S1).
Most patients had non-squamous histology (1,562, 86%), and a wide percentage were diagnosed with adenocarcinoma (1,308, 72%).
Diagnostic procedures and biomarker detection
The turnaround time from test orders to availability of results was similar among different PPUs, median time of 15.5 working days, according to local guidelines reported in our lung cancer care pathways (16).
Most of the specimens were cytological samples and small biopsies, including bronchial and transbronchial biopsies (43%). Surgical resections (35%) were mostly performed in hub hospitals (30% vs. 10%; P<0.001) (Figure 2).
When the different tissue sources were compared, a significantly different biomarker performance testing was found between cytological, biopsy, and surgical samples (Table 1).
Table 1
Biomarkers | Biopsy (N=1,060) |
Cytology (N=215) |
Surgical resection (N=516) | P value | ||
---|---|---|---|---|---|---|
Biopsy vs. cytology | Biopsy vs. surgical resection | Cytology vs. surgical resection | ||||
PD-L1 | 0.005** | 0.07 | <0.001*** | |||
Assessable | 974 (99%) | 177 (96%) | 455 (100%) | |||
Not assessable | 10 (1%) | 8 (4%) | 0 (0%) | |||
EGFR | <0.001*** | 0.02* | <0.001*** | |||
Assessable | 773 (96%) | 159 (83%) | 390 (99%) | |||
Not assessable | 31 (4%) | 32 (17%) | 4 (1%) | |||
ALK (IHC) | 0.04* | 0.07 | <0.001*** | |||
Assessable | 511 (98%) | 78 (93%) | 298 (100%) | |||
Not assessable | 12 (2%) | 6 (7%) | 1 (0%) | |||
ALK | <0.001*** | 0.07 | <0.001*** | |||
Assessable | 401 (82%) | 87 (58%) | 136 (89%) | |||
Not assessable | 87 (18%) | 63 (42%) | 17 (11%) | |||
ROS1 (IHC) | 0.12 | 0.01* | <0.001*** | |||
Assessable | 404 (97%) | 75 (93%) | 275 (100%) | |||
Not assessable | 13 (3%) | 6 (7%) | 0 (0%) | |||
ROS1 | <0.001*** | 0.02* | <0.001*** | |||
Assessable | 491 (80%) | 65 (43%) | 176 (88%) | |||
Not assessable | 124 (20%) | 85 (57%) | 23 (12%) | |||
BRAF | <0.001*** | 0.20 | <0.001*** | |||
Assessable | 530 (97%) | 103 (74%) | 221 (99%) | |||
Not assessable | 14 (3%) | 37 (26%) | 2 (1%) | |||
RET | <0.001*** | 0.004** | <0.001*** | |||
Assessable | 424 (74%) | 64 (42%) | 180 (86%) | |||
Not assessable | 150 (26%) | 87 (58%) | 29 (14%) | |||
KRAS | <0.001*** | 0.07 | <0.001*** | |||
Assessable | 571 (96%) | 111 (76%) | 254 (99%) | |||
Not assessable | 22 (4%) | 36 (24%) | 3 (1%) | |||
MET (IHC) | >0.99 | >0.99 | >0.99 | |||
Assessable | 1 (33%) | 3 (38%) | 0 (NA) | |||
Not assessable | 2 (67%) | 5 (63%) | 0 (NA) | |||
MET | <0.001*** | 0.005** | <0.001*** | |||
Assessable | 484 (83%) | 84 (55%) | 208 (92%) | |||
Not assessable | 101 (17%) | 68 (45%) | 18 (8%) | |||
NTRK (IHC) | <0.001*** | >0.99 | <0.001*** | |||
Assessable | 94 (99%) | 8 (62%) | 66 (99%) | |||
Not assessable | 1 (1%) | 5 (38%) | 1 (1%) | |||
NTRK1–3 | 0.90 | 0.20 | 0.10 | |||
Assessable | 19 (16%) | 7 (13%) | 11 (27%) | |||
Not assessable | 99 (84%) | 46 (87%) | 30 (73%) |
P value, Benjamini & Hochberg correction for multiple testing. *, P<0.05; **, P<0.01; ***, P<0.001. IHC, immunohistochemistry.
As expected, surgical specimens showed a better performance for the detection of most biomarkers compared to cytology (P<0.001). The biopsy (both transbronchial/bronchial and CT-guided biopsy) performance was satisfactory compared to cytology which was significantly less reliable in the assessment of almost all the molecular targets. When the biopsy was compared with the surgical specimen, a similar performance was observed for PD-L1, ALK [both by immunohistochemistry (IHC) and molecular test], BRAF, and KRAS determination, whereas it was slightly worse for EGFR, ROS1, MET, and RET assessment (Table 1).
Overall biomarker testing rate
PD-L1 assessment was available in 91% of samples (n=1,653) with one third characterized by PD-L1 negative expression (<1%), another third showed mean PD-L1 expression (1≤ PD-L1 <49%) and the other third had high PD-L1 expression (≥50%). EGFR testing was performed on 1,411 patients (78%). The overall population had at least one biomarker test available. The results from all 5 biomarkers were available in 30% of the whole population and in 36% of the advanced NSCLC patients.
Results of all biomarkers and how they changed over time are reported in Table 2 and Figure 3.
Table 2
Biomarker | % | Assessable, n [% of 1,817] |
---|---|---|
PD-L1 | 1,653 [91] | |
<1% | 29 | |
1–49% | 32 | |
≥50% | 25 | |
Not assessable | 5 | |
EGFR1 | ||
Molecular test | 1,411 [78] | |
NGS | 24 | |
RT-PCR | 76 | |
Molecular result | ||
Mutated | 16 | |
Wild type | 79 | |
Not assessable | 5 | |
BRAF2 | ||
Molecular test | 925 [51] | |
NGS | 35 | |
RT-PCR | 64 | |
Molecular result | ||
Mutated | 5 | |
Wild type | 89 | |
Not assessable | 6 | |
KRAS3 | ||
Molecular test | 1,020 [56] | |
NGS | 33 | |
RT-PCR | 67 | |
Molecular result | ||
Mutated | 34 | |
Wild type | 60 | |
Not assessable | 6 | |
RET4 | ||
Molecular test | 955 [53] | |
NGS | 15 | |
RT-PCR | 85 | |
Molecular result | ||
Mutated | 2 | |
Wild type | 70 | |
Not assessable | 28 | |
MET5 | ||
Molecular test | 986 [54] | |
NGS | 27 | |
RT-PCR | 73 | |
Molecular result | ||
Mutated | 4 | |
Wild type | 77 | |
Not assessable | 19 | |
ALK | ||
Immunohistochemistry score | 917 [50] | |
0 | 92 | |
1 | 2 | |
2 | 2 | |
3 | 2 | |
Not assessable | 2 | |
Molecular test | 750 [41] | |
FISH | 7 | |
NGS | 16 | |
RT-PCR | 77 | |
Molecular result | ||
Mutated | 4 | |
Wild type | 75 | |
Not assessable | 21 | |
ROS1 | ||
Immunohistochemistry score | 784 [43] | |
0 | 79 | |
1 | 6 | |
2 | 9 | |
3 | 3 | |
Not assessable | 3 | |
Molecular test | 979 [54] | |
FISH | 22 | |
NGS | 14 | |
RT-PCR | 64 | |
Molecular result | ||
Mutated | 1 | |
Wild type | 75 | |
Not assessable | 24 | |
NTRK1–3 | ||
Immunohistochemistry | 178 [10] | |
Positive | 2 | |
Negative | 94 | |
Not assessable | 4 | |
Molecular test | 212 [12] | |
FISH | 10 | |
NGS | 49 | |
RT-PCR | 41 | |
Molecular result | ||
Mutated | 0 | |
Wild type | 17 | |
Not assessable | 83 |
1, the most common EGFR aberrancy were exon 19 deletion (51%) and exon 21 L858R mutation (37%). 2, the BRAF V600E mutation was most commonly detected. 3, G12C was the most frequently detected KRAS alteration. 4, exon 12 fusions were the main RET aberrancies detected. 5, MET exon 14 skipping skipping alteration was more frequently detected. FISH, fluorescent in situ hybridization; NGS, next-generation sequencing; RT-PCR, reverse transcriptase-polymerase chain reaction.
Testing with NGS was performed in 14% of the overall population and 16% of the advanced NSCLC cases. NGS testing was more often executed in hub than spoke hospitals (17% vs. 3%; P<0.001). Availability of NGS test results increased significantly over time (P<0.001), as shown in Figure 4.
Co-occurring biomarkers
Logistic regression models, adjusted for histo-type, were developed to investigate the association between PD-L1 expression and the mutational status of each oncogene. A significantly higher frequency of ALK rearrangement was found in samples with 1%≤ PD-L1 <49% and PD-L1 ≥50% compared to PD-L1 <1% [OR (95% CI): 2.56 (1–7.57); P=0.04 and OR (95% CI): 3.59 (1.42–10.56); P<0.001, respectively]. Of interest, PD-L1 >50% was associated to increased risk of MET [OR (95% CI): 2.55 (1.07–6.57); P=0.03], KRAS [OR (95% CI): 1.73 (1.27–2.36); P<0.001] and BRAF [OR (95% CI): 2.63 (1.18–6.35); P=0.02] mutations. High PD-L1 expression (>50%) was rarely detected in EGFR-mutated cases [OR (95% CI): 0.33 (0.22–0.49); P<0.001].
Among the 1,817 samples examined, at least one molecular aberrancy was detected in 742 (41%). Co-occurring molecular targets were detected in 42 cases (2%) (Figure 5). NGS testing was applied in 34% of the samples harboring 2 or more molecular targets and in 14% of those with one or none (P=0.001). Among these, the most common were the concomitant alterations of ALK and KRAS (n=3), MET and KRAS (n=4), BRAF and KRAS (n=6). Further details are listed in Table S2.
Association between pathological/molecular data and clinical findings
Former smokers [OR (95% CI): 0.6 (0.41–0.91); P=0.02] and never-smokers [OR (95% CI): 0.6 (0.37–0.99); P=0.048] had less probability to show PD-L1 expression >50% than current smokers.
Patients with hemoptysis at the time of diagnosis shared a higher probability of PD-L1 staining >50% than asymptomatic ones [OR (95% CI): 1.98 (1.06–3.64); P=0.02].
ALK rearrangement was more common among non-smokers than current smokers [OR (95% CI): 7.29 (1.78–49.3); P=0.01].
Patients complaining pain at the time of diagnosis had a higher probability of sharing ALK alterations than asymptomatic patients [OR (95% CI): 2.68 (1.03–6.19); P=0.02].
MET abnormalities were more common in patients with respiratory failure than normoxic ones [OR (95% CI): 6.67 (0.92–32.1); P=0.02].
Males had a lower probability of harboring EGFR abnormalities than females [OR (95% CI): 0.28 (0.19–0.4); P<0.001]. The probability of EGFR mutations was higher in asymptomatic never-smokers compared to current smokers [OR (95% CI): 3.75 (1.96–7.51); P<0.001] and symptomatic patients [OR (95% CI): 1.58 (1.06–2.532); P=0.02].
KRAS aberrancies were more common in patients with professional exposure to pneumotoxic agents [OR (95% CI): 2.07 (1.12–3.85); P=0.02] and in both current [OR (95% CI): 4.41 (2.24–9.38); P<0.001] and former smokers [OR (95% CI): 4.12 (1.97–9.19); P<0.001] compared to never-smokers.
The risk of neurologic symptoms at diagnosis was higher in BRAF-mutated patients [OR (95% CI): 3.7 (1.2–9.53); P=0.01].
A trend was detected when the association between squamous cell carcinoma and high PD-L1 expression was analyzed [OR (95% CI): 1.33 (0.99–1.78); P=0.06].
The probabilities of detecting PD-L1 expression >50%, any genomic aberrancies, and at least one targetable alteration were similar when the early stages were compared to advanced stages (Figure 6).
Two or more concomitant molecular targets were more frequent among women than men (58% vs. 42%; P<0.001), never-smokers compared to current smokers (50% vs. 6.3%; P<0.001), and patients without dyspnea than patients complaining of shortness of breath (15% vs. 6%; P=0.01).
The co-occurrence of three different molecular abnormalities was detected in three early-stage adenocarcinomas: (I) MET [NM_001127500.2(MET):c.3029C>T (p.Thr101Ile)], BRAF [NM_004333.4(BRAF):c.1391G>T (p.Gly464Val)], and PIK3CA [NM_006218.3(PIK3CA):c.1624G>A (p.Glu542VLys)] in a 73-year-old former smoker with stage Ib adenocarcinoma; (II) MET [MET exon-14-skipping], EGFR [NM_005228.5(EGFR):c.2573T>G (p.Leu858Arg)], and KRAS [NM_004985.5(KRAS):c.35G>A (p.Gly12Asp)] in a 77-year-old woman who had never smoked and had no significant medical history with surgically resected stage IIIa adenocarcinoma (Figure 7); (III) KRAS [NM_004985.5(KRAS):c.34G>A (p.Gly12Ser)], MET [NM_020975.6(RET):c.3116C>T (p.Pro1039Leu)], and BRAF [NM_004333.6(BRAF):c.1390G>A (p.Gly464Arg)] in a 63-year-old man with surgically resected stage Ib adenocarcinoma and history of thyroid and kidney cancers.
Discussion
In this real-world study of an unselected multicenter cohort of patients with NSCLC, we documented the diagnostic journey mainly focusing on molecular assessment by PPUs of hub and spoke hospitals, according to our local lung cancer care pathway (16).
PD-L1 expression was assessed in over 90% of samples while the oncogenes EGFR, ALK, BRAF and ROS1 were evaluated in about 50% (78%, 50%, 43% and 51%, respectively) of the overall study population. This rate was similar to the metastatic NSCLC of the US oncology network (18), with the simultaneous assessment of all 5 essential biomarkers achieved in a similar percentage of our advanced cases, namely 22–49% vs. 33–46% in the study by Robert et al.
These low percentages probably reflect the screening in fewer representative samples as cytologies and small biopsies, even with the advent of tissue sparing procedures like NGS which, anyway, was increasingly applied in our centers over time. Indeed, even if several pathology laboratories are now equipped for cytology smear analysis and cytoblock evaluation of biomarkers either in situ by immunohistochemistry or molecular analyses their performance has often been reported to be limited (19,20) as it also turned out in our study. NTRK1–3 fusions were investigated only in 212 (12%) samples as the target treatment was recently approved in NSCLC assessment (5).
Across the study period, a stable percentage of samples was tested for PD-L1 while oncogene assessment had a steep increase between the first months of 2021 and the following time points.
The accessibility of testing facilities and healthcare services during periods of heightened pandemic-related restrictions could have posed barriers to patient engagement with biomarker testing. Factors such as limited transportation options, reduced clinic hours, and prioritization of resources for COVID-19 testing and treatment may have inadvertently impeded access to NSCLC biomarker testing for some individuals (21). However, it is essential to acknowledge that the decline in testing rates is likely influenced by a combination of factors, reflecting the multifaceted nature of healthcare delivery during the pandemic.
In our study, 41% of patients harbored a driving molecular aberrancy. Among those, a small but relevant percentage (2%) shared two or more co-occurring genomic alterations more often detected by NGS whose use was progressively implemented in the last months of our study (22). The occurrence of multiple genomic aberrancies in NSCLC is potentially more impactful than distinct mutations in oncogenic drivers and represents a challenge for medical oncologists who are asked to choose the most appropriate target of treatment and further personalize patient management (23). In our study, EGFR mutant adenocarcinomas showed a significantly lower frequency of PD-L1 >50%. The link between the EGFR signaling pathway and PD-L1 expression in NSCLC is currently under investigation (24). Further studies will explain the inefficacy of anti-PD-1/PD-L1 immune check-point inhibitors compared to chemotherapy in advanced EGFR-mutant NSCLC (25) and of the combination EGFR-tyrosine kinase inhibitor (TKI) plus anti-PD-1 inhibitor compared to EGFR-TKI monotherapy (26).
It is noteworthy that the three patients who showed multiple concomitant genomic alterations had all been diagnosed with early-stage adenocarcinomas. Evidence of the frequency (27) and the importance (7,28) of EGFR mutation in the early stage is accumulating. Osimertinib, an oral EGFR-TKI, effectively improves disease-free survival, reduces the risk of local and distant recurrence after complete tumor resection (ADAURA 1 and 2 trials), and is now being tested as a neoadjuvant approach for resectable stage II–IIIb N2 EGFR mutated lung cancers (29). Nonetheless, since the advent of NGS, it has become increasingly evident that treatment response is far from being homogeneous even in target therapy. Such variability, along with de novo resistance, could be linked to the molecular intra-driver heterogeneity (30). In this context, our observations support the importance of accurate molecular profiling even in the early stage of NSCLC as well. Recently, a few real-world results from other centers have already underlined the importance of comprehensive tumor characterization, including early-stage adenocarcinoma, to better define the clinical/molecular phenotypes, to guide the following therapy choices (31-33).
Clinical-pathological and molecular correlations revealed intriguing findings, some confirming data already reported in the literature and others expanding previous knowledge, that could be helpful for more appropriate management of patients. Never-smoking women with minor symptoms had the highest probability of harboring coexistent aberrancies which included not only EGFR, as expected based on a large volume of literature, but also KRAS and MET mutations, usually found in smokers. Of interest, smoking-related molecular aberrancies were found in never smokers in a recent genome-wide study suggesting that clinically based classification of NSCLC could be biased (34). Along this line, our data indicate the importance of deep molecular profiling even in early-stage settings, regardless of clinical characteristics such as smoking history. Further research and analysis are needed to fully understand how these associations actually translate into actionable clinical insights and influence patient care.
In our cohort, squamous cell carcinoma patients who were active smokers and had hemoptysis showed high expression of PD-L1. On the link between PD-L1 and smoking history, contradictory results have been reported in previous studies (35,36), perhaps because former/current smokers were not distinguished and because of the co-occurrence of genetic and epigenetic mechanisms. Cigarette smoke has been shown to induce PD-L1 expression on lung epithelial cells in vitro and in vivo by the selective link between the carcinogen benzo(a)pyrene and the aryl hydrocarbon receptor (37).
On the other hand, 7% of our nonsmoker adenocarcinoma cases showed the typical ALK translocation, a carcinogenic abnormality shared by several different cancers which, like EGFR mutations (38), is less common in patients exposed to cigarette smoke (39).
Supporting the previously suggested link between KRAS mutation and occupational asbestos exposure in lung adenocarcinoma (40), we found a higher frequency of KRAS aberrancies among NSCLC patients with professional exposure to pneumotoxic agents (mainly asbestos).
The presence of neurologic symptoms at diagnosis was common in our BRAF-mutated cases, whose association between brain metastasis and specific mutations has been described (41). In this large case series of BRAF-mutant NSCLC, almost 1/10 patients with V600E mutation and extrathoracic localizations had brain metastasis. Even higher percentages were detected in patients with different functional classes of BRAF mutations, poorly represented in our cohort.
A limitation of our work is that some patient variables were missing due to the observational and retrospective design of the study. However, the high number of cases and data collected by different centers has provided a reliable portrait of the biomarker landscape of NSCLC in the Veneto region. This indicates the need for an effective collaboration not only between different centers (hub and spoke) but above all the different PPUs with consolidated activities. Indeed, in the effort to provide quality data for the study, the participating researchers/personnel frequently met, shared experiences and difficulties. Moreover, the team was used to find solutions for practical limitations, strengthening the link between the specialists of the NSCLC diagnostic pathway. Along with depicting the pathologic and clinical phenotype of the patients diagnosed with NSCLC, this study represents an example of self-criticism and growth for integrated care teams.
Conclusions
This real-world study of patients diagnosed with NSCLC, the majority of whom were tested for biomarkers, was conducted in a regional network of pathologists and pulmonologists. Due to the advent of new molecular testing techniques, the evaluation of complementary genomic aberrancies has progressively increased. Complex advanced NSCLC cases requiring complete molecular profiling could benefit from being referred to hub centers where lung surgery and NGS testing techniques are suitable and standardized. Clinical-molecular phenotypes, if confirmed in future larger studies, could give insights not only into patient management but also for investigating new pathogenetic pathways.
Acknowledgments
We thank the whole Thoracic Oncology Multidisciplinary Team and, overall, all our patients.
Funding: This work was supported by
Footnote
Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-107/rc
Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-107/dss
Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-107/prf
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-107/coif). The authors have no conflicts of interest to declare.
Ethical Statement:
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
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