Circulating tumor DNA: An alternative to tissue biopsy for detecting EGFR mutation in NSCLC

Circulating tumor DNA: An alternative to tissue biopsy for detecting EGFR mutation in NSCLC | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Circulating tumor DNA: An alternative to tissue biopsy for detecting EGFR mutation in NSCLC View ORCID Profile Md Kabirul Islam Soroar , Sharmistha Roy , Hosne Ara , Sharif al-Nur , Riyadh Arifin Akanda , View ORCID Profile Mohammad Masum Alam doi: https://doi.org/10.1101/2025.09.19.25336178 Md Kabirul Islam Soroar 1 Department of Biochemistry and Molecular Biology, Bangabandhu Sheikh Mujib Medical University , Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Md Kabirul Islam Soroar For correspondence: kabirulislam.r22{at}bsmmu.edu.bd kabirul.dmc{at}gmail.com Sharmistha Roy 1 Department of Biochemistry and Molecular Biology, Bangabandhu Sheikh Mujib Medical University , Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hosne Ara 1 Department of Biochemistry and Molecular Biology, Bangabandhu Sheikh Mujib Medical University , Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sharif al-Nur 1 Department of Biochemistry and Molecular Biology, Bangabandhu Sheikh Mujib Medical University , Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Riyadh Arifin Akanda 1 Department of Biochemistry and Molecular Biology, Bangabandhu Sheikh Mujib Medical University , Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mohammad Masum Alam 1 Department of Biochemistry and Molecular Biology, Bangabandhu Sheikh Mujib Medical University , Dhaka, Bangladesh Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mohammad Masum Alam Abstract Full Text Info/History Metrics Data/Code Preview PDF ABSTRACT Background Non-small cell lung cancer (NSCLC) patients who have mutations in their EGFR gene respond more favorably to Tyrosine Kinase Inhibitors (TKIs) than to standard chemotherapy. However, tissue biopsy-based EGFR testing is invasive, costly, and technically challenging. Plasma-derived circulating tumor DNA (ctDNA) offers a minimally invasive and cost-efficient alternative for mutation profiling. This study assessed the agreement between EGFR mutation detection in plasma-derived ctDNA and tissue biopsy in NSCLC patients from tertiary care hospitals in Bangladesh. Methods In this cross-sectional analytical study, we recruited 32 patients with NSCLC before EGFR-TKI treatment. EGFR mutations in ctDNA samples were identified using the Amplification Refractory Mutation System (ARMS) PCR method. Tissue biopsy results were obtained from routine diagnostic procedures. Agreement between ctDNA and tissue biopsy results was assessed using kappa statistics, and diagnostic performance metrics were calculated. Results Most of our study participants were male (75%) and had stage IV lung adenocarcinoma (72%). We observed substantial agreement between plasma-derived ctDNA samples and tissue biopsies (kappa, κ = 0.683). This agreement was almost perfect (κ = 0.826) when calculated for patients with stage IV disease. The overall concordance was 84.4%. Compared with tissue biopsy, ctDNA testing yielded a sensitivity of 73.3% and specificity of 94.1%. Conclusion Plasma-derived ctDNA demonstrates substantial agreement with tissue biopsy for EGFR mutation detection in patients with NSCLC, particularly those with advanced-stage disease. These findings support ctDNA as a viable alternative for molecular profiling in settings where tissue biopsy is limited or impractical. INTRODUCTION Cancer stands as a leading cause of mortality worldwide. In 2022, it was responsible for overall 16.8% of deaths and accounted for 22.8% of deaths related to non-communicable diseases. Among all cancer types, lung cancer stands out as the most lethal, giving rise to around 2.5 million incident cases and 1.8 million deaths each year ( 1 ). In Bangladesh, it is the third most frequently diagnosed cancer and the second leading cause of cancer mortality ( 2 ). NSCLC is responsible for nearly 85% of all lung cancer ( 3 ). For accurate categorization and targeted therapy, mutation analysis of NSCLC is necessary and mandated by different societies ( 4 – 6 ). Among the various mutations identified in NSCLC, the Epidermal Growth Factor Receptor (EGFR) mutation exhibits the highest prevalence among Asian patients. It is detected in approximately 55% of cases in East Asia and between 23% and 44% of cases in India. However, their prevalence among Caucasian patients is notably lower, ranging from 10% to 15% ( 7 – 9 ). Notably, about 93% of EGFR mutations are detected within exons 18 to 21 ( 10 ). NSCLC patients harboring mutations in the EGFR tyrosine kinase domain are eligible for targeted therapy with tyrosine kinase inhibitors (TKIs). TKIs radically overturned the conventional chemotherapy regimen by almost doubling the progression-free survival ( 8 ). Detecting EGFR mutations in tissue is considered a prerequisite for starting TKI treatment and predicting treatment responses and prognoses. For this purpose, the College of American Pathologists has recommended testing of the cell block (from excisional biopsy or small biopsy) or cytological sample (e.g. smear) with adequate cellularity and at least 20% or more malignant cell content ( 4 ). However, lung cancer is often detected at an advanced stage, at which point excisional biopsy becomes impractical. Therefore, small biopsies and cytological specimens are the only sources for morphological assessment and mutation analysis ( 11 ). These biopsy procedures are invasive and can cause complications such as hemoptysis, pneumothorax and pneumonitis ( 12 ). Additionally, the results of EGFR mutation analysis can be influenced by the tumor sampling location, as a biopsy from one part of a tumor may not capture the complete molecular heterogeneity ( 13 ). Furthermore, pathological evaluation reveals malignant cells in approximately 73% of specimens ( 14 ), often necessitating repeat biopsies to get enough tissue for genetic testing. The limitations of tissue biopsies can be overcome using a rapidly emerging technique, known as liquid biopsy. In this technique, the plasma or serum of a patient with cancer is used to separate circulating tumor DNA (ctDNA). It is then used for mutation analysis. ctDNA analysis offers multiple benefits over conventional tissue biopsy. First, sample collection for ctDNA is less invasive. Therefore, ctDNA testing can serve as an early screening tool for NSCLC. Second, it can detect minimal residual disease after intervention and can be used to detect disease recurrence ( 15 , 16 ). Third, ctDNA has a half-life of approximately 114 min ( 17 ). Therefore, it can be used to track disease status and drug responsiveness in real time. Fourth, serial ctDNA analyses during treatment can detect resistant mutations, such as T790M ( 18 ). In recent years, researchers have attempted to determine whether ctDNA can replace tissue biopsy or is complementary to it. Numerous studies have used ctDNA to predict EGFR-TKI treatment responses and assess progression-free survival as a primary outcome. Many of these studies have yielded promising results ( 15 , 19 ). Several studies have also assessed the concordance and agreement between ctDNA and tissue biopsies, primarily across Europe, the United States, and the Asia-Pacific region. However, research from South Asia remains limited, with no published data currently available from Bangladesh. Therefore, this study assessed the agreement between EGFR mutation profile in ctDNA and tissue biopsies in NSCLC patients attending tertiary care hospitals in Bangladesh. MATERIALS AND METHODS Study design and participants This cross-sectional analytical study was conducted at Bangabandhu Sheikh Mujib Medical University, now known as Bangladesh Medical University, in Bangladesh, over a one-year period from March 2024 to February 2025. Ethical clearance for this study was granted by the university’s Institutional Review Board. The sample size was calculated using the sample size calculation method for the agreement test of a two-rater study on a dichotomous variable ( 20 ). Considering the availability of patients and the duration of the study, a total of 32 patients with lung cancer were recruited using a consecutive sampling approach from the oncology inpatient and outpatient departments of several tertiary care hospitals across the country. Participants were aged ≥ 40 years and had histologically confirmed NSCLC. The eligibility criteria included no prior treatment with systemic anti-cancer drugs, including TKIs, and the availability of an EGFR mutation test result from tissue biopsy within one week of blood sample collection. After obtaining informed written consent from the study participants, an initial evaluation was performed by history-taking. The clinical history of the participants and EGFR test results from tissue biopsy were subsequently recorded in a pre-formed data collection sheet. cfDNA extraction and EGFR mutation analysis Whole blood was collected in two four mL K 2 EDTA tubes for ctDNA extraction from each study participant. Following collection, the samples were processed within two hours. Initially, they were centrifuged at 3,000 × g for 10 minutes to separate plasma. Subsequently, a microcentrifugation at 11,000 × g for 10 minutes was performed to produce clear samples for mutation analysis. The samples were stored at −80 °C. ctDNA extraction and mutations analysis were conducted at the Department of Biochemistry and Molecular Biology of the University. The ctDNA was extracted using the CatchGene Catch-cfDNA Serum/Plasma 1000 Kit (CatchGene Co., Ltd., Taiwan). EGFR mutation status was assessed using the AmoyDx EGFR 29 Mutations Detection Kit (Amoy Diagnostics, Xiamen, China) on a Rotor-Gene Q (72 wells) real-time PCR machine (Qiagen, Hilden, Germany). This kit is an amplification refractory mutation system (ARMS)-based PCR kit which qualitatively detects 29 somatic mutations in the EGFR gene, especially targeting exons 18 (G719X), 19 (deletions), 20 (exon 20 ins9, T790M, and S768I), and 21 (L858R and L861Q). Each PCR run included seven test samples, one positive control, and one no-template control, and was subjected to 46 cycles of amplification. PCR data were interpreted in accordance with the manufacturer’s guidelines. Statistical analysis Data from this study were analyzed using the Statistical Package for Social Sciences (ver. 27) software. Chi-square and Fisher’s exact tests were applied to compare the EGFR mutation status across various clinicopathological characteristics. Agreement between plasma-derived ctDNA samples and tissue biopsies were assessed using the kappa statistics. Additionally, the diagnostic performance of plasma samples was assessed in comparison with that of tissue biopsies. Statistical significance was assigned to results with p-values ≤ 0.05. RESULTS Clinicopathological characteristics of study participants This study included a total of 32 NSCLC patients. Key clinicopathological parameters of the participants are summarized in Table 1 . The mean age of the participants was 59.2 (59.2 ± 10.9) years. Most of them were male (n=24, 75%) and had adenocarcinoma histology (n=30, 94%). The TNM staging of the tumor was determined using the International Association for the Study of Lung Cancer’s 9 th edition of the lung cancer TNM staging system. Among the study participants, 23 (72%) had stage IV disease. View this table: View inline View popup Download powerpoint Table 1: Clinicopathological characteristics and EGFR mutation frequency of the study subjects (n = 32). EGFR mutation status Of 32 study subjects, EGFR mutations were present in 15 (47%) tissue biopsy samples and mutations were identified in 12 (38%) plasma-derived ctDNA samples, with exon 19 deletion being the most frequent alteration in both specimen types ( Table 1 ). One plasma mutation was a TKI-resistant mutation (T790M), whereas two of the tissue mutations were TKI-resistant (T790M and exon 20 ins9). Table 2 outlines the relationship between EGFR mutation status and various clinicopathological parameters of the patients. In plasma, EGFR mutation rates were significantly higher in patients aged > 60 years and in never smokers (p-values of 0.043 and 0.028, respectively). However, sex distribution, smoking history, histological grade, and tumor stage did not differ significantly across the groups. In tissue samples, mutations were significantly higher in never smokers (p-values of 0.013). View this table: View inline View popup Download powerpoint Table 2: Relationship between EGFR mutation status and clinicopathological characteristics (n = 32). Agreement on EGFR mutation status Of the 32 samples, 27 were concordant (11 positive and 16 negative), yielding a concordance rate of 84.4% ( Tables 3 and 4 ). Among the 15 mutations present in the tissue sample, 11 were also positive in the plasma, resulting in a sensitivity of 73.3%. The overall specificity was 94.1%, with a positive predictive value (PPV) of 91.7% and a negative predictive value (NPV) of 80%. Concordance and sensitivity increased to 91.3% and 90.9%, respectively, when calculated from patients with stage IV disease. We also assessed the agreement between these two sample types ( Table 3 ). Overall, we found a kappa (κ) value of 0.683, indicating substantial agreement between the two sample types. κ increased to 0.826 and reached almost perfect agreement when calculated from participants with stage IV disease ( 21 ). View this table: View inline View popup Download powerpoint Table 3: Comparison of EGFR mutations between plasma-derived ctDNA and tissue biopsy samples. View this table: View inline View popup Download powerpoint Table 4: Diagnostic performance of plasma-derived ctDNA samples compared to tissue biopsy samples for detecting EGFR mutation in NSCLC. DISCUSSION Based on the currently available data, no prior study from Bangladesh has compared EGFR mutation detection between tissue biopsies and ctDNA samples. Our study showed good agreement and concordance between these two. The majority of the participants were aged 55 - 70 years, with a mean age of 59.2 years, consistent with previous studies ( 9 , 22 ). The PIONEER study, the most extensive epidemiological analysis in Asia, also found a similar mean age ( 23 ). Most of the subjects in our study were male (75%) and no statistically significant difference was found between sex distribution and mutation status in the plasma or tissue ( p-values of 0.433 and 1.0, respectively). This result may reflect our relatively small sample size and imbalanced sex ratio (male: female = 3:1). Similar results were observed in some other studies ( 22 , 24 – 26 ). However, in the large database, female sex has been significantly associated with EGFR mutations, as in the IGNITE study ( 27 ). Smoking is the most important factor for EGFR mutation detection, as EGFR mutations are more common in never smokers ( 23 ). In our study, half of the participants were never smokers (50%). However, 75% of the mutations in plasma (9 out of 12) and 73% of the mutations in tissue (11 out of 15) were detected in never smokers. In the IGNITE study, Han et al. ( 27 ) observed similar results. In their study, 67% of mutations in tissue samples and 64% of mutations in plasma samples were found in never smokers. In our study, 72% of the study participants had stage IV NSCLC. In ctDNA samples, we found that the EGFR mutation was strongly positive in this group (11 out of 23 stage IV subjects) compared to stages II–III. These findings were similar to those reported by Wulandari et al. ( 22 ). In the metastatic stage, the ctDNA content in the plasma sample of the patient becomes very high compared to that in the earlier stage, resulting in a high mutation detection rate in the metastatic stage ( 22 ). In our study, we found good agreement and concordance between the tissue biopsy and ctDNA samples. We obtained an overall kappa value of 0.683, which increased to 0.826 when calculated from stage IV disease subjects. Our results were supported by some small- and large-scale studies ( 19 , 28 , 29 ). Soria-Comes et al. ( 28 ) reported an overall kappa value of 0.6, which increased to 0.7 when calculated from subjects with stage IV disease. Veldore et al. ( 29 ) published their study on 132 Indian patients having stage IV NSCLC with distal metastasis, where they used NGS to test plasma samples. Therefore, they found almost perfect agreement (κ = 0.931) between the plasma and tissue samples. In the IFUM study, we calculated a kappa value of 0.755 from the given data. In this study, the authors included patients with locally advanced or metastatic NSCLC, which was reflected in their high kappa values ( 19 ). In our study, we also found a high concordance between tissue and plasma samples. The overall concordance rate was 84.4%. Compared with tissue biopsy, ctDNA demonstrated a sensitivity of 73.3%, specificity of 94.1%, PPV of 91.7%, and NPV of 80%. Concordance and sensitivity substantially increased when calculated from subjects with stage IV disease (concordance, 84.4% to 91.3%; sensitivity, 73.3% to 90.9%). Our study was also supported by some studies conducted in India, the Asia-Pacific region, and Europe (9,19,24,28,29). Three studies reported similar results in the Indian population. Joshi et al. ( 24 ) and Prabhash et al. ( 9 ) reported concordance of 83% and 82.9% respectively. Veldore et al. ( 29 ) did their study on stage IV disease subjects and found high concordance (98.48%), high sensitivity (94.44%) and perfect specificity (100%), which was very close to our results from stage IV disease. Soria-Comes et al. ( 28 ) published a study on the Spanish population, which provided results similar to those of our study (concordance, 87.4%; sensitivity, 70.6%; and specificity, 91.7%). The large IFUM study on the Caucasian population also reported similar results (concordance, 94.3%; sensitivity, 65.7%; specificity, 99.8%; and PPV, 98.6%) ( 19 ). Other studies from Asia have also reported similar concordance (ranging from 80% to 90%) ( 26 , 27 , 30 , 31 ). The ASSESS study ( 31 ), the IGNITE study ( 27 ) and Duan et al. ( 30 ) reported similar specificity, PPV and NPV. However, their published sensitivities were lower than those in our study (sensitivity ranged from 46% to 50%). This was because we had very few false-negative results. In our study, 11 out of 15 tissue EGFR-positive patients had stage IV disease, and from these 11 cases, we found that 10 of them also became positive in plasma. Therefore, we only had one false-negative result in this group. As a result, we observed a high overall sensitivity. Therefore, this study indicates a good agreement between the EGFR mutations detected in the ctDNA samples and tissue biopsies. It was also found that the concordance, sensitivity, and specificity of ctDNA samples were very high compared to tissue biopsies, which is comparable to the findings in other parts of the world. Conclusion We observed substantial agreement, which increased to almost perfect agreement in patients with Stage IV disease. This high level of agreement, along with high concordance, sensitivity, and specificity, strongly indicates that EGFR mutations can be reliably identified using ctDNA. These promising findings highlight the effectiveness of plasma-derived ctDNA as an alternative to tissue biopsy for detecting EGFR mutations in NSCLC patients in Bangladesh, especially when tissue biopsy is not feasible due to financial constraints or advanced disease stages, or when the tissue sample is inadequate for analysis. Limitation This study had a limited sample size, with the majority of patients being male, resulting in a non-homogeneous distribution of the study population. In our study, EGFR mutation detection in tissue biopsies was performed as part of routine clinical investigations, and we performed it in ctDNA samples. This may have introduced operator-related variability. Recommendation It is recommended that EGFR mutations be detected in tissue biopsies and ctDNA samples in the same center, possibly by the same operator, to minimize operator-related variability in the results. Future research should include a more balanced number of male and female patients to avoid any gender bias. Ethics Statement Ethical approval for this study was granted by the Institutional Review Board of Bangabandhu Sheikh Mujib Medical University (Registration No. 5112, Date 13.07.2024). All procedures were conducted in accordance with the ethical standards outlined in the Declaration of Helsinki and relevant national guidelines. Patient data were anonymized prior to analysis to ensure confidentiality. Informed consent statement Written informed consent was obtained from all study participants using a preformatted consent form, following a detailed explanation of the study’s purpose and procedures. Author Contributions Study conception and design: Md Kabirul Islam Soroar, Mohammad Masum Alam Data acquisition and laboratory work: Md Kabirul Islam Soroar, Sharmistha Roy, Hosne Ara Statistical analysis and data interpretation: Md Kabirul Islam Soroar, Sharmistha Roy, Sharif al-Nur, Riyadh Arifin Akanda, Mohammad Masum Alam Study supervision: Mohammad Masum Alam Manuscript drafting, critical revision for important intellectual content, and final approval of the version to be published: Md Kabirul Islam Soroar, Sharmistha Roy, Hosne Ara, Sharif al-Nur, Riyadh Arifin Akanda, Mohammad Masum Alam All authors have read and approved the final manuscript and agree to be accountable for all aspects of the work, ensuring its accuracy and integrity. Conflict of Interest Md Kabirul Islam Soroar: None declared. Sharmistha Roy: None declared. Hosne Ara: None declared. Sharif al-Nur: None declared. Riyadh Arifin Akanda: None declared. Mohammad Masum Alam: None declared. Funding Statement This research was fully funded by Md Kabirul Islam Soroar. Following its completion, he received a student thesis grant from Bangabandhu Sheikh Mujib Medical University. However, this grant had no role in the study design, data collection, statistical analysis, manuscript preparation, or the decision to publish. No other external funding, payment, or services from a third party were received by the authors or their institutions for any part of this work. Data availability statement The datasets analyzed during the current study are available from the corresponding author upon reasonable request. REFERENCE 1. ↵ Bray F , Laversanne M , Sung H , Ferlay J , Siegel RL , Soerjomataram I , et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries . CA Cancer J Clin . 2024 ; 74 ( 3 ): 229 – 63 . OpenUrl CrossRef PubMed 2. ↵ Ferlay J , Ervik M , Lam F , Laversanne M , Colombet M , Mery L , et al. Global Cancer Observatory: Cancer Today . Lyon, France: International Agency for Research on Cancer . https://gco.iarc.who.int/today . Date last updated: February 02 2024 . Date last accessed: August 01 2025 . 3. ↵ Larsen JE , Minna JD . Molecular Biology of Lung Cancer: Clinical Implications . Clin Chest Med . 2011 Dec ; 32 ( 4 ): 703 – 40 . OpenUrl CrossRef PubMed Web of Science 4. ↵ Lindeman NI , Cagle PT , Aisner DL , Arcila ME , Beasley MB , Bernicker EH , et al. Updated Molecular Testing Guideline for the Selection of Lung Cancer Patients for Treatment With Targeted Tyrosine Kinase Inhibitors: Guideline From the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology . Arch Pathol Lab Med . 2018 Mar ; 142 ( 3 ): 321 – 46 . OpenUrl CrossRef PubMed 5. Remon J , Soria JC , Peters S. Early and locally advanced non-small-cell lung cancer: an update of the ESMO Clinical Practice Guidelines focusing on diagnosis, staging, systemic and local therapy . Annals of Oncology . 2021 Dec ; 32 ( 12 ): 1637 – 42 . OpenUrl CrossRef PubMed 6. ↵ Nicholson AG , Tsao MS , Beasley MB , Borczuk AC , Brambilla E , Cooper WA , et al. The 2021 WHO Classification of Lung Tumors: Impact of Advances Since 2015 . Journal of Thoracic Oncology . 2022 Mar ; 17 ( 3 ): 362 – 87 . OpenUrl PubMed 7. ↵ Choughule A , Noronha V , Joshi A , Desai S , Jambhekar N , Utture S , et al. Epidermal growth factor receptor mutation subtypes and geographical distribution among Indian non-small cell lung cancer patients . In: Indian Journal of Cancer . 2013 . p. 107 – 11 . 8. ↵ Tsubata Y , Tanino R , Isobe T. Current Therapeutic Strategies and Prospects for EGFR Mutation-Positive Lung Cancer Based on the Mechanisms Underlying Drug Resistance . Cells . 2021 Nov 16; 10 ( 11 ): 3192 . OpenUrl PubMed 9. ↵ Prabhash K , Biswas B , Khurana S , Batra U , Biswas G , Advani SH , et al. CONCORDANCE: A real-world evidence study to evaluate the concordance of detecting epidermal growth factor receptor (EGFR) mutation by circulating tumor DNA * versus tissue biopsy in patients with metastatic non-small cell lung cancer . Indian J Cancer . 2022 Mar ; 59 (Supplement): S11 – 8 . OpenUrl PubMed 10. ↵ Chevallier M , Borgeaud M , Addeo A , Friedlaender A. Oncogenic driver mutations in non-small cell lung cancer: Past, present and future . World J Clin Oncol . 2021 Apr 24; 12 ( 4 ): 217 – 37 . OpenUrl CrossRef PubMed 11. ↵ Ofiara LM , Navasakulpong A , Ezer N , Gonzalez A V. The importance of a satisfactory biopsy for the diagnosis of lung cancer in the era of personalized treatment . Current Oncology . 2012 Jun 1; 19 ( S1 ): S16 – 23 . OpenUrl 12. ↵ Kuo CY , Lee MH , Tsai MJ , Yang CJ , Hung JY , Chong IW . The factors predicting concordant epidermal growth factor receptor (EGFR) mutation detected in liquid/tissue biopsy and the related clinical outcomes in patients of advanced lung adenocarcinoma with EGFR mutations . J Clin Med . 2019 Nov 1; 8 ( 11 ): 1758 . OpenUrl PubMed 13. ↵ Diaz LA , Bardelli A. Liquid Biopsies: Genotyping Circulating Tumor DNA . Journal of Clinical Oncology . 2014 Feb 20; 32 ( 6 ): 579 – 86 . OpenUrl Abstract / FREE Full Text 14. ↵ Liao BC , Bai YY , Lee JH , Lin CC , Lin SY , Lee YF , et al. Outcomes of research biopsies in clinical trials of EGFR mutation-positive non-small cell lung cancer patients pretreated with EGFR-tyrosine kinase inhibitors . Journal of the Formosan Medical Association . 2018 Apr 1; 117 ( 4 ): 326 – 31 . OpenUrl PubMed 15. ↵ Li YZ , Kong SN , Liu YP , Yang Y , Zhang HM . Can Liquid Biopsy Based on ctDNA/cfDNA Replace Tissue Biopsy for the Precision Treatment of EGFR-Mutated NSCLC? J Clin Med . 2023 Feb 1; 12 ( 4 ): 1438 . OpenUrl PubMed 16. ↵ Wu CY , Lee CL , Wu CF , Fu JY , Yang CT , Wen CT , et al. Circulating tumor cells as a tool of minimal residual disease can predict lung cancer recurrence: A longitudinal, Prospective Trial . Diagnostics . 2020 Feb 1; 10 ( 3 ): 144 . OpenUrl PubMed 17. ↵ Diehl F , Schmidt K , Choti MA , Romans K , Goodman S , Li M , et al. Circulating mutant DNA to assess tumor dynamics . Nat Med . 2008 Sep ; 14 ( 9 ): 985 – 90 . OpenUrl CrossRef PubMed Web of Science 18. ↵ Herbreteau G , Vallée A , Charpentier S , Normanno N , Hofman P , Denis MG . Circulating free tumor DNA in non-small cell lung cancer (NSCLC): clinical application and future perspectives . J Thorac Dis . 2019 Jan ; 11 ( S1 ): S113 – 26 . OpenUrl PubMed 19. ↵ Douillard JY , Ostoros G , Cobo M , Ciuleanu T , Cole R , McWalter G , et al. Gefitinib treatment in EGFR mutated caucasian NSCLC: circulating-free tumor DNA as a surrogate for determination of EGFR status . J Thorac Oncol [Internet] . 2014 [cited 2024 May 31 ]; 9 ( 9 ): 1345 – 53 . Available from: https://pubmed.ncbi.nlm.nih.gov/25122430/ OpenUrl 20. ↵ Sim J , Wright CC . The Kappa Statistic in Reliability Studies: Use, Interpretation, and Sample Size Requirements . Phys Ther [Internet] . 2005 Mar 1 [cited 2024 Jun 10 ]; 85 ( 3 ): 257 – 68 . Available from : doi: 10.1093/ptj/85.3.257 OpenUrl Abstract / FREE Full Text 21. ↵ Landis JR , Koch GG . The measurement of observer agreement for categorical data . Biometrics . 1977 Mar ; 33 ( 1 ): 159 – 74 . OpenUrl CrossRef PubMed Web of Science 22. ↵ Wulandari L , Soegiarto G , Febriani A , Fatmawati F , Sahrun. Comparison of Detection of Epidermal Growth Factor Receptor (EFGR) Gene Mutation in Peripheral Blood Plasma (Liquid Biopsy) with Cytological Specimens in Lung Adenocarcinoma Patients . Indian J Surg Oncol . 2021 Apr 1; 12 : 65 – 71 . OpenUrl PubMed 23. ↵ Shi Y , Au JSK , Thongprasert S , Srinivasan S , Tsai CM , Khoa MT , et al. A prospective, molecular epidemiology study of EGFR mutations in Asian patients with advanced nonsmall-cell lung cancer of adenocarcinoma histology (PIONEER) . J Thorac Oncol . 2014 Feb ; 9 ( 2 ): 154 – 62 . OpenUrl CrossRef PubMed 24. ↵ Joshi J , Raval A , Desai U , Upadhyay V , Bhavsar M , Shah K , et al. EGFR Mutation Analysis in Non-small Cell Lung Carcinoma Patients: A Liquid Biopsy Approach . Indian Journal of Clinical Biochemistry . 2021 Jan 1; 36 ( 1 ): 51 – 8 . OpenUrl PubMed 25. Long C , Li K , Liu Z , Zhang N , Xing X , Xu L , et al. Real-world analysis of the prognostic value of EGFR mutation detection in plasma ctDNA from patients with advanced nonsmall cell lung cancer . Cancer Med . 2023 Apr 1; 12 ( 7 ): 7982 – 91 . OpenUrl PubMed 26. ↵ Mirtavoos-Mahyari H , Ghadami M , Khosravi A , Esfahani-Monfared Z , Seifi S , Motevaseli E , et al. Cell free tumoral DNA versus paraffin block epidermal growth factor receptor mutation detection in patients with non-small cell lung cancer . Asian Pacific Journal of Cancer Prevention . 2019 ; 20 ( 12 ): 3591 – 6 . OpenUrl PubMed 27. ↵ Han B , Tjulandin S , Hagiwara K , Normanno N , Wulandari L , Laktionov K , et al. EGFR mutation prevalence in Asia-Pacific and Russian patients with advanced NSCLC of adenocarcinoma and non-adenocarcinoma histology: The IGNITE study . Lung Cancer . 2017 Nov 1; 113 : 37 – 44 . OpenUrl PubMed 28. ↵ Soria-Comes T , Palomar-Abril V , Ureste MM , Guerola MT , Maiques ICM . Real-World Data of the Correlation between EGFR Determination by Liquid Biopsy in Nonsquamous Non-small Cell Lung Cancer (NSCLC) and the EGFR Profile in Tumor Biopsy . Pathology and Oncology Research . 2020 Apr 1; 26 ( 2 ): 845 – 51 . OpenUrl 29. ↵ Veldore VH , Choughule A , Routhu T , Mandloi N , Noronha V , Joshi A , et al. Validation of liquid biopsy: Plasma cell-free DNA testing in clinical management of advanced nonsmall cell lung cancer . Lung Cancer: Targets and Therapy . 2018 Jan 3; 9 : 1 – 11 . OpenUrl 30. ↵ Duan H , Lu J , Lu T , Gao J , Zhang J , Xu Y , et al. Comparison of EGFR mutation status between plasma and tumor tissue in non-small cell lung cancer using the Scorpion ARMS method and the possible prognostic significance of plasma EGFR mutation status . Int J Clin Exp Pathol . 2015 ; 8 ( 10 ): 13136 – 45 . OpenUrl PubMed 31. ↵ Reck M , Hagiwara K , Han B , Tjulandin S , Grohé C , Yokoi T , et al. CtDNA determination of EGFR mutation status in European and Japanese patients with advanced NSCLC: The ASSESS study . Journal of Thoracic Oncology . 2016 ; 11 ( 10 ): 1682 – 9 . OpenUrl PubMed View the discussion thread. Back to top Previous Next Posted September 21, 2025. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Circulating tumor DNA: An alternative to tissue biopsy for detecting EGFR mutation in NSCLC Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Circulating tumor DNA: An alternative to tissue biopsy for detecting EGFR mutation in NSCLC Md Kabirul Islam Soroar , Sharmistha Roy , Hosne Ara , Sharif al-Nur , Riyadh Arifin Akanda , Mohammad Masum Alam medRxiv 2025.09.19.25336178; doi: https://doi.org/10.1101/2025.09.19.25336178 Share This Article: Copy Citation Tools Circulating tumor DNA: An alternative to tissue biopsy for detecting EGFR mutation in NSCLC Md Kabirul Islam Soroar , Sharmistha Roy , Hosne Ara , Sharif al-Nur , Riyadh Arifin Akanda , Mohammad Masum Alam medRxiv 2025.09.19.25336178; doi: https://doi.org/10.1101/2025.09.19.25336178 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Oncology Subject Areas All Articles Addiction Medicine (568) Allergy and Immunology (863) Anesthesia (300) Cardiovascular Medicine (4435) Dentistry and Oral Medicine (444) Dermatology (382) Emergency Medicine (608) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1509) Epidemiology (15229) Forensic Medicine (30) Gastroenterology (1124) Genetic and Genomic Medicine (6600) Geriatric Medicine (668) Health Economics (997) Health Informatics (4536) Health Policy (1368) Health Systems and Quality Improvement (1613) Hematology (541) HIV/AIDS (1264) Infectious Diseases (except HIV/AIDS) (15916) Intensive Care and Critical Care Medicine (1103) Medical Education (623) Medical Ethics (146) Nephrology (667) Neurology (6599) Nursing (346) Nutrition (998) Obstetrics and Gynecology (1144) Occupational and Environmental Health (957) Oncology (3332) Ophthalmology (974) Orthopedics (369) Otolaryngology (420) Pain Medicine (436) Palliative Medicine (130) Pathology (663) Pediatrics (1693) Pharmacology and Therapeutics (691) Primary Care Research (711) Psychiatry and Clinical Psychology (5447) Public and Global Health (9232) Radiology and Imaging (2198) Rehabilitation Medicine and Physical Therapy (1370) Respiratory Medicine (1196) Rheumatology (593) Sexual and Reproductive Health (712) Sports Medicine (530) Surgery (712) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a008bcdc3810df94',t:'MTc3OTU4ODM1MQ=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();