Introduction

Cancer is the second leading cause of death worldwide, accounting for approximately one in six deaths in 2018.1 The incidence of new lung cancer cases in Indonesia has increased more than fivefold over the past decade, with the majority (85%) being Non-Small Cell Lung Cancer (NSCLC).2,3 This condition has low survival rates, with a first, second, and third-year overall survival rate of 94%, 91%, and 78% respectively.4 The 5-year survival rate is only 24% with one of the contributing factors being delayed diagnosis and treatment.5,6 Statistical data show that 65% of NSCLC cases are diagnosed at an advanced stage,3,7 leading to delayed initiation of treatment. Meanwhile, platinum-based (PB) chemotherapy is known to have variability in effectiveness, with an overall response rate (ORR) ranging from 26% to 63%.6,8 Studies in the UK have reported rates of 20% to 40%, while a pooled analysis yielded an ORR range of 29.7% to 46.7% for PB regimens.9,10 This has evolved into a significant concern, given that PB treatment protocols are integrated into the national healthcare coverage and persist as the predominant choice for initial therapy among Indonesian NSCLC patients with wildtype Epidermal Growth Factor Receptor (EGFR) profile.3 Targeted therapies including Vascular Endothelial Growth Factor (VEGF) inhibitors, bevacizumab, or ALK-inhibitors namely crizotinib for ALK and c-ros oncogene 1 (ROS1)-positive mutations, as well as immunotherapy (atezolizumab) for those with high Programmed Death-Ligand 1 (PD-L1) expression, are not currently provided by the national healthcare coverage.11–16 The widespread use of PB regimens in Indonesia is in contrast to the potential benefits associated with biologic agents, which are generally regarded as more effective for NSCLC treatment whether used individually or in combination.14

In the context of platinum-based chemotherapy response, genetic factors, particularly single nucleotide polymorphisms (SNPs), play a crucial role in influencing treatment response. These genetic markers, which impact either the pharmacodynamics (PD) or pharmacokinetics (PK) of the drug, are essential for understanding the variability in patient outcomes. While PK-related genes are involved in the Absorption, Distribution, Metabolism, Excretion (ADME), or detoxification pathways, PD-related genes are associated with the platinum’s mechanism of action, particularly in DNA repair processes like nucleotide excision repair (NER) and base excision repair (BER). Variations in these genes can alter the activity of DNA repair pathways, which play a key role in tolerating the DNA damage caused by the formation of platinum-DNA adducts.17 Furthermore, polymorphism associated with NER and BER genes, including Excision Repair Cross-Complementing group 1/2 (ERCC1/ERCC2), and X-ray repair cross-complementing protein 1/2/3 (XRCC1/2/3), have been identified in several meta-analysis as the best factors related to alteration of sensitivity to PB chemotherapy,18–20 while Xeroderma Pigmentosum Group A-Complementing Protein (XPA) polymorphism have been associated with clinical benefit.21 From The Clinical Pharmacogenetics Implementation Consortium (CPIC) lists five genes, including ERCC1, as having a D evidence level, and one gene, MTHFR, as having a C evidence level. According to PharmGKB data, ERCC1, ERCC2, XPC, and XRCC1 are listed at level 3. This information indicates that these genetic markers, particularly ERCC1 and ERCC2, which have been the primary focus of previous studies evaluating individual responses to platinum-based chemotherapy in NSCLC, are key markers in the NER pathway. In addition to being known for its association with chemotherapy response, ERCC2 rs13181 polymorphism is also recognized for its significant sensitivity to ethnicity/race.20,22,23 This issue becomes crucial as we enter the era of precision medicine. The lack of global genetic diversity in research limits the applicability of biomedical findings across different ethnicities and populations. Most human genomics studies have focused on individuals of European ancestry, who represent only a small fraction of the global population.24–26 However, they currently have weak evidence for use in pharmacogenetic screening.18,27–31 This is largely due to the limited number of studies on this topic, especially those conducted in developing countries.32–34 Additionally, no studies have yet investigated the relationship between ERCC2 and the clinical response to platinum-based chemotherapy in Indonesia.29

Another equally important fact is Indonesia has significant genetic diversity, largely influenced by the history of archaic humans. This diversity drives variation in gene regulation within the Indonesian population, including variations inherited from archaic humans such as Denisovans and Neanderthals. These factors contribute to a unique genetic architecture in Indonesia, impacting how genes are regulated and expressed in this population.35 Recent meta-analysis of 121 eligible studies found that subgroup analysis by ethnicity for ERCC1 rs11615 indicated an increased risk of platinum-based chemotherapy resistance in Asians across all genetic models examined, while for ERCC2 rs13181, Asians had a higher odds ratio (OR) compared to Europeans, suggesting that population stratification contributes to the high heterogeneity observed. The confounding effect of ethnicity is apparent, as ERCC2 rs13181 showed significant associations in Europeans but not in Asians under the dominant model. Nevertheless, the association analysis between polymorphisms and chemotherapy response from that study still yielded non-significant results.20

However, other reports presented varying results between polymorphisms in ERCC2 and the clinical outcomes of platinum-based chemotherapy.36,37 Based on all the data we have gathered, research on ERCC2 rs13181 is needed to support the evidence level and to provide additional information regarding the relationship of this SNP with the response to platinum-based chemotherapy in Asian populations, as it is known that this gene is significantly influenced by race.

Materials and Methods Study Design and Population

This study obtained ethical approval from the Research Ethics Commission of Dr. H.A. Rotinsulu Lung Hospital and Dharmais Cancer Hospital, in accordance with the requirements of the Helsinki Declaration. Additionally, informed consent was obtained from all participants prior to their involvement in the study. Additionally, informed consent was obtained from all participants prior to their involvement in the study. An observational cohort study was conducted at Dr. H.A. Rotinsulu Lung Hospital, Bandung and Dharmais Cancer Hospital, Jakarta, Indonesia which focused on inpatients with inoperable (stage III and/ IV) NSCLC treated with PB chemotherapy as first-line and exhibiting wildtype EGFR mutations. Data collection was focused on the analysis of genotypes using 3 mL whole blood samples, as well as the retrieval of medical records containing patient profiles, including age, gender, history of alcohol and smoking, histology type, cancer stage, and details of the chemotherapy regimen.

Smoking and alcohol history is categorized into “former” and “never” classes. A “former smoker” is defined as someone who has smoked at least 100 cigarettes in their lifetime and had quit smoking at the time of the interview. A “former alcoholic” is defined as someone who has had a history of consuming at least one drink but has not consumed any alcohol in the past year. Evaluate the effectiveness of the chemotherapy response using the Response Evaluation Criteria in Solid version 1.1 (RECIST 1.1) criteria after the completion of chemotherapy fourth cycles based on the results of Computed Tomography (CT) scans of the thorax. RECIST 1.1 results were categorized into responders including Complete Response (CR) and Partial Response (PR) as well as non-responders, namely Stable Disease (SD) and Progressive Disease (PD). However, SD was considered a responder criterion for patients at advanced cancer stages (IVA and IVB). Patients who were lost to follow-up, delayed chemotherapy for more than two cycles, changed regimen before RECIST 1.1 was obtained, had a comorbid disease treated with immunosuppressants or antiviral medications, had incomplete medical records, or untraceable RECIST 1.1 results were excluded.

Genotyping Analysis

Vacutainers without anticoagulants were used to collect 3 mL of whole blood, leading to the separation of serum and blood clot components. Subsequently, DNA was isolated from the blood clot and PCR was conducted before analyzing the polymorphisms using the Sanger sequencing method. The Forward Primer was (F): 5’-GCC CGC TCT GGA TTA TAC G - 3’ while the Reverse Primer was (R): 5’-CTA TCA TCT CCT GGC CCC C-3’ with an expected fragment length of 436 bp.

Statistical Analysis

The statistical data analysis was conducted in two stages, the first stage entailed the distribution of genotype frequencies and testing for Hardy-Weinberg genetic equilibrium using the chi-square test with a significance level of P=0.05. Subsequently, the association between polymorphisms and chemotherapy effectiveness was analysed using a bivariate approach to estimate the Odds Ratio and 95% Confidence Interval (CI). The presence or absence of a significant relationship between these variables was tested using the Chi-Square (χ2) method.

Results Genotype Distribution and Frequency

The distribution of all genotypes including wild-type, heterozygous, and homozygous polymorphic variants with Hardy-Weinberg equilibrium (HWE) is presented in Table 1. This study showed that there was no significant difference between the observed frequencies and the expected frequencies. In other words, the genotype frequencies conformed to the HWE. The p-value exceeded the designated significance level (α) (0.917 > 0.05) and the calculated Chi-Square value was less than the critical value from the table (0.174 < 5.991). Consequently, the null hypothesis (H0) was accepted, and the alternative hypothesis (H1) was rejected.

Table 1 Hardy-Weinberg Equilibrium Test

Characteristics of Patients

A total of 268 patients with cytologically or histologically confirmed NSCLC with wildtype profile of EGFR, treated with PB chemotherapy as first-line treatment, were recruited. All 268 patients provided signed informed consent prior to their participation in the study. The patients were followed up until the completion of at least four cycles of chemotherapy to obtain the RECIST 1.1 data. Finally, 82 patients met the inclusion criteria, with the majority being male (64.6%) and older than 57 years old (50%) (p=0,033). In terms of lung cancer risk factors, a significant association was found between gender and the history of smoking, with the majority of male patients being former smokers (62,2%), while only a small percentage of females had a history of smoking (7,3%) with p<0,05. However, there was no significant association with alcohol consumption habit history based on gender.

The majority of patients, regardless of gender, were at an advanced stage, either IVA or IVB, with adenocarcinoma as the predominant histological type. Treatment was carried out using PB chemotherapy combined with non-pemetrexed, namely taxane (Table 2). Furthermore, multivariate analysis showed that adenocarcinoma posed a higher risk of being categorized as non-responders compared to non-adenocarcinoma types including squamous and large cell carcinoma (OR=0.660, CI: 0.244–1.785). Similarly, patients with a history of smoking and alcohol consumption were also at higher risk of being non-responders (OR=0.684, CI: 0.234–2.004 and OR=0.829, CI: 0.299–2.299). Patients older than 57 years old have a potentially higher risk of being categorized as non-responders to PB therapy (OR=1.971, CI: 0.681–5.709). The adjusted odds ratio analysis, a method for confounding analysis, showed differences in interpretation for histopathology and smoking status (OR=1.146, CI: 0.245–5.360 and OR=1.412, CI: 0.289–6.893). However, the statistical results did not indicate any significant associations between all the patient characteristics and the treatment outcomes according to RECIST 1.1 (p > 0.05) (Table 3).

Table 2 Characteristics of Patients and Clinical Features

Table 3 Effect of ERCC2 rs13181 on Treatment Outcomes

Genetic Polymorphism and RECIST 1.1

The results showed that among the Indonesian population, the majority were wildtype (AA) for ERCC2 rs13181 (82.9%). Regardless of genetic polymorphism, 58 (70.7%) out of the 82 patients were classified as responders. Among these, patients with the wildtype genotype comprised 82.7% of the responder category. The results showed an odds ratio (OR) of 1.389 for the AC genotype, indicating that patients with this variation had 1.389 times the odds of responding to treatment compared to those with the AA variation. Additionally, polymorphisms in ERCC2 rs13181, specifically the mutant genotype (AC+CC), tend to have a chemotherapy response categorized as a responder (OR=1.042, CI: 0.292–3.715). When adjusted for clinical staging and regimen factors, the mutant genotype had a worse chemotherapy response than the wildtype (OR= 0.970, CI: 0.263–3.568). Based on the statistical analysis results, no significant association was found with chemotherapy response (P>0,05) (Table 4).

Table 4 Association Between ERCC2 rs13181 with Platinum-Based Chemotherapy Responses Based on RECIST 1.1

Discussion

Lung cancer has sex-specific trends with males generally having a higher lifetime risk of development. These differences can be attributed to environmental factors, including smoking status, along with inherent biological differences, such as the contribution of sex hormones and differences in immune responses.38,39 Approximately 80% of lung cancer cases in men are attributed to smoking. Among the various types of non-small cell lung cancer (NSCLC), squamous cell carcinoma (SCC) has a particularly strong association with smoking.40 This study found similar results as the majority of male patients had a history of smoking (62.2%). There was also a statistically significant difference based on gender in relation to smoking history (p=0.000). A large proportion of male patients had either quit smoking upon being diagnosed with lung cancer or stopped during the chemotherapy treatment after one or two cycles. Although only a few patients had a history of alcohol consumption (30,5%), both smoking and alcohol consumption are well-established risk factors for lung cancer. Smoking is directly associated with lung cancer mortality, causing premature deaths. It contributes to approximately 30% of total cancer deaths, and about 90% of lung cancer deaths.41,42

The reduced effectiveness and tolerance of chemotherapy due to alcohol consumption are associated with the activation of cell growth cycles and the stimulation of survival pathways that manifest as apoptosis resistance.43–45 Alcohol consumption also influences the prognosis and survival rate of cancer patients. Statistical data from 2002, for instance, indicated that 3.5% of cancer deaths were connected with alcohol.46 This may explain the odds ratio (OR) of smoking and alcohol consumption history in relation to treatment outcomes, posing a risk for non-responder categorization among patients, although the result was not statistically significant. Similarly, regarding age, the majority of males above 57 years had a statistically significant difference compared to females (p=0.033). Previous studies on NSCLC in the US indicated that new cases/incidence, and the prevalence of lung cancer, are predominantly found in the elderly. Patients with stage IV NSCLC aged 65 years or older were most likely to be untreated (38.3%).47

The choice of chemotherapy regimen may also influence treatment outcomes. For instance, adenocarcinoma patients may benefit from pemetrexed. Although cisplatin is slightly more effective as a platinum agent, it has been associated with various side effects. Evidence suggests that patients with a performance status (PS) of 2 may require only one drug, typically not platinum-based.48–50

The underlying theory regarding the association of rs13181 polymorphisms with chemotherapy response is the drug resistance mechanism, which entails DNA repair activity that could inhibit the apoptosis process of cancer cells. The polymorphism in rs13181, which codes for a protein component of the DNA helicase enzyme associated with the recognition of damaged DNA sites caused by platinum agent, and unwinding process leads to alterations in the amino acid Lysine (Lys) to Glutamine (Gln). This alteration manifests as changes in Nucleotide Excision Repair (NER) activity, leading to a decrease in the effectiveness of PB chemotherapy. It primarily impacts the incision stage of the NER mechanism, causing direct changes in NER activity.21,51–53 From the previous meta-analysis study, ERCC1 rs11615 and ERCC2 rs13181 were found to be the best predictors of chemotherapy response (Overall Survival and/ Progression Free Survival) among many other genes associated with the chemotherapy resistance mechanism. Several other polymorphisms include ERCC1 rs3212986 (ORR), XPA rs1800975 (ORR), ERCC2 rs1052555 (OS, PFS), XPG rs2296147 (OS), XRCC1 rs1799782 (ORR), XRCC3 rs861539 (ORR), GSTP1 rs1695 (ORR), MTHFR rs1801133 (ORR), and MDR1 rs1045642 (ORR).30

Among the nine genes associated with chemotherapy response or clinical outcomes, the majority were associated with DNA repair mechanisms including EXCC1, XPA, XPD, XPG, XRCC1, and XRCC3. Genes related to chemotherapy resistance through drug pharmacokinetics mechanisms include drug influx and efflux (MDR1) as well as metabolism and detoxification (GSTP1), while the last gene, MTHFR, plays a role in the DNA synthesis process.19 Another meta-analysis study stated that ERCC2 rs13181, along with other Single Nucleotide Polymorphism (SNPs) such as ERCC1 (rs11615) and XRCC1 (rs25487, 1,799,782), ranked among the top three predictor genes for sensitivity/response to PB chemotherapy. These genes are associated with DNA repair pathways, both in NER and Base Excision Repair (BER).18

Previous studies have yielded positive statistically significant results regarding the association between rs13181 and the impact on the clinical outcomes of PB chemotherapy. For example, a study of 72 subjects from the US population found that individuals with the A allele were significantly less likely to respond to treatment (HR 0.33; 95% CI 0.13–0.83).54 Similarly, a case-control study involving 1,016 subjects from the Chinese population found that the mutant (C) allele significantly increased the chemotherapy response (OR 2.37; 95% CI 1.12–5.01; p=0.021).55 Furthermore, the results of a meta-analysis with 2,125 subjects, including both Asian populations (China and Korea) and European populations (Spain, Italy, UK, Netherlands), showed significant results for the overall response rate (OR 0.81; 95% CI 0.66–0.99)18. In contrast, another meta-analysis with 29,478 subjects showed no significant results for the response rate across five comparison models (allele comparison, homozygote comparison, heterozygote comparison, recessive model, and dominant model).20

Based on the results of this study indicated no significant association between the mutant polymorphism (AC+CC) and therapeutic response (p=0.950) despite an odds ratio (OR) value of 1.042 (95% CI: 0.292–3.715) found in the analysis. Further analysis was performed by adjusting the OR for variables such as cancer stage and regimen. However, the results showed no significant association (aOR: 0.970; 95% CI: 0.263–3.568; p=0.963). These findings are in line with the majority of reports on ERCC2 rs13181 in PhamGKB. Differences from other studies discussed earlier may be attributed to study design and sample size contributing to research outcome variations. Additionally, in previous studies, the response was assessed in the second cycle,54 whereas in Indonesia, the evaluation is performed in the fourth cycle, following the national healthcare coverage policies.

Another potential factor influencing the study results is genotype distribution. A study in a Japanese population reported genotype distribution results where the AA genotype was dominant, with 73 subjects (98.6%), the AC genotype with one subject (1.4%), and no subjects with the CC genotype. The high dominance of the AA genotype complicates the interpretation of the relationship between allelic variation and response.54 In addition, based on meta-analysis, population stratification contributes to high heterogeneity scores in an analysis.20 In this study, the results of genotype identification showed that the AA genotype dominated, with 68 subjects (82.9%), followed by the AC genotype with 13 subjects (15.9%), and the CC genotype with one subject (1.2%). A study reported that genetic variation in the Indonesian population is diverse due to the interaction of multiple ancestral populations. This variation reflects a unique genetic composition within the population, which may lead to differences in treatment response compared to European and other Asian populations.35

During advanced stages, particularly in the metastasis of lung cancer, the interpretations of RECIST 1.1 results may vary. For instance, the classification of stable disease as a responder has been a subject of debate. Previous studies suggested that in advanced NSCLC patients given a combination of chemotherapy and targeted therapy as initial treatment followed by assessment using RECIST 1.1 criteria, stable disease (SD) demonstrated a comparable overall survival advantage to partial response (PR). This implies that assessing the effectiveness of anti-tumor treatments based solely on RECIST criteria may not always be consistent with overall survival benefits. Consequently, a more comprehensive assessment approach is needed to enhance the precision of RECIST 1.1 criteria, particularly for patients taking chemotherapy combined with targeted therapy for NSCLC.56,57

As previously mentioned, the limited amount of data can influence the confidence interval and probability values, underscoring the need for further studies with a more adequate sample size. However, the results may be considered in the evaluation of chemotherapy response especially for patients treated using PB chemotherapy for NSCLC in Indonesia. To obtain clinical confirmation regarding the association between rs13181 and the clinical outcomes of PB chemotherapy, further cohort studies with larger sample sizes, including subjects representing clusters from different regions of Indonesia, and more comprehensive sample data to minimize bias are required. Additionally, several single nucleotide polymorphisms (SNPs) should be analysed in association with resistance mechanisms in PB treatment, including pharmacodynamic and pharmacokinetic.

Conclusion

In conclusion, there were no statistically significant associations between ERCC2 rs13181 polymorphisms and chemotherapy response according to RECIST 1.1 criteria. However, this research highlights the presence of genetic variation within the Indonesian population, with the AA genotype being the most prevalent, which may influence chemotherapy responses. These findings offer preliminary data and lay the foundation for future, more extensive cohort observational studies aimed at more accurately assessing potential clinical implications.

Acknowledgments

We would like to express our sincere gratitude to all individuals who have contributed to the completion of this manuscript. Foremost, all the Dr. H.A Rotinsulu Lung Hospital and Dharmais Cancer Hospital laboratory and pharmacy staff.

Funding

This study was partially supported by Universitas Padjadjaran under the Doctoral Research Scheme for the Padjadjaran Doctoral Scholarship Program for NNA and the Ministry of Education, Culture, Research, and Technology of the Republic of Indonesia under the Fundamental Research Scheme for MIB.

Disclosure

The authors report no conflicts of interest in this work.

References

1. World Health Organization. Cancer Fact Sheets. WHO Press.

2. Altekruse S, Kosary C, Krapcho M, et al. SEER cancer statistics review 1975-2017 national cancer institute SEER cancer statistics review 1975-2017 national cancer institute. Nat Cancer Inst. 2017.

3. Kemenkes RI. Pedoman Nasional Pelayanan Kedokteran Kanker Paru. 2017.

4. Srikrishnan A, Fuster MM, Montgrain PR. Curative stereotactic body radiotherapy is safe and effective in early stage non-small cell lung cancer: a single-center retrospective review of a cohort of veterans. Am J Respir Crit Care Med. 2018;197

5. American Cancer Society. Lung cancer survival rates | 5-year survival rates for lung cancer. Am Cancer Society. 2019;7–9.

6. Torre LA, Siegel RL, Jemal A. Lung cancer statistics. Am Cancer Society. 2016. doi:10.1007/978-3-319-24223-1

7. Adebonojo SA, Bowser AN, Moritz DM, Corcoran PC. Impact of revised stage classification of lung cancer on survival: a military experience. Chest. 1999;115(6):1507–1513. doi:10.1378/chest.115.6.1507

8. Bahl A, Falk S. Meta-analysis of single agents in the chemotherapy of NSCLC: what do we want to know? Br J Cancer. 2001;84(9):1143–1145. doi:10.1054/bjoc.2000.1740

9. Sirohi B, Ashley S, Norton A, et al. Early response to platinum-based first-line chemotherapy in non-small cell lung cancer may predict survival. J Thorac Oncol. 2007;2(8):735–740. doi:10.1097/JTO.0b013e31811f3a7d

10. Petrelli F, Coinu A, Cabiddu M, Ghilardi M, Ardine M, Barni S. Platinum rechallenge in patients with advanced NSCLC: a pooled analysis. Lung Cancer. 2013;81(3):337–342. doi:10.1016/j.lungcan.2013.06.022

11. Dantoing E, Piton N, Salaün M, Thiberville L, Guisier F. Anti-PD1/PD-L1 immunotherapy for non-small cell lung cancer with actionable oncogenic driver mutations. Int J Mol Sci. 2021;22(12):6288. doi:10.3390/ijms22126288

12. Gendarme S, Bylicki O, Chouaid C, Guisier F. ROS-1 fusions in non-small-cell lung cancer: evidence to date. Current Oncol. 2022;29(2):641–658. doi:10.3390/curroncol29020057

13. Liao BC, Lin CC, Shih JY, Yang JCH. Treating patients with ALK-positive non-small cell lung cancer: latest evidence and management strategy. Ther Adv Med Oncol. 2015;7(5):274–290. doi:10.1177/1758834015590593

14. Zugazagoitia J, Molina-Pinelo S, Lopez-Rios F, Paz-Ares L. Biological therapies in nonsmall cell lung cancer. Eur Respir J. 2017;49(3):1601520. doi:10.1183/13993003.01520-2016

15. Mortezaee K, Majidpoor J. Anti-PD-(L)1 therapy of non-small cell lung cancer–A summary of clinical trials and current progresses. Heliyon. 2023;9(3):e14566. doi:10.1016/j.heliyon.2023.e14566

16. Kementerian Kesehatan Republik Indonesia. KEPUTUSAN MENTERI KESEHATAN REPUBLIK Indonesia.; 2022.

17. Amable L. Cisplatin resistance and opportunities for precision medicine. Pharmacol Res. 2016;106:27–36. doi:10.1016/j.phrs.2016.01.001

18. Fu BH, Zhang Q, Li X, et al. Evaluation of prediction of polymorphisms of DNA repair genes on the efficacy of platinum-based chemotherapy in patients with non-small cell lung cancer: a network meta-analysis. J Cell Biochem. 2017;118(12):4782–4791. doi:10.1002/jcb.26147

19. Tan LM, Qiu CF, Zhu T, et al. Genetic polymorphisms and platinum-based chemotherapy treatment outcomes in patients with non-small cell lung cancer: a genetic epidemiology study based meta-analysis. Sci Rep. 2017;7(1):1–19. doi:10.1038/s41598-017-05642-0

20. Sito H, Sharzehan MAK, Islam MA, Tan SC. Genetic variants associated with response to platinum-based chemotherapy in non-small cell lung cancer patients: a field synopsis and meta‐analysis. Br J Biomed Sci. 2024;81. doi:10.3389/bjbs.2024.11835

21. Song X, Wang S, Hong X, et al. Single nucleotide polymorphisms of nucleotide excision repair pathway are significantly associated with outcomes of platinum-based chemotherapy in lung cancer. Sci Rep. 2017;7(1):1–11. doi:10.1038/s41598-017-08257-7

22. Fu BH, Yu XL, Zhang Q, et al. Evaluation of prediction of polymorphisms of DNA repair genes on the efficacy (meta analysis).pdf.

23. Zhang H, Li Y, Guo S, et al. Effect of ERCC2 rs13181 and rs1799793 polymorphisms and environmental factors on the prognosis of patients with lung cancer. Am J Transl Res. 2020;12(10):6941–6953.

24. Landry LG, Ali N, Williams DR, Rehm HL, Bonham VL. Lack of diversity in genomic databases is a barrier to translating precision medicine research into practice. Health Aff. 2018;37(5):780–785. doi:10.1377/hlthaff.2017.1595

25. Sirugo G, Williams SM, Tishkoff SA. The missing diversity in human genetic studies. Cell. 2019;177(4):1080. doi:10.1016/j.cell.2019.04.032

26. Duncan L, Shen H, Gelaye B, et al. Analysis of polygenic risk score usage and performance in diverse human populations. Nat Commun. 2019;10(1):3328. doi:10.1038/s41467-019-11112-0

27. PharmGKB. Cisplatin - clinical annotation. US Department of Health & Human Services (HHS); 2024. Available from: https://www.pharmgkb.org/chemical/PA449014/clinicalAnnotation. Accessed August20, 2024.

28. Clinical Pharmacogenetics Implementation Consortium. Genes-Drugs in Published Guidelines. US Department of Health & Human Services (HHS); 2024. Available fromhttps://cpicpgx.org/genes-drugs/. Accessed, 2024.

29. Yang Y, Xian L. The association between the ERCC1/2 polymorphisms and the clinical outcomes of the platinum-based chemotherapy in non-small cell lung cancer (NSCLC): a systematic review and meta-analysis. Tumour Biol. 2013;35(4):2905–2921. doi:10.1007/s13277-013-1493-5

30. Tang N, Lyu D, Zhang Y, Liu H. Association between the ERCC1 polymorphism and platinum-based chemotherapy effectiveness in ovarian cancer: a meta-analysis. BMC Women's Health. 2017;17(1):1–8. doi:10.1186/s12905-017-0393-z

31. Wei SZ, Zhan P, Shi MQ, et al. Predictive value of ERCC1 and XPD polymorphism in patients with advanced non-small cell lung cancer receiving platinum-based chemotherapy: a systematic review and meta-analysis. Med Oncol. 2010;28(1):315–321. doi:10.1007/s12032-010-9443-1

32. PharmGKB. Variant Frequencies - rs13181. US Department of Health & Human Services (HHS). 2024.Available from: https://www.pharmgkb.org/variant/PA166155343. Accessed August20, 2024.

33. El Shamieh S, Zgheib NK. Pharmacogenetics in developing countries and low resource environments. Hum Genet. 2022;141(6):1159–1164. doi:10.1007/s00439-021-02260-9

34. Zgheib NK, Patrinos GP, Akika R, Mahfouz R. Precision Medicine in Low- and Middle-Income Countries. Clin Pharmacol Ther. 2020;107(1):29–32. doi:10.1002/cpt.1649

35. Natri HM, Hudjashov G, Jacobs G, et al. Genetic architecture of gene regulation in Indonesian populations identifies QTLs associated with global and local ancestries. Am J Hum Genet. 2022;109(1):50–65. doi:10.1016/j.ajhg.2021.11.017

36. Qiu M, Yang X, Hu J, et al. Predictive value of XPD polymorphisms on platinum-based chemotherapy in non-small cell lung cancer: a systematic review and meta-analysis. PLoS One. 2013;8(8):e72251. doi:10.1371/journal.pone.0072251

37. Yin M, Yan J, Voutsina A, et al. No evidence of an association of ERCC1 and ERCC2 polymorphisms with clinical outcomes of platinum-based chemotherapies in non-small cell lung cancer: a meta-analysis. Lung Cancer. 2010;72(3):370–377. doi:10.1016/j.lungcan.2010.10.011

38. May L, Shows K, Nana-Sinkam P, Li H, Landry JW. Sex Differences in Lung Cancer. Cancers (Basel). 2023;15(12):3111. doi:10.3390/cancers15123111

39. Sagerup CMT, Sm Astuen M, Johannesen TB, Helland A, Brustugun OT. Sex-specific trends in lung cancer incidence and survival: a population study of 40 118 cases. Thorax. 2011;66(4):301–307. doi:10.1136/thx.2010.151621

40. Sabbula BR, Gasalberti DP, Anjum F. Squamous Cell Lung Cancer. Treasure Island (FL): StatPearls Publishing;2023.

41. Peto R, Lopez AD, Boreham J, Thun M, Heath CJ. Mortality from tobacco in developed countries: indirect estimation from national vital statistics. Lancet. 1992;339(8804):1268–1278. doi:10.1016/0140-6736(92)91600-d

42. World Health Organization. Indonesian cancer statistics: cancer country profile 2020.; 2020.

43. Dasgupta P, Chellappan SP. Nicotine-mediated cell proliferation and angiogenesis: new twists to an old story. Cell Cycle. 2006;5(20):2324–2328. doi:10.4161/cc.5.20.3366

44. Minna JD. Nicotine exposure and bronchial epithelial cell nicotinic acetylcholine receptor expression in the pathogenesis of lung cancer. J Clin Investig. 2003;111(1):31–33. doi:10.1172/JCI200317492

45. Xu J, Huang H, Pan C, Zhang B, Liu X, Zhang L. Nicotine inhibits apoptosis induced by cisplatin in human oral cancer cells. Int J Oral Maxillofac Surg. 2007;36(8):739–744. doi:10.1016/j.ijom.2007.05.016

46. Seitz HK, Stickel F. Molecular mechanisms of alcohol-mediated carcinogenesis. Nat Rev Cancer. 2007;7(8):599–612. doi:10.1038/nrc2191

47. Ganti AK, Klein AB, Cotarla I, Seal B, Chou E. Update of incidence, prevalence, survival, and initial treatment in patients with non–small cell lung cancer in the US. JAMA Oncol. 2021;7(12):1824–1832. doi:10.1001/jamaoncol.2021.4932

48. Gridelli C, Ardizzoni A, Le Chevalier T, et al. Treatment of advanced non-small-cell lung cancer patients with ECOG performance status 2: results of an European experts panel. Ann Oncol. 2004;15(3):419–426. doi:10.1093/annonc/mdh087

49. Soetandyo N, Hanafi AR, Agustini S, Sinulingga DT. Prognosis of advanced stage non-small-cell lung cancer patients receiving chemotherapy: adenocarcinoma versus squamous cell carcinoma. Med J Indonesia. 2020;29(1):26–31. doi:10.13181/mji.oa.203787

50. Zappa C, Mousa SA. Non-small cell lung cancer: current treatment and future advances. Transl Lung Cancer Res. 2016;5(3):288–300. doi:10.21037/tlcr.2016.06.07

51. Zhou J, Kang Y, Chen L, et al. The drug-resistance mechanisms of five platinum-based antitumor agents. Front Pharmacol. 2020:11(March):1–17. doi:10.3389/fphar.2020.00343

52. Bowden NA. Nucleotide excision repair: why is it not used to predict response to platinum-based chemotherapy? Cancer Lett. 2014;346(2):163–171. doi:10.1016/j.canlet.2014.01.005

53. Afifah NN, Diantini A, Intania R, Abdulah R, Barliana MI. Genetic polymorphisms and the efficacy of platinum-based chemotherapy: review. Pharmgenomics Pers Med. 2020;13:427–444. doi:10.2147/PGPM.S267625

54. Gandara DR, Mack PC, Li T, Lara PN, Herbst RS. Evolving treatment algorithms for advanced non-small-cell lung cancer: 2009 looking toward 2012. Chinese J Lung Cancer. 2010;13(3):238–241. doi:10.3779/j.issn.1009-3419.2010.03.16

55. Li M, Chen R, Ji B, et al. Contribution of XPD and XPF polymorphisms to susceptibility of non-small cell lung cancer in high-altitude areas. Public Health Genomics. 2021;24(3–4):189–198. doi:10.1159/000512641

56. Zhou T, Zheng L, Hu Z, et al. The effectiveness of RECIST on survival in patients with NSCLC receiving chemotherapy with or without target agents as first-line treatment. Sci Rep. 2015;5(1):7683. doi:10.1038/srep07683

57. Toffart AC, Moro-Sibilot D, Couraud S, et al. Evaluation of RECIST in chemotherapy-treated lung cancer: the pharmacogenoscan study. BMC Cancer. 2014;14(1):1–7. doi:10.1186/1471-2407-14-989