Therapy For Lung Cancer Patients Research Articles

Artificial Intelligence and Lung Cancer: Impact on Improving Patient Outcomes

Lung cancer remains one of the leading causes of cancer-related deaths worldwide, emphasizing the need for improved diagnostic and treatment approaches. In recent years, the emergence of artificial intelligence (AI) has sparked considerable interest in its potential role in lung cancer. This review aims to provide an overview of the current state of AI applications in lung cancer screening, diagnosis, and treatment. AI algorithms like machine learning, deep learning, and radiomics have shown remarkable capabilities in the detection and characterization of lung nodules, thereby aiding in accurate lung cancer screening and diagnosis. These systems can analyze various imaging modalities, such as low-dose CT scans, PET-CT imaging, and even chest radiographs, accurately identifying suspicious nodules and facilitating timely intervention. AI models have exhibited promise in utilizing biomarkers and tumor markers as supplementary screening tools, effectively enhancing the specificity and accuracy of early detection. These models can accurately distinguish between benign and malignant lung nodules, assisting radiologists in making more accurate and informed diagnostic decisions. Additionally, AI algorithms hold the potential to integrate multiple imaging modalities and clinical data, providing a more comprehensive diagnostic assessment. By utilizing high-quality data, including patient demographics, clinical history, and genetic profiles, AI models can predict treatment responses and guide the selection of optimal therapies. Notably, these models have shown considerable success in predicting the likelihood of response and recurrence following targeted therapies and optimizing radiation therapy for lung cancer patients. Implementing these AI tools in clinical practice can aid in the early diagnosis and timely management of lung cancer and potentially improve outcomes, including the mortality and morbidity of the patients.

Metformin induces ferroptosis through the Nrf2/HO-1 signaling in lung cancer

BackgroundMetformin is the most frequently prescribed medication for the treatment of type II diabetes mellitus and has played an anti-tumor potential in a variety of cancer types. Metformin can inhibit the growth of many cancer cells through various mechanisms, including ferroptosis. However, it is still unclear whether metformin can induce ferroptosis in lung cancer.MethodsThis study evaluated the anti-tumor effect of metformin by detecting the levels of oxidative stress factors, the levels of ferrous ions, and the expression of ferroptosis-related genes in A549 and H1299 lung cancer cell lines treated with or without metformin.ResultsThe results showed that metformin treatment increased the levels of MDA, ROS and iron ions, while decreased the levels of GSH, T-SOD and CAT. Meanwhile, metformin treatment reduced the protein expression levels of Gpx4 and SLC7A11, Nrf2 and HO-1, while the addition of ferroptosis inhibitor ferrostatin-1 reversed the reduction.ConclusionsThese results demonstrated that metformin exerts anti-tumor effects by inducing ferroptosis through the Nrf2/HO-1 signaling pathway in lung cancer cells, providing a theoretical basis for drug therapy of lung cancer patients.

Longitudinal high-dimensional analysis identifies immune features associating with response to anti-PD-1 immunotherapy

Response to immunotherapy widely varies among cancer patients and identification of parameters associating with favourable outcome is of great interest. Here we show longitudinal monitoring of peripheral blood samples of non-small cell lung cancer (NSCLC) patients undergoing anti-PD1 therapy by high-dimensional cytometry by time of flight (CyTOF) and Meso Scale Discovery (MSD) multi-cytokines measurements. We find that higher proportions of circulating CD8+ and of CD8+CD101hiTIM3+ (CCT T) subsets significantly correlate with poor clinical response to immune therapy. Consistently, CD8+ T cells and CCT T cell frequencies remain low in most responders during the entire multi-cycle treatment regimen; and higher killer cell lectin-like receptor subfamily G, member 1 (KLRG1) expression in CCT T cells at baseline associates with prolonged progression free survival. Upon in vitro stimulation, CCT T cells of responders produce significantly higher levels of cytokines, including IL-1β, IL-2, IL-8, IL-22 and MCP-1, than of non-responders. Overall, our results provide insights into the longitudinal immunological landscape underpinning favourable response to immune checkpoint blockade therapy in lung cancer patients.

Clinical evaluation of synthetic computed tomography methods in adaptive proton therapy of lung cancer patients.

Efficient workflows for adaptive proton therapy are of high importance. This study evaluated the possibility to replace repeat-CTs (reCTs) with synthetic CTs (sCTs), created based on cone-beam CTs (CBCTs), for flagging the need of plan adaptations in intensity-modulated proton therapy (IMPT) treatment of lung cancer patients. Forty-two IMPT patients were retrospectively included. For each patient, one CBCT and a same-day reCT were included. Two commercial sCT methods were applied; one based on CBCT number correction (Cor-sCT), and one based on deformable image registration (DIR-sCT). The clinical reCT workflow (deformable contour propagation and robust dose re-computation) was performed on the reCT as well as the two sCTs. The deformed target contours on the reCT/sCTs were checked by radiation oncologists and edited if needed. A dose-volume-histogram triggered plan adaptation method was compared between the reCT and the sCTs; patients needing a plan adaptation on the reCT but not on the sCT were denoted false negatives. As secondary evaluation, dose-volume-histogram comparison and gamma analysis (2%/2mm) were performed between the reCT and sCTs. There were five false negatives, two for Cor-sCT and three for DIR-sCT. However, three of these were only minor, and one was caused by tumour position differences between the reCT and CBCT and not by sCT quality issues. An average gamma pass rate of 93% was obtained for both sCT methods. Both sCT methods were judged to be of clinical quality and valuable for reducing the amount of reCT acquisitions.

Multi-institutional survey of antiemetic therapy in lung cancer patients treated with carboplatin in Hokushin region

ObjectiveAppropriate monitoring and management of chemotherapy-induced nausea and vomiting (CINV) with prophylactic antiemetics is important for cancer patients. This study was performed to validate the clinical practice of antiemetic use with carboplatin-based chemotherapy in lung cancer patients in the Hokushin region (Toyama, Ishikawa, Fukui, and Nagano prefectures), Japan.MethodsWe surveyed retrospective data of newly diagnosed and registered lung cancer patients initially treated with carboplatin-based chemotherapy in 21 principal hospitals in the Hokushin region linked with health insurance claims data between 2016 and 2017.ResultsA total of 1082 lung cancer patients (861 [79.6%] men, 221 [20.4%] women; median age 69.4 years [range, 33–89 years]). All patients received antiemetic therapy, with 613 (56.7%) and 469 patients (43.3%) receiving 5-hydroxytryptamine-3 receptor antagonist/dexamethasone double regimen and 5-hydroxytryptamine-3 receptor antagonist/dexamethasone/neurokinin-1 receptor antagonist triple regimen, respectively. However, the rates of double regimen and use of palonosetron were higher in Toyama and Fukui prefectures. Thirty-nine patients (3.6%) changed from double to triple regimen, while 41 patients (3.8%) changed from triple to double regimen after the second cycle, but six of these returned to triple antiemetics in subsequent cycles.ConclusionAdherence to antiemetic guidelines in clinical practice was high in Hokushin region. However, rates of double and triple antiemetic regimens differed between the four prefectures. Simultaneous analysis of nationwide registry and insurance data was valuable for evaluating and comparing the differences in the status of antiemesis and management.

OC-0444 Clinical feasibility of synthetic CTs for adaptive proton therapy in lung cancer patients

OC-0444 Clinical feasibility of synthetic CTs for adaptive proton therapy in lung cancer patients

Consensus-based failure mode and effect analysis in group decision-making with incomplete weights of risk factors: Case study of stereotactic body radiation therapy for lung cancer

Failure mode and effect analysis (FMEA) is a widely used management technique to identify potential failure modes in products, processes, systems, and services to assign limited resources for implementing improvement efforts. For the FMEA with a number of experts, the experts may take different influences on the decision-making process due to the difference between individual rationality and cognition and the influence of social relations. Besides, incomplete weights of risk factors are vital to capturing the fuzziness of experts’ evaluation. Therefore, this paper proposes a consensus-based FMEA method to explore that how cooperative relationship network of experts, the consensus process, and incomplete weight information of risk factors in FMEA influence the decision-making process. First, a consensus reaching process considering cooperative relationships between experts, the self-confidence of experts, and minimum adjustment of expert opinion is proposed to derive a collective evaluation of group. Afterward, the stochastic multicriteria acceptability analysis method is integrated with the gained and lost dominance score method to deal with incomplete weights of risk factors in the FMEA. The proposed method is employed in a case study about ranking the failure modes of stereotactic body radiation therapy for lung cancer patients. The robustness and feasibility of the proposed method are validated by comparative analysis.

Abstract 264: Framework to determine fusion junction of novel RNA fusions and their actionability for personalized therapy of lung cancer patients

Abstract Background: Current therapies including chemotherapy, radiotherapy, and targeted therapies have not worked well for treating lung cancer as is evident by the high lung cancer-related mortality rate. This is because we continue to treat all lung cancers as a homogenous disease. Therefore, personalized therapies based on individual molecular characteristics of patient tumors are needed to improve lung cancer treatment outcomes. Objective: The objective of the current project is to identify novel actionable RNA fusions that can be targeted for the personalized treatment of lung cancer. Fusions, including the ones that are created by joining at the RNA level, can form during cancer development and thus present an attractive way of personalized cancer treatment. Methodology: A list of RNA fusion candidates was processed through a multistep pipeline framework to map the fusion junction of these novel fusions and evaluate their actionability. We had previously obtained this list of RNA fusions by mining the RNA sequencing data from lung cancer samples. The workflow of the project included the following steps: 1) a literature search to assess the oncogenic role of individual gene partners, 2) Blat to map the fusion junction 3) cBioPortal/Survival analysis to predict the association of individual gene partners with lung cancer patient survival and prognosis, 4) cBioPortal/Co-Expression analysis to study if the gene partners are expressed together or have common gene partners and lastly, 5) Open Reading Frame (ORF) Finder to identify if the fusion is predicted to be translated and makes a unique product. Results: RNA fusions such as TMPRSS13-TMPRSS13, SUPT6H-ESR1, PTPRK-RSPO3, and KIF5B-RET were investigated and fusion junctions were successfully determined. Gene partners from multiple fusion pairs (e.g., SUPT6H-ESR1 and KIF5B-RET) were found to have an oncogenic role in lung cancer. Mutations in KIF5B and RET genes were found to associate with poor survival in the TCGA dataset suggesting that the novel RNA fusions may also play an oncogenic role in lung cancer. Lastly, several of these RNA fusions generated unique ORFs suggesting that these fusions are predicted to be translated and these novel proteins can be selectively targeted sparing the normal cells that don’t harbor these mutants. Future directions: Next steps will involve preclinical testing of the driver role of these novel RNA fusions and testing of existing drugs such as RET inhibitors for their efficacy to treat lung cancer in tumors that harbor these novel RNA fusions. Citation Format: Prisha Verma, Sakuni Rankothgedera, Micah Castillo, Preethi Gunaratne. Framework to determine fusion junction of novel RNA fusions and their actionability for personalized therapy of lung cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 264.

IL-36 expression is increased in NSCLC with IL-36 stimulation of lung cancer cells promoting a pro-tumorigenic phenotype

The IL-36 cytokines are a recently described subset of the IL-1 family of cytokines, and have been shown to play a role in the pathogenesis of respiratory diseases such as asthma and COPD. Given the common aetiological links between COPD and lung cancer development, as well as the involvement of other IL-1 family members in lung tumorigenesis, the aim of this work was to investigate the role of IL-36 cytokines in the pathogenesis of lung cancer. In this study we demonstrate that expression of IL-36 cytokines and receptor mRNA and protein are significantly increased in lung cancer tissue compared to adjacent non-tumour tissue. In vitro assays showed that stimulation of two lung cancer cell lines, SKMES-1 human squamous cell and LLC murine lung cancer, with IL-36R agonists resulted in increased cellular migration and proliferation. All IL-36 cytokines induced the expression of pro-inflammatory chemokines in both lung cancer cell lines with synergistic effects identified upon co-stimulation of cells with IL-17, IL-22 and TNFα. Furthermore, we report that IL-36 cytokines induce protein expression of the immune checkpoint inhibitor protein PD-L1 on lung cancer cells. Taken together, this data indicates that targeting IL-36R signalling may be a useful targeted therapy for lung cancer patients with IL-36R+ cancer cells.

The Correlation between Peripheral Blood Index and Immune Cell Expansion in Vietnamese Elderly Lung Cancer Patients.

(1) Background: The dysfunction and reduced proliferation of peripheral CD8+ T cells and natural killer (NK) cells have been observed in both aging and cancer patients, thereby challenging the adoption of immune cell therapy in these subjects. In this study, we evaluated the growth of these lymphocytes in elderly cancer patients and the correlation of peripheral blood (PB) indices to their expansion. (2) Method: This retrospective study included 15 lung cancer patients who underwent autologous NK cell and CD8+ T cell therapy between January 2016 and December 2019 and 10 healthy individuals. (3) Results: On average, CD8+ T lymphocytes and NK cells were able to be expanded about 500 times from the PB of elderly lung cancer subjects. Particularly, 95% of the expanded NK cells highly expressed the CD56 marker. The expansion of CD8+ T cells was inversely associated with the CD4+:CD8+ ratio and the frequency of PB-CD4+ T cells in PB. Likewise, the expansion of NK cells was inversely correlated with the frequency of PB-lymphocytes and the number of PB-CD8+ T cells. The growth of CD8+ T cells and NK cells was also inversely correlated with the percentage and number of PB-NK cells. (4) Conclusion: PB indices are intrinsically tied to immune cell health and could be leveraged to determine CD8 T and NK cell proliferation capacity for immune therapies in lung cancer patients.

Use of Complementary Therapy in Lung Cancer Patients Treated with Chemotherapy and its Effect on Survival: A Cross-sectional Study

Use of Complementary Therapy in Lung Cancer Patients Treated with Chemotherapy and its Effect on Survival: A Cross-sectional Study

Blood exosome PD-L1 is associated with PD-L1 expression measured by immunohistochemistry, and lymph node metastasis in lung cancer

BackgroundPrevious observations illustrated that programmed cell death ligand 1 in exosomes (Exo-PD-L1) may lead to immunosuppression. This study proposed to investigate the significance of Exo-PD-L1 and the results of PD-L1 immunohistochemistry (IHC) assay in the clinical diagnosis and treatment of lung cancer. Methods29 lung cancer patients were enrolled. Exosomes were extracted from the blood of patients and purified, and the extracts were identified by Western blot and transmission electron microscope. Next, the levels of Exo-PD-L1 and PD-L1 in tumor tissue were evaluated by enzyme-linked immunosorbent assay (ELISA) and IHC, respectively. The correlation between Exo-PD-L1, IHC PD-L1 status and pathological features of patients was analyzed by applying Chi-square test. After immune checkpoint inhibitor (ICI) treatment, the objective response rate (ORR) was calculated, and drug response prediction in lung cancer patients by using Exo-PD-L1 alone, IHC PD-L1 alone, and their combined detection were analyzed. ResultsThis study confirmed that lung cancer patients had much expression of PD-L1 in blood exosomes and that Exo-PD-L1 level was associated with IHC PD-L1 status. The expression level of Exo-PD-L1 was evidently related to the positive lymph node metastasis of lung cancer patients, while IHC PD-L1 status was not correlated with clinicopathological features of patients. Moreover, Exo-PD-L1 and IHC PD-L1 alone or their combined detection could be utilized to predict the efficacy of ICI therapy in lung cancer patients. ConclusionThe correlation between Exo-PD-L1 and IHC PD-L1 status was indicated, and Exo-PD-L1 could assist in determining the suitable lung cancer patients suitable for ICI therapy using IHC PD-L1. This study provides references for the application of Exo-PD-L1 as an effective predictor of ICI therapy.

A prediction model for dosimetric-based lung adaptive radiotherapy.

Anatomical changes occurred during the treatment course of radiation therapy for lung cancer patients may introduce clinically unacceptable dosimetric deviations from the planned dose. Adaptive radiotherapy (ART) can compensate these dosimetric deviations in subsequent treatments via plan adaption. Determining whether and when to trigger plan adaption during the treatment course is essential to the effectiveness and efficiency of ART. In this study, we aimed to develop a prediction model as an auxiliary decision-making tool for lung ART to identify the patients with intrathoracic anatomical changes that would potentially benefit from the plan adaptions during the treatment course. Seventy-one pairs of weekly cone-beam computer tomography (CBCT) and planning CT (pCT) from 17 advanced non-small cell lung cancer patients were enrolled in this study. To assess the dosimetric impacts brought by anatomical changes observed on each CBCT, dose distribution of the original treatment plan on the CBCT anatomy was calculated on a virtual CT generated by deforming the corresponding pCT to the CBCT and compared to that of the original plan. A replan was deemed needed for the CBCT anatomy once the recalculated dose distribution violated our dosimetric-based trigger criteria. A three-dimensional region of significant anatomical changes (region of interest, ROI) between each CBCT and the corresponding pCT was identified, and 16 morphological features of the ROI were extracted. Additionally, eight features from the overlapped volume histograms (OVHs) of patient anatomy were extracted for each patient to characterize the patient-specific anatomy. Based on the 24 extracted features and the evaluated replanning needs of the pCT-CBCT pairs, a nonlinear supporting vector machine was used to build a prediction model to identify the anatomical changes on CBCTs that would trigger plan adaptions. The most relevant features were selected using the sequential backward selection (SBS) algorithm and a shuffling-and-splitting validation scheme was used for model evaluation. Fifty-five CBCT-pCT pairs were identified of having an ROI, among which 21 CBCT anatomies required plan adaptions. For these 21 positive cases, statistically significant improvements in the sparing of lung, esophagus and spinal cord were achieved by plan adaptions. A high model performance of 0.929 AUC (area under curve) and 0.851 accuracy was achieved with six selected features, including five ROI shape features and one OVH feature. Without involving the OVH features in the feature selection process, the mean AUC and accuracy of the model significantly decreased to 0.826 and 0.779, respectively. Further investigation showed that poor prediction performance with AUC of 0.76 was achieved by the univariate model in solving this binary classification task. We built a prediction model based on the features of patient anatomy and the anatomical changes captured by on-treatment CBCT imaging to trigger plan adaption for lung cancer patients. This model effectively associated the anatomical changes with the dosimetric impacts for lung ART. This model can be a promising tool to assist the clinicians in making decisions for plan adaptions during the treatment courses.

Abstract PL03-02: Somatic mutations, germline risk and ancestry in lung adenocarcinoma

Abstract Like most cancer types, lung cancer is caused predominantly by somatic genome alterations. In lung adenocarcinoma, the most common histological type of lung cancer, these alterations are known to occur in multiple pathways including the p53 pathway, the receptor tyrosine kinase (RTK)/Ras/Raf/MAP kinase (MAPK) pathway and PI3 kinase pathway, the Rb1/cell cycle pathway, the Swi/Snf pathway, the Myc pathway, and the telomerase pathway, among others. Genome-wide association studies comparing polymorphisms in germline DNA from patients with lung cancer and from unaffected control subjects have led to the identification of multiple germline risk alleles for lung adenocarcinoma, including the HLA locus, the telomerase catalytic subunit gene locus, and, notably, the nicotinic acetylcholine receptor locus, where polymorphisms appear to modulate individual propensity for smoking. The components of inherited lung cancer risk, particularly in nonsmokers, are not fully understood, but there appear to be variations in lung adenocarcinoma mutations in distinct ancestry groups, which may be related to inherited factors. In particular, the frequency of somatic EGFR and KRAS mutations in lung cancer varies by ethnicity. Somatic EGFR mutation rates are higher in lung cancers from patients with East Asian ancestry and lower in lung cancers from patients with European or African ancestry. Somatic KRAS and STK11 mutation rates show the opposite pattern, higher in lung cancers from patients with European or African ancestry and lower in lung cancers from patients with East Asian ancestry. In patients from Latin America, somatic lung cancer EGFR mutation frequencies vary by country, with higher frequencies in Peru, intermediate frequencies in Mexico, Colombia, Costa Rica and Brazil, and lower frequencies in Argentina. To explore the relationship between the somatic genome in lung cancer and ethnicity related germline risk, we performed cancer gene panel sequencing of DNA from over 1,000 lung cancers from Mexico and Colombia, countries with significant population admixture. We developed methods to infer ancestry from the tumor DNA sequence based on coverage of single nucleotide polymorphisms. This study revealed associations between ancestry and somatic lung cancer genomic alterations, including tumor mutational burden, and specific driver mutations in EGFR, KRAS, and STK11. A local ancestry score was more strongly correlated with EGFR mutation frequency compared with global ancestry correlation, suggesting that germline genetics, rather than environmental exposure, could underlie these disparities. Our study suggests that the variation in EGFR and KRAS somatic mutation frequency in lung cancer is associated with genetic ancestry in patients from Latin America, and suggests further studies to identify germline alleles that underpin this association. If we find a germline locus or loci that could impact the development of lung cancers with EGFR and/or KRAS mutation, this might help in improving lung cancer prevention and screening for populations of Latin American origin and others. Furthermore, multiple studies now highlight the importance of EGFR mutation screening and EGFR-directed targeted therapy for lung cancer patients in Latin America and with origins in Latin America. Citation Format: Matthew L. Meyerson. Somatic mutations, germline risk and ancestry in lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr PL03-02.

Predictive value of the biomarker of peripheral blood of lung carcinoma patients responding to PD-1 treatment: A real-word study.

e20549 Background: The introduction of anti-PD-1 antibody has greatly improved the clinical outcomes of patients with lung cancer. Pre-treatment biomarkers in peripheral blood such as neutrophil-lymphocyte ratio, cytokine level, or clinical features such as BMI, lactate dehydrogenase, and prognostic nutrition index have been shown to be predictive markers treated by immunotherapy. Here we retrospectively analyzed the efficacy of PD-1 antibody-based therapy in patients with locally advanced un-operable or metastatic lung cancer patients and report an association between peripheral blood biomarkers with clinical response in these patients. Methods: We conducted a single-center study by including medical record data for lung cancer patients treated with PD-1 antibody first-line or posterior-line either as monotherapy or in combination with chemotherapy. The patients enrolled from March 2020 to December 2021 were treated with albumin paclitaxel or pemetrexed plus carboplatin、lobaplatin or cisplatin combined with PD-1 antibody. The clinical response were assessed after 2 circles of therapy. Peripheral blood were drawn prior to therapy and post therapy. Multiple Th1 and Th2 cytokines levels in the blood serum were evaluated and phenotype of T cells of peripheral blood were also analyzed. The association between cytokines levels, T cells phenotype and clinical response were investigated. Results: 61 patients with stage IIIA-IV lung cancer were enrolled in the study. 40 non-squamous NSCLC patients, 15 Squamous NSCLC patients and 6 SCLC patients received PD-1 antibody with chemotherapy. 40(65.6%)patients were first-line therapy and 21(34.4%) were posterior-line treatment. 42(68.9%) patients achieved partial response(PR), 7 (11.5%) patients were stable(SD) and 12(19.6%) patients had progressed disease (PD). The disease control rare(DCR) was 80.4%. In DCR group, higher levels of IFN-γ(P = 0.023,P < 0.05), TNF-α(P = 0.007,P < 0.05)and IL-5 (P = 0.002, P < 0.005) were detected in peripheral blood prior to the treatment comparing to PD group. Besides, the reduction of lymphocyte absolute counts in peripheral blood after PD-1 antibody-based therapy was associated with disease progression(P = 0.023,P < 0.05). Furthermore, higher CD8+CD27+T cells in peripheral blood before therapy was associated with worse clinical response(P = 0.019,P < 0.05) and higher ratio of CD4+CD45RO+CD62L+/ CD4+CD45RO+CD62L-seems to related with better clinical response, though without statistic difference due to limited sample size. Conclusions: These results suggest for the first time that serum IFN-γ, TNF-α and IL-5 levels could predict clinical efficacy with anti-PD-1 blockade therapy in lung cancer patients. Other biomarkers include lymphocyte counts or phenotype may also have predictive value. Large prospective studies need to further clarify the value of these biomarkers.

Unique characteristics of G719X and S768I compound double mutations of epidermal growth factor receptor (EGFR) gene in lung cancer of coal-producing areas of East Yunnan in Southwestern China

BackgroundThe principal objective of this project was to investigate the Epidermal Growth Factor Receptor (EGFR) gene mutation characteristics of lung cancer patients, which can provide a molecular basis for explaining the clinicopathological features, epidemiology and use of targeted therapy in lung cancer patients in the coal-producing areas of East Yunnan.MethodologyWe collected 864 pathologically confirmed lung cancer patients’ specimens in First People’s Hospital of Qujing City of Yunnan Province from September 2016 to September 2021. We thereafter employed Next Generation Sequencing (NGS) technology to detect all exons present in the EGFR gene.ResultsThe overall mutation frequency of the EGFR gene was 47.22%. The frequency of EGFR gene mutations in the tissue, plasma, and cytology samples were found to be 53.40%, 23.33%, and 62.50%, respectively. Univariate analysis indicated that the coal-producing areas and Fuyuan county origin were significantly associated with relatively low EGFR gene mutation frequency. Female, non-smoking history, adenocarcinoma, non-brain metastasis, and tissue specimens were found to be related to high EGFR gene mutation frequency. Multivariate logistic regression analysis suggested the lung cancer patients in the central area of Qujing City, stage Ia, non-coal-producing areas, non-Fuyuan origin, and non-Xuanwei origin were more likely to develop EGFR gene mutations. The most common mutations were L858R point mutation (33.09%) and exon 19 deletion (19-del) (21.32%). Interestingly, the mutation frequency of G719X (p = 0.001) and G719X + S768I (p = 0.000) in the coal-producing areas were noted to be more significant than those in non-coal-producing regions.ConclusionThis findings of this study might be important in establishing the correlation between routine using NGS for EGFR gene mutation diagnosis and clinical practice in the lung cancer patients.

Prospective Study of Proton Therapy for Lung Cancer Patients with Poor Lung Function or Pulmonary Fibrosis.

Simple SummaryUnderlying lung disease can affect the pulmonary toxicity after radiotherapy for lung cancer, but treatment outcomes after proton beam therapy (PBT) for lung cancer patients with underlying lung disease have been limited to small retrospective studies. In this prospective study, we aimed to assess pulmonary toxicity following PBT for lung cancer with poor lung function or pulmonary fibrosis. We found that idiopathic pulmonary fibrosis (IPF) was associated with severe pulmonary toxicity and poor survival even after PBT, while PBT seems to be a safe treatment modality for lung cancer patients with chronic obstructive pulmonary disease.PBT has a unique depth–dose curve with a Bragg peak that enables one to reduce the dose to normal lung tissue. We prospectively enrolled 54 patients with non-small cell lung cancer treated with definitive PBT. The inclusion criteria were forced expiratory volume in 1 s (FEV1) ≤ 1.0 L or FEV1 ≤ 50% of predicted or diffusing capacity of the lungs for carbon monoxide (DLco) ≤ 50%, or pulmonary fibrosis. The primary endpoint was grade ≥ 3 pulmonary toxicity, and secondary endpoints were changes in pulmonary function and quality of life. The median age was 71.5 years (range, 57–87). Fifteen (27.8%) and fourteen (25.9%) patients had IPF and combined pulmonary fibrosis and emphysema, respectively. The median predicted forced vital capacity (FVC), FEV1, and DLco were 77% (range, 42–104%), 66% (range, 31–117%), and 46% (range, 23–94%), respectively. During the follow-up (median, 14.7 months), seven (13.0%) patients experienced grade ≥ 3 pulmonary toxicity. Seven months after the completion of PBT, patients with IPF or non-IPF interstitial lung disease (ILD) experienced a decrease in the FVC but the decrease in DLco was not significant. Under careful monitoring by pulmonologists, PBT could be a useful treatment modality for lung cancer patients with poor lung function or pulmonary fibrosis.

Polymorphism in Thymidylate Synthase Gene Predicts Survival and Toxicity in North Indian Lung Cancer Patients Undergoing Platinum-Based Doublet Chemotherapy.

With an estimated 1.8 million deaths, lung cancer is one of the widely reported malignancies, with substantial morbidity and mortality rates. Thymidylate synthase (TS) is an important drug target for platinum-based doublet chemotherapy as it is the only de novo source of thymidylate production in the cell. TS polymorphisms in the 5'UTR of Thymidylate synthase enhancer region (TSER) 2R/3R and 3'- UTR 1494del6 are investigated in this study. A total of 700 lung cancer patients with platinum-based doublet chemotherapy were recruited in this study. TSER (2R/3R) and TS 1494del6 polymorphisms in North Indian lung cancer patients were examined, and statistical analysis was performed. According to our findings, patients with the wild genotype (2R/2R) for the TSER polymorphism had a longer median survival time as compared to patients harboring the mutant type genotype (3R/3R) [MST=9.77 vs. 7.57 months; p=0.04]. On the contrary, patients with the mutant 14946del6 polymorphism (-6/-6) had a longer survival time than patients with the wild-type genotype (+6/+6) [MST=7.23 vs. 9 months]. Further, our findings elucidated that the patients with heterozygous genotype (2R3R) for TSER polymorphism had a 2.30-fold increased risk of developing leukopenia (AOR=2.30, 95% CI=0.96-5.52; p=0.05). A substantial risk of 5.14-fold constipation was found in heterozygous genotype (2R3R) when intermediate grade 2 toxicity was compared with low toxicity (grade 1) (p=0.007).An increased risk of nausea/vomiting was observed in patients with mutant genotype (-6/-6bp) for 1494 ins/del6 polymorphism compared to patients with wild-type genotype (+6/+6bp) (AOR= 2.77; 95%CI=1.10-6.96, p=0.03). According to our findings, TSER and the 1494del6 polymorphism may operate as a prognostic marker in lung cancer patients receiving platinum-based chemotherapy. Furthermore, TS polymorphisms may influence the onset of platinum-related toxicity, such as hematological and gastrointestinal toxicity. These findings might facilitate therapeutic decisions for individualized therapy in lung cancer patients.

Unraveling the Role of STK11/LKB1 in Non-small Cell Lung Cancer.

There are two major groups of lung cancer: non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). NSCLCs can be further separated into three different categories: lung adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. Pulmonary adenocarcinomas represent nearly half of all lung cancer cases and are known to be caused by smoking, certain occupational exposures, and specific genetic mutations. Scientists have noticed that most NSCLCs are driven by defects in the following genes: EGFR, BRAF, ALK, MET, and HER. Abnormalities in the STK11/LKB1 gene have also been shown to induce lung adenocarcinoma. LKB1-deficient cancer cells contain an overactive AMPK “energy sensor,” which inhibits cellular death and promotes glucose, lipid, and protein synthesis via the mTOR protein complex. Studies have also discovered that the loss of STK11/LKB1 favors oncogenesis by creating an immunosuppressive environment for tumors to grow and accelerate events such as angiogenesis, epithelial-mesenchymal transition (EMT), and cell polarity destabilization. STK11/LKB1-mutant lung cancers are currently treated with radiotherapy with or without chemotherapy. Recent clinical trials studying the effects of glutaminase inhibitors, mTOR inhibitors, and anti-PD-L1 therapy in lung cancer patients have yielded promising results. This narrative review provides an overview of the STK11/LKB1 gene and its role in cancer development. Additionally, a summary of the LKB1/APMK/mTOR is provided.

Targeted Therapies for Lung Cancer Patients With Oncogenic Driver Molecular Alterations.

Lung cancer has traditionally been classified by histology. However, a greater understanding of disease biology and the identification of oncogenic driver alterations has dramatically altered the therapeutic landscape. Consequently, the new classification paradigm of non-small-cell lung cancer is further characterized by molecularly defined subsets actionable with targeted therapies and the treatment landscape is becoming increasingly complex. This review encompasses the current standards of care for targeted therapies in lung cancer with driver molecular alterations. Targeted therapies for EGFR exon 19 deletion and L858R mutations, and ALK and ROS1 rearrangements are well established. However, there is an expanding list of approved targeted therapies including for BRAF V600E, EGFR exon 20 insertion, and KRAS G12C mutations, MET exon 14 alterations, and NTRK and RET rearrangements. In addition, there are numerous other oncogenic drivers, such as HER2 exon 20 insertion mutations, for which there are emerging efficacy data for targeted therapies. The importance of diagnostic molecular testing, intracranial efficacy of novel therapies, the optimal sequencing of therapies, role for targeted therapies in early-stage disease, and future directions for precision oncology approaches to understand tumor evolution and therapeutic resistance are also discussed.