Dataset Information

Genetic changes of non-small cell lung cancer under neoadjuvant therapy.

ABSTRACT:

Background

Large scale sequencing efforts defined common molecular alterations in non-small cell lung cancer (NSCLC) and revealed potentially druggable mutations. Yet, systematic data on the changes of the respective molecular profiles under standard therapy in NSCLC are limited.

Results

14 out of 68 observed coding mutations (21%) and 6 out of 33 (18%) copy number variations (CNV) were lost or gained during therapy. Mutational and CNV changes clustered in 6/37 (16%) and 3/37 (8%) patients. Changes in clinically relevant mutations were rare but present in single cases for genes such as BRAF and PIK3CA. The type of radiochemotherapy but not the duration of therapy impacted on the frequency of mutational changes.

Methods

We established a lung cancer specific next-generation sequencing panel covering ~7500 hotspots of 41 genes frequently mutated in NSCLC and performed ultradeep multigene sequencing of 37 corresponding pre- and post-therapeutic formalin fixed paraffin-embedded specimens to discover mutational changes and copy number variations under neo-adjuvant radio- (RTX) and/or chemotherapy (CTX).

Conclusion

We unraveled changes in common driver gene candidates in NSCLC under neo-adjuvant therapy. Our data shed first light on the genetic changes of NSCLC under conventional therapy and might be taken into account when the relevance of sequential biopsy approaches is discussed.

SUBMITTER: Warth A

PROVIDER: S-EPMC5045431 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Publications

Genetic changes of non-small cell lung cancer under neoadjuvant therapy.

Warth Arne A Endris Volker V Stenzinger Albrecht A Penzel Roland R Harms Alexander A Duell Thomas T Abdollahi Amir A Lindner Michael M Schirmacher Peter P Muley Thomas T Dienemann Hendrik H Fink Ludger L Morresi-Hauf Alicia A Pfarr Nicole N Weichert Wilko W

Oncotarget 20160501 20

<h4>Background</h4>Large scale sequencing efforts defined common molecular alterations in non-small cell lung cancer (NSCLC) and revealed potentially druggable mutations. Yet, systematic data on the changes of the respective molecular profiles under standard therapy in NSCLC are limited.<h4>Results</h4>14 out of 68 observed coding mutations (21%) and 6 out of 33 (18%) copy number variations (CNV) were lost or gained during therapy. Mutational and CNV changes clustered in 6/37 (16%) and 3/37 (8%) ...[more]

PMID: 27105513

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Project description:IntroductionSurvival rates for early-stage non-small cell lung cancer (NSCLC) remain poor despite the decade-long established standard of surgical resection and systemic adjuvant therapy. Realizing this, researchers are exploring novel therapeutic targets and deploying neoadjuvant therapies to predict and improve clinical and pathological outcomes in lung cancer patients. Neoadjuvant therapy is also increasingly being used to downstage disease to allow for resection with a curative intent. In this review, we aim to summarize the current and developing landscape of using neoadjuvant therapy in the management of NSCLC.MethodsThe PubMed.gov and the ClinicalTrials.gov databases were searched on 15 January 2023, to identify published research studies and trials relevant to this review. One hundred and seven published articles and seventeen ongoing clinical trials were selected, and relevant findings and information was reviewed.Results & discussionNeoadjuvant therapy, proven through clinical trials and meta-analyses, exhibits safety and efficacy comparable to or sometimes surpassing adjuvant therapy. By attacking micro-metastases early and reducing tumor burden, it allows for effective downstaging of disease, allowing for curative surgical resection attempts. Research into neoadjuvant therapy has necessitated the development of surrogate endpoints such as major pathologic response (MPR) and pathologic complete response (pCR) allowing for shorter duration clinical trials. Novel chemotherapy, immunotherapy, and targeted therapy agents are being tested at a furious rate, paving the way for a future of personalized systemic therapy in NSCLC. However, challenges remain that prevent further mainstream adoption of preoperative (Neoadjuvant) therapy. These include the risk of delaying curative surgical resection in scenarios of adverse events or treatment resistance. Also, the predictive value of surrogate markers of disease cure still needs robust verification. Finally, the body of published data is still limited compared to adjuvant therapy. Addressing these concerns with more large scale randomized controlled trials is needed.

Project description:ObjectivesRecent clinical studies have demonstrated that immunotherapy-based neoadjuvant therapy have promising effectiveness for patients with resectable non-small cell lung cancer (NSCLC) in terms of pathologic response. Therefore, we performed this study to investigate whether immunotherapy-based neoadjuvant therapy is effective and safe for patients with resectable NSCLC.Materials and methodsThis open-label observational two-arm clinical study was performed at Shanghai Chest Hospital in China with patients who had resectable NSCLC and received two to three cycles of immunotherapy-based neoadjuvant therapy or neoadjuvant chemotherapy alone, followed by surgical resection. The primary endpoint was a major pathologic response (MPR). The secondary endpoints include a complete pathological response (pCR), a radiologic response to neoadjuvant therapy (TRR), event-free survival (EFS), and overall survival (OS).ResultsA total of 51 patients was included in this clinical study, of which 31 patients received immunotherapy-based neoadjuvant therapy and 20 patients received neoadjuvant chemotherapy alone. The percentage of patients achieving a major pathologic response was 41.9% with immunotherapy-based neoadjuvant therapy and 15.0% (95% CI, 0.008 to 0.468; P = 0.043) with neoadjuvant chemotherapy alone. The percentage of patients with pathologic complete response was 19.4% in the immunotherapy-based group and 5% (95% CI, -0.069 to 0.318; P = 0.223) in the chemotherapy group. The radiographic response rate was 71% after immunotherapy-based neoadjuvant therapy and 60% (95% CI, -0.143 to 0.359; P = 0.417) after neoadjuvant chemotherapy. At a median follow-up of 28 months, the median EFS and OS endpoints were not reached.ConclusionsNeoadjuvant immunotherapy offers a considerable advantage over chemotherapy alone for resectable NSCLC in terms of the major pathologic response. Moreover, it did not enhance the risk of adverse events or hinder surgical resection.

Project description:BackgroundThe response to neoadjuvant chemotherapy (NAC) differs substantially among individual patients with non-small cell lung cancer (NSCLC). Major pathological response (MPR) is a histomorphological read-out used to assess treatment response and prognosis in patients NSCLC after NAC. Although spatial metabolomics is a promising tool for evaluating metabolic phenotypes, it has not yet been utilized to assess therapy responses in patients with NSCLC. We evaluated the potential application of spatial metabolomics in cancer tissues to assess the response to NAC, using a metabolic classifier that utilizes mass spectrometry imaging combined with machine learning.MethodsResected NSCLC tissue specimens obtained after NAC (n = 88) were subjected to high-resolution mass spectrometry, and these data were used to develop an approach for assessing the response to NAC in patients with NSCLC. The specificities of the generated tumor cell and stroma classifiers were validated by applying this approach to a cohort of biologically matched chemotherapy-naïve patients with NSCLC (n = 85).ResultsThe developed tumor cell metabolic classifier stratified patients into different prognostic groups with 81.6% accuracy, whereas the stroma metabolic classifier displayed 78.4% accuracy. By contrast, the accuracies of MPR and TNM staging for stratification were 62.5% and 54.1%, respectively. The combination of metabolic and MPR classifiers showed slightly lower accuracy than either individual metabolic classifier. In multivariate analysis, metabolic classifiers were the only independent prognostic factors identified (tumor: P = 0.001, hazards ratio [HR] = 3.823, 95% confidence interval [CI] = 1.716-8.514; stroma: P = 0.049, HR = 2.180, 95% CI = 1.004-4.737), whereas MPR (P = 0.804; HR = 0.913; 95% CI = 0.445-1.874) and TNM staging (P = 0.078; HR = 1.223; 95% CI = 0.977-1.550) were not independent prognostic factors. Using Kaplan-Meier survival analyses, both tumor and stroma metabolic classifiers were able to further stratify patients as NAC responders (P < 0.001) and non-responders (P < 0.001).ConclusionsOur findings indicate that the metabolic constitutions of both tumor cells and the stroma are valuable additions to the classical histomorphology-based assessment of tumor response.

Dataset Information

Genetic changes of non-small cell lung cancer under neoadjuvant therapy.

Background

Results

Methods

Conclusion

Publications

Genetic changes of non-small cell lung cancer under neoadjuvant therapy.

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