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Smoking signature is superior to programmed death-ligand 1 expression in predicting pathological response to neoadjuvant immunotherapy in lung cancer patients

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TLDR
In this paper, the authors show that CT scan-based evaluation is not able to accurately reflect the pathological response to immunotherapy and that smoking signature is a superior marker to programmed death-ligand 1 (PD-L1) expression in predicting the benefit of immunotherapy in non-small cell lung cancer patients.
Abstract
Background There is a paucity of biomarkers that can predict the degree of pathological response [e.g., pathological complete response (pCR) or major response (pMR)] to immunotherapy. Neoadjuvant immunotherapy provides an ideal setting for exploring responsive biomarkers because the pathological responses can be directly and accurately evaluated. Methods We retrospectively collected the clinicopathological characteristics and treatment outcomes of non-small cell lung cancer (NSCLC) patients who received neoadjuvant immunotherapy or chemo-immunotherapy followed by surgery between 2018 and 2020 at a large academic thoracic cancer center. Clinicopathological factors associated with pathological response were analyzed. Results A total of 39 patients (35 males and 4 females) were included. The most common histological subtype was lung squamous cell carcinoma (LUSC) (n=28, 71.8%), followed by lung adenocarcinoma (LUAD) (n=11, 28.2%). After neoadjuvant treatment, computed tomography (CT) scan-based evaluation showed poor agreement with the postoperatively pathological examination (weighted kappa =0.0225; P=0.795), suggesting the poor performance of CT scans in evaluating the response to immunotherapy. Importantly, we found that the smoking signature displayed a better performance than programmed death-ligand 1 (PD-L1) expression in predicting the pathological response (area under the curve: 0.690 vs. 0.456; P=0.0259), which might have resulted from increased tumor mutational burden (TMB) and/or microsatellite instability (MSI) relating to smoking exposure. Conclusions These findings suggest that CT scan-based evaluation is not able to accurately reflect the pathological response to immunotherapy and that smoking signature is a superior marker to PD-L1 expression in predicting the benefit of immunotherapy in NSCLC patients.

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Multi-scale characterization of tumor-draining lymph nodes in resectable lung cancer treated with neoadjuvant immune checkpoint inhibitors

TL;DR: Yao et al. as discussed by the authors characterized and compared the radiological, metabolic (18F-FDG) and pathologic responses between primary tumor beds and paired tumor-draining LNs (invaded/non-invaded) from 68 lung cancer patients who underwent neoadjuvant ICIs plus surgery.
Journal ArticleDOI

Implementation of smoking signature as an improved biomarker predicting the response to immunotherapy

TL;DR: The study revealed that lung cancer patients with heavy smoking history had improved responses to ICIs, and agreed with Li and colleagues that TMB weights more than MSI in terms of interpreting the above observations.
Journal ArticleDOI

Prediction of Disease Progression to Upfront Pembrolizumab Monotherapy in Advanced Non-Small-Cell Lung Cancer with High PD-L1 Expression Using Baseline CT Disease Quantification and Smoking Pack Years

TL;DR: In this paper , a combination of baseline CT and clinical factors can help identify those patients who may progress with pembrolizumab monotherapy and can potentially facilitate decision-making for the optimal first-line treatment.
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Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma

TL;DR: In this paper , the authors discuss the current state of immunotherapy for hepatocellular carcinoma (HCC), the results of the predictive biomarker studies, and future direction.
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The influence of baseline characteristics on the efficacy of immune checkpoint inhibitors for advanced lung cancer: A systematic review and meta-analysis

TL;DR: Some critical baseline characteristics could indicate the efficacy of ICI therapy for lung cancer, including smoking history or brain metastasis status of patients and the type of therapy (i.e., monotherapy or combination therapy) had potential influences on the efficacy.
References
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Journal ArticleDOI

Tumor mutational load predicts survival after immunotherapy across multiple cancer types.

Robert M. Samstein, +84 more
- 14 Jan 2019 - 
TL;DR: Analysis of advanced cancer patients treated with immune-checkpoint inhibitors shows that tumor mutational burden, as assessed by targeted next-generation sequencing, predicts survival after immunotherapy across multiple cancer types.
Journal ArticleDOI

B cells and tertiary lymphoid structures promote immunotherapy response

TL;DR: B cell markers were the most differentially expressed genes in the tumours of responders versus non-responders and insights are provided into the potential role of B cells and tertiary lymphoid structures in the response to ICB treatment, with implications for the development of biomarkers and therapeutic targets.
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