CONFERENCE UPDATE: WCLC 2020
Monitoring biomarkers in non-small cell lung cancer patients treated with immune checkpoint inhibitors
The introduction of immune checkpoint inhibitors (ICIs) has revolutionized the approach to advanced non-small cell lung cancer (NSCLC) by offering durable disease control with less side effects than traditional chemotherapy.1 However, as most patients do not benefit from ICIs, it is important to identify potential well-responders.1 Response assessment by conventional imaging is frequently unable to identify patients who will achieve durable clinical benefit (DCB), and the radiologic assessment of ICI response is neither accurate nor prompt.2,3 Dr. Qing Zhou, Guangdong Lung Cancer Institute, China, explained that tissue biomarkers are traditionally obtained from tissue biopsies which require invasive, risky and costly surgical interventions.2 Also, sufficient tumor tissue molecular analysis may not be obtainable in a substantial number of patients.2 As a result, it may be more difficult to find monitoring biomarkers to predict drug response, resistance and disease relapse for immunotherapy than for genomic or proteomic therapy.
To address the unmet needs from tissue biomarkers, circulating tumor DNA (ctDNA) is a promising biomarker that is expected to have greater specificity than most serum protein markers as it is a byproduct of dying cancer cells - its level provides a real-time snapshot of active tumor cell death.1 In a study that evaluated the longitudinal changes in ctDNA levels among NSCLC patients receiving ICIs, ctDNA response was found to precede and correlate with radiographic response of tumors.1 In addition, a reduction in ctDNA level to half its pre-treatment value was associated with improved patient survival, indicating that ctDNA monitoring could provide an early measure of therapeutic efficacy.1 Peripheral CD8 T-cell levels were also found to be independently associated with DCB in stage IV NSCLC patients receiving programmed death ligand-1 (PD-L1) blockade-based ICIs.2 As such, the benefit of ICIs can be better predicted by integrating pre-treatment ctDNA, pretreatment circulating immune cell profiling and early on-treatment ctDNA dynamics in a Bayesian model than assessing the individual parameters.2 Using this model, subsequent treatment strategies following PD-L1 or other ICIs can be better personalized.2
Apart from predicting the drug response, ctDNA can also be used to identify patients at high risk of disease recurrence by monitoring the post-surgical minimal residual disease (MRD).6 As MRD is defined as cancer that persists after treatment, ctDNA can be used to monitor this occult stage of cancer progression.4 In addition, circulating tumor cells (CTCs) can enable subsequent analyses at the DNA, RNA and protein levels to compliment ctDNA analyses that identify genetic and epigenetic changes in the DNA.4 The use of CTCs and ctDNA for detecting micro-metastasis would also enable the testing of new adjuvant or post-adjuvant treatment strategies to delay or prevent disease progression, and Dr. Zhou shared that there are several ongoing clinical trials that investigate MRD monitoring after adjuvant ICI treatment.4
However, Dr. Zhou also pointed out that ctDNA monitoring remains a clinical challenge in practice. As only a small amount of ctDNA is shed by tumors during the early cancer stage, the most sensitive NGS-based method to detect ctDNA, i.e.,CAPP-seq method, can only detect 50% of stage I cancer. ctDNA levels need to be quantified using maximum or mean variant allele frequencies or ctDNA concentration and do not have a consistent definition. Additionally, a positive ctDNA response is variably defined as any decrease from baseline to up to 90% decrease from baseline. Similarly, the challenges of monitoring MRD also include determining the detection threshold, as well as optimal detection time and follow-up intervals. “In the future, we need to do the clinical decision-making model based on big data and artificial intelligence mechanistic learning. We can combine the baseline data, dynamic biomarker data and long-term survival data in one model, so that we can make the best clinical decision for a specific patient,” concluded Dr. Zhou.
A real-world experience of using denosumab in treating lung cancer patients with bone metastasis
Lung cancer is the leading cause of cancer-related deaths worldwide with 2.09 million cases annually.1 In Hong Kong, lung cancer was responsible for 27.1% of all cancer deaths in 2017.2 Among all lung cancers, non-small cell lung cancer
First-line treatment with immunotherapy in metastatic squamous NSCLC
Immunotherapy has dramatically changed the therapeutic scenario in the treatment-naïve advanced NSCLC. While the single agent pembrolizumab has become the standard first-line therapy in patients with ≥50% PD-L1 expression on tumor cells,
A next generation ALK inhibitor: Clinical findings of brigatinib against crizotinib in ALK+ NSCLC from ALTA-1L
The potent and orally available anaplastic lymphoma kinase (ALK) inhibitor, brigatinib, had successfully demonstrated activity and efficacy against non-small cell lung cancer (NSCLC) in patients who are refractory or could not tolerate crizotinib.1,2
Applying low-dose computerized tomography for lung cancer screening in Taiwan
Lung cancer is the leading cause of cancer death worldwide, accounting for nearly 20% of all cancer deaths.1 Previously, low-dose computerized tomography (LDCT) was shown to detect asymptomatic lung cancer cases better than chest radiography, and many countries in the West have initiated small rando
Lung cancer in the evolving field of precision medicine
According to Dr. David Gandara, University of California Davis, Comprehensive Cancer Center, United States, the requisites for implementing precision medicine are: i) the ability to profile tumors for biomarkers, ii) having drugs against these biomarker targets, and iii) having clinical trial design