Lung Cancer Clinical Trial
Official title:
Dynamic Monitor of Serum Chromosomal Instability Detected by UCAD as a Surrogate Biomarker of Treatment Efficacy in PD1 Inhibitor Based Immunotherapy for Lung Cancer Patients
PD1, as an immune checkpoint inhibitor, has provided a new therapeutic approach for patients with cancer, including patients. Although immunotherapy has proven effective, most patients do not benefit from it because of a large proportion which developing primary and acquired resistance. However, there is still a lack of accurate and effective molecular biomarkers to accurately evaluate the drug resistance of patients treated with immune checkpoint inhibitors (ICI), so as to maximize the therapeutic effect in patients. Chromosomal instability (CIN) is one of the most prominent and common characteristics of solid tumors, accelerating the development of anti-cancer drug resistance, often leading to treatment failure and disease recurrence, which limits the effectiveness of most current treatments. Hence the aim of this study is to evaluate dynamic CIN continuously monitored in the blood of patients with lung cancer treated with ICIs with Ultrasensitive Chromosomal Aneuploidy Detection (UCAD) to establish a new molecular immune resistance evaluation index. Further, the correlation between the evolution of tumor cloning and ICI resistance in patients during treatment was analyzed based on the results of dynamic CIN detection. This not only evaluate the efficacy of the ICI treatment in real-time, but also enables better understanding and overcoming the resistance mechanism of immunotherapy in the future.
Immune checkpoint inhibitors (ICI) targeted to PD-1/PD-L1 axis has a higher response rate and
lower incidence of side effects compared with anti-CTLA4, and has been proved to have
survival advantages in many different malignant tumors, which has been approved as a
second-line or first-line treatment for a growing number of malignancies, including lung
cancer. As results of retrospective analysis led by Roberto Ferrara, although the efficacy of
ICI treatment is obvious in non-small cell lung cancer (NSCLC), there are significant
differences in efficacy and responsiveness in different patients. Therefore, establishing
predictive biomarkers for immunotherapy is the key to maximizing the therapeutic effect and
studying drug resistance. According to clinical trial data after immunotherapy, there are
three main groups: (1) those who respond initially and continue to respond (responders); (2)
those who have never responded (primary resistance); (3) Those who initially respond but
eventually develop into disease progression (secondary resistance).Currently, PD-L1
expression is one of the most common biomarkers for immunotherapy, PD-L1 expression itself
does not accurately predict immunotherapy response, due to that the many patients with higher
PD-L1 have no response to clinical treatment, and many patients with lower PD-L1 respond
better. Although tumor mutation burden (TMB ) used as a biomarker for the treatment of NSCLC
by Opdivo could better differentiate the people who benefit compared with PD-L1, however, TMB
as a biomarker to determine the criteria for the application of ICI treatment resistance is
also limited because of its specific mechanism involved in tumor immune regulation needs to
be further clarified and high cost of TMB detection using NGS for whole exome sequencing
analysis.
As one of the most prominent and common features of solid tumors, chromosomal instability
(CIN) accelerates the development of anticancer drug resistance, often leading to treatment
failure and disease recurrence, which limits the effectiveness of most current treatments.
Previous studies have shown that CIN promotes the emergence of multidrug resistance by
providing higher levels of genetic diversity, leading to multidrug resistance. In NSCLC, the
researchers found that genomic doubling and sustained dynamic CIN were associated with
intratumoral heterogeneity and led to parallel evolution of CDNAs, including CDK4, FOXA1, and
BCL11A. It is worth noting that the study found consistency in the variation of mutation
levels, indicating that CIN in lung cancer is more likely to select driving events than other
mutation processes. CIN enables cells to enter several different evolutionary trajectories
and adapt to the selective pressure generated by treatment, which is the basis of drug
resistance. Based on the above, CIN may become a more accurate and effective biomarker for
the study of drug resistance mechanism of ICI in lung cancer. NGS technology can obtain more
comprehensive genomic information while detecting cost reduction, making CIN detection more
accurate and practical than FISH used for evaluating CIN in patient commonly.As a new
Detection method based on NGS technology, Ultrasensitive Chromosomal Aneuploidy Detection
(UCAD) has been developed in our previous study. In which, low-coverage whole-genome
sequencing technology based on NGS was adopted to detect CIN of ctDNA in patients' peripheral
blood, and bioinformatics analysis was performed to determine the risk of malignancy (or
recurrence) and the extent of tumor burden and CIN. It has important clinical value in
auxiliary diagnosis, therapeutic effect monitoring, recurrence and metastasis monitoring and
prognosis evaluation of tumor patients.
This study proposes that continuous dynamic CIN is related to intratumor heterogeneity, which
drives parallel evolution of somatic copy-number alterations (SCNAs) and promotes the
emergence of drug-resistant clones by providing a higher level of genetic diversity of tumor
cells, thus leading to drug resistance in patients treated with ICI. Investigators aimed to
continuously monitor dynamic CIN in the blood of patients with lung cancer after second-line
treatment with UCAD to establish a new molecular immune resistance evaluation index. Further,
the correlation between the evolution of tumor cloning and ICI resistance in patients during
treatment was analyzed based on the detection results of dynamic CIN.
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